Sample records for table state estimated

  1. FY 2009 State Table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment6 FY 2007 FY 2008State Tables

  2. FY 2010 State Table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment6 FY 2007 FY 2008State7 FY0 ServiceState

  3. FY 2011 State Table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment6 FY 2007 FY 2008State71Laboratory1State

  4. FY 2006 State Table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment of EnergyME-0035Organization6State

  5. FY 2008 State Table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment ofAppropriationBudgetLaboratoryState

  6. Qualified Energy Conservation Bond State-by-State Summary Tables

    Broader source: Energy.gov [DOE]

    Provides a list of qualified energy conservation bond state summary tables. Author: Energy Programs Consortium

  7. State Energy Production Estimates

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConference |6: "Regulating

  8. State Historical Tables for 2001 - 2003

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConference |6: "Regulating3 Released:

  9. State Historical Tables for 2001 - 2004

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConference |6: "Regulating3 Released:4

  10. Measurement enhancement for state estimation

    E-Print Network [OSTI]

    Chen, Jian

    2009-05-15T23:59:59.000Z

    in the power system. A robust state estimation should have the capability of keeping the system observable during different contingencies, as well as detecting and identifying the gross errors in measurement set and network topology. However, this capability...

  11. An efficient algorithm for real-time estimation and prediction of dynamic OD tables

    E-Print Network [OSTI]

    Bierlaire, Michel

    An efficient algorithm for real-time estimation and prediction of dynamic OD tables M. Bierlaire and F. Crittin February, 2002 Abstract The problem of estimating and predicting Origin-Destination (OD more intricate. We consider here a least-square modeling approach for solving the OD estimation

  12. Efficient Power System State Estimation

    E-Print Network [OSTI]

    Lavaei, Javad

    monitoring of power systems. 2. Background Power systems have four main components: transmission, sub-transmissionEfficient Power System State Estimation Zafirah Baksh Expected BS, Department of Electrical Engineering May 2013 ELEN E4511 Power Systems Analysis Professor Javad Lavaeiyanesi #12;1. Introduction Power

  13. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14Total DeliveredPrincipal shale gas:1 Table 7 Created

  14. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14Total DeliveredPrincipal shale gas:1 Table 7

  15. Enhanced State Estimators Final Project Report

    E-Print Network [OSTI]

    . State estimators, integrated into control center energy management systems, provide estimates of varying magnitude. As a result, a state estimator is an essential tool for system monitoring becauseEnhanced State Estimators Final Project Report Power Systems Engineering Research Center A National

  16. Table 4. Estimation Results for PAD District Regions

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousandCubic Feet) DecadeV49 155 181 Estimation Results for

  17. State energy data report 1994: Consumption estimates

    SciTech Connect (OSTI)

    NONE

    1996-10-01T23:59:59.000Z

    This document provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), operated by EIA. SEDS provides State energy consumption estimates to members of Congress, Federal and State agencies, and the general public, and provides the historical series needed for EIA`s energy models. Division is made for each energy type and end use sector. Nuclear electric power is included.

  18. Table 42. Residual Fuel Oil Prices by PAD District and State

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

    Information AdministrationPetroleum Marketing Annual 1999 203 Table 42. Residual Fuel Oil Prices by PAD District and State (Cents per Gallon Excluding Taxes) - Continued...

  19. Table 42. Residual Fuel Oil Prices by PAD District and State

    Gasoline and Diesel Fuel Update (EIA)

    Information AdministrationPetroleum Marketing Annual 1998 203 Table 42. Residual Fuel Oil Prices by PAD District and State (Cents per Gallon Excluding Taxes) - Continued...

  20. Table 42. Residual Fuel Oil Prices by PAD District and State

    Gasoline and Diesel Fuel Update (EIA)

    Information Administration Petroleum Marketing Annual 1995 245 Table 42. Residual Fuel Oil Prices by PAD District and State (Cents per Gallon Excluding Taxes) - Continued...

  1. Uncertainty Quantification in ocean state estimation

    E-Print Network [OSTI]

    Kalmikov, Alexander G

    2013-01-01T23:59:59.000Z

    Quantifying uncertainty and error bounds is a key outstanding challenge in ocean state estimation and climate research. It is particularly difficult due to the large dimensionality of this nonlinear estimation problem and ...

  2. State energy data report 1993: Consumption estimates

    SciTech Connect (OSTI)

    NONE

    1995-07-01T23:59:59.000Z

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public; and (2) to provide the historical series necessary for EIA`s energy models.

  3. State energy data report 1995 - consumption estimates

    SciTech Connect (OSTI)

    NONE

    1997-12-01T23:59:59.000Z

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public, and (2) to provide the historical series necessary for EIA`s energy models.

  4. State Energy Data Report, 1991: Consumption estimates

    SciTech Connect (OSTI)

    Not Available

    1993-05-01T23:59:59.000Z

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to the Government, policy makers, and the public; and (2) to provide the historical series necessary for EIA`s energy models.

  5. Frequency tracking and parameter estimation for robust quantum state estimation

    SciTech Connect (OSTI)

    Ralph, Jason F. [Department of Electrical Engineering and Electronics, University of Liverpool, Brownlow Hill, Liverpool L69 3GJ (United Kingdom); Jacobs, Kurt [Department of Physics, University of Massachusetts at Boston, 100 Morrissey Blvd, Boston, Massachusetts 02125 (United States); Hill, Charles D. [Centre for Quantum Computation and Communication Technology, School of Physics, University of Melbourne, Victoria 3010 (Australia)

    2011-11-15T23:59:59.000Z

    In this paper we consider the problem of tracking the state of a quantum system via a continuous weak measurement. If the system Hamiltonian is known precisely, this merely requires integrating the appropriate stochastic master equation. However, even a small error in the assumed Hamiltonian can render this approach useless. The natural answer to this problem is to include the parameters of the Hamiltonian as part of the estimation problem, and the full Bayesian solution to this task provides a state estimate that is robust against uncertainties. However, this approach requires considerable computational overhead. Here we consider a single qubit in which the Hamiltonian contains a single unknown parameter. We show that classical frequency estimation techniques greatly reduce the computational overhead associated with Bayesian estimation and provide accurate estimates for the qubit frequency.

  6. Parallel State Estimation Assessment with Practical Data

    SciTech Connect (OSTI)

    Chen, Yousu; Jin, Shuangshuang; Rice, Mark J.; Huang, Zhenyu

    2014-10-31T23:59:59.000Z

    This paper presents a full-cycle parallel state estimation (PSE) implementation using a preconditioned conjugate gradient algorithm. The developed code is able to solve large-size power system state estimation within 5 seconds using real-world data, comparable to the Supervisory Control And Data Acquisition (SCADA) rate. This achievement allows the operators to know the system status much faster to help improve grid reliability. Case study results of the Bonneville Power Administration (BPA) system with real measurements are presented. The benefits of fast state estimation are also discussed.

  7. State energy data report 1996: Consumption estimates

    SciTech Connect (OSTI)

    NONE

    1999-02-01T23:59:59.000Z

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the Combined State Energy Data System (CSEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining CSEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. CSEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public and (2) to provide the historical series necessary for EIA`s energy models. To the degree possible, energy consumption has been assigned to five sectors: residential, commercial, industrial, transportation, and electric utility sectors. Fuels covered are coal, natural gas, petroleum, nuclear electric power, hydroelectric power, biomass, and other, defined as electric power generated from geothermal, wind, photovoltaic, and solar thermal energy. 322 tabs.

  8. Table 42. Residual Fuel Oil Prices by PAD District and State

    Gasoline and Diesel Fuel Update (EIA)

    45.5 49.2 W W 44.5 45.4 See footnotes at end of table. 42. Residual Fuel Oil Prices by PAD District and State Energy Information Administration Petroleum...

  9. Table 42. Residual Fuel Oil Prices by PAD District and State

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

    55.1 47.1 W W 55.1 46.2 See footnotes at end of table. 42. Residual Fuel Oil Prices by PAD District and State Energy Information Administration Petroleum...

  10. PMU Deployment for Optimal State Estimation Performance

    E-Print Network [OSTI]

    Roy, Sumit

    the observability of candidate deployments at each step and improves the convergence speed of the search. In [5PMU Deployment for Optimal State Estimation Performance Yue Yang, Student Member IEEE, and Sumit electronic devices (IED), that sense the grid state variables so as to support enhanced, real-time monitoring

  11. Sub-Second Parallel State Estimation

    SciTech Connect (OSTI)

    Chen, Yousu; Rice, Mark J.; Glaesemann, Kurt R.; Wang, Shaobu; Huang, Zhenyu

    2014-10-31T23:59:59.000Z

    This report describes the performance of Pacific Northwest National Laboratory (PNNL) sub-second parallel state estimation (PSE) tool using the utility data from the Bonneville Power Administrative (BPA) and discusses the benefits of the fast computational speed for power system applications. The test data were provided by BPA. They are two-days’ worth of hourly snapshots that include power system data and measurement sets in a commercial tool format. These data are extracted out from the commercial tool box and fed into the PSE tool. With the help of advanced solvers, the PSE tool is able to solve each BPA hourly state estimation problem within one second, which is more than 10 times faster than today’s commercial tool. This improved computational performance can help increase the reliability value of state estimation in many aspects: (1) the shorter the time required for execution of state estimation, the more time remains for operators to take appropriate actions, and/or to apply automatic or manual corrective control actions. This increases the chances of arresting or mitigating the impact of cascading failures; (2) the SE can be executed multiple times within time allowance. Therefore, the robustness of SE can be enhanced by repeating the execution of the SE with adaptive adjustments, including removing bad data and/or adjusting different initial conditions to compute a better estimate within the same time as a traditional state estimator’s single estimate. There are other benefits with the sub-second SE, such as that the PSE results can potentially be used in local and/or wide-area automatic corrective control actions that are currently dependent on raw measurements to minimize the impact of bad measurements, and provides opportunities to enhance the power grid reliability and efficiency. PSE also can enable other advanced tools that rely on SE outputs and could be used to further improve operators’ actions and automated controls to mitigate effects of severe events on the grid. The power grid continues to grow and the number of measurements is increasing at an accelerated rate due to the variety of smart grid devices being introduced. A parallel state estimation implementation will have better performance than traditional, sequential state estimation by utilizing the power of high performance computing (HPC). This increased performance positions parallel state estimators as valuable tools for operating the increasingly more complex power grid.

  12. State energy data report 1992: Consumption estimates

    SciTech Connect (OSTI)

    Not Available

    1994-05-01T23:59:59.000Z

    This is a report of energy consumption by state for the years 1960 to 1992. The report contains summaries of energy consumption for the US and by state, consumption by source, comparisons to other energy use reports, consumption by energy use sector, and describes the estimation methodologies used in the preparation of the report. Some years are not listed specifically although they are included in the summary of data.

  13. Estimated Water Flows in 2005: United States

    SciTech Connect (OSTI)

    Smith, C A; Belles, R D; Simon, A J

    2011-03-16T23:59:59.000Z

    Flow charts depicting water use in the United States have been constructed from publicly available data and estimates of water use patterns. Approximately 410,500 million gallons per day of water are managed throughout the United States for use in farming, power production, residential, commercial, and industrial applications. Water is obtained from four major resource classes: fresh surface-water, saline (ocean) surface-water, fresh groundwater and saline (brackish) groundwater. Water that is not consumed or evaporated during its use is returned to surface bodies of water. The flow patterns are represented in a compact 'visual atlas' of 52 state-level (all 50 states in addition to Puerto Rico and the Virgin Islands) and one national water flow chart representing a comprehensive systems view of national water resources, use, and disposition.

  14. Parallel State Estimation Assessment with Practical Data

    SciTech Connect (OSTI)

    Chen, Yousu; Jin, Shuangshuang; Rice, Mark J.; Huang, Zhenyu

    2013-07-31T23:59:59.000Z

    This paper presents a parallel state estimation (PSE) implementation using a preconditioned gradient algorithm and an orthogonal decomposition-based algorithm. The preliminary tests against a commercial Energy Management System (EMS) State Estimation (SE) tool using real-world data are performed. The results show that while the precondition gradient algorithm can solve the SE problem quicker with the help of parallel computing techniques, it might not be good for real-world data due to the large condition number of gain matrix introduced by the wide range of measurement weights. With the help of PETSc package and considering one iteration of the SE process, the orthogonal decomposition-based PSE algorithm can achieve 5-20 times speedup comparing against the commercial EMS tool. It is very promising that the developed PSE can solve the SE problem for large power systems at the SCADA rate, to improve grid reliability.

  15. Estimated United States Transportation Energy Use 2005

    SciTech Connect (OSTI)

    Smith, C A; Simon, A J; Belles, R D

    2011-11-09T23:59:59.000Z

    A flow chart depicting energy flow in the transportation sector of the United States economy in 2005 has been constructed from publicly available data and estimates of national energy use patterns. Approximately 31,000 trillion British Thermal Units (trBTUs) of energy were used throughout the United States in transportation activities. Vehicles used in these activities include automobiles, motorcycles, trucks, buses, airplanes, rail, and ships. The transportation sector is powered primarily by petroleum-derived fuels (gasoline, diesel and jet fuel). Biomass-derived fuels, electricity and natural gas-derived fuels are also used. The flow patterns represent a comprehensive systems view of energy used within the transportation sector.

  16. Estimating Power System Dynamic States Using Extended Kalman Filter

    SciTech Connect (OSTI)

    Huang, Zhenyu; Schneider, Kevin P.; Nieplocha, Jaroslaw; Zhou, Ning

    2014-10-31T23:59:59.000Z

    Abstract—The state estimation tools which are currently deployed in power system control rooms are based on a steady state assumption. As a result, the suite of operational tools that rely on state estimation results as inputs do not have dynamic information available and their accuracy is compromised. This paper investigates the application of Extended Kalman Filtering techniques for estimating dynamic states in the state estimation process. The new formulated “dynamic state estimation” includes true system dynamics reflected in differential equations, not like previously proposed “dynamic state estimation” which only considers the time-variant snapshots based on steady state modeling. This new dynamic state estimation using Extended Kalman Filter has been successfully tested on a multi-machine system. Sensitivity studies with respect to noise levels, sampling rates, model errors, and parameter errors are presented as well to illustrate the robust performance of the developed dynamic state estimation process.

  17. Table 1. Annual estimates, uncertainty, and change Figure 1. Area of timberland and forest land by

    E-Print Network [OSTI]

    errors/bars provided in figures and tables represent 68 percent confidence intervals 0.0 1.0 2.0 3.0 4/American elm/red maple White oak/red oak/hickory Area (1,000 acres) Small Medium Large #12;Table 2. ­ Top 10

  18. Back-and-forth Operation of State Observers and Norm Estimation of Estimation Error

    E-Print Network [OSTI]

    Back-and-forth Operation of State Observers and Norm Estimation of Estimation Error Hyungbo Shim with the plant, this paper proposes a state estimation algorithm that executes Luenberger observers in a back in the past have employed time-varying gains to over- come this problem [1], where the basic idea is to obtain

  19. aided state estimation: Topics by E-print Network

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

    estimated from the information content Szilagyi, Jozsef 7 STATE AID TO ENTERPRISES IN CROATIA IN 2001 CiteSeer Summary: State aid to enterprises is a form of government...

  20. Quantum phase estimation using a multi-headed cat state

    E-Print Network [OSTI]

    Su-Yong Lee; Chang-Woo Lee; Hyunchul Nha; Dagomir Kaszlikowski

    2015-05-16T23:59:59.000Z

    It was recently shown that an entangled coherent state, which is a superposition of two different coherent states, can surpass the performance of noon state in estimating an unknown phase-shift. This may hint at further enhancement in phase estimation by incorporating more component states in the superposition of resource state. We here introduce a four-headed cat state (4HCS), a superposition of four different coherent states, and propose its application to quantum phase estimation. We demonstrate the enhanced performance in phase estimation by employing an entangled state via the 4HCS, which can surpass that of the two-headed cat state (2HCS), particularly in the regime of small average photon numbers. Moreover, we show that an entangled state modified from the 4HCS can further enhance the phase estimation, even in the regime of large average photon number under a photon-loss channel. Our investigation further extends to incorporate an increasingly large number of component states in the resource superposition state and clearly show its merit in phase estimation.

  1. Quantum phase estimation using a multi-headed cat state

    E-Print Network [OSTI]

    Su-Yong Lee; Chang-Woo Lee; Hyunchul Nha; Dagomir Kaszlikowski

    2015-03-12T23:59:59.000Z

    It was recently shown that an entangled coherent state, which is a superposition of two different coherent states, can surpass the performance of N00N state in estimating an unknown phase-shift. This may hint at further enhancement in phase estimation by incorporating more component states in the superposition of resource state. We here study a four-headed cat state (4HCS), a superposition of four different coherent states, and propose its application to quantum phase estimation. We first investigate how the 4HCS is more nonclassical than a 2HCS in view of some nonclassical measures including sub-Poissonian statistics, negativity of Wigner distribution, and entanglement potential. We then demonstrate the enhanced performance in phase estimation by employing an entangled state via the 4HCS, which can surpass that of the 2HCS particularly in the regime of small average photon number. Moreover, we show that an entangled state modified from the 4HCS can further enhance the phase estimation even in the regime of large average photon number under a photon-loss channel. Our investigation further extends to incorporate an increasingly large number of component states in the resource superposition state and clearly show its merit in phase estimation.

  2. Table 1. Updated estimates of power plant capital and operating costs

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConference |6:Welcome toU.S.

  3. State energy data report: Consumption estimates, 1960--1987

    SciTech Connect (OSTI)

    Not Available

    1989-04-20T23:59:59.000Z

    The State Energy Data Report presents estimates of annual energy consumption at the state and national levels by major economic sector and by principal energy type for 1960 through 1987. Included in the report are documentation describing how the estimates were made for each energy source, sources of all input data, and a summary of changes from the State Energy Data Report published in April 1988.

  4. Dynamic State Estimation Utilizing High Performance Computing Methods

    SciTech Connect (OSTI)

    Schneider, Kevin P.; Huang, Zhenyu; Yang, Bo; Hauer, Matthew L.; Nieplocha, Jaroslaw

    2009-03-18T23:59:59.000Z

    The state estimation tools which are currently deployed in power system control rooms are based on a quasi-steady-state assumption. As a result, the suite of operational tools that rely on state estimation results as inputs do not have dynamic information available and their accuracy is compromised. This paper presents an overview of the Kalman Filtering process and then focuses on the implementation of the predication component on multiple processors.

  5. SWOT Satellite Mission: Combined State Parameter Estimation

    E-Print Network [OSTI]

    Washington at Seattle, University of

    -parameter estimation problem Data assimilation experiments ­ Water depth ­ Discharge ­ Channel width ­ Roughness coefficient #12;3 Need for a surface water mission Importance to hydrology ­ gauge measurements insufficient hydraulics Amazon Siberia Ohio #12;4 Global gauge measurements #12;5 SWOT Technology These surface water

  6. Distributed Dynamic State Estimation with Extended Kalman Filter

    SciTech Connect (OSTI)

    Du, Pengwei; Huang, Zhenyu; Sun, Yannan; Diao, Ruisheng; Kalsi, Karanjit; Anderson, Kevin K.; Li, Yulan; Lee, Barry

    2011-08-04T23:59:59.000Z

    Increasing complexity associated with large-scale renewable resources and novel smart-grid technologies necessitates real-time monitoring and control. Our previous work applied the extended Kalman filter (EKF) with the use of phasor measurement data (PMU) for dynamic state estimation. However, high computation complexity creates significant challenges for real-time applications. In this paper, the problem of distributed dynamic state estimation is investigated. One domain decomposition method is proposed to utilize decentralized computing resources. The performance of distributed dynamic state estimation is tested on a 16-machine, 68-bus test system.

  7. Table Search (or Ranking Tables)

    E-Print Network [OSTI]

    Halevy, Alon

    ;Table Search #3 #12;Outline · Goals of table search · Table search #1: Deep Web · Table search #3 search Table search #1: Deep Web · Table search #3: (setup): Fusion Tables · Table search #2: WebTables ­Version 1: modify document search ­Version 2: recover table semantics #12;Searching the Deep Web store

  8. Transition state theory: Variational formulation, dynamical corrections, and error estimates

    E-Print Network [OSTI]

    Van Den Eijnden, Eric

    Transition state theory: Variational formulation, dynamical corrections, and error estimates Eric, Brazil Received 18 February 2005; accepted 9 September 2005; published online 7 November 2005 Transition which aim at computing dynamical corrections to the TST transition rate constant. The theory

  9. Table 3. Estimation Results for National and Sub-PAD District Regions

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousandCubic Feet) DecadeV49 155 181 1773 Estimation

  10. Electric Grid State Estimators for Distribution Systems with Microgrids

    E-Print Network [OSTI]

    Gupta, Vijay

    46556 Emails: {jhuang6,vgupta2,huang}@nd.edu Abstract--In the development of smart grid, state] into the distribution systems of the power grid. Such integration complicates the operation of distribution systemsElectric Grid State Estimators for Distribution Systems with Microgrids Jing Huang, Vijay Gupta

  11. Current (2009) State-of-the-Art Hydrogen Production Cost Estimate...

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

    Current (2009) State-of-the-Art Hydrogen Production Cost Estimate Using Water Electrolysis Current (2009) State-of-the-Art Hydrogen Production Cost Estimate Using Water...

  12. Bounds on Quantum Multiple-Parameter Estimation with Gaussian State

    E-Print Network [OSTI]

    Yang Gao; Hwang Lee

    2014-07-28T23:59:59.000Z

    We investigate the quantum Cramer-Rao bounds on the joint multiple-parameter estimation with the Gaussian state as a probe. We derive the explicit right logarithmic derivative and symmetric logarithmic derivative operators in such a situation. We compute the corresponding quantum Fisher information matrices, and find that they can be fully expressed in terms of the mean displacement and covariance matrix of the Gaussian state. Finally, we give some examples to show the utility of our analytical results.

  13. UNSCENTED KALMAN FILTERING FOR SPACECRAFT ATTITUDE STATE AND PARAMETER ESTIMATION

    E-Print Network [OSTI]

    Hall, Christopher D.

    AAS-04-115 UNSCENTED KALMAN FILTERING FOR SPACECRAFT ATTITUDE STATE AND PARAMETER ESTIMATION Matthew C. VanDyke , Jana L. Schwartz , Christopher D. Hall An Unscented Kalman Filter (UKF) is derived with an Extended Kalman Filter (EKF). The EKF is an extension of the linear Kalman Filter for nonlinear systems

  14. Estimation of steady-state basic parameters of stars

    B. V. Vasiliev

    2000-03-30T23:59:59.000Z

    From a minimum of total energy of celestial bodies, their basic parameters are obtained. The steady-state values of the mass, radius, and temperature of stars and white dwarfs, as well as masses of pulsars are calculated. The luminosity and giromagnetic ratio of celestial bodies are estimated. All the obtained values are in a satisfactory agreement with observation data.

  15. Optimal Estimation of States in Quantum Image Processing

    E-Print Network [OSTI]

    Mario Mastriani

    2014-06-19T23:59:59.000Z

    An optimal estimator of quantum states based on a modified Kalman Filter is presented in this work. Such estimator acts after state measurement, allowing to obtain an optimal estimation of quantum state resulting in the output of any quantum image algorithm. Besides, a new criteria, logic, and arithmetic based on projections onto vertical axis of Bloch Sphere exclusively are presented too. This approach will allow us: 1) a simpler development of logic and arithmetic quantum operations, where they will closer to those used in the classical digital image processing algorithms, 2) building simple and robust classical-to-quantum and quantum-to-classical interfaces. Said so far is extended to quantum algorithms outside image processing too. In a special section on metrics and simulations, three new metrics based on the comparison between the classical and quantum versions algorithms for filtering and edge detection of images are presented. Notable differences between the results of classical and quantum versions of such algorithms (outside and inside of quantum computer, respectively) show the need for modeling state and measurement noise inside estimation scheme.

  16. The Lithium-Ion Cell: Model, State Of Charge Estimation

    E-Print Network [OSTI]

    Schenato, Luca

    The Lithium-Ion Cell: Model, State Of Charge Estimation and Battery Management System Tutor degradation mechanisms of a Li-ion cell based on LiCoO2", Journal of Power Sources #12;Lithium ions and e and Y. Fuentes. Computer simulations of a lithium-ion polymer battery and implications for higher

  17. Multiple phase estimation for arbitrary pure states under white noise

    E-Print Network [OSTI]

    Yao Yao; Li Ge; Xing Xiao; Xiaoguang Wang; C. P. Sun

    2014-09-08T23:59:59.000Z

    In any realistic quantum metrology scenarios, the ultimate precision in the estimation of parameters is limited not only by the so-called Heisenberg scaling, but also the environmental noise encountered by the underlying system. In the context of quantum estimation theory, it is of great significance to carefully evaluate the impact of a specific type of noise on the corresponding quantum Fisher information (QFI) or quantum Fisher information matrix (QFIM). Here we investigate the multiple phase estimation problem for a natural parametrization of arbitrary pure states under white noise. We obtain the explicit expression of the symmetric logarithmic derivative (SLD) and hence the analytical formula of QFIM. Moreover, the attainability of the quantum Cram\\'{e}r-Rao bound (QCRB) is confirmed by the commutability of SLDs and the optimal estimators are elucidated for the experimental purpose. These findings generalize previously known partial results and highlight the role of white noise in quantum metrology.

  18. Multi-area power system state estimation utilizing boundary measurements and phasor measurement units ( PMUs)

    E-Print Network [OSTI]

    Freeman, Matthew A

    2006-10-30T23:59:59.000Z

    investigates the benefits that stem from utilizing a multi-area state estimator instead of a serial state estimator. These benefits are largely in the form of increased accuracy and decreased processing time. First, the theory behind power system state...

  19. Estimated Carbon Dioxide Emissions in 2008: United States

    SciTech Connect (OSTI)

    Smith, C A; Simon, A J; Belles, R D

    2011-04-01T23:59:59.000Z

    Flow charts depicting carbon dioxide emissions in the United States have been constructed from publicly available data and estimates of state-level energy use patterns. Approximately 5,800 million metric tons of carbon dioxide were emitted throughout the United States for use in power production, residential, commercial, industrial, and transportation applications in 2008. Carbon dioxide is emitted from the use of three major energy resources: natural gas, coal, and petroleum. The flow patterns are represented in a compact 'visual atlas' of 52 state-level (all 50 states, the District of Columbia, and one national) carbon dioxide flow charts representing a comprehensive systems view of national CO{sub 2} emissions. Lawrence Livermore National Lab (LLNL) has published flow charts (also referred to as 'Sankey Diagrams') of important national commodities since the early 1970s. The most widely recognized of these charts is the U.S. energy flow chart (http://flowcharts.llnl.gov). LLNL has also published charts depicting carbon (or carbon dioxide potential) flow and water flow at the national level as well as energy, carbon, and water flows at the international, state, municipal, and organizational (i.e. United States Air Force) level. Flow charts are valuable as single-page references that contain quantitative data about resource, commodity, and byproduct flows in a graphical form that also convey structural information about the system that manages those flows. Data on carbon dioxide emissions from the energy sector are reported on a national level. Because carbon dioxide emissions are not reported for individual states, the carbon dioxide emissions are estimated using published energy use information. Data on energy use is compiled by the U.S. Department of Energy's Energy Information Administration (U.S. EIA) in the State Energy Data System (SEDS). SEDS is updated annually and reports data from 2 years prior to the year of the update. SEDS contains data on primary resource consumption, electricity generation, and energy consumption within each economic sector. Flow charts of state-level energy usage and explanations of the calculations and assumptions utilized can be found at: http://flowcharts.llnl.gov. This information is translated into carbon dioxide emissions using ratios of carbon dioxide emissions to energy use calculated from national carbon dioxide emissions and national energy use quantities for each particular sector. These statistics are reported annually in the U.S. EIA's Annual Energy Review. Data for 2008 (US. EIA, 2010) was updated in August of 2010. This is the first presentation of a comprehensive state-level package of flow charts depicting carbon dioxide emissions for the United States.

  20. Estimating inventory thresholds for nuclear facilities using DOE STD-1027-92 Attachment 1 Table A.1 ``Thresholds for Radionuclides``

    SciTech Connect (OSTI)

    Price, D. [Onsite Engineering and Management, Inc. (United States); Hildum, J.S.; Williams, A.C. [Onsite Engineering and Management, Inc. (United States)

    1997-04-01T23:59:59.000Z

    It has recently been reports that Table A.1 of Attachment 1 of DOE STD-1027-92 is being improperly used to determine the Category 3 inventory threshold values for non-reactor nuclear facilities. The concern of this paper is that Safety Analysts and Facility Managers at the Lawrence Livermore National Laboratory (LLNL), as well as at other locations in the DOE Complex, are improperly using the entries in Table A.1. It is noted at this point that the common use of this table is to establish the lower thresholds for both Categories 2 and 3 non-reactor nuclear facilities by considering inventory quantities, as opposed to a postulated accident scenario. This paper will provide insight regarding this error and will show that the error is most likely non-conservative in nature.

  1. Petroleum Products Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan Feb Mar AprYear JanPricePrice

  2. Numerical Estimation of Frictional Torques with Rate and State Friction

    E-Print Network [OSTI]

    Arun K. Singh; T. N. Singh

    2015-01-20T23:59:59.000Z

    In this paper, numerical estimation of frictional torques is carried out of a rotary elastic disc on a hard and rough surface under different rotating conditions. A one dimensional spring- mass rotary system is numerically solved under the quasistatic condition with the rate and state dependent friction model. It is established that torque of frictional strength as well as torque of steady dynamic stress increases with radius and found to be maximum at the periphery of the disc. Torque corresponding to frictional strength estimated using the analytical solution matches closely with the simulation only in the case of high stiffness of the connecting spring. In steady relaxation simulation, a steadily rotating disc is suddenly stopped and relaxational angular velocity and corresponding frictional torque decreases with both steady angular velocity and stiffness of the connecting spring in the velocity strengthening regime. In velocity weakening regime, in contrast, torque of relaxation stress deceases but relaxation velocity increases. The reason for the contradiction is explained.

  3. Table 1. Summary statistics for natural gas in the United States, 2009-2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API Gravity Period: Monthly Annual Download Series History Download Series History Definitions, SourcesType"A50. Table 1.

  4. Petroleum Products Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan Feb Mar AprYear JanPricePrice (Percent)by69.6 69.1

  5. Petroleum Products Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan Feb Mar AprYear JanPricePrice (Percent)by69.6 69.170.4

  6. Petroleum Products Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan Feb Mar AprYear JanPricePrice (Percent)by69.6

  7. Petroleum Products Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan Feb Mar AprYear JanPricePrice (Percent)by69.61,312.3

  8. Petroleum Products Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan Feb Mar AprYear JanPricePrice5,594.9 37,614.8 44,971.0

  9. Petroleum Products Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan Feb Mar AprYear JanPricePrice5,594.9 37,614.8

  10. Estimated United States Residential Energy Use in 2005

    SciTech Connect (OSTI)

    Smith, C A; Johnson, D M; Simon, A J; Belles, R D

    2011-12-12T23:59:59.000Z

    A flow chart depicting energy flow in the residential sector of the United States economy in 2005 has been constructed from publicly available data and estimates of national energy use patterns. Approximately 11,000 trillion British Thermal Units (trBTUs) of electricity and fuels were used throughout the United States residential sector in lighting, electronics, air conditioning, space heating, water heating, washing appliances, cooking appliances, refrigerators, and other appliances. The residential sector is powered mainly by electricity and natural gas. Other fuels used include petroleum products (fuel oil, liquefied petroleum gas and kerosene), biomass (wood), and on-premises solar, wind, and geothermal energy. The flow patterns represent a comprehensive systems view of energy used within the residential sector.

  11. Distributed Dynamic State Estimator, Generator Parameter Estimation and Stability Monitoring Demonstration

    SciTech Connect (OSTI)

    Meliopoulos, Sakis; Cokkinides, George; Fardanesh, Bruce; Hedrington, Clinton

    2013-12-31T23:59:59.000Z

    This is the final report for this project that was performed in the period: October1, 2009 to June 30, 2013. In this project, a fully distributed high-fidelity dynamic state estimator (DSE) that continuously tracks the real time dynamic model of a wide area system with update rates better than 60 times per second is achieved. The proposed technology is based on GPS-synchronized measurements but also utilizes data from all available Intelligent Electronic Devices in the system (numerical relays, digital fault recorders, digital meters, etc.). The distributed state estimator provides the real time model of the system not only the voltage phasors. The proposed system provides the infrastructure for a variety of applications and two very important applications (a) a high fidelity generating unit parameters estimation and (b) an energy function based transient stability monitoring of a wide area electric power system with predictive capability. Also the dynamic distributed state estimation results are stored (the storage scheme includes data and coincidental model) enabling an automatic reconstruction and “play back” of a system wide disturbance. This approach enables complete play back capability with fidelity equal to that of real time with the advantage of “playing back” at a user selected speed. The proposed technologies were developed and tested in the lab during the first 18 months of the project and then demonstrated on two actual systems, the USVI Water and Power Administration system and the New York Power Authority’s Blenheim-Gilboa pumped hydro plant in the last 18 months of the project. The four main thrusts of this project, mentioned above, are extremely important to the industry. The DSE with the achieved update rates (more than 60 times per second) provides a superior solution to the “grid visibility” question. The generator parameter identification method fills an important and practical need of the industry. The “energy function” based transient stability monitoring opens up new ways to protect the power grid, better manage disturbances, confine their impact and in general improve the reliability and security of the system. Finally, as a by-product of the proposed research project, the developed system is able to “play back” disturbances by a click of a mouse. The importance of this by-product is evident by considering the tremendous effort exerted after the August 2003 blackout to piece together all the disturbance recordings, align them and recreate the sequence of events. This project has moved the state of art from fault recording by individual devices to system wide disturbance recording with “play back” capability.

  12. Reduced Measurement-space Dynamic State Estimation (ReMeDySE) for Power Systems

    SciTech Connect (OSTI)

    Zhang, Jinghe; Welch, Greg; Bishop, Gary; Huang, Zhenyu

    2011-06-19T23:59:59.000Z

    Abstract- Applying Kalman filtering techniques to dynamic state estimation is a developing research area in modern power systems.

  13. Connections of geometric measure of entanglement of pure symmetric states to quantum state estimation

    SciTech Connect (OSTI)

    Chen Lin [Centre for Quantum Technologies, National University of Singapore, Singapore 117543 (Singapore); Zhu Huangjun [Centre for Quantum Technologies, National University of Singapore, Singapore 117543 (Singapore); Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore 117597 (Singapore); Wei, Tzu-Chieh [Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, V6T 1Z1 (Canada)

    2011-01-15T23:59:59.000Z

    We study the geometric measure of entanglement (GM) of pure symmetric states related to rank 1 positive-operator-valued measures (POVMs) and establish a general connection with quantum state estimation theory, especially the maximum likelihood principle. Based on this connection, we provide a method for computing the GM of these states and demonstrate its additivity property under certain conditions. In particular, we prove the additivity of the GM of pure symmetric multiqubit states whose Majorana points under Majorana representation are distributed within a half sphere, including all pure symmetric three-qubit states. We then introduce a family of symmetric states that are generated from mutually unbiased bases and derive an analytical formula for their GM. These states include Dicke states as special cases, which have already been realized in experiments. We also derive the GM of symmetric states generated from symmetric informationally complete POVMs (SIC POVMs) and use it to characterize all inequivalent SIC POVMs in three-dimensional Hilbert space that are covariant with respect to the Heisenberg-Weyl group. Finally, we describe an experimental scheme for creating the symmetric multiqubit states studied in this article and a possible scheme for measuring the permanence of the related Gram matrix.

  14. Table 15. Recoverable Coal Reserves at Producing Mines, Estimated Recoverable Reserves, and Demonstrated Reserve Base by Mining

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConferenceInstalled:a. AverageRecoverable

  15. Improving parameter estimation and water table depth simulation in a land surface model using GRACE water storage and estimated base flow data

    E-Print Network [OSTI]

    Lo, Min-Hui; Famiglietti, James S; Yeh, P. J.-F.; Syed, T. H

    2010-01-01T23:59:59.000Z

    2007), Estimating ground water storage changes in thestorage (i.e. , all of the snow, ice, surface water, soil moisture, and ground-

  16. Feasibility Studies of Applying Kalman Filter Techniques to Power System Dynamic State Estimation

    SciTech Connect (OSTI)

    Huang, Zhenyu; Schneider, Kevin P.; Nieplocha, Jarek

    2007-08-01T23:59:59.000Z

    Abstract—Lack of dynamic information in power system operations mainly attributes to the static modeling of traditional state estimation, as state estimation is the basis driving many other operations functions. This paper investigates the feasibility of applying Kalman filter techniques to enable the inclusion of dynamic modeling in the state estimation process and the estimation of power system dynamic states. The proposed Kalman-filter-based dynamic state estimation is tested on a multi-machine system with both large and small disturbances. Sensitivity studies of the dynamic state estimation performance with respect to measurement characteristics – sampling rate and noise level – are presented as well. The study results show that there is a promising path forward to implementation the Kalman-filter-based dynamic state estimation with the emerging phasor measurement technologies.

  17. State Energy Profiles and Estimates (SEDS) Report Archives

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oilAll Tables TablesPricesSpot Prices

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

    SciTech Connect (OSTI)

    Clark, E.L.

    1993-08-01T23:59:59.000Z

    Error propagation equations, based on the Taylor series model, are derived for the nondimensional ratios and coefficients most often encountered in high-speed wind tunnel testing. These include pressure ratio and coefficient, static force and moment coefficients, dynamic stability coefficients, calibration Mach number and Reynolds number. The error equations contain partial derivatives, denoted as sensitivity coefficients, which define the influence of free-stream Mach number, M{infinity}, on various aerodynamic ratios. To facilitate use of the error equations, sensitivity coefficients are derived and evaluated for nine fundamental aerodynamic ratios, most of which relate free-stream test conditions (pressure, temperature, density or velocity) to a reference condition. Tables of the ratios, R, absolute sensitivity coefficients, {partial_derivative}R/{partial_derivative}M{infinity}, and relative sensitivity coefficients, (M{infinity}/R) ({partial_derivative}R/{partial_derivative}M{infinity}), are provided as functions of M{infinity}.

  19. Table 40. No. 2 Diesel Fuel Prices by Sales Type, PAD District, and Selected States

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousandCubic Feet) DecadeV49 155 181 Estimation Results

  20. Table 40. No. 2 Diesel Fuel Prices by Sales Type, PAD District, and Selected States

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousandCubic Feet) DecadeV49 155 181 Estimation Results61.7

  1. Table 40. No. 2 Diesel Fuel Prices by Sales Type, PAD District, and Selected States

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousandCubic Feet) DecadeV49 155 181 Estimation

  2. Table 40. No. 2 Diesel Fuel Prices by Sales Type, PAD District, and Selected States

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousandCubic Feet) DecadeV49 155 181 Estimation57.1 62.0

  3. Table 40. No. 2 Diesel Fuel Prices by Sales Type, PAD District, and Selected States

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousandCubic Feet) DecadeV49 155 181 Estimation57.1

  4. Hierarchical models for estimating state and demographic trends in U.S. death penalty public opinion

    E-Print Network [OSTI]

    Gelman, Andrew

    Hierarchical models for estimating state and demographic trends in U.S. death penalty public?" Because the death penalty is governed by state laws rather than federal laws, it is of special interest logistic regression model to estimate support for the death penalty as a function of the year, the state

  5. Table HIST002R_2. Death rates for 113 selected causes by 5-year age groups, race and sex: United States, 1979-98

    E-Print Network [OSTI]

    Hunter, David

    _2. Death rates for 113 selected causes, by 5-year age groups, race and sex: United States, 1979Table HIST002R_2. Death rates for 113 selected causes by 5-year age groups, race and sex: United though the cause-of-death titles may be the same. Deaths rates are per 100,000 population in specified

  6. Table HIST002R_1. Death rates for 113 selected causes by 5-year age groups, race and sex: United States, 1979-98

    E-Print Network [OSTI]

    Hunter, David

    _1. Death rates for 113 selected causes, by 5-year age groups, race and sex: United States, 1979Table HIST002R_1. Death rates for 113 selected causes by 5-year age groups, race and sex: United though the cause-of-death titles may be the same. Deaths rates are per 100,000 population in specified

  7. Table 2. 2011 State energy-related carbon dioxide emisssions by fuel

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO) Highlights1,943,742Coalbed2011 State

  8. Table 3. 2011 State energy-related carbon dioxide emissions by sector

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO) Highlights1,943,742Coalbed20112011 State

  9. Table 1. State energy-related carbon dioxide emissions by year (2000-2011

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1 U.S. Department of Energy Energy Information3 OutlookSurveyState

  10. Table 2. 2011 State energy-related carbon dioxide emissions by fuel

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1 U.S. Department of Energy Energy Information32. Average Price2011 State

  11. Table 4. 2011 State energy-related carbon dioxide emission shares by sector

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1 U.S. Department of Energy Energy Information32. Average2011 State2011

  12. Table 5. Per capita energy-related carbon dioxide emissions by State (2000-201

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1 U.S. Department of Energy Energy Information32. Average2011 State2011Per

  13. Demonstration experiments for solid state physics using a table top mechanical Stirling refrigerator

    E-Print Network [OSTI]

    Osorio, M R; Rodrigo, J G; Suderow, H; Vieira, S; 10.1088/0143-0807/33/4/757

    2012-01-01T23:59:59.000Z

    Liquid free cryogenic devices are acquiring importance in basic science and engineering. But they can also lead to improvements in teaching low temperature an solid state physics to graduate students and specialists. Most of the devices are relatively expensive, but small sized equipment is slowly becoming available. Here, we have designed several simple experiments which can be performed using a small Stirling refrigerator. We discuss the measurement of the critical current and temperature of a bulk YBa2Cu3O(7-d) (YBCO) sample, the observation of the levitation of a magnet over a YBCO disk when cooled below the critical temperature and the observation of a phase transition using ac calorimetry. The equipment can be easily handled by students, and also used to teach the principles of liquid free cooling.

  14. Table 17. Estimated natural gas plant liquids and dry natural gas content of total wet natural gas proved reserves, 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14Total Delivered Residential Energy Consumption,Estimated

  15. Multi-area power system state estimation utilizing boundary measurements and phasor measurement units ( PMUs) 

    E-Print Network [OSTI]

    Freeman, Matthew A

    2006-10-30T23:59:59.000Z

    The objective of this thesis is to prove the validity of a multi-area state estimator and investigate the advantages it provides over a serial state estimator. This is done utilizing the IEEE 118 Bus Test System as a sample system. This thesis...

  16. 1240 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 15, NO. 4, NOVEMBER 2000 State Estimation Distributed Processing

    E-Print Network [OSTI]

    Baldick, Ross

    ) and the Southwest Power Pool (SPP) systems. I. INTRODUCTION TO HOST SCADA and Energy Management System soft- ware1240 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 15, NO. 4, NOVEMBER 2000 State Estimation Distributed- rithm to Power Systems State Estimation. We apply the Auxiliary Problem Principle to develop

  17. Communication Capacity Requirement for Reliable and Secure State Estimation in Smart Grid

    E-Print Network [OSTI]

    Qiu, Robert Caiming

    1 Communication Capacity Requirement for Reliable and Secure State Estimation in Smart Grid Husheng, Cookeville, TN Abstract-- Secure system state estimation is an important issue in smart grid to assure the information the- oretic perspective. The smart grid is modeled as a linear dynamic system. Then, the channel

  18. Trust-aware State Estimation Under False Data Injection in Distributed Sensor Networks

    E-Print Network [OSTI]

    Baras, John S.

    1 Trust-aware State Estimation Under False Data Injection in Distributed Sensor Networks Shanshan of nodes and the volatility of the network. In this paper, we focus on robust distributed state estimation Engineering University of Maryland, College Park, MD, 20742 Email: {sszheng,tjiang,baras}@umd.edu Abstract--Distributed

  19. Load Modeling and State Estimation Methods for Power Distribution Systems: Final Report

    SciTech Connect (OSTI)

    Tom McDermott

    2010-05-07T23:59:59.000Z

    The project objective was to provide robust state estimation for distribution systems, comparable to what has been available on transmission systems for decades. This project used an algorithm called Branch Current State Estimation (BCSE), which is more effective than classical methods because it decouples the three phases of a distribution system, and uses branch current instead of node voltage as a state variable, which is a better match to current measurement.

  20. FY 2013 State Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33Frequently20,000 Russian NuclearandJunetrackEllen|JulyR--FOIA SupportDOE's FY3 SummaryBusiness9

  1. FY 2005 State Table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment of Energy QuarterlyFWP95Office of

  2. FY 2007 State Table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment ofAppropriationBudget DOE: Energy,

  3. FY 2012 State Table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment6 FY 2007 FYEnergy And2 Federal

  4. QUANTITATIVE ESTIMATES ON THE HYDROGEN GROUND STATE ENERGY IN NON-RELATIVISTIC QED

    E-Print Network [OSTI]

    QUANTITATIVE ESTIMATES ON THE HYDROGEN GROUND STATE ENERGY IN NON-RELATIVISTIC QED J.-M. BARBAROUX for the hydrogen ground state energy in the Pauli-Fierz model up to the order O(5 log -1), where denotes). As a consequence, we prove that the ground state energy is not a real analytic function of , and verify

  5. Efficient Hydraulic State Estimation Technique Using Reduced Models of Urban Water Networks

    E-Print Network [OSTI]

    Preis, Ami

    This paper describes and demonstrates an efficient method for online hydraulic state estimation in urban water networks. The proposed method employs an online predictor-corrector (PC) procedure for forecasting future water ...

  6. N. Logic, E. Kyriakides, G. T. Heydt, "Lp State Estimators for Power Systems," N. Logic, E. Kyriakides, G. T. Heydt, "Lp state estimators for power systems," Journal of Electric Power

    E-Print Network [OSTI]

    1 N. Logic, E. Kyriakides, G. T. Heydt, "Lp State Estimators for Power Systems," N. Logic, E. Kyriakides, G. T. Heydt, "Lp state estimators for power systems," Journal of Electric Power Components and Systems, accepted for publication, 2002. #12;2 Lp State Estimators for Power Systems N. Logic E

  7. Study of the utilization and benefits of phasor measurement units for large scale power system state estimation

    E-Print Network [OSTI]

    Yoon, Yeo Jun

    2006-04-12T23:59:59.000Z

    This thesis will investigate the impact of the use of the Phasor Measurement Units (PMU) on the state estimation problem. First, incorporation of the PMU measurements in a conventional state estimation program will be discussed. Then, the effect...

  8. Petroleum Products Table 31. Motor Gasoline Prices by Grade...

    Gasoline and Diesel Fuel Update (EIA)

    table. 56 Energy Information AdministrationPetroleum Marketing Annual 2000 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  9. Petroleum Products Table 31. Motor Gasoline Prices by Grade...

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

    table. 56 Energy Information Administration Petroleum Marketing Annual 1995 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  10. Simultaneous parameter estimation and state smoothing of complex GARCH process in the presence of additive noise

    E-Print Network [OSTI]

    Cohen, Israel

    Simultaneous parameter estimation and state smoothing of complex GARCH process in the presence 2010 Keywords: GARCH Parameter estimation Noisy data Maximum likelihood Recursive maximum likelihood a b s t r a c t ARCH and GARCH models have been used recently in model-based signal processing

  11. Measurement calibration/tuning & topology processing in power system state estimation

    E-Print Network [OSTI]

    Zhong, Shan

    2005-02-17T23:59:59.000Z

    the implementation of this algorithm. A concise substation model is defined for this purpose. A friendly user interface that incorporates the two-stage algorithm into the conventional state estimator is developed. The performances of the two-stage state... estimation algorithms rely on accurate determination of suspect substations. A comprehensive identification procedure is described in chapter III. In order to evaluate the proposed procedure, a topology error library is created. Several identification...

  12. Survey of State-Level Cost and Benefit Estimates of Renewable Portfolio Standards

    SciTech Connect (OSTI)

    Heeter, J.; Barbose, G.; Bird, L.; Weaver, S.; Flores-Espino, F.; Kuskova-Burns, K.; Wiser, R.

    2014-05-01T23:59:59.000Z

    Most renewable portfolio standards (RPS) have five or more years of implementation experience, enabling an assessment of their costs and benefits. Understanding RPS costs and benefits is essential for policymakers evaluating existing RPS policies, assessing the need for modifications, and considering new policies. This study provides an overview of methods used to estimate RPS compliance costs and benefits, based on available data and estimates issued by utilities and regulators. Over the 2010-2012 period, average incremental RPS compliance costs in the United States were equivalent to 0.8% of retail electricity rates, although substantial variation exists around this average, both from year-to-year and across states. The methods used by utilities and regulators to estimate incremental compliance costs vary considerably from state to state and a number of states are currently engaged in processes to refine and standardize their approaches to RPS cost calculation. The report finds that state assessments of RPS benefits have most commonly attempted to quantitatively assess avoided emissions and human health benefits, economic development impacts, and wholesale electricity price savings. Compared to the summary of RPS costs, the summary of RPS benefits is more limited, as relatively few states have undertaken detailed benefits estimates, and then only for a few types of potential policy impacts. In some cases, the same impacts may be captured in the assessment of incremental costs. For these reasons, and because methodologies and level of rigor vary widely, direct comparisons between the estimates of benefits and costs are challenging.

  13. Improved estimates of the total correlation energy in the ground state of the water molecule

    E-Print Network [OSTI]

    Anderson, James B.

    Improved estimates of the total correlation energy in the ground state of the water molecule Arne National Laboratory, Richland, Washington 99352 Received 1 October 1996; accepted 5 February 1997 Two new calculations of the electronic energy of the ground state of the water molecule yield energies lower than those

  14. Estimated Benefits of IBWC Rio Grande Flood-Control Projects in the United States

    E-Print Network [OSTI]

    Sturdivant, Allen W.; Lacewell, Ronald D.; Michelsen, Ari M.; Rister, M. Edward; Assadian, Naomi; Eriksson, Marian; Freeman, Roger; Jacobs, Jennifer H.; Madison, W. Tom; McGuckin, James T.; Morrison, Wendy; Robinson, John R.C.; Staats, Chris; Sheng, Zhuping; Srinivasan, R.; Villalobos, Joshua I.

    TR- 275 2004 Estimated Benefits of IBWC Rio Grande Flood-Control Projects in the United States Allen W. Sturdivant Ronald D. Lacewell Ari M. Michelsen M. Edward Rister Naomi Assadian Marian Eriksson Roger Freeman Jennifer H... Flood-Control Projects in the United States Prepared for: INTERNATIONAL BOUNDARY AND WATER COMMISSION, UNITED STATES SECTION EL PASO, TEXAS SEPTEMBER 2004 Prepared by: Texas Agriculture Experiment Station, and Texas Water Resources Institute of the Texas...

  15. Asymptotic Efficiency and Finite Sample Performance of Frequentist Quantum State Estimation

    E-Print Network [OSTI]

    Raj Chakrabarti; Anisha Ghosh

    2011-11-15T23:59:59.000Z

    We undertake a detailed study of the performance of maximum likelihood (ML) estimators of the density matrix of finite-dimensional quantum systems, in order to interrogate generic properties of frequentist quantum state estimation. Existing literature on frequentist quantum estimation has not rigorously examined the finite sample performance of the estimators and associated methods of hypothesis testing. While ML is usually preferred on the basis of its asymptotic properties - it achieves the Cramer-Rao (CR) lower bound - the finite sample properties are often less than optimal. We compare the asymptotic and finite-sample properties of the ML estimators and test statistics for two different choices of measurement bases: the average case optimal or mutually unbiased bases (MUB) and a representative set of suboptimal bases, for spin-1/2 and spin-1 systems. We show that, in both cases, the standard errors of the ML estimators sometimes do not contain the true value of the parameter, which can render inference based on the asymptotic properties of the ML unreliable for experimentally realistic sample sizes. The results indicate that in order to fully exploit the information geometry of quantum states and achieve smaller reconstruction errors, the use of Bayesian state reconstruction methods - which, unlike frequentist methods, do not rely on asymptotic properties - is desirable, since the estimation error is typically lower due to the incorporation of prior knowledge.

  16. Table 16. Recoverable Coal Reserves and Average Recovery Percentage at Producing Underground Coal Mines by State and Mining Method,

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConferenceInstalled:a.Total

  17. Table 16. Natural gas delivered to consumers by sector, 2009-2013, and by state and sector, 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API Gravity Period: MonthlyDistrict of Columbia"Maryland" "TechnologyDakota"Virginia"1 Table 16. Natural

  18. Table ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2012, United States

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks4.E9. Total End-UseET1.

  19. 2003 CBECS RSE Tables

    Gasoline and Diesel Fuel Update (EIA)

    of the Excel tables (access from main detailed tables page) or in PDF format here: Building Characteristics for All Buildings (Tables A1-A8) RSE Tables: PDF, 16 pages, 312KB...

  20. Using graph theory to resolve state estimator issues faced by deregulated power systems

    E-Print Network [OSTI]

    Lei, Jiansheng

    2009-05-15T23:59:59.000Z

    ) Jiansheng Lei, B.S., Tsinghua University, Beijing, China; M.S., Tsinghua University, Beijing, China Chair of Advisory Committee: Dr. Garng M. Huang Power industry is undergoing a transition from the traditional regulated environment to the competitive... even under a contingency.............................................................................................1 B. Challenge 2: Run state estimator over a grid with extremely large size ...2 1.2 Topic 1: Network observability...

  1. Distributed state estimation and model predictive control of linear interconnected system

    E-Print Network [OSTI]

    Boyer, Edmond

    requirements, modern control systems are becoming more and more complex. For these processes, different controlDistributed state estimation and model predictive control of linear interconnected system: In this paper, a distributed and networked control system architecture based on independent Model Predictive

  2. Kalman filtering with unknown inputs via optimal state estimation of singular systems

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Kalman filtering with unknown inputs via optimal state estimation of singular systems M. DAROUACH de Lorraine, 54400 COSNES ET ROMAIN, FRANCE A new method for designing a Kalman filter for linear the Kalman filter, it is generally assumed that all system parameters, noise covariances, and inputs

  3. Cell Equalization In Battery Stacks Through State Of Charge Estimation Polling

    E-Print Network [OSTI]

    Stefanopoulou, Anna

    stack storage capacity, shortening the battery lifetime and, eventually, permanently damaging the cellsCell Equalization In Battery Stacks Through State Of Charge Estimation Polling Carmelo Speltino but it reduces the computational load of multiple EKF for every cell in the stack. Keywords: Battery Equalization

  4. False Data Injection Attacks against State Estimation in Electric Power Grids

    E-Print Network [OSTI]

    Ning, Peng

    False Data Injection Attacks against State Estimation in Electric Power Grids Yao Liu, Peng Ning@cs.unc.edu ABSTRACT A power grid is a complex system connecting electric power generators to consumers through power using IEEE test systems. Our results indicate that security protection of the electric power grid must

  5. False Data Injection Attacks against State Estimation in Electric Power Grids

    E-Print Network [OSTI]

    Reiter, Michael

    the measurements of meters at physically protected locations such as substations, such attacks can introduce13 False Data Injection Attacks against State Estimation in Electric Power Grids YAO LIU and PENG also defeat malicious measurements injected by attackers. In this article, we expose an unknown

  6. False Data Injection Attacks against State Estimation in Electric Power Grids

    E-Print Network [OSTI]

    Ning, Peng

    the measurements of meters at physically protected locations such as substations, such attacks can introduceFalse Data Injection Attacks against State Estimation in Electric Power Grids Yao Liu and Peng Ning also defeat malicious measurements injected by attackers. In this paper, we expose an unknown

  7. False Data Injection Attacks against State Estimation in Electric Power Grids

    E-Print Network [OSTI]

    Qiu, Robert Caiming

    @cs.unc.edu Abstract--A power grid is a complex system connecting electric power generators to consumers through power estimate the power grid state through analysis of meter measure- ments and power system models. Various malicious attacks. I. INTRODUCTION A power grid is a complex system connecting a variety of electric power

  8. A Biochemical Ocean State Estimate in the Southern1 Ocean Gas Exchange Experiment2

    E-Print Network [OSTI]

    Haine, Thomas W. N.

    of the oceanic31 carbon pool. It influences light penetration with consequences for primary productivity1 A Biochemical Ocean State Estimate in the Southern1 Ocean Gas Exchange Experiment2 S. Dwivedi1 , T. W. N. Haine2 and C. E. Del Castillo3 3 1 Department of Atmospheric and Ocean Sciences, University

  9. Table 7

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14Total DeliveredPrincipal shale gas:1 Table 7 Created on:

  10. General Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC) Environmental AssessmentsGeoffrey Campbelllong version)ConfinementGeneral Tables The

  11. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, VOL. 42, NO. 6, JUNE 1997 771 Optimal State Estimation for Stochastic Systems

    E-Print Network [OSTI]

    Latchman, Haniph A.

    when the system is Gaussian. Index Terms-- Dual control, entropy, Kalman filtering, state estimation. I systems. Fol- lowing the classical work of Gauss on least squares estimation and the modern day approach studies on least squares estimation. When applied to stochastic control systems, Kalman filtering theory

  12. Simultaneous state and unknown inputs estimation with PI and PMI observers for Takagi Sugeno model with unmeasurable premise

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Simultaneous state and unknown inputs estimation with PI and PMI observers for Takagi Sugeno model-- In this paper, a proportional integral (PI) and a proportional multiple integral observer (PMI) are proposed and PMI observers developed for linear systems. The state estimation error is written as a perturbed

  13. Capturing Dynamics in the Power Grid: Formulation of Dynamic State Estimation through Data Assimilation

    SciTech Connect (OSTI)

    Zhou, Ning; Huang, Zhenyu; Meng, Da; Elbert, Stephen T.; Wang, Shaobu; Diao, Ruisheng

    2014-03-31T23:59:59.000Z

    With the increasing complexity resulting from uncertainties and stochastic variations introduced by intermittent renewable energy sources, responsive loads, mobile consumption of plug-in vehicles, and new market designs, more and more dynamic behaviors are observed in everyday power system operation. To operate a power system efficiently and reliably, it is critical to adopt a dynamic paradigm so that effective control actions can be taken in time. The dynamic paradigm needs to include three fundamental components: dynamic state estimation; look-ahead dynamic simulation; and dynamic contingency analysis (Figure 1). These three components answer three basic questions: where the system is; where the system is going; and how secure the system is against accidents. The dynamic state estimation provides a solid cornerstone to support the other 2 components and is the focus of this study.

  14. Estimation of the Dynamic States of Synchronous Machines Using an Extended Particle Filter

    SciTech Connect (OSTI)

    Zhou, Ning; Meng, Da; Lu, Shuai

    2013-11-11T23:59:59.000Z

    In this paper, an extended particle filter (PF) is proposed to estimate the dynamic states of a synchronous machine using phasor measurement unit (PMU) data. A PF propagates the mean and covariance of states via Monte Carlo simulation, is easy to implement, and can be directly applied to a non-linear system with non-Gaussian noise. The extended PF modifies a basic PF to improve robustness. Using Monte Carlo simulations with practical noise and model uncertainty considerations, the extended PF’s performance is evaluated and compared with the basic PF and an extended Kalman filter (EKF). The extended PF results showed high accuracy and robustness against measurement and model noise.

  15. A Cyber Security Study of a SCADA Energy Management System: Stealthy Deception Attacks on the State Estimator

    E-Print Network [OSTI]

    Teixeira, André; Sandberg, Henrik; Johansson, Karl H

    2010-01-01T23:59:59.000Z

    The electrical power network is a critical infrastructure in today's society, so its safe and reliable operation is of major concern. State estimators are commonly used in power networks, for example, to detect faulty equipment and to optimally route power flows. The estimators are often located in control centers, to which large numbers of measurements are sent over unencrypted communication channels. Therefore cyber security for state estimators becomes an important issue. In this paper we analyze the cyber security of state estimators in supervisory control and data acquisition (SCADA) for energy management systems (EMS) operating the power network. Current EMS state estimation algorithms have bad data detection (BDD) schemes to detect outliers in the measurement data. Such schemes are based on high measurement redundancy. Although these methods may detect a set of basic cyber attacks, they may fail in the presence of an intelligent attacker. We explore the latter by considering scenarios where stealthy de...

  16. A Unified Open-Circuit-Voltage Model of Lithium-ion Batteries for State-of-Charge Estimation and State-of-Health Monitoring $

    E-Print Network [OSTI]

    Peng, Huei

    A Unified Open-Circuit-Voltage Model of Lithium-ion Batteries for State-of-Charge Estimation. Keywords: Electric vehicles, Lithium-ion batteries, Open-Circuit-Voltage, State-of-Charge, State is widely used for characterizing battery properties under different conditions. It contains important

  17. A framework for simulating and estimating the state and functional topology of complex dynamic geometric networks

    E-Print Network [OSTI]

    Marius Buibas; Gabriel A. Silva

    2010-06-22T23:59:59.000Z

    We present a framework for simulating signal propagation in geometric networks (i.e. networks that can be mapped to geometric graphs in some space) and for developing algorithms that estimate (i.e. map) the state and functional topology of complex dynamic geometric net- works. Within the framework we define the key features typically present in such networks and of particular relevance to biological cellular neural networks: Dynamics, signaling, observation, and control. The framework is particularly well-suited for estimating functional connectivity in cellular neural networks from experimentally observable data, and has been implemented using graphics processing unit (GPU) high performance computing. Computationally, the framework can simulate cellular network signaling close to or faster than real time. We further propose a standard test set of networks to measure performance and compare different mapping algorithms.

  18. FY 2009 Statistical Table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment6 FY 2007 FY 2008State TablesStatistical

  19. Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District...

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

    table. 56 Energy Information AdministrationPetroleum Marketing Annual 1998 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  20. Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District...

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

    table. 56 Energy Information AdministrationPetroleum Marketing Annual 1999 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  1. Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District...

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

    table. 56 Energy Information Administration Petroleum Marketing Annual 1995 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  2. Quantum process tomography and Linblad estimation of a solid state qubit

    E-Print Network [OSTI]

    M. Howard; J. Twamley; C. Wittmann; T. Gaebel; F. Jelezko; J. Wrachtrup

    2006-01-25T23:59:59.000Z

    We present an example of quantum process tomography (QPT) performed on a single solid state qubit. The qubit used is two energy levels of the triplet state in the Nitrogen-Vacancy defect in Diamond. Quantum process tomography is applied to a qubit which has been allowed to decohere for three different time periods. In each case the process is found in terms of the chi matrix representation and the affine map representation. The discrepancy between experimentally estimated process and the closest physically valid process is noted. The results of QPT performed after three different decoherence times are used to find the error generators, or Lindblad operators, for the system, using the technique introduced by Boulant et al. [N. Boulant, T.F. Havel, M.A. Pravia and D.G. Cory, Phys. Rev. A 67, 042322 (2003)].

  3. A robust state-of-charge estimator for multiple types of lithium-ion batteries using adaptive extended Kalman filter

    E-Print Network [OSTI]

    Mi, Chunting "Chris"

    A robust state-of-charge estimator for multiple types of lithium-ion batteries using adaptive a SOC estimator for suitable for multiple lithium ion battery chemistries. Proved the system robustness of charge (SoC) of multiple types of lithium ion battery (LiB) cells with adaptive extended Kalman filter

  4. Estimate of the Geothermal Energy Resource in the Major Sedimentary Basins in the United States (Presentation)

    SciTech Connect (OSTI)

    Esposito, A.; Porro, C.; Augustine, C.; Roberts, B.

    2012-09-01T23:59:59.000Z

    Because most sedimentary basins have been explored for oil and gas, well logs, temperatures at depth, and reservoir properties such as depth to basement and formation thickness are well known. The availability of this data reduces exploration risk and allows development of geologic exploration models for each basin. This study estimates the magnitude of recoverable geothermal energy from 15 major known U.S. sedimentary basins and ranks these basins relative to their potential. The total available thermal resource for each basin was estimated using the volumetric heat-in-place method originally proposed by (Muffler, 1979). A qualitative recovery factor was determined for each basin based on data on flow volume, hydrothermal recharge, and vertical and horizontal permeability. Total sedimentary thickness maps, stratigraphic columns, cross sections, and temperature gradient information was gathered for each basin from published articles, USGS reports, and state geological survey reports. When published data were insufficient, thermal gradients and reservoir properties were derived from oil and gas well logs obtained on oil and gas commission databases. Basin stratigraphy, structural history, and groundwater circulation patterns were studied in order to develop a model that estimates resource size, temperature distribution, and a probable quantitative recovery factor.

  5. CPMS Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy China U.S. Department ofJune 2,The BigSidingState6Report,COMMENTS ONPRGM Quality Program

  6. Design-Basis Flood Estimation for Site Characterization at Nuclear Power Plants in the United States of America

    SciTech Connect (OSTI)

    Prasad, Rajiv; Hibler, Lyle F.; Coleman, Andre M.; Ward, Duane L.

    2011-11-01T23:59:59.000Z

    The purpose of this document is to describe approaches and methods for estimation of the design-basis flood at nuclear power plant sites. Chapter 1 defines the design-basis flood and lists the U.S. Nuclear Regulatory Commission's (NRC) regulations that require estimation of the design-basis flood. For comparison, the design-basis flood estimation methods used by other Federal agencies are also described. A brief discussion of the recommendations of the International Atomic Energy Agency for estimation of the design-basis floods in its member States is also included.

  7. Developing a tool to estimate water withdrawal and consumption in electricity generation in the United States.

    SciTech Connect (OSTI)

    Wu, M.; Peng, J. (Energy Systems); ( NE)

    2011-02-24T23:59:59.000Z

    Freshwater consumption for electricity generation is projected to increase dramatically in the next couple of decades in the United States. The increased demand is likely to further strain freshwater resources in regions where water has already become scarce. Meanwhile, the automotive industry has stepped up its research, development, and deployment efforts on electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs). Large-scale, escalated production of EVs and PHEVs nationwide would require increased electricity production, and so meeting the water demand becomes an even greater challenge. The goal of this study is to provide a baseline assessment of freshwater use in electricity generation in the United States and at the state level. Freshwater withdrawal and consumption requirements for power generated from fossil, nonfossil, and renewable sources via various technologies and by use of different cooling systems are examined. A data inventory has been developed that compiles data from government statistics, reports, and literature issued by major research institutes. A spreadsheet-based model has been developed to conduct the estimates by means of a transparent and interactive process. The model further allows us to project future water withdrawal and consumption in electricity production under the forecasted increases in demand. This tool is intended to provide decision makers with the means to make a quick comparison among various fuel, technology, and cooling system options. The model output can be used to address water resource sustainability when considering new projects or expansion of existing plants.

  8. A Two-Stage Kalman Filter Approach for Robust and Real-Time Power System State Estimation

    SciTech Connect (OSTI)

    Zhang, Jinghe; Welch, Greg; Bishop, Gary; Huang, Zhenyu

    2014-04-01T23:59:59.000Z

    As electricity demand continues to grow and renewable energy increases its penetration in the power grid, realtime state estimation becomes essential for system monitoring and control. Recent development in phasor technology makes it possible with high-speed time-synchronized data provided by Phasor Measurement Units (PMU). In this paper we present a two-stage Kalman filter approach to estimate the static state of voltage magnitudes and phase angles, as well as the dynamic state of generator rotor angles and speeds. Kalman filters achieve optimal performance only when the system noise characteristics have known statistical properties (zero-mean, Gaussian, and spectrally white). However in practice the process and measurement noise models are usually difficult to obtain. Thus we have developed the Adaptive Kalman Filter with Inflatable Noise Variances (AKF with InNoVa), an algorithm that can efficiently identify and reduce the impact of incorrect system modeling and/or erroneous measurements. In stage one, we estimate the static state from raw PMU measurements using the AKF with InNoVa; then in stage two, the estimated static state is fed into an extended Kalman filter to estimate the dynamic state. Simulations demonstrate its robustness to sudden changes of system dynamics and erroneous measurements.

  9. Tracking shocked dust: State estimation for a complex plasma during a shock wave

    SciTech Connect (OSTI)

    Oxtoby, Neil P.; Ralph, Jason F.; Durniak, Celine; Samsonov, Dmitry [Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, L69 3GJ (United Kingdom)

    2012-01-15T23:59:59.000Z

    We consider a two-dimensional complex (dusty) plasma crystal excited by an electrostatically-induced shock wave. Dust particle kinematics in such a system are usually determined using particle tracking velocimetry. In this work we present a particle tracking algorithm which determines the dust particle kinematics with significantly higher accuracy than particle tracking velocimetry. The algorithm uses multiple extended Kalman filters to estimate the particle states and an interacting multiple model to assign probabilities to the different filters. This enables the determination of relevant physical properties of the dust, such as kinetic energy and kinetic temperature, with high precision. We use a Hugoniot shock-jump relation to calculate a pressure-volume diagram from the shocked dust kinematics. Calculation of the full pressure-volume diagram was possible with our tracking algorithm, but not with particle tracking velocimetry.

  10. Tabled Execution in Scheme

    SciTech Connect (OSTI)

    Willcock, J J; Lumsdaine, A; Quinlan, D J

    2008-08-19T23:59:59.000Z

    Tabled execution is a generalization of memorization developed by the logic programming community. It not only saves results from tabled predicates, but also stores the set of currently active calls to them; tabled execution can thus provide meaningful semantics for programs that seemingly contain infinite recursions with the same arguments. In logic programming, tabled execution is used for many purposes, both for improving the efficiency of programs, and making tasks simpler and more direct to express than with normal logic programs. However, tabled execution is only infrequently applied in mainstream functional languages such as Scheme. We demonstrate an elegant implementation of tabled execution in Scheme, using a mix of continuation-passing style and mutable data. We also show the use of tabled execution in Scheme for a problem in formal language and automata theory, demonstrating that tabled execution can be a valuable tool for Scheme users.

  11. Appendix B Tables

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

    B Right-of-Way Tower Configuration Tables and Figures Page B-1 Table B-1 West Alternative Tower Configurations Segment Segment Length (miles) Section (Tower to Tower) Additional...

  12. A critical review of methods used in the estimation of natural gas reserves: Natural gas reserves in the state of Texas. Some educational prerequisites in the field of petroleum economics and evaluation. 

    E-Print Network [OSTI]

    Crichton, John Alston

    1953-01-01T23:59:59.000Z

    A CRITICAL REVIEW OF METHODS USED IN THE ESTIMATION OF NATURAL GAS RESERVES NATURAL GAS RESERVES IN THE SI'AT. S OF TEXAS SOME EDUCATIONAL PREREQUISITES IN THE FIELD OF PETROLEUM ECONOMICS AND EVAI UATION Sy John Alston Crichton... ENGINEERING TABLE of CONTENTS ~Pa e A CRITICAL REVIEW OF METHODS USED IN THE ESTIMATION OF NATURAL GAS RESERVES Abstract Introdu=tion History of the Estimation of Gas Reserves Present Methods of Estimating Gas Reserves Meth& ds of Estimating Non...

  13. MA 111 --Worksheet 2.2 1. Given below is a table of values of the Consumer Price Index in December of the stated

    E-Print Network [OSTI]

    Lee, Carl

    MA 111 -- Worksheet 2.2 1. Given below is a table of values of the Consumer Price Index in December this average rate of real increase, project the tuition rates for the following years: Year Tuition in 2009 assess the amount of inflation using the Consumer Price Index. This index gives us the relative increase

  14. Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales...

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

    250 Energy Information AdministrationPetroleum Marketing Annual 1999 Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales Type, PAD District, and State (Thousand Gallons...

  15. Table 32. Conventional Motor Gasoline Prices by Grade, Sales...

    Gasoline and Diesel Fuel Update (EIA)

    Information AdministrationPetroleum Marketing Annual 1998 Table 32. Conventional Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  16. Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales...

    Gasoline and Diesel Fuel Update (EIA)

    - - - - W W - - - - - - See footnotes at end of table. 44. Refiner Motor Gasoline Volumes by Formulation, Sales Type, PAD District, and State 292 Energy...

  17. Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type...

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

    220 Energy Information AdministrationPetroleum Marketing Annual 1998 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per...

  18. Table 34. Reformulated Motor Gasoline Prices by Grade, Sales...

    Gasoline and Diesel Fuel Update (EIA)

    Information AdministrationPetroleum Marketing Annual 1998 Table 34. Reformulated Motor Gasoline Prices by Grade, Sales Type, PAD District, and Selected States (Cents per...

  19. Table 48. Prime Supplier Sales Volumes of Motor Gasoline by...

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

    Petroleum Marketing Annual 1995 Table 48. Prime Supplier Sales Volumes of Motor Gasoline by Grade, Formulation, PAD District, and State (Thousand Gallons per Day) -...

  20. Table 34. Reformulated Motor Gasoline Prices by Grade, Sales...

    Gasoline and Diesel Fuel Update (EIA)

    Information Administration Petroleum Marketing Annual 1995 Table 34. Reformulated Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  1. Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type...

    Gasoline and Diesel Fuel Update (EIA)

    220 Energy Information AdministrationPetroleum Marketing Annual 1999 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per...

  2. Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type...

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

    Energy Information Administration Petroleum Marketing Annual 1995 Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  3. Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type...

    Gasoline and Diesel Fuel Update (EIA)

    134 Energy Information AdministrationPetroleum Marketing Annual 1998 Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  4. Petroleum Products Table 43. Refiner Motor Gasoline Volumes...

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

    220 Energy Information AdministrationPetroleum Marketing Annual 2000 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per...

  5. Table 48. Prime Supplier Sales Volumes of Motor Gasoline by...

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

    Petroleum Marketing Annual 1998 Table 48. Prime Supplier Sales Volumes of Motor Gasoline by Grade, Formulation, PAD District, and State (Thousand Gallons per Day) -...

  6. Table 32. Conventional Motor Gasoline Prices by Grade, Sales...

    Gasoline and Diesel Fuel Update (EIA)

    - - - - W W - - - - - - See footnotes at end of table. 32. Conventional Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 86 Energy Information...

  7. Table 32. Conventional Motor Gasoline Prices by Grade, Sales...

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

    Information Administration Petroleum Marketing Annual 1995 Table 32. Conventional Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  8. Table 48. Prime Supplier Sales Volumes of Motor Gasoline by...

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

    Petroleum Marketing Annual 1999 Table 48. Prime Supplier Sales Volumes of Motor Gasoline by Grade, Formulation, PAD District, and State (Thousand Gallons per Day) -...

  9. Table 32. Conventional Motor Gasoline Prices by Grade, Sales...

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

    - - - - 64.7 64.7 - - - - - - See footnotes at end of table. 32. Conventional Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 86 Energy Information...

  10. Table 33. Oxygenated Motor Gasoline Prices by Grade, Sales Type...

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

    - - - - - - - - - - - - See footnotes at end of table. 33. Oxygenated Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 116 Energy Information...

  11. Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type...

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

    Energy Information Administration Petroleum Marketing Annual 1995 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per...

  12. Petroleum Products Table 43. Refiner Motor Gasoline Volumes...

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

    Energy Information Administration Petroleum Marketing Annual 1995 Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State (Thousand Gallons per...

  13. Table 33. Oxygenated Motor Gasoline Prices by Grade, Sales Type...

    Gasoline and Diesel Fuel Update (EIA)

    Information Administration Petroleum Marketing Annual 1995 Table 33. Oxygenated Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  14. Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales...

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

    250 Energy Information AdministrationPetroleum Marketing Annual 1998 Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales Type, PAD District, and State (Thousand Gallons...

  15. Table 34. Reformulated Motor Gasoline Prices by Grade, Sales...

    Gasoline and Diesel Fuel Update (EIA)

    Information AdministrationPetroleum Marketing Annual 1999 Table 34. Reformulated Motor Gasoline Prices by Grade, Sales Type, PAD District, and Selected States (Cents per...

  16. Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales...

    Gasoline and Diesel Fuel Update (EIA)

    Energy Information Administration Petroleum Marketing Annual 1995 Table 44. Refiner Motor Gasoline Volumes by Formulation, Sales Type, PAD District, and State (Thousand Gallons...

  17. Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type...

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

    134 Energy Information AdministrationPetroleum Marketing Annual 1999 Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon...

  18. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

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

    Marketing Annual 1999 Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State (Thousand Gallons per Day) -...

  19. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

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

    See footnotes at end of table. 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State 386 Energy Information...

  20. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

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

    Marketing Annual 1995 Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State (Thousand Gallons per Day) -...

  1. Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane...

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

    Marketing Annual 1998 Table 49. Prime Supplier Sales Volumes of Aviation Fuels, Propane, and Residual Fuel Oil by PAD District and State (Thousand Gallons per Day) -...

  2. Table 50. Prime Supplier Sales Volumes of Distillate Fuel Oils...

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

    Marketing Annual 1998 359 Table 50. Prime Supplier Sales Volumes of Distillate Fuel Oils and Kerosene by PAD District and State (Thousand Gallons per Day) - Continued...

  3. Table 50. Prime Supplier Sales Volumes of Distillate Fuel Oils...

    Gasoline and Diesel Fuel Update (EIA)

    Marketing Annual 1999 359 Table 50. Prime Supplier Sales Volumes of Distillate Fuel Oils and Kerosene by PAD District and State (Thousand Gallons per Day) - Continued...

  4. Abstract--This paper investigates the errors introduced in the positive sequence state estimation due to the usual assumptions of

    E-Print Network [OSTI]

    transposed transmission lines. A three-phase state estimator is first developed in order to verify the actual to be met: · Transposition of the transmission lines · Even distribution of bus loads · Maintaining balanced an uneven distribution among the three phases, or relatively long but non-transposed transmission lines

  5. Experimental Validation of a Lithium-Ion Battery State of Charge Estimation with an Extended Kalman Filter

    E-Print Network [OSTI]

    Stefanopoulou, Anna

    Experimental Validation of a Lithium-Ion Battery State of Charge Estimation with an Extended Kalman unobservable conditions as discussed in [3] and allow the application of an extended Kalman Filter (EKF) from Kalman Filter (EKF) based on the averaged model and the performance is shown experimentally in a 10 cell

  6. State Estimation for Force-Controlled Humanoid Balance using Simple Models in the Presence of Modeling Error

    E-Print Network [OSTI]

    State Estimation for Force-Controlled Humanoid Balance using Simple Models in the Presence-based control frameworks, such as model predictive control (MPC), use the expected dynamics to generate that requires active balance control in the presence of modeling error. Primus humanoid shown in Figure 1

  7. Robustness analysis of State-of-Charge estimation methods for two types of Li-ion batteries

    E-Print Network [OSTI]

    Peng, Huei

    Robustness analysis of State-of-Charge estimation methods for two types of Li-ion batteries i g h l i g h t s battery model parameters are optimized. 2012 Accepted 1 June 2012 Available online 9 June 2012 Keywords: Battery management systems SOC

  8. Lithium-Ion battery State of Charge estimation with a Kalman Filter based on a electrochemical model

    E-Print Network [OSTI]

    Stefanopoulou, Anna

    Lithium-Ion battery State of Charge estimation with a Kalman Filter based on a electrochemical model Domenico Di Domenico, Giovanni Fiengo and Anna Stefanopoulou Abstract-- Lithium-ion battery hybrid electric vehicles (HEV). In most cases the lithium-ion battery performance plays an important role

  9. IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 16, NO. 2, MAY 2001 273 State Estimator Condition Number Analysis

    E-Print Network [OSTI]

    Baldick, Ross

    data detection. In this analysis, to make the problem manageable, we use the 1-norm to calculateIEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 16, NO. 2, MAY 2001 273 State Estimator Condition Number is related to available finite precision arithmetic. The more precision in the calculations, the higher

  10. A Passive State-Machine Based Approach for Reliable Estimation of TCP Sushant Rewaskar Jasleen Kaur Don Smith

    E-Print Network [OSTI]

    North Carolina at Chapel Hill, University of

    A Passive State-Machine Based Approach for Reliable Estimation of TCP Losses Sushant Rewaskar Technical report No. TR06-002 January 20, 2006 Abstract - While it is well-known that TCP performance degrades significantly on experiencing packet losses, not much is known about the way in which TCP losses

  11. Environmental Justice Tables

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

    ... H-1 Table H-1. Poverty Thresholds in 1999 by Size of Family and Number of Related Children Under 18 Years...

  12. State-level evaluations of the Weatherization Assistance Program in 1990-1996: a metaevaluation that estimates national savings

    SciTech Connect (OSTI)

    Berry, L.

    1997-01-01T23:59:59.000Z

    The DOE Weatherization Assistance Program is one of the largest energy conservation programs in the nation. To obtain an updated estimate of national Program savings, an approach of metaevaluation was selected, which involved locating, assembling, and summarizing the results of all state-level evaluations of the Program that have become available since 1990. All of the savings estimates that are presented in this report are for dwellings that heat primarily with natural gas.This review of the state-level evaluations conducted since 1990 concluded that Program performance has improved significantly in the last seven years. The finding that savings are increasing are supported by a literature review, within-state comparisons of savings over time, and regression modeling results.

  13. Estimated Value of Service Reliability for Electric Utility Customers in the United States

    E-Print Network [OSTI]

    Sullivan, M.J.

    2009-01-01T23:59:59.000Z

    Goods: The Contingent Valuation Method. Resources for theare called contingent valuation methods or stated preference

  14. Neural Drive Estimation Using the Hypothesis of Muscle Synergies and the State-Constrained Kalman Filter

    E-Print Network [OSTI]

    Bouaynaya, Nidhal

    estimated, the neural drive can be used to control upper- extremity myoelectric prosthesis. Commonly prosthesis control problem [1]. Such algorithms are based on the assumption that there exist distinguishable the hypothesis of muscle synergies to estimate the neural drive from the surface myoelectric signal. Once

  15. Convolution particle filtering for parameter estimation in general state-space models

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    of these aspects [6] [4]. The second approach takes place in a classical Bayesian framework, a prior probability suited, given the context of parameter estimation. Firstly the usual non Bayesian statistical estimates results in practice but suffer from an absence of theoretical backing. The particle filters propose a good

  16. Abstract--This paper addresses a problem in state estimators for power systems. The issue of non-collocated measurements is

    E-Print Network [OSTI]

    .e., the `states') are estimated. The process usually uses minimum least squares methods. Power system measurements to information loss through analog to digital conver- sion. State estimation methods can flag and smooth out bad into a digital signal by an analog / digital converter

  17. Cyber Security Analysis of State Estimators in Electric Power Systems Andre Teixeira, Saurabh Amin, Henrik Sandberg, Karl H. Johansson, and Shankar S. Sastry

    E-Print Network [OSTI]

    Johansson, Karl Henrik

    Cyber Security Analysis of State Estimators in Electric Power Systems Andr´e Teixeira, Saurabh Amin security of state estimators in Supervisory Control and Data Acquisition (SCADA) systems operating in power random outliers in the measurement data. Such schemes are based on high measurement redundancy. Although

  18. Discrete State Estimators for Systems on a Lattice D. Del Vecchio

    E-Print Network [OSTI]

    Murray, Richard M.

    to be final state determinable are given [4]. In Alessandri et al., Luenberger-like observers are proposed

  19. Current (2009) State-of-the-Art Hydrogen Production Cost Estimate Using Water Electrolysis

    Fuel Cell Technologies Publication and Product Library (EERE)

    This independent review examines DOE cost targets for state-of-the art hydrogen production using water electrolysis.

  20. ESTIMATING THE ECONOMIC IMPACT OF UNIVERSITIES: THE CASE OF BOWLING GREEN STATE UNIVERSITY

    E-Print Network [OSTI]

    Michael C. Carroll; Bruce W. Smith

    study of Bowling Green State University, Ohio. The most widely cited finding of the study was that for

  1. Current (2009) State-of-the-Art Hydrogen Production Cost Estimate Using Water Electrolysis: Independent Review

    SciTech Connect (OSTI)

    Not Available

    2009-09-01T23:59:59.000Z

    This independent review examines DOE cost targets for state-of-the art hydrogen production using water electrolysis.

  2. 2003 CBECS Detailed Tables: Summary

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

    c12-pdf c12.xls c12.html Electricity (Tables C13-C22) set10.pdf Table C13. Total Electricity Consumption and Expenditures c13.pdf c13.xls c13.html Table C14. Electricity...

  3. Embedded avionics with Kalman state estimation for a novel micro-scale unmanned aerial vehicle

    E-Print Network [OSTI]

    Tzanetos, Theodore

    2013-01-01T23:59:59.000Z

    An inertial navigation system leveraging Kalman estimation techniques and quaternion dynamics is developed for deployment to a micro-scale unmanned aerial vehicle (UAV). The capabilities, limitations, and requirements of ...

  4. Estimated Value of Service Reliability for Electric Utility Customers in the United States

    SciTech Connect (OSTI)

    Sullivan, M.J.; Mercurio, Matthew; Schellenberg, Josh

    2009-06-01T23:59:59.000Z

    Information on the value of reliable electricity service can be used to assess the economic efficiency of investments in generation, transmission and distribution systems, to strategically target investments to customer segments that receive the most benefit from system improvements, and to numerically quantify the risk associated with different operating, planning and investment strategies. This paper summarizes research designed to provide estimates of the value of service reliability for electricity customers in the US. These estimates were obtained by analyzing the results from 28 customer value of service reliability studies conducted by 10 major US electric utilities over the 16 year period from 1989 to 2005. Because these studies used nearly identical interruption cost estimation or willingness-to-pay/accept methods it was possible to integrate their results into a single meta-database describing the value of electric service reliability observed in all of them. Once the datasets from the various studies were combined, a two-part regression model was used to estimate customer damage functions that can be generally applied to calculate customer interruption costs per event by season, time of day, day of week, and geographical regions within the US for industrial, commercial, and residential customers. Estimated interruption costs for different types of customers and of different duration are provided. Finally, additional research and development designed to expand the usefulness of this powerful database and analysis are suggested.

  5. Estimated Value of Service Reliability for Electric Utility Customers in the United States

    E-Print Network [OSTI]

    Sullivan, M.J.

    2009-01-01T23:59:59.000Z

    kW demand and costs per annual kWh sales. Cost estimates arePer Un-served kWh Cost Per Annual kWh Small C&I Cost PerPer Un-served kWh Cost Per Annual kWh Residential Cost Per

  6. Real-time State Estimation on Micro-grids Ying Hu, Anthony Kuh, Aleksandar Kavcic

    E-Print Network [OSTI]

    Kavcic, Aleksandar

    . In addition, the proposed graphical model can integrate new models for solar/wind cor- relation that will help been made on the individual feeder circuit estimating the customer load characteristics. One reason for this lack of study is that there is hardly any real-time load measure- ments for individual customers

  7. Los Angeles, California, May 6 -9, 2012 A Behavioral Algorithm for State of Charge Estimation

    E-Print Network [OSTI]

    He, Lei

    conditions while producing adequate re- sults with other battery types or discharge con- ditions. Moreover an electrochemical battery. A variety of methods to solve this estimation problem have been proposed in the literature. However, most of these methods either assume equivalent circuit models for the battery and thus

  8. A Method for Estimating Undiscovered Geothermal Resources in...

    Open Energy Info (EERE)

    was estimated using digital maps of geothermal wells, temperature gradient holes, oil wells, water wells, and depth to the water table. The resulting resource estimate does...

  9. Table 1 -ESTIMATED REDUCTION IN 1985 COTTON YIELDS RESULTING FROM INSECTDAMAGE TOTAL YIELD 13,622 bales INSECTS Loss in AL AZ AR CA FL GA LA MS MO NM NC OK SC TN TX VA No.

    E-Print Network [OSTI]

    Ray, David

    Average cost for all states nTotal yield for all states o Total acres for all states *Does not include BWE cost

  10. Performance Contracting and Energy Efficiency in the State Government Market

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2008-01-01T23:59:59.000Z

    2 Table 3. ESPC projects completed in state governmentlevel characteristics for ESPC projects in state government11 Table 11. Aggregate ESPC project

  11. Geothermal -- The Energy Under Our Feet: Geothermal Resource Estimates for the United States

    SciTech Connect (OSTI)

    Green, B. D.; Nix, R. G.

    2006-11-01T23:59:59.000Z

    On May 16, 2006, the National Renewable Energy Laboratory (NREL) in Golden, Colorado hosted a geothermal resources workshop with experts from the geothermal community. The purpose of the workshop was to re-examine domestic geothermal resource estimates. The participating experts were organized into five working groups based on their primary area of expertise in the following types of geothermal resource or application: (1) Hydrothermal, (2) Deep Geothermal Systems, (3) Direct Use, (4) Geothermal Heat Pumps (GHPs), and (5) Co-Produced and Geopressured. The workshop found that the domestic geothermal resource is very large, with significant benefits.

  12. A Biochemical Upper Ocean State Estimate in the Southern Ocean GasEx Region

    E-Print Network [OSTI]

    Haine, Thomas W. N.

    Methods: Data Sources: In-situ: T, S, CDOM (350, 380, 400 nm), SF6 from SO GasEx cruise. Satellite: Sea. CDOM photodegradation model (del Vecchio & Blough, 2002). SF6 model including deliberate release multipliers ("4DVAR" method). Controls are Initial conditions for T, S, (u, v), CDOM,& SF6 . The state

  13. Approximate Conditional Least Squares Estimation of a Nonlinear State-Space Model via Unscented Kalman

    E-Print Network [OSTI]

    Chan, Kung-Sik

    Kalman Filter Kwang Woo Ahn Division of Biostatistics Medical College of Wisconsin, Milwaukee, WI 53226 function computed approximately via unscented Kalman filter (UKF). We derive conditions 1 #12;under which. ---------------------------- Keywords: Nonlinear time series; State-space model; Unscented Kalman filter; SIR model. 1. INTRODUCTION

  14. Table of Contents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn April 23, 2014,ZaleskiThis Decision considersTable 1: Points of Entry/Exit andTable

  15. Table_of_Contents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn April 23, 2014,ZaleskiThis Decision considersTable 1: Points of Entry/ExitTable of

  16. 1020 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 62, NO. 3, MARCH 2013 State of Charge Estimation of Lithium-Ion Batteries

    E-Print Network [OSTI]

    Mi, Chunting "Chris"

    Estimation of Lithium-Ion Batteries in Electric Drive Vehicles Using Extended Kalman Filtering Zheng Chen. Index Terms--Extended Kalman filter (EKF), hardware-in- the-loop, lithium-ion battery, nonlinear battery accurate battery state of charge (SOC) estimation method for electric drive vehicles is developed based

  17. 1614 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 63, NO. 4, MAY 2014 The State of Charge Estimation of Lithium-Ion

    E-Print Network [OSTI]

    Mi, Chunting "Chris"

    Estimation of Lithium-Ion Batteries Based on a Proportional-Integral Observer Jun Xu, Student Member, IEEE--With the development of electric drive vehicles (EDVs), the state-of-charge (SOC) estimation for lithium-ion (Li of lithium-ion batteries in EDVs. The structure of the proposed PI observer is analyzed, and the con

  18. Quantitative estimates on the Hydrogen ground state energy in non-relativistic QED

    E-Print Network [OSTI]

    Jean-Marie Barbaroux; Thomas Chen; Semjon Vugalter; Vitali Vougalter

    2010-06-04T23:59:59.000Z

    In this paper, we determine the exact expression for the hydrogen binding energy in the Pauli-Fierz model up to the order $O(\\alpha^5\\log\\alpha^{-1})$, where $\\alpha$ denotes the finestructure constant, and prove rigorous bounds on the remainder term of the order $o(\\alpha^5\\log\\alpha^{-1})$. As a consequence, we prove that the binding energy is not a real analytic function of $\\alpha$, and verify the existence of logarithmic corrections to the expansion of the ground state energy in powers of $\\alpha$, as conjectured in the recent literature.

  19. State energy price and expenditure report 1989

    SciTech Connect (OSTI)

    Not Available

    1991-09-30T23:59:59.000Z

    The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates for the 50 States, the District of Columbia, and the United States. The estimates are provided by energy source (e.g., petroleum, natural gas, coal, and electricity) and by major consuming or economic sector. This report is an update of the State Energy Price and Expenditure Report 1988 published in September 1990. Changes from the last report are summarized in a section of the documentation. Energy price and expenditure estimates are published for the years 1970, 1975, 1980, and 1985 through 1989. Documentation follows the tables and describes how the price estimates are developed, including sources of data, methods of estimation, and conversion factors applied. Consumption estimates used to calculate expenditures, and the documentation for those estimates, are from the State Energy Data Report, Consumption Estimates, 1960--1989 (SEDR), published in May 1991. Expenditures are calculated by multiplying the price estimates by the consumption estimates, adjusted to remove process fuel and intermediate product consumption. All expenditures are consumer expenditures, that is, they represent estimates of money directly spent by consumers to purchase energy, generally including taxes. 11 figs., 43 tabs.

  20. Cost Recovery Charge (CRC) Calculation Tables

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

    Cost Recovery Charge (CRC) Calculation Table Updated: March 20, 2015 FY 2016 February 2015 CRC Calculation Table (pdf) Final FY 2015 CRC Letter & Table (pdf) Note: The Cost...

  1. Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type...

    Gasoline and Diesel Fuel Update (EIA)

    150.0 2,026.7 W W 234.5 161.7 - 396.3 See footnotes at end of table. 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State 262 Energy Information...

  2. Table 48. Prime Supplier Sales Volumes of Motor Gasoline by...

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

    - - 466.1 466.1 See footnotes at end of table. 48. Prime Supplier Sales Volumes of Motor Gasoline by Grade, Formulation, PAD District, and State 356 Energy Information...

  3. Table 43. Refiner Motor Gasoline Volumes by Grade, Sales Type...

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

    253.2 2,222.4 W W 206.4 134.3 - 340.7 See footnotes at end of table. 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State 262 Energy Information...

  4. Petroleum Products Table 43. Refiner Motor Gasoline Volumes...

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

    150.0 2,026.7 W W 234.5 161.7 - 396.3 See footnotes at end of table. 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State 262 Energy Information...

  5. Petroleum Products Table 43. Refiner Motor Gasoline Volumes...

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

    253.2 2,222.4 W W 206.4 134.3 - 340.7 See footnotes at end of table. 43. Refiner Motor Gasoline Volumes by Grade, Sales Type, PAD District, and State 262 Energy Information...

  6. Table 48. Prime Supplier Sales Volumes of Motor Gasoline by...

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

    - - 532.1 532.1 See footnotes at end of table. 48. Prime Supplier Sales Volumes of Motor Gasoline by Grade, Formulation, PAD District, and State 356 Energy Information...

  7. DOE Zero Energy Ready Home Second Production Builder Round Table

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

    Second Production Builder Round Table January 2015 NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United...

  8. State coal profiles, January 1994

    SciTech Connect (OSTI)

    Not Available

    1994-02-02T23:59:59.000Z

    The purpose of State Coal Profiles is to provide basic information about the deposits, production, and use of coal in each of the 27 States with coal production in 1992. Although considerable information on coal has been published on a national level, there is a lack of a uniform overview for the individual States. This report is intended to help fill that gap and also to serve as a framework for more detailed studies. While focusing on coal output, State Coal Profiles shows that the coal-producing States are major users of coal, together accounting for about three-fourths of total US coal consumption in 1992. Each coal-producing State is profiled with a description of its coal deposits and a discussion of the development of its coal industry. Estimates of coal reserves in 1992 are categorized by mining method and sulfur content. Trends, patterns, and other information concerning production, number of mines, miners, productivity, mine price of coal, disposition, and consumption of coal are detailed in statistical tables for selected years from 1980 through 1992. In addition, coal`s contribution to the State`s estimated total energy consumption is given for 1991, the latest year for which data are available. A US summary of all data is provided for comparing individual States with the Nation as a whole. Sources of information are given at the end of the tables.

  9. Advanced Vehicle Technologies Awards Table

    Broader source: Energy.gov [DOE]

    The table contains a listing of the applicants, their locations, the amounts of the awards, and description of each project.

  10. Mentoring Guide TABLE OF CONTENTS

    E-Print Network [OSTI]

    Dasgupta, Dipankar

    Mentoring Guide 1 #12;TABLE OF CONTENTS Introduction...........................................................................................................3 CCFA Mentoring Guide.........................................................................................3 Why Do I Need A Mentor

  11. Table SI-1. kOH, a, F, and SOA yield values for VOCs. Not all VOCs are listed. Yields are for Mo = 5 g/m3. "(E)" indicates that the values are estimated.

    E-Print Network [OSTI]

    Meskhidze, Nicholas

    ) a F Y (%) CO 0.24 1.0 1 0 methane 0.0063 2.0 1 0 ethane 0.3 2.0 0.98 0 propane 1.1 2.0 0.96 0 n-butane,2,3,4 tetramethylbenzene (M) 3-methyl 2-butanone (T) propanal (T) methylethylketone (T) #12;Table SI-2. P(Ox) pptv/s % P(SOA) 10-6 µg m-3 /s % CO 3500 0.8 8.0 0 0 ethane 27.3 0.02 0.1 0 0 propane 205 0.44 4.1 0 0

  12. Estimating effects of energy planning on environmental impacts in the Western United States

    SciTech Connect (OSTI)

    Baechler, M.C.; Cothran, J.N.

    1994-12-01T23:59:59.000Z

    As part of their long-term planning process, utilities and government agencies are choosing power generation and conservation strategies that will effect environmental interactions for decades to come. In the US, power marketing administrations within the US Department of Energy have a strong influence over the strategies to be implemented in large multi-state regions. Pacific Northwest Laboratories (PNL) prepared environmental impact statements (EIS) for two power marketing agencies, the Western Area Power Administration (Western) and Bonneville Power Administration (Bonneville). The Western EIS assessed the effects of integrated resource planing (IRP) on the public utilities Western serves, while the Bonneville EIS assessed the effects of acquiring new energy resources in the pacific Northwest. The results were found using models that simulated utility systems. In both cases, environmental impacts were reduced when the conservation strategy in question was considered. This paper describes the results of the environmental analyses for the two agencies and compares the results with those of another simplified approach that relies on attributing emissions of new resources based on an extrapolation of existing capacity.

  13. Application of a Rule-Based Model to Estimate Mercury Exchange for Three Background Biomes in the Continental United States

    SciTech Connect (OSTI)

    Hartman, Jelena S. [University of Nevada, Reno; Weisberg, Peter J [University of Nevada, Reno; Pillai, Rekha [University of Nevada, Reno; Ericksen, Joey A. [University of Nevada, Reno; Gustin, Mae S. [University of Nevada, Reno; Kuiken, Todd [Tennessee Technological University; Zhang, Hong [Tennessee Technological University; Lindberg, Steven Eric [ORNL; Rytuba, J. J. [U.S. Geological Survey, Menlo Park, CA

    2009-07-01T23:59:59.000Z

    Ecosystems that have low mercury (Hg) concentrations (i.e., not enriched or impacted by geologic or anthropogenic processes) cover most of the terrestrial surface area of the earth yet their role as a net source or sink for atmospheric Hg is uncertain. Here we use empirical data to develop a rule-based model implemented within a geographic information system framework to estimate the spatial and temporal patterns of Hg flux for semiarid deserts, grasslands, and deciduous forests representing 45% of the continental United States. This exercise provides an indication of whether these ecosystems are a net source or sink for atmospheric Hg as well as a basis for recommendation of data to collect in future field sampling campaigns. Results indicated that soil alone was a small net source of atmospheric Hg and that emitted Hg could be accounted for based on Hg input by wet deposition. When foliar assimilation and wet deposition are added to the area estimate of soil Hg flux these biomes are a sink for atmospheric Hg.

  14. 1999 CBECS Detailed Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National and Regional Data; Row: NAICS8) Distribution Category UC-950 Cost and Quality of Fuels for Electric Utility Plants 1998 Tables

  15. Origin State Destination State

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

    5. Estimated rail transportation rates for coal, state to state, STB data Origin State Destination State 2001 2002 2003 2004 2005 2006 2007 2008 2009 2001-2009 2008-2009 Alabama...

  16. Origin State Destination State

    Gasoline and Diesel Fuel Update (EIA)

    6. Estimated rail transportation rates for coal, state to state, STB data Origin State Destination State 2001 2002 2003 2004 2005 2006 2007 2008 2009 2001-2009 2008-2009 Alabama...

  17. Savings estimates for the United States Environmental Protection Agency?s ENERGY STAR voluntary product labeling program

    SciTech Connect (OSTI)

    Sanchez, Marla Christine; Sanchez, Marla Christine; Brown, Richard; Homan, Gregory; Webber, Carrie

    2008-06-03T23:59:59.000Z

    ENERGY STAR is a voluntary energy efficiency-labeling program operated jointly by the United States Department of Energy and the United States Environmental Protection Agency (US EPA). Since the program inception in 1992, ENERGY STAR has become a leading international brand for energy efficient products. ENERGY STAR's central role in the development of regional, national, and international energy programs necessitates an open process whereby its program achievements to date as well as projected future savings are shared with committed stakeholders. Through 2006, US EPA?S ENERGY STAR labeled products saved 4.8 EJ of primary energy and avoided 82 Tg C equivalent. We project that US EPA?S ENERGY STAR labeled products will save 12.8 EJ and avoid 203 Tg C equivalent over the period 2007-2015. A sensitivity analysis examining two key inputs (carbon factor and ENERGY STAR unit sales) bounds the best estimate of carbon avoided between 54 Tg C and 107 Tg C (1993 to 2006) and between 132 Tg C and 278 Tg C (2007 to 2015).

  18. Table A1. Refiner/Reseller Motor Gasoline Prices by Grade, PAD...

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

    AdministrationPetroleum Marketing Annual 1999 401 Table A1. RefinerReseller Motor Gasoline Prices by Grade, PAD District and State, 1984-Present (Cents per Gallon...

  19. Table A1. Refiner/Reseller Motor Gasoline Prices by Grade, PAD...

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

    Information Administration Petroleum Marketing Annual 1995 Table A1. RefinerReseller Motor Gasoline Prices by Grade, PAD District and State, 1984-Present (Cents per Gallon...

  20. Table 40. No. 2 Diesel Fuel Prices by Sales Type, PAD District...

    Gasoline and Diesel Fuel Update (EIA)

    Energy Information AdministrationPetroleum Marketing Annual 1999 191 Table 40. No. 2 Diesel Fuel Prices by Sales Type, PAD District, and Selected States (Cents per Gallon...

  1. Table 40. No. 2 Diesel Fuel Prices by Sales Type, PAD District...

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

    Energy Information AdministrationPetroleum Marketing Annual 1998 191 Table 40. No. 2 Diesel Fuel Prices by Sales Type, PAD District, and Selected States (Cents per Gallon...

  2. Table 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil...

    Gasoline and Diesel Fuel Update (EIA)

    Petroleum Marketing Annual 1998 295 Table 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil Volumes by PAD District and State (Thousand Gallons per Day) - Continued...

  3. Table 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil...

    Gasoline and Diesel Fuel Update (EIA)

    Petroleum Marketing Annual 1995 337 Table 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil Volumes by PAD District and State (Thousand Gallons per Day) - Continued...

  4. Table 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil...

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

    Petroleum Marketing Annual 1999 295 Table 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil Volumes by PAD District and State (Thousand Gallons per Day) - Continued...

  5. Overpressure prediction by mean total stress estimate using well logs for compressional environments with strike-slip or reverse faulting stress state

    E-Print Network [OSTI]

    Ozkale, Aslihan

    2007-04-25T23:59:59.000Z

    OVERPRESSURE PREDICTION BY MEAN TOTAL STRESS ESTIMATE USING WELL LOGS FOR COMPRESSIONAL ENVIRONMENTS WITH STRIKE-SLIP OR REVERSE FAULTING STRESS STATE A Thesis by ASLIHAN OZKALE Submitted to the Office of Graduate Studies... of Texas A&M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE December 2006 Major Subject: Petroleum Engineering OVERPRESSURE PREDICTION BY MEAN TOTAL STRESS ESTIMATE USING WELL LOGS...

  6. State estimation of an acid gas removal (AGR) plant as part of an integrated gasification combined cycle (IGCC) plant with CO2 capture

    SciTech Connect (OSTI)

    Paul, P.; Bhattacharyya, D.; Turton, R.; Zitney, S.

    2012-01-01T23:59:59.000Z

    An accurate estimation of process state variables not only can increase the effectiveness and reliability of process measurement technology, but can also enhance plant efficiency, improve control system performance, and increase plant availability. Future integrated gasification combined cycle (IGCC) power plants with CO2 capture will have to satisfy stricter operational and environmental constraints. To operate the IGCC plant without violating stringent environmental emission standards requires accurate estimation of the relevant process state variables, outputs, and disturbances. Unfortunately, a number of these process variables cannot be measured at all, while some of them can be measured, but with low precision, low reliability, or low signal-to-noise ratio. As a result, accurate estimation of the process variables is of great importance to avoid the inherent difficulties associated with the inaccuracy of the data. Motivated by this, the current paper focuses on the state estimation of an acid gas removal (AGR) process as part of an IGCC plant with CO2 capture. This process has extensive heat and mass integration and therefore is very suitable for testing the efficiency of the designed estimators in the presence of complex interactions between process variables. The traditional Kalman filter (KF) (Kalman, 1960) algorithm has been used as a state estimator which resembles that of a predictor-corrector algorithm for solving numerical problems. In traditional KF implementation, good guesses for the process noise covariance matrix (Q) and the measurement noise covariance matrix (R) are required to obtain satisfactory filter performance. However, in the real world, these matrices are unknown and it is difficult to generate good guesses for them. In this paper, use of an adaptive KF will be presented that adapts Q and R at every time step of the algorithm. Results show that very accurate estimations of the desired process states, outputs or disturbances can be achieved by using the adaptive KF.

  7. FY 2008 Laboratory Table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment ofAppropriationBudgetLaboratory Table

  8. Microsoft Word - table_08

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14 Jan-15LiquidBG 0 20 40 60 807 Created on:3 Table

  9. A=19 Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032) -Less2012KE01)93TI07) (Not observed)95TI07)95TI07)72AJ02) (SeeTables

  10. TABLE OF CONTENTS

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposed Action(InsertAbout theSystems3, Revision 0 i TABLE OF

  11. TABLE OF CONTENTS

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposed Action(InsertAbout theSystems3, Revision 0 i TABLE

  12. TABLE OF CONTENTS

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposed Action(InsertAbout theSystems3, Revision 0 i TABLE5,

  13. 1992 CBECS Detailed Tables

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Building Floorspace (Square Feet) 1,001 to7. Electricity4.Rocky6 AprilTables

  14. 8He General Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032) -Less isNFebruaryOctober 2, AlgeriaQ1 Q2 Q3 U . SHe General Tables

  15. 9Be General Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032) -Less isNFebruaryOctober 2, AlgeriaQ1 Q2 Q3 U . SHeBBe General Table

  16. Table of Contents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengthening a solidSynthesis of 2D Alloys &8-5070P3. U.S.7. U.S.8.5TABLE

  17. Table of Contents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengthening a solidSynthesis of 2D Alloys &8-5070P3. U.S.7. U.S.8.5TABLE2

  18. The Human Carbon Budget: An Estimate of the Spatial Distribution of Metabolic Carbon Consumption and Release in the United States

    SciTech Connect (OSTI)

    West, Tristram O. [ORNL; Singh, Nagendra [ORNL; Marland, Gregg [ORNL; Bhaduri, Budhendra L [ORNL

    2009-01-01T23:59:59.000Z

    Carbon dioxide is taken up by agricultural crops and released soon after during the consumption of agricultural commodities. The global net impact of this process on carbon flux to the atmosphere is negligible, but impact on the spatial distribution of carbon dioxide uptake and release across regions and continents is significant. To estimate the consumption and release of carbon by humans over the landscape, we developed a carbon budget for humans in the United States. The budget was derived from food commodity intake data for the US and from algorithms representing the metabolic processing of carbon by humans. Data on consumption, respiration, and waste of carbon by humans were distributed over the US using geospatial population data with a resolution of approximately 450 x 450 m. The average adult in the US contains about 21 kg C and consumes about 67 kg C yr-1 which is balanced by the annual release of about 59 kg C as expired CO2, 7 kg C as feces and urine, and less than 1 kg C as flatus, sweat, and aromatic compounds. In 2000, an estimated 17.2 Tg C were consumed by the US population and 15.2 Tg C were expired to the atmosphere as CO2. Historically, carbon stock in the US human population has increased between 1790-2006 from 0.06 Tg to 5.37 Tg. Displacement and release of total harvested carbon per capita in the US is nearly 12% of per capita fossil fuel emissions. Humans are using, storing, and transporting carbon about the Earth s surface. Inclusion of these carbon dynamics in regional carbon budgets can improve our understanding of carbon sources and sinks.

  19. Distribution System State Estimation

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power AdministrationField Campaign:INEA : Papers SubfoldersU.S.PV FOR ELECTRICITYExports[pic] Load

  20. Frothy Bloat Mitigation in Grazing Cattle Frothy bloat impacts on cattle production in the United States in 1999 were estimated to be greater than $300 million dollars.

    E-Print Network [OSTI]

    Frothy Bloat Mitigation in Grazing Cattle Frothy bloat impacts on cattle production in the United States in 1999 were estimated to be greater than $300 million dollars. Frothy bloat is the major nonpathogenic cause of death loss and depressed weight gains in stocker cattle grazing winter wheat

  1. Estimating monthly and state-level NO sub x , SO sub 2 , VOC and CO sub 2 emissions using the MSCET database

    SciTech Connect (OSTI)

    Cilek, C.M.; Kohout, E.

    1992-01-01T23:59:59.000Z

    This paper describes the Month and State Current Emission Trends (MSCET) database. It describes the methodology used to estimate NO{sub x}, SO{sub 2}, VOC, and CO{sub 2} emissions and the data sources used by the methodology. Selected emissions results from the database are presented. 2 refs., 6 figs.

  2. Estimating monthly and state-level NO{sub x}, SO{sub 2}, VOC and CO{sub 2} emissions using the MSCET database

    SciTech Connect (OSTI)

    Cilek, C.M.; Kohout, E.

    1992-07-01T23:59:59.000Z

    This paper describes the Month and State Current Emission Trends (MSCET) database. It describes the methodology used to estimate NO{sub x}, SO{sub 2}, VOC, and CO{sub 2} emissions and the data sources used by the methodology. Selected emissions results from the database are presented. 2 refs., 6 figs.

  3. Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

    SciTech Connect (OSTI)

    Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, N.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen

    2014-05-06T23:59:59.000Z

    Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m?2 yr?1 and total NPP in the range of 318–490 Tg C yr?1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m?2 yr?1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m?2 yr?1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

  4. FNANO12 Table of Contents Table of Contents

    E-Print Network [OSTI]

    Reif, John H.

    Bardram Software tools for automated design of dynamic nucleic acid systems Table of Contents In Silico Design, In Vitro Characterization and Ex-Vivo Studies of Functional RNA-based Nanoparticles

  5. FY 2015 Summary Control Table by Appropriation

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

    Summary Control Table by Appropriation (dollars in thousands - OMB Scoring) Summary Control Table by Appropriation Page 1 FY 2015 Congressional Request FY 2013 FY 2014 FY 2014 FY...

  6. SimHydro 2012: Hydraulic modeling and uncertainty, 12-14 September 2012, Sophia Antipolis N. Jean-Baptiste, C. Dore, P-O. Malaterre, J. Sau -Data assimilation for hydraulic state estimation of a development project

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    SimHydro 2012: Hydraulic modeling and uncertainty, 12-14 September 2012, Sophia Antipolis ­ N. Jean-Baptiste, C. Dorée, P-O. Malaterre, J. Sau - Data assimilation for hydraulic state estimation of a development project Data assimilation for hydraulic state estimation of a development project Assimilation de données

  7. Analytical Estimation of CO2 Storage Capacity in Depleted Oil and Gas Reservoirs Based on Thermodynamic State Functions

    E-Print Network [OSTI]

    Valbuena Olivares, Ernesto

    2012-02-14T23:59:59.000Z

    Numerical simulation has been used, as common practice, to estimate the CO2 storage capacity of depleted reservoirs. However, this method is time consuming, expensive and requires detailed input data. This investigation proposes an analytical method...

  8. Automation of BESSY scanning tables

    E-Print Network [OSTI]

    Hanton, J

    1981-01-01T23:59:59.000Z

    A microprocessor M6800 is used for the automation of scanning and premeasuring BESSY tables. The tasks achieved by the microprocessor are: control of spooling of the four asynchronous film winding devices and switching on and off the 4 projection lamps; preprocessing of the data coming from a bipolar coordinates measuring device; bidirectional interchange of information between the operator, the BESSY table and the DEC PDP 11/34 mini computer controlling the scanning operations; control of the magnification on the table by swapping the projection lenses of appropriate focal lengths and the associated light boxes (under development). In connection with the last of these, study is being made for the use of BESSY tables for accurate measurements (+/- 5 microns), by encoding the displacements of the projection lenses. (0 refs).

  9. TABLE OF CONTENTS ABSTRACT . . .. . . .. . . . . . . . . . . . . . . . . . . . . . v

    E-Print Network [OSTI]

    Oak Ridge National Laboratory

    ............................................... 12 Water-Source Heat Pump Performance ............................ 18 Air-Source Heat Pump QUARTZ CONTENT OF SEDIMENTARY ROCK LAYERS ........ 17 TABLE 10. PROPERTIES OF SEDIMENTARY ROCK LAYERS OF PERFORMANCE OF WATER-SOURCE HEAT PUMP .............................. ................. 23 FIGURE 2. NODAL

  10. Sample size requirements for estimating effective dose from computed tomography using solid-state metal-oxide-semiconductor field-effect transistor dosimetry

    SciTech Connect (OSTI)

    Trattner, Sigal [Department of Medicine, Division of Cardiology, Columbia University Medical Center and New York-Presbyterian Hospital, New York, New York 10032 (United States)] [Department of Medicine, Division of Cardiology, Columbia University Medical Center and New York-Presbyterian Hospital, New York, New York 10032 (United States); Cheng, Bin [Department of Biostatistics, Columbia University Mailman School of Public Health, New York, New York 10032 (United States)] [Department of Biostatistics, Columbia University Mailman School of Public Health, New York, New York 10032 (United States); Pieniazek, Radoslaw L. [Center for Radiological Research, Columbia University Medical Center and New York-Presbyterian Hospital, New York, New York 10032 (United States)] [Center for Radiological Research, Columbia University Medical Center and New York-Presbyterian Hospital, New York, New York 10032 (United States); Hoffmann, Udo [Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114 (United States)] [Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114 (United States); Douglas, Pamela S. [Department of Medicine, Division of Cardiology, Duke University, Durham, North Carolina 27715 (United States)] [Department of Medicine, Division of Cardiology, Duke University, Durham, North Carolina 27715 (United States); Einstein, Andrew J., E-mail: andrew.einstein@columbia.edu [Department of Medicine, Division of Cardiology, Columbia University Medical Center and New York-Presbyterian Hospital, New York, New York and Department of Radiology, Columbia University Medical Center and New York-Presbyterian Hospital, New York, New York (United States)

    2014-04-15T23:59:59.000Z

    Purpose: Effective dose (ED) is a widely used metric for comparing ionizing radiation burden between different imaging modalities, scanners, and scan protocols. In computed tomography (CT), ED can be estimated by performing scans on an anthropomorphic phantom in which metal-oxide-semiconductor field-effect transistor (MOSFET) solid-state dosimeters have been placed to enable organ dose measurements. Here a statistical framework is established to determine the sample size (number of scans) needed for estimating ED to a desired precision and confidence, for a particular scanner and scan protocol, subject to practical limitations. Methods: The statistical scheme involves solving equations which minimize the sample size required for estimating ED to desired precision and confidence. It is subject to a constrained variation of the estimated ED and solved using the Lagrange multiplier method. The scheme incorporates measurement variation introduced both by MOSFET calibration, and by variation in MOSFET readings between repeated CT scans. Sample size requirements are illustrated on cardiac, chest, and abdomen–pelvis CT scans performed on a 320-row scanner and chest CT performed on a 16-row scanner. Results: Sample sizes for estimating ED vary considerably between scanners and protocols. Sample size increases as the required precision or confidence is higher and also as the anticipated ED is lower. For example, for a helical chest protocol, for 95% confidence and 5% precision for the ED, 30 measurements are required on the 320-row scanner and 11 on the 16-row scanner when the anticipated ED is 4 mSv; these sample sizes are 5 and 2, respectively, when the anticipated ED is 10 mSv. Conclusions: Applying the suggested scheme, it was found that even at modest sample sizes, it is feasible to estimate ED with high precision and a high degree of confidence. As CT technology develops enabling ED to be lowered, more MOSFET measurements are needed to estimate ED with the same precision and confidence.

  11. Made ill Ullited States of :\\meTica Hcprintcd from TilE \\\\'!Loun: SOCIlITY BULu.'ls

    E-Print Network [OSTI]

    . ANDERSON, Utah Cooperative Wildlife Rellearch Unit, Utah State Univer.ity, Logan, UT 84322 Abstract, Laurel, Mary- land, as shot or found dead during the hunting season were included in our analysis. Many) and Anderson (1975). Only birds 80-W #12;SURVIVAL ESTIMATES FOR CANADA GEESE' Ratti et al. 147 Table 1. Bandiu

  12. Collision-Free State Estimation Lawson L.S. Wong, Leslie Pack Kaelbling, and Tomas Lozano-Perez

    E-Print Network [OSTI]

    Lozano-Perez, Tomas

    . For example, for objects within a refrigerator, they cannot interpenetrate each other or the refrigerator inside a refrigerator before planning to pick one up. The state of the problem is the positions and orientations of the objects within the refrigerator; we need a representation of distributions over states

  13. Spatially Resolved Estimation of Ozone-related Mortality in the United States under Two Representative Concentration Pathways (RCPs) and their Uncertainty

    SciTech Connect (OSTI)

    Kim, Young-Min; Zhou, Ying; Gao, Yang; Fu, Joshua S.; Johnson, Brent; Huang, Cheng; Liu, Yang

    2015-01-01T23:59:59.000Z

    BACKGROUND: The spatial pattern of the uncertainty in climate air pollution health impact has rarely been studied due to the lack of high-resolution model simulations, especially under the latest Representative Concentration Pathways (RCPs). OBJECTIVES: We estimated county-level ozone (O3) and PM2.5 related excess mortality (EM) and evaluated the associated uncertainties in the continental United States in the 2050s under RCP4.5 and RCP8.5. METHODS: Using dynamically downscaled climate model simulations, we calculated changes in O3 and PM2.5 levels at 12 km resolution between the future (2057-2059) and present (2001-2004) under two RCP scenarios. Using concentration-response relationships in the literature and projected future populations, we estimated EM attributable to the changes in O3 and PM2.5. We finally analyzed the contribution of input variables to the uncertainty in the county-level EM estimation using Monte Carlo simulation. RESULTS: O3-related premature deaths in the continental U.S. were estimated to be 1,082 deaths/year under RCP8.5 (95% confidence interval (CI): -288 to 2,453), and -5,229 deaths/year under RCP4.5 (-7,212 to -3,246). Simulated PM2.5 changes resulted in a significant decrease in EM under the two RCPs. The uncertainty of O3-related EM estimates was mainly caused by RCP scenarios, whereas that of PM2.5-related EMs was mainly from concentration-response functions. CONCLUSION: EM estimates attributable to climate change-induced air pollution change as well as the associated uncertainties vary substantially in space, and so are the most influential input variables. Spatially resolved data is crucial to develop effective mitigation and adaptation policy.

  14. FY 2010 Laboratory Table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment6 FY 2007 FY 2008State7 FY 2008

  15. FY 2010 Statistical Table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment6 FY 2007 FY 2008State7 FY0

  16. FY 2011 Laboratory Table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment6 FY 2007 FY 2008State71Laboratory

  17. 9B General Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032) -Less isNFebruaryOctober 2, AlgeriaQ1 Q2 Q3 U . SHeB Ground-StateB

  18. Speed Search in Truth Tables (SSTT) A complete inductive approach to SAT

    E-Print Network [OSTI]

    Adriaans, Pieter

    Speed Search in Truth Tables (SSTT) A complete inductive approach to SAT Pieter Adriaans pietera knowledge this class of algorithms, which I call Speed Search in Truth Tables (SSTT), has not been stud- iedÃ?cient than state-of-the-art probabilistic local search algorithms, such as GSAT, WSAT or Sch

  19. University Housing and Residence Life Table of Contents

    E-Print Network [OSTI]

    1 University Housing and Residence Life Fall `07 #12;2 Table of Contents Assignments / Roommates 4 Employment 9 Banking 9 Move in dates/times 10 Key pick up 10 Campus Housing & Residence Life Offices 11 Welcome to University Housing at Rutgers, The State University of New Jersey! This book has been designed

  20. Table 34. Reformulated Motor Gasoline Prices by Grade, Sales...

    Gasoline and Diesel Fuel Update (EIA)

    61.5 70.8 92.7 90.7 81.5 72.8 - 78.0 See footnotes at end of table. 34. Reformulated Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 146 Energy Information...

  1. Petroleum Products Table 31. Motor Gasoline Prices by Grade...

    Gasoline and Diesel Fuel Update (EIA)

    82.4 77.1 68.9 62.6 71.6 92.3 89.9 82.6 72.7 - 78.2 See footnotes at end of table. 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 56 Energy Information...

  2. Table 34. Reformulated Motor Gasoline Prices by Grade, Sales...

    Gasoline and Diesel Fuel Update (EIA)

    62.6 71.7 92.3 89.9 82.6 72.7 - 78.2 See footnotes at end of table. 34. Reformulated Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 146 Energy Information...

  3. Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type...

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

    71.8 W 70.5 78.9 W 76.0 83.6 W 69.2 75.2 See footnotes at end of table. 35. Refiner Motor Gasoline Prices by Grade, Sales Type, PAD District and State 176 Energy Information...

  4. Table 35. Refiner Motor Gasoline Prices by Grade, Sales Type...

    Gasoline and Diesel Fuel Update (EIA)

    W 68.4 70.8 W W 78.6 W 85.7 81.8 W 69.3 73.8 See footnotes at end of table. 35. Refiner Motor Gasoline Prices by Grade, Sales Type, PAD District and State 176 Energy Information...

  5. Cash Flow and Discount Rate news estimation: which method to choose?

    E-Print Network [OSTI]

    Khimich, Natalya V.

    2012-01-01T23:59:59.000Z

    form the VAR method . Implied Cost of Capital estimates byt+1 . TABLE 3: Cost of Capital Estimates by Year Year Numberdifferent estimates of the implied cost of capital. See

  6. Estimation of Net Ecosystem Carbon Exchange for the Conterminous UnitedStates by Combining MODIS and AmeriFlux Data

    SciTech Connect (OSTI)

    Xiao, Jingfeng; Zhuang, Qianlai; Baldocchi, Dennis D.; Law, Beverly E.; Richardson, Andrew D.; Chen, Jiquan; Oren, Ram; Starr, Gregory; Noormets, Asko; Ma, Siyan; Verma, Shashi B.; Wharton, Sonia; Wofsy, Steven C.; Bolstad, Paul V.; Burns, Sean P.; Cook, David R.; Curtis, Peter S.; Drake, Bert G.; Falk, Matthias; Fischer, Marc L.; Foster, David R.; Gu, Lianhong; Hadley, Julian L.; Hollinger, David Y.; Katul, Gabriel G.; Litvak, Marcy; Martin, Timothy A.; Matamala, Roser; McNulty, Steve; Meyers, Tilden P.; Monson, Russell K.; Munger, J. William; Oechel, Walter C.; U, Kyaw Tha Paw; Schmid, Hans Peter; Scott, Russell L.; Sun, Ge; Suyker, Andrew E.; Torn, Margaret S.

    2009-03-06T23:59:59.000Z

    Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board NASA's Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a regression tree approach. The predictive model was trained and validated using NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE reasonably well at the site level. We then applied the model to the continental scale and estimated NEE for each 1 km x 1 km cell across the conterminous U.S. for each 8-day period in 2005 using spatially-explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets for large areas.

  7. Estimation of net ecosystem carbon exchange for the conterminous United States by combining MODIS and AmeriFlux data

    SciTech Connect (OSTI)

    Xiao, Jingfeng; Zhuang, Qianlai; Baldocchi, Dennis D.; Bolstad, Paul V.; Burns, Sean P.; Chen, Jiquan; Cook, David R.; Curtis, Peter S.; Drake, Bert G.; Foster, David R.; Gu, Lianhong; Hadley, Julian L.; Hollinger, David Y.; Katul, Gabriel G.; Law, Beverly E.; Litvak, Marcy; Ma, Siyan; Martin, Timothy A.; Matamala, Roser; McNulty, Steve; Meyers, Tilden P.; Monson, Russell K.; Munger, J. William; Noormets, Asko; Oechel, Walter C.; Oren, Ram; Richardson, Andrew D.; Schmid, Hans Peter; Scott, Russell L.; Starr, Gregory; Sun, Ge; Suyker, Andrew E.; Torn, Margaret S.; Paw, Kyaw; Verma, Shashi B.; Wharton, Sonia; Wofsy, Steven C.

    2008-10-01T23:59:59.000Z

    Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board the National Aeronautics and Space Administration's (NASA) Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a modified regression tree approach. The predictive model was trained and validated using eddy flux NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE well (r = 0.73, p < 0.001). We then applied the model to the continental scale and estimated NEE for each 1 km x 1 km cell across the conterminous U.S. for each 8-day interval in 2005 using spatially explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE as determined from measurements and the literature. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets over large areas.

  8. Table of Contents INTRODUCTION 2

    E-Print Network [OSTI]

    O'Mahony, Donal E.

    #12;1 Table of Contents INTRODUCTION 2 SECTION ONE: PRINCIPLES OF GOOD PRACTICE 4 SECTION TWO, it offers a practical guide to staff and volunteers who work with children by outlining a number of fundamental principles of good practice, highlighting the key elements of each one and discussing the issues

  9. Table 1.--Annual estimates and uncertainty for Nebraska, 2011

    E-Print Network [OSTI]

    .9 37.7 12.2 110.6 Other hardwoods 178.3 12.0 302.8 19.1 All Species 2,081.5 6.9 4,628.2 12.2 0 100 200 Land 0 50 100 150 200 250 Eastern redcedar Ponderosa pine Cottonwood Bur oak Sugarberry/hackberry/elm.7 15.0 42.5 9 American elm 55.7 14.3 39.1 32.6 10 Siberian elm 39.5 28.5 35.2 42.8 Other softwoods 18

  10. Cost Estimating Guide, Table of Contents - DOE Directives, Delegations...

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

    1997 CRD: No DNFSB: No Related History Exemptions Standards Related to: DOE G 430.1-1 Chp 9, Operating Costs DOE G 430.1-1 Chp 19, Data Collection and Normalization for the...

  11. Table 1. Updated estimates of power plant capital and operating...

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

    CT",85,10850,,973,7.34,15.45,"Y" "Advanced CT",210,9750,,676,7.04,10.37,"Y" "Fuel Cells",10,9500,,7108,0,43,"Y" " Uranium" "Dual Unit Nuclear",2234,"N...

  12. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008, 2007, 2006,Wyoming"

  13. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008, 2007, 2006,Wyoming"Arizona"

  14. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008, 2007,

  15. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008, 2007,Colorado" "Emission

  16. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008, 2007,Colorado"

  17. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008, 2007,Colorado"Delaware"

  18. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008, 2007,Colorado"Delaware"District of

  19. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008, 2007,Colorado"Delaware"District

  20. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008,

  1. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008,Hawaii" "Emission type", 2013,

  2. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008,Hawaii" "Emission type",

  3. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008,Hawaii" "Emission

  4. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008,Hawaii" "EmissionIndiana"

  5. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008,Hawaii"

  6. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008,Hawaii"Kansas" "Emission

  7. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008,Hawaii"Kansas"

  8. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009, 2008,Hawaii"Kansas"Louisiana"

  9. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009,

  10. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009,Maryland" "Emission type", 2013,

  11. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009,Maryland" "Emission type",

  12. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009,Maryland" "Emission

  13. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009,Maryland" "EmissionMississippi"

  14. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009,Maryland"

  15. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009,Maryland"Montana" "Emission

  16. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009,Maryland"Montana"

  17. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010, 2009,Maryland"Montana"Nevada"

  18. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,

  19. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey" "Emission type", 2013, 2012, 2011,

  20. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey" "Emission type", 2013, 2012,

  1. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey" "Emission type", 2013,

  2. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey" "Emission type",

  3. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey" "Emission type",Dakota"

  4. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey" "Emission

  5. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey" "EmissionOklahoma" "Emission

  6. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey" "EmissionOklahoma"

  7. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey"

  8. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey"Rhode Island" "Emission type",

  9. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey"Rhode Island" "Emission

  10. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey"Rhode Island" "EmissionDakota"

  11. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey"Rhode Island"

  12. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey"Rhode Island"Texas" "Emission

  13. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey"Rhode Island"Texas"

  14. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey"Rhode Island"Texas"Utah"

  15. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey"Rhode

  16. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey"RhodeVirginia" "Emission

  17. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey"RhodeVirginia"

  18. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey"RhodeVirginia"West Virginia"

  19. Table 7. Electric power industry emissions estimates, 1990 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013, 2012, 2011, 2010,Jersey"RhodeVirginia"West

  20. Table C3. Primary Energy Consumption Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. Coal Stocks at Manufacturing:: Total

  1. Table E10. Residential Sector Energy Expenditure Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks DefinitionsWeekly.0.

  2. Table E11. Commercial Sector Energy Expenditure Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks DefinitionsWeekly.0.1.

  3. Table E13. Transportation Sector Energy Expenditure Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks

  4. Table E14. Electric Power Sector Energy Expenditure Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks4. Electric Power Sector

  5. Table E3. Residential Sector Energy Price Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks4. Electric

  6. Table E4. Commercial Sector Energy Price Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks4. ElectricE4.

  7. Table E5. Industrial Sector Energy Price Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks4. ElectricE4.E5.

  8. Table E6. Transportation Sector Energy Price Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks4. ElectricE4.E5.E6.

  9. Table E7. Electric Power Sector Energy Price Estimates, 2012

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. CoalInputsTotal Stocks4. ElectricE4.E5.E6.E7.

  10. A maximum entropy-least squares estimator for elastic origin-destination trip matrix estimation

    E-Print Network [OSTI]

    Kockelman, Kara M.

    A maximum entropy-least squares estimator for elastic origin- destination trip matrix estimation propose a combined maximum entropy-least squares (ME-LS) estimator, by which O- D flows are distributed-destination trip table; elastic demand; maximum entropy; least squares; subnetwork analysis; convex combination

  11. International energy indicators. [Statistical tables and graphs

    SciTech Connect (OSTI)

    Bauer, E.K. (ed.)

    1980-05-01T23:59:59.000Z

    International statistical tables and graphs are given for the following: (1) Iran - Crude Oil Capacity, Production and Shut-in, June 1974-April 1980; (2) Saudi Arabia - Crude Oil Capacity, Production, and Shut-in, March 1974-Apr 1980; (3) OPEC (Ex-Iran and Saudi Arabia) - Capacity, Production and Shut-in, June 1974-March 1980; (4) Non-OPEC Free World and US Production of Crude Oil, January 1973-February 1980; (5) Oil Stocks - Free World, US, Japan, and Europe (Landed, 1973-1st Quarter, 1980); (6) Petroleum Consumption by Industrial Countries, January 1973-December 1979; (7) USSR Crude Oil Production and Exports, January 1974-April 1980; and (8) Free World and US Nuclear Generation Capacity, January 1973-March 1980. Similar statistical tables and graphs included for the United States include: (1) Imports of Crude Oil and Products, January 1973-April 1980; (2) Landed Cost of Saudi Oil in Current and 1974 Dollars, April 1974-January 1980; (3) US Trade in Coal, January 1973-March 1980; (4) Summary of US Merchandise Trade, 1976-March 1980; and (5) US Energy/GNP Ratio, 1947 to 1979.

  12. EIA - Annual Energy Outlook (AEO) 2013 Data Tables

    Gasoline and Diesel Fuel Update (EIA)

    Floorspace, and Equipment Efficiency XLS Table 24. Industrial Sector Macroeconomic Indicators XLS Table 25. Refining Industry Energy Consumption XLS Table 26. Food Industry...

  13. Table 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil...

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

    132.9 1,418.3 See footnotes at end of table. 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil Volumes by PAD District and State Energy Information Administration ...

  14. Table 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil...

    Gasoline and Diesel Fuel Update (EIA)

    839.2 135.0 1,251.9 See footnotes at end of table. 46. Refiner No. 2 Distillate, Diesel Fuel, and Fuel Oil Volumes by PAD District and State Energy Information Administration ...

  15. SOFA 2 Documentation Table of contents

    E-Print Network [OSTI]

    SOFA 2 Documentation Table of contents 1 Overview...................................................................................................................... 2 2 Documentation............................................................................................................. 2 3 Other documentation and howtos

  16. The Interactive Dining Table Florian Echtler

    E-Print Network [OSTI]

    Deussen, Oliver

    into the table lamp for sensing interaction and a small LED-based projector mounted on the ceiling for displaying

  17. Chemistry Department Assessment Table of Contents

    E-Print Network [OSTI]

    Bogaerts, Steven

    0 Chemistry Department Assessment May, 2006 Table of Contents Page Executive Summary 1 Prelude 1 Mission Statement and Learning Goals 1 Facilities 2 Staffing 3 Students: Chemistry Majors and Student Taking Service Courses Table: 1997-2005 graduates profile Table: GRE Score for Chemistry Majors, 1993

  18. Table 1. 2013 Summary Statistics

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API Gravity Period: Monthly Annual Download Series History Download Series History Definitions, SourcesType"A50. Table

  19. Mineral balances, including in drinking water, estimated for Merced County dairy herds

    E-Print Network [OSTI]

    Castillo, Alejandro R Dr.; Santos, Jose Eduardo P.; Tabone, Tom J.

    2007-01-01T23:59:59.000Z

    et al. (1994). TABLE 3. Estimates of daily mineral intake,drinking-water mineral contributionand net mineral excretion in lactating cows on Merced County

  20. Estimating Demand Response Market Potential Among Large Commercial and Industrial Customers: A Scoping Study

    E-Print Network [OSTI]

    Goldman, Charles; Hopper, Nicole; Bharvirkar, Ranjit; Neenan, Bernie; Cappers, Peter

    2007-01-01T23:59:59.000Z

    of Program Participation Rates on Demand Response MarketTable 3-1. Methods of Estimating Demand Response PenetrationDemand Response

  1. Uncertainties in Estimating the Indirect Production of $B_c$ and Its Excited States Via Top Quark Decays at CERN LHC

    E-Print Network [OSTI]

    Xing-Gang Wu

    2008-12-08T23:59:59.000Z

    Main theoretical uncertainties in estimating the indirect production of $(b\\bar{c})$-quarkonium ($B^-_c$ meson and its excited states) via top quark decays, $t\\to (b\\bar{c})+c+W^{+}$, are studied within the non-relativistic QCD framework. It is found that the dimensionless reduced decay width for a particular $(b\\bar{c})$-quarkonium state, $\\bar\\Gamma_{n}=\\Gamma_{n} /\\Gamma_{t\\to W^{+}+b}$, is very sensitive to the $c$-quark mass, while the uncertainties from the $b$-quark and $t$-quark masses are small, where $n$ stands for the eight $(b\\bar{c})$-quarkonium states up to ${\\cal O}(v^4)$: $|(b\\bar{c})(^1S_0)_1>$, $|(b\\bar{c})(^3S_1)_1>$, $|(b\\bar{c})(^1P_1)_1>$, $|(b\\bar{c})(^3P_J)_1>$ (with $J=(1,2,3)$), $|(b\\bar{c})(^1S_0)_{8}g>$ and $|(b\\bar{c})(^3S_1)_{8}g>$ respectively. About $10^8$ $t\\bar{t}$-pairs shall be produced per year at CERN LHC, if adopting the assumption that all the higher Fock states decay to the ground state with 100% probability, then we shall have $(1.038^{+1.353}_{-0.782})\\times 10^5$ $B^-_c $ events per year. So the indirect production provides another important way to study the properties of $B^-_c$ meson in comparison to that of the direct hadronic production at CERN LHC.

  2. Estimating Methods

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

    1997-03-28T23:59:59.000Z

    Based on the project's scope, the purpose of the estimate, and the availability of estimating resources, the estimator can choose one or a combination of techniques when estimating an activity or project. Estimating methods, estimating indirect and direct costs, and other estimating considerations are discussed in this chapter.

  3. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a Geologic5/15/2013May 7,Operations from

  4. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a Geologic5/15/2013May 7,Operations

  5. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a Geologic5/15/2013May 7,Operations8

  6. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a Geologic5/15/2013May 7,Operations838

  7. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a Geologic5/15/2013May 7,Operations8385

  8. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a Geologic5/15/2013May

  9. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a Geologic5/15/2013May6 from (1991AJ01):

  10. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a Geologic5/15/2013May6 from

  11. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a Geologic5/15/2013May6 from7AJ02):

  12. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a Geologic5/15/2013May6

  13. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a Geologic5/15/2013May60AJ01): Some

  14. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a Geologic5/15/2013May60AJ01):

  15. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a Geologic5/15/2013May60AJ01):3TI07):

  16. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a

  17. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a5TI07): Electromagnetic transitions in

  18. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a5TI07): Electromagnetic transitions

  19. Table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over Our InstagramStructureProposedPAGE Creating a5TI07): Electromagnetic

  20. An optimal Wegner estimate and its application to the global continuity of the integrated density of states for random Schrödinger operators

    E-Print Network [OSTI]

    Jean-Michel Combes; Peter Hislop; Frédéric Klopp

    2006-10-14T23:59:59.000Z

    We prove that the integrated density of states (IDS) of random Schr\\"{o}dinger operators with Anderson-type potentials on $L^2 (\\R^d)$, for $d \\geq1$, is locally H\\"{o}lder continuous at all energies with the same H\\"{o}lder exponent $0energies. The single-site potential $u\\in L\\_0^\\infty (\\R^d)$ must be nonnegative and compactly-supported. The unperturbed Hamiltonian must be periodic and satisfy a unique continuation principle. We also prove analogous continuity results for the IDS of random Anderson-type perturbations of the Landau Hamiltonian in two-dimensions. All of these results follow from a new Wegner estimate for local random Hamiltonians with rather general probability measures.

  1. SALTSTONE DISPOSAL FACILITY: DETERMINATION OF THE PROBABLE MAXIMUM WATER TABLE ELEVATION

    SciTech Connect (OSTI)

    Hiergesell, R

    2005-04-01T23:59:59.000Z

    A coverage depicting the configuration of the probable maximum water table elevation in the vicinity of the Saltstone Disposal Facility (SDF) was developed to support the Saltstone program. This coverage is needed to support the construction of saltstone vaults to assure that they remain above the maximum elevation of the water table during the Performance Assessment (PA) period of compliance. A previous investigation to calculate the historical high water table beneath the SDF (Cook, 1983) was built upon to incorporate new data that has since become available to refine that estimate and develop a coverage that could be extended to the perennial streams adjacent to the SDF. This investigation incorporated the method used in the Cook, 1983 report to develop an estimate of the probable maximum water table for a group of wells that either existed at one time at or near the SDF or which currently exist. Estimates of the probable maximum water table at these wells were used to construct 2D contour lines depicting this surface beneath the SDF and extend them to the nearby hydrologic boundaries at the perennial streams adjacent to the SDF. Although certain measures were implemented to assure that the contour lines depict a surface above which the water table will not rise, the exact elevation of this surface cannot be known with complete certainty. It is therefore recommended that the construction of saltstone vaults incorporate a vertical buffer of at least 5-feet between the base of the vaults and the depicted probable maximum water table elevation. This should provide assurance that the water table under the wet extreme climatic condition will never rise to intercept the base of a vault.

  2. CBECS Buildings Characteristics --Revised Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at CommercialDecade Year-0Proved ReservesBuildings Use Tables (24

  3. CBECS Buildings Characteristics --Revised Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at CommercialDecade Year-0Proved ReservesBuildings Use Tables

  4. 2003 CBECS Detailed Tables: Summary

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40Coal Stocks at Commercial andSeptember 25,9,1996 N Y M E2003 Detailed Tables 2003

  5. Table 1. 2013 Summary statistics

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConference |6:Welcome to the3421,097

  6. Table 1. 2013 Summary statistics

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConference |6:Welcome to

  7. ARM - Instrument - s-table

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006Datastreamstwrcam40mgovInstrumentsmwr3c DocumentationgovInstrumentsrain DocumentationgovInstrumentss-table

  8. Microsoft Word - table_13.doc

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade1 Source: Office of Fossil Energy, U.S. Department of28 Third23 Table

  9. Microsoft Word - table_14.doc

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade1 Source: Office of Fossil Energy, U.S. Department of28 Third23 Table4

  10. Microsoft Word - table_15.doc

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade1 Source: Office of Fossil Energy, U.S. Department of28 Third23 Table40

  11. Microsoft Word - table_18.doc

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade1 Source: Office of Fossil Energy, U.S. Department of28 Third235 Table

  12. Microsoft Word - table_19.doc

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade1 Source: Office of Fossil Energy, U.S. Department of28 Third235 Table7

  13. Microsoft Word - table_21.doc

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade1 Source: Office of Fossil Energy, U.S. Department of28 Third2359 Table

  14. Environmental Regulatory Update Table, August 1991

    SciTech Connect (OSTI)

    Houlberg, L.M., Hawkins, G.T.; Salk, M.S.

    1991-09-01T23:59:59.000Z

    This Environmental Regulatory Update Table (August 1991) provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  15. Environmental Regulatory Update Table, September 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-10-01T23:59:59.000Z

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  16. Environmental regulatory update table, March 1989

    SciTech Connect (OSTI)

    Houlberg, L.; Langston, M.E.; Nikbakht, A.; Salk, M.S.

    1989-04-01T23:59:59.000Z

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  17. Environmental regulatory update table, July 1991

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1991-08-01T23:59:59.000Z

    This Environmental Regulatory Update Table (July 1991) provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  18. Environmental Regulatory Update Table, December 1989

    SciTech Connect (OSTI)

    Houlbert, L.M.; Langston, M.E. (Tennessee Univ., Knoxville, TN (USA)); Nikbakht, A.; Salk, M.S. (Oak Ridge National Lab., TN (USA))

    1990-01-01T23:59:59.000Z

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  19. Environmental Regulatory Update Table, April 1989

    SciTech Connect (OSTI)

    Houlberg, L.; Langston, M.E.; Nikbakht, A.; Salk, M.S.

    1989-05-01T23:59:59.000Z

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated each month with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  20. TABLE20.CHP:Corel VENTURA

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

    due to independent rounding. Sources: Energy Information Administration (EIA) Form EIA-814, "Monthly Imports Report." 266 Table 20. Imports of Crude Oil and Petroleum...

  1. TABLE27.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    due to independent rounding. Sources: Energy Information Administration (EIA) Form EIA-810, "Monthly Refinery Report" and the U.S. Bureau of the Census. 410 Table 27....

  2. TABLE53.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    Table 53. Movements of Crude Oil and Petroleum Products by Pipeline, Tanker, and Barge Between July 2004 Crude Oil ... 0 383 0...

  3. Peer Mentor Handbook Table of Contents

    E-Print Network [OSTI]

    Lin, Zhiqun

    Peer Mentor Handbook #12;Table of Contents Learning Communities Characteristics ..............................................................................................4 Skills for Effective Mentors ...............................................................................................................7 Ethical Considerations for the Peer Mentor

  4. TABLE54.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    Administration (EIA) Forms EIA-812, "Monthly Product Pipeline Report," and EIA-813, Monthly Crude Oil Report." Table 54. Movements of Crude Oil and Petroleum Products by Pipeline...

  5. TABLE11.CHP:Corel VENTURA

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

    (Thousand Barrels) Table 11. PAD District II-Year-to-Date Supply, Disposition, and Ending Stocks of Crude Oil and Petroleum January-July 2004 Products, Crude Oil...

  6. TABLE15.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    Table 15. PAD District III-Year-to-Date Supply, Disposition, and Ending Stocks of Crude Oil and Petroleum (Thousand Barrels) January-July 2004 Products, Crude Oil...

  7. TABLE19.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    Table 19. PAD District IV-Year-to-Date Supply, Disposition, and Ending Stocks of Crude Oil and Petroleum (Thousand Barrels) January-July 2004 Products, Crude Oil...

  8. TABLE OF CONTENTS NIST Map ...................................................................................................................................................3

    E-Print Network [OSTI]

    TABLE OF CONTENTS NIST Map the Power Grid PML TIME SPEAKER UNIVERSITY TITLE LAB 3:00P Brian Weinstein American University Temperature

  9. Stem cubic-foot volume tables for tree species in the piedmont. Forest Service research paper

    SciTech Connect (OSTI)

    Clark, A.; Souter, R.A.

    1996-03-01T23:59:59.000Z

    Steamwood cubic-foot volume inside bark tables are presented for 16 species and 8 species groups based on equations used to estimate timber sale volumes on national forests in the Piedmont. Tables are based on form class measurement data for 2,753 trees sampled in the Piedmont and taper data collected across the South. A series of tables is presented for each species based on diameter at breast height (d.b.h.) in combination with total height and height to a 4-inch diameter outside bark (d.o.b.) top. Volume tables are also presented based on d.b.h. in combination with height to a 7-inch d.o.b. top for softwoods and height to a 9-inch d.o.b. top for hardwoods.

  10. PROPERTY TABLES AND CHARTS (SI UNITS) Table A1 Molar mass, gas constant, and

    E-Print Network [OSTI]

    Kostic, Milivoje M.

    Table A­20 Ideal-gas properties of carbon dioxide, CO2 Table A­21 Ideal-gas properties of carbon.1355 n-Butane C4H10 58.124 0.1430 425.2 3.80 0.2547 Carbon dioxide CO2 44.01 0.1889 304.2 7.39 0Appendix 1 PROPERTY TABLES AND CHARTS (SI UNITS) Table A­1 Molar mass, gas constant, and critical

  11. Abundance, Distribution and Estimated Consumption (kg fish) of Piscivorous Birds Along the Yakima River, Washington State; Implications for Fisheries Management, 2002 Annual Report.

    SciTech Connect (OSTI)

    Major, III, Walter; Grassley, James M.; Ryding, Kristen E. (University of Washington, Quantitive Ecology Program, Seattle, WA)

    2003-05-01T23:59:59.000Z

    This report is divided into two chapters. The abstract for chapter one is--Understanding of the abundance and spatial and temporal distributions of piscivorous birds and their potential consumption of fish is an increasingly important aspect of fisheries management. During 1999-2002, we determined the abundance and distribution and estimated the maximum consumption (kg biomass) of fish-eating birds along the length of the Yakima River in Washington State. Sixteen different species were observed during the 4-yr study, but only half of those were observed during all years. Abundance and estimated consumption of fish within the upper and middle sections of the river were dominated by common mergansers (Mergus merganser) which are known to breed in those reaches. Common mergansers accounted for 78 to 94% of the estimated total fish take for the upper river or approximately 28,383 {+-} 1,041 kg over the 4 yrs. A greater diversity of avian piscivores occurred in the lower river and potential impacts to fish populations was more evenly distributed among the species. In 1999-2000, great blue herons potentially accounted for 29 and 36% of the fish consumed, whereas in 2001-2002 American white pelicans accounted for 53 and 55%. We estimated that approximately 75,878 {+-} 6,616 kg of fish were consumed by piscivorous birds in the lower sections of the river during the study. Bird assemblages differed spatially along the river with a greater abundance of colonial nesting species within the lower sections of the river, especially during spring and the nesting season. The abundance of avian piscivores and consumption estimates are discussed within the context of salmonid supplementation efforts on the river and juvenile out-migration. The abstract for chapter two is--Consumption of fish by piscivorous birds may be a significant constraint on efforts to enhance salmonid populations within tributaries to the Columbia River in Washington State. During 1999-2002, we determined the abundance of fish-eating birds, primarily ring-billed (Larus delawarensis) and California (L. californicus) gulls and monitored their behavior at two man-made structures within the Yakima River in eastern Washington: Horn Rapids Dam, a low-head irrigation dam, and the return pipe for the Chandler Juvenile Fish Handling Facility. Earlier observations of congregations of gulls at these structures suggested an increased likelihood of predation of out-migrating juvenile salmonids. We estimated the number of fish consumed and examined the relationship between river flow and gull numbers and fish taken. Numbers of gulls at the structures varied daily between their arrival in Late March-early April and departure in late June (mean ({+-}SE) - Horn Rapids: 11.7 ({+-}2.0), Chandler: 20.1 ({+-}1.5) ). During the 4-yr study, numbers at Horn Rapids peaked dramatically during the last 2 weeks in May (between 132.9 ({+-}4.2) to 36.6 ({+-}2.2) gulls/day) and appeared to the associated with the release of > 1-mil hatchery juvenile fall chinook (Oncorhynchus tshawytscha) above the 2 study sites. A comparable peak in gull abundance was not observed at Chandler. Diurnal patterns of gull abundance also varied among years and sites. The relationship between foraging efficiency and gull numbers was not consistent among years or sites. Gull numbers were not correlated with river flow when year was considered. However, variations in flow among years appeared to be associated with average gull numbers at each site, but trends were not consistent between sites. Low seasonal flows were associated with increased predation at Chandler, whereas high seasonal flows were associated with increased predation at Horn Rapids. Assuming all fish taken were salmonids, we estimate gulls consumed between 0.1-10.3 % of the juvenile salmonids passing or being released from the Chandler Juvenile Fish Monitoring Facility located above the two structures. Staggered releases of hatchery fish, nocturnal releases of fish entrained in the Chandler facility, changes in the orientation of the outflow from the f

  12. State Energy Program Strategic Plan: February 2007

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

    State Energy Program Strategic Plan )HEUXDU SEP Strategic Plan February 2007 TABLE OF CONTENTS Foreword iii Mission and Operations 1 Current Energy Trends 1 Key Drivers 3 Setting...

  13. Measurement enhancement for state estimation 

    E-Print Network [OSTI]

    Chen, Jian

    2009-05-15T23:59:59.000Z

    ........................................................................ 51 3.6.1 IEEE 57-bus System ........................................................... 52 3.6.2 IEEE 118-bus System ......................................................... 54... Test System ............................................................ 80 4.5.2 IEEE 30-bus Test System.................................................... 83 4.5.3 Topology Error...

  14. Confidence Intervals for OD Demand Estimation Yingying Chen, Fernando Ordo~nez

    E-Print Network [OSTI]

    Ordóñez, Fernando

    Confidence Intervals for OD Demand Estimation Yingying Chen, Fernando Ord´o~nez , and Kurt Palmer Representative origin-destination (OD) demand tables are a crucial part of making many transportation models relevant to practice. However estimating these OD tables is a challenging problem, even more so determining

  15. Analysis and behavioral modeling of the Finite State Machines of the Xpress Transfer Protocol

    E-Print Network [OSTI]

    Madduri, Venkateswara Rao

    1994-01-01T23:59:59.000Z

    OF THE 3. 4 SPECIFICATION OF THE XTP FINITE STATE MACHINES . A. XTP Context Manager State Machine B. XTP Output State Machine C. XTP Sync State Machine. D. XTP Rate Control State Machine E. XTP Control-Send State Machine. . . F. XTP Input State... control parameters 26 II XTP context manager state transition table[12]. III XTP output state machine transition table [12]. IV XTP sync state machine transition table[12]. 40 V XTP rate control state machine transition table[12]. VI XTP control...

  16. Supplemental Tables to the Annual Energy Outlook

    Reports and Publications (EIA)

    2014-01-01T23:59:59.000Z

    The Annual Energy Outlook (AEO) Supplemental tables were generated for the reference case of the AEO using the National Energy Modeling System, a computer-based model which produces annual projections of energy markets. Most of the tables were not published in the AEO, but contain regional and other more detailed projections underlying the AEO projections.

  17. Universal Expression for the Lowest Excitation Energy of Natural Parity Even Multipole States

    E-Print Network [OSTI]

    Doohwan Kim; Eunja Ha; Dongwoo Cha

    2007-10-08T23:59:59.000Z

    We present a new expression for the energy of the lowest collective states in even-even nuclei throughout the entire periodic table. Our empirical formula is extremely valid and holds universally for all of the natural parity even multipole states. This formula depends only on the mass number and the valence nucleon numbers with six parameters. These parameters are determined easily and unambiguously from the data for each multipole state. We discuss the validity of our empirical formula by comparing our results with those of other studies and also by estimating the average and the dispersion of the logarithmic errors of the calculated excitation energies with respect to the measured ones.

  18. Cost-E ective Flow Table Designs for High-Speed Routers: Architecture and Performance Evaluation

    E-Print Network [OSTI]

    Xu, Jun "Jim"

    Cost-E#11;ective Flow Table Designs for High-Speed Routers: Architecture and Performance Evaluation State variables Service Parameters update read read Incoming packet action Search Y N Lookup Initialize to be performed (e.g., which output port to route the packet) on the packet and the new values the state variables

  19. Thermodynamic estimation: Ionic materials

    SciTech Connect (OSTI)

    Glasser, Leslie, E-mail: l.glasser@curtin.edu.au

    2013-10-15T23:59:59.000Z

    Thermodynamics establishes equilibrium relations among thermodynamic parameters (“properties”) and delineates the effects of variation of the thermodynamic functions (typically temperature and pressure) on those parameters. However, classical thermodynamics does not provide values for the necessary thermodynamic properties, which must be established by extra-thermodynamic means such as experiment, theoretical calculation, or empirical estimation. While many values may be found in the numerous collected tables in the literature, these are necessarily incomplete because either the experimental measurements have not been made or the materials may be hypothetical. The current paper presents a number of simple and relible estimation methods for thermodynamic properties, principally for ionic materials. The results may also be used as a check for obvious errors in published values. The estimation methods described are typically based on addition of properties of individual ions, or sums of properties of neutral ion groups (such as “double” salts, in the Simple Salt Approximation), or based upon correlations such as with formula unit volumes (Volume-Based Thermodynamics). - Graphical abstract: Thermodynamic properties of ionic materials may be readily estimated by summation of the properties of individual ions, by summation of the properties of ‘double salts’, and by correlation with formula volume. Such estimates may fill gaps in the literature, and may also be used as checks of published values. This simplicity arises from exploitation of the fact that repulsive energy terms are of short range and very similar across materials, while coulombic interactions provide a very large component of the attractive energy in ionic systems. Display Omitted - Highlights: • Estimation methods for thermodynamic properties of ionic materials are introduced. • Methods are based on summation of single ions, multiple salts, and correlations. • Heat capacity, entropy, lattice energy, enthalpy, Gibbs energy values are available.

  20. FY 2015 Summary Control Table by Organization

    Energy Savers [EERE]

    5 Summary Control Table by Organization (dollars in thousands - OMB Scoring) Summary Control by Organization Page 1 FY 2015 Congressional Request FY 2013 FY 2014 FY 2014 FY 2014 FY...

  1. TABLES3.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    S3. Crude Oil and Petroleum Product Imports, 1988 - Present (Thousand Barrels per Day) See footnotes at end of table. 1988 Average ... 300 58 345 343 92 80 0 0 1989...

  2. Nozick's minimal state?

    E-Print Network [OSTI]

    Russell, Darrell James

    1995-01-01T23:59:59.000Z

    seemed to have problems doing so, myself. Finally, I must give special acknowledgment to Debbie Hutchins for listening to me whine. TABLE OF CONTENTS ABSTRACT. DEDICATION. Page iv ACKNOWLEDGMENTS. . TABLE OF CO~5. . CHAPTER I INTRODUCTION. II.... Protective Policy Possibilities. . IV PROTECTIVE WELFARE. 8 11 14 25 29 30 34 39 43 50 56 Case 1: Roads. . Case 2: Education. Case 3: The Marshall Plan. . Arguments and Analysis. V A NOZICKIAN STATE Policy Objedions...

  3. La Thuile 2014: Theoretical premises to neutrino round table

    E-Print Network [OSTI]

    Francesco Vissani

    2014-05-25T23:59:59.000Z

    This talk, dedicated to the memory of G. Giacomelli, introduced the round table on neutrinos held in February 2014. The topics selected for the discussion are: 1) the neutrinoless double beta decay rate (interpretation in terms of light neutrinos, nuclear uncertainties); 2) the physics in the gigantic water Cherenkov detectors (proton decay, atmospheric neutrinos); 3) the study of neutrino oscillations (mass hierarchy and CP violation; other neutrino states); 4) the neutrino astronomy at low and high energies (solar, supernova, cosmic neutrinos). The importance of an active interplay between theory and experiment is highlighted.

  4. TABLE OF CONTENTS DIRECTOR'S DESK

    E-Print Network [OSTI]

    Weston, Ken

    MATTER SCIENCE Technique development, graphene, magnetism & magnetic materials, topological insulators to Insulator Transition on the N=0 Landau Level in Graphene 10 Evidence for Fractional Quantum Hall States in Suspended Bilayer and Trilayer Graphene 11 Fractional Quantum Hall Effect in Graphene on Boron Nitride 12

  5. Table Of Contents Section: Page

    E-Print Network [OSTI]

    US Army Corps of Engineers

    or Licenses that a Master or Journeyman Electrician may hold, depending on work being performed, and should be identified in the appropriate AHA. Journeyman/Apprentice ratio shall be in accordance with State, Local or Journeyman Electrician may hold, or USACE sponsored local training programs (e.g., hydropower training

  6. Florida State Bowling Team

    E-Print Network [OSTI]

    Weston, Ken

    The Florida State University Bowling Team Handbook 2012-2013 #12;THE FLORIDA STATE UNIVERSITY BOWLING TEAM HANDBOOK 2012-2013 2 Table of Contents WELCOME 3 VIRES, ARTES AND MORES 4 THE FSU BOWLING TEAM COACHING STAFF 5 PROGRAM PHILOSOPHY 7 Team Goals 7 Methods of Meeting Goals 7 Physical Game 8

  7. Florida State Bowling Team

    E-Print Network [OSTI]

    McQuade, D. Tyler

    The Florida State University Bowling Team Handbook 2014-2015 #12;THE FLORIDA STATE UNIVERSITY BOWLING TEAM HANDBOOK 2014-2015 2 Table of Contents WELCOME 3 VIRES, ARTES AND MORES 4 THE FSU BOWLING TEAM COACHING STAFF 5 PROGRAM PHILOSOPHY 8 Team Goals 8 Methods of Meeting Goals 9 Physical Game 10

  8. Florida State Bowling Team

    E-Print Network [OSTI]

    Ronquist, Fredrik

    The Florida State University Bowling Team Handbook 2014-2015 #12;THE FLORIDA STATE UNIVERSITY BOWLING TEAM HANDBOOK 2014-2015 2 Table of Contents WELCOME 3 VIRES, ARTES AND MORES 4 THE FSU BOWLING TEAM COACHING STAFF 5 PROGRAM PHILOSOPHY 7 Team Goals 7 Methods of Meeting Goals 7 Physical Game 8

  9. INTERNSHIP HANDBOOK Montana State University

    E-Print Network [OSTI]

    Dyer, Bill

    INTERNSHIP HANDBOOK Montana State University Counseling Program 2014-2015 #12;2 TABLE OF CONTENTS..........................................................................................................................................4 INTERNSHIP ASSIGNMENT TO YOUR PLACEMENT SITES........................................................................................5 APPLICATION TO INTERNSHIP SITES INTERNSHIP AT PLACE OF EMPLOYMENT OTHER IMPORTANT INFORMATION

  10. State Energy Price System: 1982 update

    SciTech Connect (OSTI)

    Imhoff, K.L.; Fang, J.M.

    1984-10-01T23:59:59.000Z

    The State Energy Price System (STEPS) contains estimates of energy prices for ten major fuels (electricity, natural gas, metallurgical coal, steam coal, distillate, motor gasoline, diesel, kerosene/jet fuel, residual fuel, and liquefied petroleum gas), by major end-use sectors (residential, commercial, industrial, transportation, and electric utility), and by state through 1982. Both physical unit prices and prices per million Btu are included in STEPS. Major changes in STEPS data base for 1981 and 1982 are described. The most significant changes in procedures for the updates occur in the residential sector distillate series and the residential sector kerosene series. All physical unit and Btu prices are shown with three significant digits instead of with four significant digits as shown in the original documentation. Details of these and other changes are contained in this report, along with the updated data files. 31 references, 65 tables.

  11. Table 1. 2013 Summary Statistics

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API Gravity Period: Monthly Annual Download SeriesPennsylvania"Tennessee"Texas"United States"

  12. Appendix A. Hydraulic Properties Statistics Tables Table A1. Hydraulic properties statistics for the alluvium (Stephens et al.).

    E-Print Network [OSTI]

    A-1 Appendix A. Hydraulic Properties Statistics Tables Table A1. Hydraulic properties statistics Deviation .1708 4.274 28.95 Harmonic Mean Number of Observations 9 8 8 2 2 2 2 2 Table A2. Hydraulic.3×10-5 Number of Observations 10 10 10 34 34 4 4 4 #12;A-2 Table A3. Hydraulic properties statistics

  13. area state-approved land: Topics by E-print Network

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

    Author Glenn Patrick Juday is associate professor of plant ecology and Alaska ecological reserves Big Windy Hot Springs; Glenn Patrick Juday 24 Table 1. Annual estimates,...

  14. FY 2009 Volume Summary table

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment6 FY 2007 FY 2008State7 FY 2008 FY3467

  15. Table 1. 2013 Summary Statistics

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API Gravity Period: Monthly Annual Download SeriesPennsylvania"Tennessee"Texas"United States"Utah"

  16. FY 2014 Budget Request State Table | Department of Energy

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directed off Energy.gov. Are you sure you want toworldPowerHome |CookingFAQs FAQs

  17. Table 6. Energy intensity by State (2000 - 2011)

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a(STEO)U.S. Coal Stocks at Manufacturing PlantsEnergy

  18. Table 6. Energy intensity by State (2000-2011

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1 U.S. Department of Energy Energy Information32. Average2011EnergyEnergy

  19. Table A1. Refiner/Reseller Motor Gasoline Prices by Grade, PAD...

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

    71.6 92.3 78.2 101.8 83.6 87.5 74.7 See footnotes at end of table. A1. RefinerReseller Motor Gasoline Prices by Grade, PAD District, and State, 1984-Present 452 Energy Information...

  20. Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District...

    Gasoline and Diesel Fuel Update (EIA)

    82.4 77.1 68.9 62.6 71.6 92.3 89.9 82.6 72.7 - 78.2 See footnotes at end of table. 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 56 Energy Information...

  1. Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District...

    Gasoline and Diesel Fuel Update (EIA)

    82.5 75.1 68.6 62.0 70.7 92.7 90.7 81.5 72.8 - 78.0 See footnotes at end of table. 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State 56 Energy Information...

  2. SECTION 2 Table of Contents 2 Province Management Plan and Inventory....................................................2

    E-Print Network [OSTI]

    2-1 SECTION 2 ­ Table of Contents 2 Province Management Plan and Inventory 2.4 Inventory of Existing Programs in the Intermountain Province................................. 48....................................................................... 80 #12;2-2 2 Province Management Plan and Inventory The Technical Guide for Subbasin Planners states

  3. The Founding of ALA's Map and Geography Round Table : Looking Back to See the Future

    E-Print Network [OSTI]

    Weimer, Katherine H.

    2011-01-01T23:59:59.000Z

    In 1979, a group of map librarians founded the American Library Association’s Map and Geography Round Table (MAGERT). An examination of the organization’s creation and early history offers a glimpse into the state of map librarianship at that time...

  4. Stem cubic-foot volume tables for tree species in the upper coastal plain. Forest Service research paper

    SciTech Connect (OSTI)

    Clark, A.; Souter, R.A.

    1996-03-01T23:59:59.000Z

    Steamwood cubic-foot volume inside bark tables are presented for 11 species and 8 species groups based on equations used to estimate timber sale volumes on national forests in the Upper Coastal Plain. Tables are based on form class measurement data for 521 trees sampled in the Upper Coastal Plain and taper data collected across the South. A series of tables is presented for each species based on diameter at breast height (d.b.h.) in combination with total height and height to a 4-inch diameter outside bark (d.o.b.) top. Volume tables are also presented based on d.b.h. in combination with height to a 7-inch d.o.b. top for softwoods and height to a 9-inch d.o.b. top for hardwoods.

  5. Stem cubic-foot volume tables for tree species in the Appalachian area. Forest Service research paper

    SciTech Connect (OSTI)

    Clark, A.; Souter, R.A.

    1996-03-01T23:59:59.000Z

    Steamwood cubic-foot volume inside bark tables are presented for 20 species and 8 species groups based on equations used to estimate timber sale volumes on national forests in the Appalachian Area. Tables are based on form class measurement data for 2,670 trees sampled in the Appalachian Area and taper data collected across the South. A series of tables is presented for each species based on diameter at breast height (d.b.h.) in combination with total height and height to a 4-inch diameter outside bark (d.o.b.) top. Volume tables are also presented based on d.b.h. in combination with height to a 7-inch d.o.b. top for softwoods and height to a 9-inch d.o.b. top for hardwoods.

  6. Stem cubic-foot volume tables for tree species in the Gulf and Atlantic coastal plain. Forest Service research paper

    SciTech Connect (OSTI)

    Clark, A.; Souter, R.A.

    1996-03-01T23:59:59.000Z

    Steamwood cubic-foot volume inside bark tables are presented for 14 species and 9 species groups based on equations used to estimate timber sale volumes on national forests in the Gulf and Atlantic Coastal Plain. Tables are based on form class measurement data for 2,728 trees sampled in the Gulf and Atlantic Coastal Plain and taper data collected across the South. A series of tables is presented for each species based on diameter at breast height (d.b.h.) in combination with total height and height to a 4-inch diameter outside bark (d.o.b.) top. Volume tables are also presented based on d.b.h. in combination with height to a 7-inch d.o.b. top for softwoods and height to a 9-inch d.o.b. top for hardwoods.

  7. Stem cubic-foot volume tables for tree species in the Arkansas area. Forest Service research paper

    SciTech Connect (OSTI)

    Clark, A.; Souter, R.A.

    1996-03-01T23:59:59.000Z

    Steamwood cubic-foot volume inside bark tables are presented for 9 species and 9 species groups based on equations used to estimate timber sale volumes on national forests in the Arkansas Area. Tables are based on form class measurement data for 1,417 trees sampled in the Arkansas Area and taper data collected across the South. A series of tables is presented for each species based on diameter at breast height (d.b.h.) in combination woth total height and height to a 4-inch diameter outside bark (d.o.b.) top. Volume tables are also presented based on d.b.h. in combination with height to a 7-inch d.o.b. top for softwoods and height to a 9-inch d.o.b. top for hardwoods.

  8. Stem cubic-foot volume tables for tree species in the Delta area. Forest Service research paper

    SciTech Connect (OSTI)

    Clark, A.; Souter, R.A.

    1996-03-01T23:59:59.000Z

    Steamwood cubic-foot volume inside bark tables are presented for 13 species and 6 species groups based on equations used to estimate timber sale volumes on national forests in the Delta Area. Tables are based on form class measurement data for 990 trees sampled in the Delta Area and taper data collected across the South. A series of tables is presented for each species based on diameter at breast height (d.b.h.) in combination with total height and height to a 4-inch diameter outside bark (d.o.b.) top. Volume tables are also presented based on diameter outside of the bark (d.o.b.) in combination with height with to a 9-inch d.o.b. top.

  9. Table Definitions, Sources, and Explanatory Notes

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oilAll Tables133,477 133,5910.9. Table

  10. NOAA Technical Memorandum ERL GLERL-101 COMPUTER PROGRAM FOR ESTIMATING EVAPOTRANSPIRATION USING THE

    E-Print Network [OSTI]

    .................................................................................................................................. 8 TABLES Table 1.--Shallow-Rooted Crops (Spinach, peas, Beans, Beets, Carrots, etc Understanding and estimating the earth's hydrologic cycle is important to water resource planners and managers.0 EVAPOTRANSPIRATION Potential evapotranspiration (PET), as described by Penman (1948), is "the amount of water

  11. Fast mix table construction for material discretization

    SciTech Connect (OSTI)

    Johnson, S. R. [Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)

    2013-07-01T23:59:59.000Z

    An effective hybrid Monte Carlo-deterministic implementation typically requires the approximation of a continuous geometry description with a discretized piecewise-constant material field. The inherent geometry discretization error can be reduced somewhat by using material mixing, where multiple materials inside a discrete mesh voxel are homogenized. Material mixing requires the construction of a 'mix table,' which stores the volume fractions in every mixture so that multiple voxels with similar compositions can reference the same mixture. Mix table construction is a potentially expensive serial operation for large problems with many materials and voxels. We formulate an efficient algorithm to construct a sparse mix table in O(number of voxels x log number of mixtures) time. The new algorithm is implemented in ADVANTG and used to discretize continuous geometries onto a structured Cartesian grid. When applied to an end-of-life MCNP model of the High Flux Isotope Reactor with 270 distinct materials, the new method improves the material mixing time by a factor of 100 compared to a naive mix table implementation. (authors)

  12. Table of Contents ODS Scholars 1

    E-Print Network [OSTI]

    Chapman, Michael S.

    Table of Contents ODS Scholars 1 Endowed Lecture 1 Senju 3 Research Awards 4 Dr. Stewart 5 OHSU (see page two) 2011 ODS Scholars Announced May 2 The $300,000 gift from the ODS Companies provides five students recently were selected as ODS Scholars for 2011-2012. The awardees were announced at the third

  13. Section 4. Inventory Table of Contents

    E-Print Network [OSTI]

    Section 4. Inventory Table of Contents 4.1 Existing Legal Protections........................................................................................................... 14 #12;Draft Umatilla/Willow Subbasin Plan May 28, 2004 4. Inventory of Existing Activities The following section contains information derived from an inventory questionnaire that was sent

  14. Philosophy 57 Greensheet (Syllabus) Table of Contents

    E-Print Network [OSTI]

    Fitelson, Branden

    Philosophy 57 Greensheet (Syllabus) Table of Contents: Instructor Information Course Home Page Greensheet Page Page 1 of 3http://philosophy.wisc.edu/fitelson/57/syllabus.htm #12;I highly recommend using/syllabus.htm #12;Your 2 lowest quiz grades will be dropped ( , your 5 best quiz scores will be averaged). i

  15. CONTROL OF HAZARDOUS ENERGY Table Of Contents

    E-Print Network [OSTI]

    US Army Corps of Engineers

    EM 385-1-1 XX Sep 13 i Section 12 CONTROL OF HAZARDOUS ENERGY Table Of Contents Section: Page 12.A General.................. .............................................. ... .12-1 12.B Hazardous Energy.......................................................12-6 #12;EM 385-1-1 XX Sep 13 12-1 SECTION 12 CONTROL OF HAZARDOUS ENERGY 12.A GENERAL 12.A.01 When

  16. A reconstruction of the tables of Thompson's

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    A reconstruction of the tables of Thompson's Logarithmetica Britannica (1952) Denis Roegel 20-21Dec2011 #12;hal-00654453,version1-21Dec2011 #12;1 Alexander John Thompson (1885­19??) Alexander John Thompson was born in 1885 in Plaistow, Essex, England. In 1920, he joined the statistical staff

  17. TABLE OF CONTENTS Organizational Profile i

    E-Print Network [OSTI]

    Magee, Joseph W.

    1 #12;2 TABLE OF CONTENTS Organizational Profile i Leadership 1 1.1a. Vision, Values and Mission 1 1.1b. Communication and Organizational Performance 3 1.2a. Organizational Governance 3 1.2b. Legal employees with ORGANIZATIONAL PROFILE $26 million in revenue. Most of that revenue was generated by its

  18. Table of hyperfine anomaly in atomic systems

    SciTech Connect (OSTI)

    Persson, J.R., E-mail: jonas.persson@ntnu.no

    2013-01-15T23:59:59.000Z

    This table is a compilation of experimental values of magnetic hyperfine anomaly in atomic and ionic systems. The last extensive compilation was published in 1984 by Büttgenbach [S. Büttgenbach, Hyperfine Int. 20 (1984) 1] and the aim here is to make an up to date compilation. The literature search covers the period up to January 2011.

  19. Schedule Worksheet -Table of Contents Subject Description

    E-Print Network [OSTI]

    Pittendrigh, Barry

    Subject Description NUPH NUPH-Nuclear Pharmacy NUR NUR-Nursing OBHR OBHR-Orgnztnl Bhvr &Hum Resrce OLS OLS Description CLPH CLPH-Clinical Pharmacy CMCI CMCI-CIC Common Market CMPL CMPL-Comparative Literature CNIT CNIT Sci NS NS-Naval Science NUCL NUCL-Nuclear Engineering #12;Schedule Worksheet - Table of Contents

  20. Schedule Worksheet -Table of Contents Subject Description

    E-Print Network [OSTI]

    Ginzel, Matthew

    ;Schedule Worksheet - Table of Contents Subject Description NUPH NUPH-Nuclear Pharmacy NUR NUR-Nursing NUTR Description CLPH CLPH-Clinical Pharmacy CMCI CMCI-CIC Common Market CMPL CMPL-Comparative Literature CNIT CNIT-Music History & Theory NRES NRES-Natural Res & Environ Sci NS NS-Naval Science NUCL NUCL-Nuclear Engineering #12

  1. VEHICLE SERVICES POLICY Table of Contents

    E-Print Network [OSTI]

    Shihadeh, Alan

    VEHICLE SERVICES POLICY Table of Contents 1. Policy 2. Procedures a. Vehicle Services Oversight b. Vehicle Maintenance and Inspection c. Authorized Drivers d. Responsibilities Back to Top (To download requirements for AUB's vehicles, the University has adopted a policy of centralizing these activities under one

  2. Streiffer's Job Market Sampler Table of Contents

    E-Print Network [OSTI]

    Streiffer, Robert

    Streiffer's Job Market Sampler Table of Contents · Cover letters addressing a variety of jobs Dean Sigman, I am writing to apply for position number 8, advertised in Jobs for Philosophers, volume. Respectfully yours, Robert Streiffer (rstreiff@mit.edu) #12;Cover letter for a job listing which

  3. VEHICLES, MACHINERY AND EQUIPMENT Table Of Contents

    E-Print Network [OSTI]

    US Army Corps of Engineers

    of a license/permit for each piece of equipment, an Operator Equipment Qualification Record (DA Form 348EM 385-1-1 XX Sep 13 i Section 18 VEHICLES, MACHINERY AND EQUIPMENT Table Of Contents Section: Page...................................................................18-16 18.G Machinery And Mechanized Equipment.........................18-16 18.H Drilling Equipment

  4. WORK PLATFORMS and SCAFFOLDING Table Of Contents

    E-Print Network [OSTI]

    US Army Corps of Engineers

    EM 385-1-1 XX Sep 13 i Section 22 WORK PLATFORMS and SCAFFOLDING Table Of Contents Section: Page 22 (Personnel) Platforms...................22-33 22.L Elevating Work Platforms..............................................22-33 22.M Vehicle-Mounted Elevating And Rotating Work Platforms (Aerial Devices

  5. Estimated monthly emissions of sulfur dioxide, oxides of nitrogen, and volatile organic compounds for the 48 contiguous states, 1985-1986: Volume 2, Sectoral emissions by month for states

    SciTech Connect (OSTI)

    Kohout, E.J.; Knudson, D.A.; Saricks, C.L.; Miller, D.J.

    1987-11-01T23:59:59.000Z

    A listing by source of sulfur dioxide, nitrogen oxides and volatile organic compounds emitted in 48 states of the US is provided. (CBS)

  6. Fusion Tables : new ways to collaborate on structured data

    E-Print Network [OSTI]

    Kidon, Jonathan Goldberg

    2010-01-01T23:59:59.000Z

    Fusion Tables allows data collaborators to create, merge, navigate and set access control permissions on structured data. This thesis focuses on the collaboration tools that were added to Googles Fusion Tables. The ...

  7. MemTable : contextual memory in group workspaces

    E-Print Network [OSTI]

    Hunter, Seth E

    2009-01-01T23:59:59.000Z

    This thesis presents the design and implementation of MemTable, an interactive touch table that supports co-located group meetings by capturing both digital and physical interactions in its memory. The goal of the project ...

  8. Analytical methods for estimating saturated hydraulic conductivity in a tile-drained field

    E-Print Network [OSTI]

    Selker, John

    Analytical methods for estimating saturated hydraulic conductivity in a tile-drained field David E; Saturated hydraulic conductivity; Field scale; Tile drains; Water table 1. Introduction The use of spatially

  9. Improving the Carbon Dioxide Emission Estimates from the Combustion of Fossil Fuels in California

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2010-01-01T23:59:59.000Z

    Sales 2006. Office of Oil and Gas, DOE/EIA-0535(06).6 2.3 Oil and Gas Extraction9 Table 6. Oil and Gas Extraction Energy Use as Estimated in

  10. 1 Estimating aquifer hydraulic properties from the inversion of surface 2 Streaming Potential (SP) anomalies

    E-Print Network [OSTI]

    Sailhac, Pascal

    1 Estimating aquifer hydraulic properties from the inversion of surface 2 Streaming Potential (SP with the geometry of the water table. It follows that 11 SP measurements can be used to estimate aquifer hydraulic and found that we 14 are able to estimate the hydraulic conductivity and the depth 15 and the thickness

  11. Environmental Regulatory Update Table, January/February 1992

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.

    1992-03-01T23:59:59.000Z

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action. This table is for January/February 1992.

  12. Effective July 1, 2013 Table of Organization: College of Law

    E-Print Network [OSTI]

    Stanier, Charlie

    Effective July 1, 2013 Table of Organization: College of Law Dean Gail Agrawal Assistant to the Dean Legal Clinic Julie Kramer {See Clinic Table for organization} Special Assistant to the Dean Gerhild Krapf Centers {See separate tables for organization} Assoc. Dean for Research Assoc. Dean Assoc

  13. Table Contents Page i 2013 Nonresidential Compliance Manual January 2014

    E-Print Network [OSTI]

    Table B-1 Room Air Conditioner, Room Air-Conditioning Heat Pump, Packaged Terminal Air Conditioner ....................................................................................11 Table B-2 Standards for Room Air Conditioners and Room Air-Conditioning Heat Pumps...........12 Table B-3 Standards for Packaged Terminal Air Conditioners and Packaged Terminal Heat Pumps

  14. Impact of price specials on estimates of retail meat prices

    E-Print Network [OSTI]

    Degner, Robert L

    1970-01-01T23:59:59.000Z

    ighting Technique V. V. SUM'JARA' AND CONCLUSIONS. 46 55 o3 69 Ti. me-of-the-Week to Collect Prices. Bias Reduced by Regression. Concluding Statement. REFEBENCES. APPENDIX. 89 90 95 100 115 vill LIST OF TABLES Table Page 1-1. Relative...' or individual items in Dallas and Houston. 101 3-1. Simulated BLS price estimates of 46 meat items based upon different sampling rates and weighted average price, or all data, July 1968. . . . . . . . . . . . 107 "Error" of price estimates; differences...

  15. Integral CFLs performance in table lamps

    SciTech Connect (OSTI)

    Page, E.; Driscoll, D.; Siminovitch, M.

    1997-03-01T23:59:59.000Z

    This paper focuses on performance variations associated with lamp geometry and distribution in portable table luminaires. If correctly retrofit with compact fluorescent lamps (CFLs), these high use fixtures produce significant energy savings, but if misused, these products could instead generate consumer dissatisfaction with CFLs. It is the authors assertion that the lumen distribution of the light source within the luminaires plays a critical role in total light output, fixture efficiency and efficacy, and, perhaps most importantly, perceived brightness. The authors studied nearly 30 different integral (screw-based) CFLs available on the market today in search of a lamp, or group of lamps, which work best in portable table luminaires. The findings conclusively indicate that horizontally oriented CFLs outperform all other types of CFLs in nearly every aspect.

  16. Tables of thermodynamic properties of sodium

    SciTech Connect (OSTI)

    Fink, J.K.

    1982-06-01T23:59:59.000Z

    The thermodynamic properties of saturated sodium, superheated sodium, and subcooled sodium are tabulated as a function of temperature. The temperature ranges are 380 to 2508 K for saturated sodium, 500 to 2500 K for subcooled sodium, and 400 to 1600 K for superheated sodium. Tabulated thermodynamic properties are enthalpy, heat capacity, pressure, entropy, density, instantaneous thermal expansion coefficient, compressibility, and thermal pressure coefficient. Tables are given in SI units and cgs units.

  17. Development of a right-of-way cost estimation and cost estimate management process framework for highway projects

    E-Print Network [OSTI]

    Lucas, Matthew Allen

    2009-05-15T23:59:59.000Z

    .............................................................. 31 Results: ROW Estimation State of Practice ................................... 31 Critical Issues ....................................................................... 32 Overview of Current Practice... ............................................... 35 Analysis: Critical Review of Practices ........................................... 41 General ROW Cost Estimation Procedure ........................... 42 ROW Cost Estimation...

  18. TABLE14.CHP:Corel VENTURA

    Gasoline and Diesel Fuel Update (EIA)

    4. Production of Crude Oil by PAD District and State, January 1998 PAD District and State Total Daily Average (Thousand Barrels) PAD District I ......

  19. adaptive parameter estimation: Topics by E-print Network

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

    Tokamak Heat Computer Technologies and Information Sciences Websites Summary: . Keywords: Thermonuclear fusion, distributed parameter systems, input state and parameter estimation,...

  20. TABLE53.CHP:Corel VENTURA

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousandCubic Feet) DecadeV - DailyPercent 0 0 09.Table 53.

  1. TABLE54.CHP:Corel VENTURA

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122Commercial ConsumersThousandCubic Feet) DecadeV - DailyPercent 0 0 09.Table

  2. Federal Buildings Supplemental Survey -- Publication and Tables

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40CoalLease(Billion2,12803 Table A1. Refiner/Reseller2009 2010 2011Overview >

  3. FY 2009 Control Table by Appropriation

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 1112011 Strategic Plan| Department of.pdf6-OPAMDepartment6 FY 2007 FY 2008 Current27Control Table

  4. Help:Tables | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDIT REPORTEnergyFarms AHefei Sungrow PowersourceSubObjects JumpTables

  5. Table of Contents for Desk Guide

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn April 23, 2014,ZaleskiThis Decision considersTable 1: Points of Entry/Exit

  6. Table 11. Net metering, 2010 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConference |6:WelcomeArkansas":

  7. Table 11. Net metering, 2010 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConference

  8. Table 12. Advanced metering, 2007 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConferenceInstalled NameplateTotal

  9. Table 12. Advanced metering, 2007 through 2013

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConferenceInstalled

  10. Table 13. Coal Production, Projected vs. Actual

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14TableConferenceInstalled: Associated-dissolved:

  11. Table 16. U.S. Coke Exports

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oilAll Tables133,477 133,5910. Average3.5.6.

  12. Table 18. U.S. Coal Imports

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oilAll Tables133,477 133,5910.

  13. Table 20. Coal Imports by Customs District

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oilAll Tables133,477 133,5910.9. Average

  14. Table 21. U.S. Coke Imports

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oilAll Tables133,477 133,5910.9. Average1.

  15. Table 7. U.S. Coal Exports

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oilAll Tables133,477 133,5910.9. Average1.2.7.

  16. Summary Statistics Table 1. Crude Oil Prices

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear Jan FebDecadeDecade21 Louisiana LouisianaCubicCubicYear Jan

  17. Tables, Graphs, and Problems | ornl.gov

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengthening a solidSynthesis of 2D Alloys &8-5070P3. U.S.7.Tables, Graphs,

  18. Cost estimates for near-term depolyment of advanced traffic management systems. Final report

    SciTech Connect (OSTI)

    Stevens, S.S.; Chin, S.M.

    1993-02-15T23:59:59.000Z

    The objective of this study is to provide cost est engineering, design, installation, operation and maintenance of Advanced Traffic Management Systems (ATMS) in the largest 75 metropolitan areas in the United States. This report gives estimates for deployment costs for ATMS in the next five years, subject to the qualifications and caveats set out in following paragraphs. The report considers infrastructure components required to realize fully a functional ATMS over each of two highway networks (as discussed in the Section describing our general assumptions) under each of the four architectures identified in the MITRE Intelligent Vehicle Highway Systems (IVHS) Architecture studies. The architectures are summarized in this report in Table 2. Estimates are given for eight combinations of highway networks and architectures. We estimate that it will cost between $8.5 Billion (minimal network) and $26 Billion (augmented network) to proceed immediately with deployment of ATMS in the largest 75 metropolitan areas. Costs are given in 1992 dollars, and are not adjusted for future inflation. Our estimates are based partially on completed project costs, which have been adjusted to 1992 dollars. We assume that a particular architecture will be chosen; projected costs are broken by architecture.

  19. Environmental regulatory update table, September--October 1992

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Lewis, E.B.; Salk, M.S.

    1992-11-01T23:59:59.000Z

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.

  20. Environmental Regulatory Update Table, January--February 1993

    SciTech Connect (OSTI)

    Houlberg, L.M.; Hawkins, G.T.; Salk, M.S.; Danford, G.S.; Lewis, E.B.

    1993-03-01T23:59:59.000Z

    The Environmental Regulatory Update Table provides information on regulatory initiatives of interest to DOE operations and contractor staff with environmental management responsibilities. The table is updated bi-monthly with information from the Federal Register and other sources, including direct contact with regulatory agencies. Each table entry provides a chronological record of the rulemaking process for that initiative with an abstract and a projection of further action.