National Library of Energy BETA

Sample records for low-end estimate usd

  1. Property:EstimatedCostLowUSD | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Name EstimatedCostLowUSD Property Type Quantity Description the low estimate of cost in USD Use this type to express a monetary value in US Dollars. The default unit is one...

  2. Property:EstimatedCostHighUSD | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Name EstimatedCostHighUSD Property Type Quantity Description the high estimate of cost in USD Use this type to express a monetary value in US Dollars. The default unit is one...

  3. Property:EstimatedCostMedianUSD | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Name EstimatedCostMedianUSD Property Type Quantity Description the median estimate of cost in USD Use this type to express a monetary value in US Dollars. The default unit is one...

  4. Oil Spill Management Market is Estimated to Reach USD 114,441...

    OpenEI (Open Energy Information) [EERE & EIA]

    Oil Spill Management Market is Estimated to Reach USD 114,441.1 Million by 2020 Home > Groups > Renewable Energy RFPs Wayne31jan's picture Submitted by Wayne31jan(150) Contributor...

  5. Oil Shale Market is Estimated to Reach USD 7,400.70 Million by...

    OpenEI (Open Energy Information) [EERE & EIA]

    Oil Shale Market is Estimated to Reach USD 7,400.70 Million by 2022 Home > Groups > Renewable Energy RFPs Wayne31jan's picture Submitted by Wayne31jan(150) Contributor 1 July, 2015...

  6. USD 422 Greensburg K-12 School

    Energy.gov [DOE]

    This poster highlights energy efficiency, renewable energy, and sustainable features of the high-performing USD 422 K-12 school in Greensburg, Kansas.

  7. Floating Production Systems Market Is Expected To Reach USD 38...

    OpenEI (Open Energy Information) [EERE & EIA]

    Production Systems Market Is Expected To Reach USD 38,752.7 Million Globally By 2019 Home > Groups > Future of Condition Monitoring for Wind Turbines Wayne31jan's picture...

  8. Rebuilding It Better: Greensburg, Kansas. USD 422 Greensburg K-12 School (Brochure)

    SciTech Connect

    Not Available

    2010-04-01

    This brochure details the energy efficient and sustainable aspects of the USD 422 K-12 school in Greensburg, Kansas.

  9. Rebuilding It Better: Greensburg, Kansas, USD 422 Greensburg K-12 School (Revised) (Brochure)

    SciTech Connect

    Not Available

    2011-04-01

    This brochure details the energy efficient and sustainable aspects of the USD 422 K-12 school in Greensburg, Kansas.

  10. USD Catalysis Group for Alternative Energy - Final report

    SciTech Connect

    Hoefelmeyer, James

    2014-10-03

    I. Project Summary Catalytic processes are a major technological underpinning of modern society, and are essential to the energy sector in the processing of chemical fuels from natural resources, fine chemicals synthesis, and energy conversion. Advances in catalyst technology are enormously valuable since these lead to reduced chemical waste, reduced energy loss, and reduced costs. New energy technologies, which are critical to future economic growth, are also heavily reliant on catalysts, including fuel cells and photo-electrochemical cells. Currently, the state of South Dakota is underdeveloped in terms of research infrastructure related to catalysis. If South Dakota intends to participate in significant economic growth opportunities that result from advances in catalyst technology, then this area of research needs to be made a high priority for investment. To this end, a focused research effort is proposed in which investigators from The University of South Dakota (USD) and The South Dakota School of Mines and Technology (SDSMT) will contribute to form the South Dakota Catalysis Group (SDCG). The multidisciplinary team of the (SDCG) include: (USD) Dan Engebretson, James Hoefelmeyer, Ranjit Koodali, and Grigoriy Sereda; (SDSMT) Phil Scott Ahrenkiel, Hao Fong, Jan Puszynski, Rajesh Shende, and Jacek Swiatkiewicz. The group is well suited to engage in a collaborative project due to the resources available within the existing programs. Activities within the SDCG will be monitored through an external committee consisting of three distinguished professors in chemistry. The committee will provide expert advice and recommendations to the SDCG. Advisory meetings in which committee members interact with South Dakota investigators will be accompanied by individual oral and poster presentations in a materials and catalysis symposium. The symposium will attract prominent scientists, and will enhance the visibility of research in the state of South Dakota. The SDCG requests

  11. Rebuilding It Better: Greensburg, Kansas. USD 422 Greensburg K-12 School (Revised) (Brochure), Energy Efficiency & Renewable Energy (EERE)

    Energy.gov [DOE]

    This brochure details the energy efficient and sustainable aspects of the USD 422 K-12 school in Greensburg, Kansas.

  12. Global Fuel Cells Market to Value USD910.3 million by 2018 |...

    OpenEI (Open Energy Information) [EERE & EIA]

    Global Fuel Cells Market to Value USD910.3 million by 2018 Home > Groups > Renewable Energy RFPs John55364's picture Submitted by John55364(100) Contributor 15 May, 2015 - 02:14...

  13. Artificial Lift Systems Market is expected to reach USD 19,806...

    OpenEI (Open Energy Information) [EERE & EIA]

    Artificial Lift Systems Market is expected to reach USD 19,806.8 Million by 2020 Home > Groups > Renewable Energy RFPs Wayne31jan's picture Submitted by Wayne31jan(150) Contributor...

  14. Template:ExplorationTechnique | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    could provide EstimatedCostLowUSD - the estimated value only of the low end of the cost range (units described in CostUnit) EstimatedCostMedianUSD - the estimated value only...

  15. Template:ExplorationGroup | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    could provide EstimatedCostLowUSD - the estimated value only of the low end of the cost range (units described in CostUnit) EstimatedCostMedianUSD - the estimated value only...

  16. Direct-Current Resistivity Survey | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    fluid type and phase state of the pore water. Thermal: Resistivity influenced by temperature.1 Cost Information Low-End Estimate (USD): 4,827.00482,700 centUSD 4.827...

  17. USD E'16 ATLANTA

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    REGISTER NOW 15th Annual DOE Small Business Forum & Expo MAY 23 - 25, 2016 Atlanta Marriott Marquis 265 Peachtree Center Avenue Atlanta, GA 30303 Government per diem 135.00night ...

  18. USD Catalysis Group for Alternative Energy

    SciTech Connect

    Hoefelmeyer, James D.; Koodali, Ranjit; Sereda, Grigoriy; Engebretson, Dan; Fong, Hao; Puszynski, Jan; Shende, Rajesh; Ahrenkiel, Phil

    2012-03-13

    The South Dakota Catalysis Group (SDCG) is a collaborative project with mission to develop advanced catalysts for energy conversion with two primary goals: (1) develop photocatalytic systems in which polyfunctionalized TiO2 are the basis for hydrogen/oxygen synthesis from water and sunlight (solar fuels group), (2) develop new materials for hydrogen utilization in fuel cells (fuel cell group). In tandem, these technologies complete a closed chemical cycle with zero emissions.

  19. Estimating Methods

    Directives, Delegations, and Other Requirements [Office of Management (MA)]

    1997-03-28

    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.

  20. USD 376 Sterling High School Wind Project | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    - Yankton School District Wind Project

  1. USD 440 Halstead Schools Wind Project | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    - Yankton School District Wind Project

  2. USD 384 Blue Valley Wind Project | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    - Yankton School District Wind Project

  3. USD 393 Solomon High School Wind Project | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    - Yankton School District Wind Project

  4. USD 307 Ell-Saline Wind Project | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    - Yankton School District Wind Project

  5. USD 375 Circle High School Wind Project | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    - Yankton School District Wind Project

  6. USD 345 Seaman High School Wind Project | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    - Yankton School District Wind Project

  7. USD 373 Walton Rural Life Wind Project | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    - Yankton School District Wind Project

  8. Turkey Marine Lubricants Market is Expected to Reach USD 177...

    OpenEI (Open Energy Information) [EERE & EIA]

    are primarily categorized into seven different applications including engine oils, hydraulic oils, grease, turbine oils, gear oils, compressor oils and heat transfer fluids....

  9. State Energy Production Estimates

    Annual Energy Outlook

    Production Estimates 1960 Through 2014 2014 Summary Tables U.S. Energy Information Administration | State Energy Data 2014: Production 1 Table P1. Energy Production Estimates in ...

  10. Cost Estimation Package

    Directives, Delegations, and Other Requirements [Office of Management (MA)]

    1997-03-28

    This chapter focuses on the components (or elements) of the cost estimation package and their documentation.

  11. Check Estimates and Independent Costs

    Directives, Delegations, and Other Requirements [Office of Management (MA)]

    1997-03-28

    Check estimates and independent cost estimates (ICEs) are tools that can be used to validate a cost estimate. Estimate validation entails an objective review of the estimate to ensure that estimate criteria and requirements have been met and well documented, defensible estimate has been developed. This chapter describes check estimates and their procedures and various types of independent cost estimates.

  12. State Energy Production Estimates

    Energy Information Administration (EIA) (indexed site)

    Energy Production Estimates 1960 Through 2012 2012 Summary Tables Table P1. Energy Production Estimates in Physical Units, 2012 Alabama 19,455 215,710 9,525 0 Alaska 2,052 351,259...

  13. Types of Cost Estimates

    Directives, Delegations, and Other Requirements [Office of Management (MA)]

    1997-03-28

    The chapter describes the estimates required on government-managed projects for both general construction and environmental management.

  14. A wedge-based approach to estimating health co-benefits of climate change mitigation activities in the United States

    SciTech Connect

    Balbus, John M.; Greenblatt, Jeffery B.; Chari, Ramya; Millstein, Dev; Ebi, Kristie L.

    2015-02-01

    While it has been recognized that actions reducing greenhouse gas (GHG) emissions can have significant positive and negative impacts on human health through reductions in ambient fine particulate matter (PM2.5) concentrations, these impacts are rarely taken into account when analyzing specific policies. This study presents a new framework for estimating the change in health outcomes resulting from implementation of specific carbon dioxide (CO2) reduction activities, allowing comparison of different sectors and options for climate mitigation activities. Our estimates suggest that in the year 2020, the reductions in adverse health outcomes from lessened exposure to PM2.5 would yield economic benefits in the range of $6 to $14 billion (in 2008 USD), depending on the specific activity. This equates to between $40 and $93 per metric ton of CO2 in health benefits. Specific climate interventions will vary in the health co-benefits they provide as well as in potential harms that may result from their implementation. Rigorous assessment of these health impacts is essential for guiding policy decisions as efforts to reduce GHG emissions increase in scope and intensity.

  15. Reservoir Temperature Estimator

    Energy Science and Technology Software Center

    2014-12-08

    The Reservoir Temperature Estimator (RTEst) is a program that can be used to estimate deep geothermal reservoir temperature and chemical parameters such as CO2 fugacity based on the water chemistry of shallower, cooler reservoir fluids. This code uses the plugin features provided in The Geochemist’s Workbench (Bethke and Yeakel, 2011) and interfaces with the model-independent parameter estimation code Pest (Doherty, 2005) to provide for optimization of the estimated parameters based on the minimization of themore » weighted sum of squares of a set of saturation indexes from a user-provided mineral assemblage.« less

  16. Estimating Specialty Costs

    Directives, Delegations, and Other Requirements [Office of Management (MA)]

    1997-03-28

    Specialty costs are those nonstandard, unusual costs that are not typically estimated. Costs for research and development (R&D) projects involving new technologies, costs associated with future regulations, and specialty equipment costs are examples of specialty costs. This chapter discusses those factors that are significant contributors to project specialty costs and methods of estimating costs for specialty projects.

  17. Cost Estimating Guide

    Directives, Delegations, and Other Requirements [Office of Management (MA)]

    2011-05-09

    This Guide provides uniform guidance and best practices that describe the methods and procedures that could be used in all programs and projects at DOE for preparing cost estimates. No cancellations.

  18. Cost Estimating Guide

    Directives, Delegations, and Other Requirements [Office of Management (MA)]

    2011-05-09

    This Guide provides uniform guidance and best practices that describe the methods and procedures that could be used in all programs and projects at DOE for preparing cost estimates.

  19. Cost Estimating Guide

    Directives, Delegations, and Other Requirements [Office of Management (MA)]

    1997-03-28

    The objective of this Guide is to improve the quality of cost estimates and further strengthen the DOE program/project management system. The original 25 separate chapters and three appendices have been combined to create a single document.

  20. Derived Annual Estimates

    Energy Information Administration (EIA) (indexed site)

    74-1988 For Methodology Concerning the Derived Estimates Total Consumption of Offsite-Produced Energy for Heat and Power by Industry Group, 1974-1988 Total Energy *** Electricity...

  1. Independent Cost Estimate (ICE)

    Energy.gov [DOE]

    Independent Cost Estimate (ICE). On August 8-12, the Office of Project Management Oversight and Assessments (PM) will conduct an ICE on the NNSA Albuquerque Complex Project (NACP) at Albuquerque, NM. This estimate will support the Critical Decision (CD) for establishing the performance baseline and approval to start construction (CD-2/3). This project is at CD-1, with a total project cost range of $183M to $251M.

  2. Parametric Hazard Function Estimation.

    Energy Science and Technology Software Center

    1999-09-13

    Version 00 Phaze performs statistical inference calculations on a hazard function (also called a failure rate or intensity function) based on reported failure times of components that are repaired and restored to service. Three parametric models are allowed: the exponential, linear, and Weibull hazard models. The inference includes estimation (maximum likelihood estimators and confidence regions) of the parameters and of the hazard function itself, testing of hypotheses such as increasing failure rate, and checking ofmore » the model assumptions.« less

  3. Magnetic nanoparticle temperature estimation

    SciTech Connect

    Weaver, John B.; Rauwerdink, Adam M.; Hansen, Eric W.

    2009-05-15

    The authors present a method of measuring the temperature of magnetic nanoparticles that can be adapted to provide in vivo temperature maps. Many of the minimally invasive therapies that promise to reduce health care costs and improve patient outcomes heat tissue to very specific temperatures to be effective. Measurements are required because physiological cooling, primarily blood flow, makes the temperature difficult to predict a priori. The ratio of the fifth and third harmonics of the magnetization generated by magnetic nanoparticles in a sinusoidal field is used to generate a calibration curve and to subsequently estimate the temperature. The calibration curve is obtained by varying the amplitude of the sinusoidal field. The temperature can then be estimated from any subsequent measurement of the ratio. The accuracy was 0.3 deg. K between 20 and 50 deg. C using the current apparatus and half-second measurements. The method is independent of nanoparticle concentration and nanoparticle size distribution.

  4. Use of Cost Estimating Relationships

    Directives, Delegations, and Other Requirements [Office of Management (MA)]

    1997-03-28

    Cost Estimating Relationships (CERs) are an important tool in an estimator's kit, and in many cases, they are the only tool. Thus, it is important to understand their limitations and characteristics. This chapter discusses considerations of which the estimator must be aware so the Cost Estimating Relationships can be properly used.

  5. Automated Estimating System

    Energy Science and Technology Software Center

    1996-04-15

    AES6.1 is a PC software package developed to aid in the preparation and reporting of cost estimates. AES6.1 provides an easy means for entering and updating the detailed cost, schedule information, project work breakdown structure, and escalation information contained in a typical project cost estimate through the use of menus and formatted input screens. AES6.1 combines this information to calculate both unescalated and escalated cost for a project which can be reported at varying levelsmore » of detail. Following are the major modifications to AES6.0f: Contingency update was modified to provide greater flexibility for user updates, Schedule Update was modified to provide user ability to schedule Bills of Material at the WBS/Participant/Cost Code level, Schedule Plot was modified to graphically show schedule by WBS/Participant/Cost Code, All Fiscal Year reporting has been modified to use the new schedule format, The Schedule 1-B-7, Cost Schedule, and the WBS/Participant reprorts were modified to determine Phase of Work from the B/M Cost Code, Utility program was modified to allow selection by cost code and update cost code in the Global Schedule update, Generic summary and line item download were added to the utility program, and an option was added to all reports which allows the user to indicate where overhead is to be reported (bottom line or in body of report)« less

  6. Turbines Market is Expected to Reach USD 191.87 Billion by 2020...

    OpenEI (Open Energy Information) [EERE & EIA]

    reaction turbines, the feed material e.g. air in case of wind turbines and rivers or dams in case of hydropower ones, goes 'through' the blades to drive the turbine. Currently,...

  7. Biomass Boiler Market is Projected to Reach USD 8,907.0 Million...

    OpenEI (Open Energy Information) [EERE & EIA]

    Naval SpA, Hurst Boiler & Welding Co, Inc., Jernforsen Energi System AB, Justsen Energiteknik AS, Kohlbach Group, LAMBION Energy Solutions GmbH, Leroux & Lotz Technologies,...

  8. Cost Estimating, Analysis, and Standardization

    Directives, Delegations, and Other Requirements [Office of Management (MA)]

    1984-11-02

    To establish policy and responsibilities for: (a) developing and reviewing project cost estimates; (b) preparing independent cost estimates and analysis; (c) standardizing cost estimating procedures; and (d) improving overall cost estimating and analytical techniques, cost data bases, cost and economic escalation models, and cost estimating systems. Cancels DOE O 5700.2B, dated 8-5-1983; DOE O 5700.8, dated 5-27-1981; and HQ 1130.1A, dated 12-30-1981. Canceled by DOE O 5700.2D, dated 6-12-1992

  9. Robust and intelligent bearing estimation

    DOEpatents

    Claassen, John P.

    2000-01-01

    A method of bearing estimation comprising quadrature digital filtering of event observations, constructing a plurality of observation matrices each centered on a time-frequency interval, determining for each observation matrix a parameter such as degree of polarization, linearity of particle motion, degree of dyadicy, or signal-to-noise ratio, choosing observation matrices most likely to produce a set of best available bearing estimates, and estimating a bearing for each observation matrix of the chosen set.

  10. Supercooled liquid water Estimation Tool

    Energy Science and Technology Software Center

    2012-05-04

    The Cloud Supercooled liquid water Estimation Tool (SEET) is a user driven Graphical User Interface (GUI) that estimates cloud supercooled liquid water (SLW) content in terms of vertical column and total mass from Moderate resolution Imaging Supercooled liquid water Estimation Tool Spectroradiometer (MODIS) spatially derived cloud products and realistic vertical cloud parameterizations that are user defined. It also contains functions for post-processing of the resulting data in tabular and graphical form.

  11. Derived Annual Estimates of Manufacturing Energy Consumption...

    Energy Information Administration (EIA) (indexed site)

    > Derived Annual Estimates - Executive Summary Derived Annual Estimates of Manufacturing Energy Consumption, 1974-1988 Figure showing Derived Estimates Executive Summary This...

  12. Examples of Cost Estimation Packages

    Directives, Delegations, and Other Requirements [Office of Management (MA)]

    1997-03-28

    Estimates can be performed in a variety of ways. Some of these are for projects for an undefined scope, a conventional construction project, or where there is a level of effort required to complete the work. Examples of cost estimation packages for these types of projects are described in this appendix.

  13. Quantity Estimation Of The Interactions

    SciTech Connect

    Gorana, Agim; Malkaj, Partizan; Muda, Valbona

    2007-04-23

    In this paper we present some considerations about quantity estimations, regarding the range of interaction and the conservations laws in various types of interactions. Our estimations are done under classical and quantum point of view and have to do with the interaction's carriers, the radius, the influence range and the intensity of interactions.

  14. GAO Cost Estimating and Assessment Guide

    Energy.gov [DOE]

    GAO Cost Estimating and Assessment Guide: Twelve Steps of a High-Quality Cost Estimating Process, from the first step of defining the estimate's purpose to the last step of updating the estimate to reflect actual costs and changes.

  15. Module: Estimating Historical Emissions from Deforestation |...

    OpenEI (Open Energy Information) [EERE & EIA]

    Website: www.leafasia.orgtoolstechnical-guidance-series-estimating-historical Cost: Free Language: English Module: Estimating Historical Emissions from Deforestation Screenshot...

  16. Weekly Coal Production Estimation Methodology

    Energy Information Administration (EIA) (indexed site)

    Weekly Coal Production Estimation Methodology Step 1 (Estimate total amount of weekly U.S. coal production) U.S. coal production for the current week is estimated using a ratio estimation from the given equation below; ̂ () = () × × { + ( - )} (1) ℎ ̂ () =

  17. Estimate Radiological Dose for Animals

    Energy Science and Technology Software Center

    1997-12-18

    Estimate Radiological dose for animals in ecological environment using open literature values for parameters such as body weight, plant and soil ingestion rate, rad. halflife, absorbed energy, biological halflife, gamma energy per decay, soil-to-plant transfer factor, ...etc

  18. Estimates of Green potentials. Applications

    SciTech Connect

    Danchenko, V I

    2003-02-28

    Optimal Cartan-type covers by hyperbolic discs of carriers of Green {alpha}-potentials are obtained in a simply connected domain in the complex plane and estimates of the potentials outside the carriers are presented. These results are applied to problems on the separation of singularities of analytic and harmonic functions. For instance, uniform and integral estimates in terms of Green capacities of components of meromorphic functions are obtained.

  19. GAO Cost Estimating and Assessment Guide Twelve Steps of a High-Quality Cost Estimating Process

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    GAO Cost Estimating and Assessment Guide Twelve Steps of a High-Quality Cost Estimating Process Step Description Associated task 1 Define estimate's purpose Determine estimate's purpose, required level of detail, and overall scope; Determine who will receive the estimate 2 Develop estimating plan Determine the cost estimating team and develop its master schedule; Determine who will do the independent cost estimate; Outline the cost estimating approach; Develop the estimate timeline 3 Define

  20. Weldon Spring historical dose estimate

    SciTech Connect

    Meshkov, N.; Benioff, P.; Wang, J.; Yuan, Y.

    1986-07-01

    This study was conducted to determine the estimated radiation doses that individuals in five nearby population groups and the general population in the surrounding area may have received as a consequence of activities at a uranium processing plant in Weldon Spring, Missouri. The study is retrospective and encompasses plant operations (1957-1966), cleanup (1967-1969), and maintenance (1969-1982). The dose estimates for members of the nearby population groups are as follows. Of the three periods considered, the largest doses to the general population in the surrounding area would have occurred during the plant operations period (1957-1966). Dose estimates for the cleanup (1967-1969) and maintenance (1969-1982) periods are negligible in comparison. Based on the monitoring data, if there was a person residing continually in a dwelling 1.2 km (0.75 mi) north of the plant, this person is estimated to have received an average of about 96 mrem/yr (ranging from 50 to 160 mrem/yr) above background during plant operations, whereas the dose to a nearby resident during later years is estimated to have been about 0.4 mrem/yr during cleanup and about 0.2 mrem/yr during the maintenance period. These values may be compared with the background dose in Missouri of 120 mrem/yr.

  1. Quick estimating for thermal conductivity

    SciTech Connect

    Sastri, S.R.S.; Rao, K.K. )

    1993-08-01

    Accurate values for thermal conductivity--an important engineering property used in heat transfer calculations of liquids--are not as readily available as those for other physical properties. Therefore, it often becomes necessary to use estimated data. A new estimating method combines ease of use with an accuracy that is generally better than existing procedures. The paper discusses how to select terms and testing correlations, then gives two examples of the use of the method for calculation of the thermal conductivity of propionic acid and chlorobenzene.

  2. Mandatory Photovoltaic System Cost Estimate

    Office of Energy Efficiency and Renewable Energy (EERE)

    If the customer has a ratio of estimated monthly kilowatt-hour (kWh) usage to line extension mileage that is less than or equal to 1,000, the utility must provide the comparison at no cost. If the...

  3. NREL Raises Rooftop Photovoltaic Technical Potential Estimate...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Raises Rooftop Photovoltaic Technical Potential Estimate New analysis nearly doubles ... its estimate of total U.S. technical potential for rooftop photovoltaic (PV) systems. ...

  4. Estimates and Recommendations for Coincidence Geometry (Technical...

    Office of Scientific and Technical Information (OSTI)

    Estimates and Recommendations for Coincidence Geometry Citation Details In-Document Search Title: Estimates and Recommendations for Coincidence Geometry You are accessing a...

  5. Background estimation in experimental spectra

    SciTech Connect

    Fischer, R.; Hanson, K. M.; Los Alamos National Laboratory, MS P940, Los Alamos, New Mexico 87545 ; Dose, V.; Linden, W. von der

    2000-02-01

    A general probabilistic technique for estimating background contributions to measured spectra is presented. A Bayesian model is used to capture the defining characteristics of the problem, namely, that the background is smoother than the signal. The signal is allowed to have positive and/or negative components. The background is represented in terms of a cubic spline basis. A variable degree of smoothness of the background is attained by allowing the number of knots and the knot positions to be adaptively chosen on the basis of the data. The fully Bayesian approach taken provides a natural way to handle knot adaptivity and allows uncertainties in the background to be estimated. Our technique is demonstrated on a particle induced x-ray emission spectrum from a geological sample and an Auger spectrum from iron, which contains signals with both positive and negative components. (c) 2000 The American Physical Society.

  6. Guidelines for Estimating Unmetered Landscapting Water Use

    SciTech Connect

    None

    2010-07-30

    Guidance to help Federal agencies estimate unmetered landscaping water use as required by Executive Order 13514

  7. 2007 Estimated International Energy Flows

    SciTech Connect

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

    2011-03-10

    An energy flow chart or 'atlas' for 136 countries has been constructed from data maintained by the International Energy Agency (IEA) and estimates of energy use patterns for the year 2007. Approximately 490 exajoules (460 quadrillion BTU) of primary energy are used in aggregate by these countries each year. While the basic structure of the energy system is consistent from country to country, patterns of resource use and consumption vary. Energy can be visualized as it flows from resources (i.e. coal, petroleum, natural gas) through transformations such as electricity generation to end uses (i.e. residential, commercial, industrial, transportation). These flow patterns are visualized in this atlas of 136 country-level energy flow charts.

  8. Bayesian estimation methods in metrology

    SciTech Connect

    Cox, M.G.; Forbes, A.B.; Harris, P.M.

    2004-11-16

    In metrology -- the science of measurement -- a measurement result must be accompanied by a statement of its associated uncertainty. The degree of validity of a measurement result is determined by the validity of the uncertainty statement. In recognition of the importance of uncertainty evaluation, the International Standardization Organization in 1995 published the Guide to the Expression of Uncertainty in Measurement and the Guide has been widely adopted. The validity of uncertainty statements is tested in interlaboratory comparisons in which an artefact is measured by a number of laboratories and their measurement results compared. Since the introduction of the Mutual Recognition Arrangement, key comparisons are being undertaken to determine the degree of equivalence of laboratories for particular measurement tasks. In this paper, we discuss the possible development of the Guide to reflect Bayesian approaches and the evaluation of key comparison data using Bayesian estimation methods.

  9. Supplemental report on cost estimates'

    SciTech Connect

    1992-04-29

    The Office of Management and Budget (OMB) and the U.S. Army Corps of Engineers have completed an analysis of the Department of Energy's (DOE) Fiscal Year (FY) 1993 budget request for its Environmental Restoration and Waste Management (ERWM) program. The results were presented to an interagency review group (IAG) of senior-Administration officials for their consideration in the budget process. This analysis included evaluations of the underlying legal requirements and cost estimates on which the ERWM budget request was based. The major conclusions are contained in a separate report entitled, ''Interagency Review of the Department of Energy Environmental Restoration and Waste Management Program.'' This Corps supplemental report provides greater detail on the cost analysis.

  10. State Energy Price and Expenditure Estimates

    Reports and Publications

    2016-01-01

    Energy price and expenditure estimates in dollars per million Btu and in million dollars, by state, 1970-2014.

  11. Cost Model and Cost Estimating Software

    Directives, Delegations, and Other Requirements [Office of Management (MA)]

    1997-03-28

    This chapter discusses a formalized methodology is basically a cost model, which forms the basis for estimating software.

  12. New Methodology for Natural Gas Production Estimates

    Reports and Publications

    2010-01-01

    A new methodology is implemented with the monthly natural gas production estimates from the EIA-914 survey this month. The estimates, to be released April 29, 2010, include revisions for all of 2009. The fundamental changes in the new process include the timeliness of the historical data used for estimation and the frequency of sample updates, both of which are improved.

  13. Robust Bearing Estimation for 3-Component Stations

    SciTech Connect

    Claassen, John P.

    1999-06-03

    A robust bearing estimation process for 3-component stations has been developed and explored. The method, called SEEC for Search, Estimate, Evaluate and Correct, intelligently exploits the in- herent information in the arrival at every step of the process to achieve near-optimal results. In particular, the approach uses a consistent framework to define the optimal time-frequency windows on which to make estimates, to make the bearing estimates themselves, to construct metrics helpful in choosing the better estimates or admitting that the bearing is immeasurable, andjinally to apply bias corrections when calibration information is available to yield a single final estimate. The method was applied to a small but challenging set of events in a seismically active region. The method demonstrated remarkable utility by providing better estimates and insights than previously available. Various monitoring implications are noted fiom these findings.

  14. Robust bearing estimation for 3-component stations

    SciTech Connect

    CLAASSEN,JOHN P.

    2000-02-01

    A robust bearing estimation process for 3-component stations has been developed and explored. The method, called SEEC for Search, Estimate, Evaluate and Correct, intelligently exploits the inherent information in the arrival at every step of the process to achieve near-optimal results. In particular the approach uses a consistent framework to define the optimal time-frequency windows on which to make estimates, to make the bearing estimates themselves, to construct metrics helpful in choosing the better estimates or admitting that the bearing is immeasurable, and finally to apply bias corrections when calibration information is available to yield a single final estimate. The algorithm was applied to a small but challenging set of events in a seismically active region. It demonstrated remarkable utility by providing better estimates and insights than previously available. Various monitoring implications are noted from these findings.

  15. Reliability Estimates for Power Supplies

    SciTech Connect

    Lee C. Cadwallader; Peter I. Petersen

    2005-09-01

    Failure rates for large power supplies at a fusion facility are critical knowledge needed to estimate availability of the facility or to set priorties for repairs and spare components. A study of the "failure to operate on demand" and "failure to continue to operate" failure rates has been performed for the large power supplies at DIII-D, which provide power to the magnet coils, the neutral beam injectors, the electron cyclotron heating systems, and the fast wave systems. When one of the power supplies fails to operate, the research program has to be either temporarily changed or halted. If one of the power supplies for the toroidal or ohmic heating coils fails, the operations have to be suspended or the research is continued at de-rated parameters until a repair is completed. If one of the power supplies used in the auxiliary plasma heating systems fails the research is often temporarily changed until a repair is completed. The power supplies are operated remotely and repairs are only performed when the power supplies are off line, so that failure of a power supply does not cause any risk to personnel. The DIII-D Trouble Report database was used to determine the number of power supply faults (over 1,700 reports), and tokamak annual operations data supplied the number of shots, operating times, and power supply usage for the DIII-D operating campaigns between mid-1987 and 2004. Where possible, these power supply failure rates from DIII-D will be compared to similar work that has been performed for the Joint European Torus equipment. These independent data sets support validation of the fusion-specific failure rate values.

  16. Time and Resource Estimation Tool

    Energy Science and Technology Software Center

    2004-06-08

    RESTORE is a computer software tool that allows one to model a complex set of steps required to accomplish a goal (e.g., repair a ruptured natural gas pipeline and restore service to customers). However, the time necessary to complete step may be uncertain and may be affected by conditions, such as the weather, the time of day, the day of the week. Therefore, "nature" can influence which steps are taken and the time needed tomore » complete each step. In addition, the tool allows one to model the costs for each step, which also may be uncertain. RESTORE allows the user to estimate the time and cost, both of which may be uncertain, to achieve an intermediate stage of completion, as well as overall completion. The software also makes it possible to model parallel, competing groups of activities (i.e., parallel paths) so that progreSs at a ‘merge point’ can proceed before other competing activities are completed. For example, RESTORE permits one to model a workaround and a simultaneous complete repair to determine a probability distribution for the earliest time service can be restored to a critical customer. The tool identifies the ‘most active path’ through the network of tasks, which is extremely important information for assessing the most effective way to speed-up or slow-down progress. Unlike other project planning and risk analysis tools, RESTORE provides an intuitive, graphical, and object-oriented environment for structuring a model and setting its parameters.« less

  17. Budget estimates. Fiscal year 1998

    SciTech Connect

    1997-02-01

    The U.S. Congress has determined that the safe use of nuclear materials for peaceful purposes is a legitimate and important national goal. It has entrusted the Nuclear Regulatory Commission (NRC) with the primary Federal responsibility for achieving that goal. The NRC`s mission, therefore, is to regulate the Nation`s civilian use of byproduct, source, and special nuclear materials to ensure adequate protection of public health and safety, to promote the common defense and security, and to protect the environment. The NRC`s FY 1998 budget requests new budget authority of $481,300,000 to be funded by two appropriations - one is the NRC`s Salaraies and Expenses appropriation for $476,500,000, and the other is NRC`s Office of Inspector General appropriation for $4,800,000. Of the funds appropriated to the NRC`s Salaries and Expenses, $17,000,000, shall be derived from the Nuclear Waste Fund and $2,000,000 shall be derived from general funds. The proposed FY 1998 appropriation legislation would also exempt the $2,000,000 for regulatory reviews and other assistance provided to the Department of Energy from the requirement that the NRC collect 100 percent of its budget from fees. The sums appropriated to the NRC`s Salaries and Expenses and NRC`s Office of Inspector General shall be reduced by the amount of revenues received during FY 1998 from licensing fees, inspection services, and other services and collections, so as to result in a final FY 1998 appropriation for the NRC of an estimated $19,000,000 - the amount appropriated from the Nuclear Waste Fund and from general funds. Revenues derived from enforcement actions shall be deposited to miscellaneous receipts of the Treasury.

  18. Notes on a New Coherence Estimator

    SciTech Connect

    Bickel, Douglas L.

    2016-01-01

    This document discusses some interesting features of the new coherence estimator in [1] . The estimator is d erived from a slightly different viewpoint. We discuss a few properties of the estimator, including presenting the probability density function of the denominator of the new estimator , which is a new feature of this estimator . Finally, we present an appr oximate equation for analysis of the sensitivity of the estimator to the knowledge of the noise value. ACKNOWLEDGEMENTS The preparation of this report is the result of an unfunded research and development activity. Sandia National Laboratories is a multi - program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE - AC04 - 94AL85000.

  19. State energy data report 1994: Consumption estimates

    SciTech Connect

    1996-10-01

    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.

  20. Methodology for Monthly Crude Oil Production Estimates

    Energy Information Administration (EIA) (indexed site)

    015 U.S. Energy Information Administration | Methodology for Monthly Crude Oil Production Estimates 1 Methodology for Monthly Crude Oil Production Estimates Executive summary The U.S. Energy Information Administration (EIA) relies on data from state and other federal agencies and does not currently collect survey data directly from crude oil producers. Summarizing the estimation process in terms of percent of U.S. production: * 20% is based on state agency data, including North Dakota and

  1. U.S. Uranium Reserves Estimates

    Gasoline and Diesel Fuel Update

    Methodology The U.S. uranium ore reserves reported by EIA for specific MFC categories represent the sums of quantities estimated to occur in known deposits on properties where data about the ore grade, configuration, and depth indicate that the quantities estimated could be recovered at or less than the stated costs given current mining and milling technology and regulations. The reserves estimates for year-end (delete: December 31, 2008), are based on historical data for uranium properties

  2. Early Internal and External Dose Magnitude Estimation

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Internal and External Dose Estimation (initial version: 08/2008, current version: 10/2015) Early Internal and External Dose Magnitude Estimation The Radiation Emergency Assistance Center/Training Site REAC/TS PO Box 117, MS-39 Oak Ridge, TN 37831 (865)576-3131 http://orise.orau.gov/reacts prepared by: Stephen L. (Steve) Sugarman, MS, CHP, CHCM Health Physics Project Manager Cytogenetic Biodosimetry Laboratory Coordinator Early Internal and External Dose Estimation (initial version: 08/2008,

  3. ORISE: Radiation Dose Estimates and Other Compendia

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    rapidly estimate internal and external radiation dose magnitudes that can be used to help ... (PDF) Health Concerns Related to Radiation Exposure of the Female Nuclear Medicine ...

  4. How EIA Estimates Natural Gas Production

    Reports and Publications

    2004-01-01

    The Energy Information Administration (EIA) publishes estimates monthly and annually of the production of natural gas in the United States. The estimates are based on data EIA collects from gas producing states and data collected by the U. S. Minerals Management Service (MMS) in the Department of Interior. The states and MMS collect this information from producers of natural gas for various reasons, most often for revenue purposes. Because the information is not sufficiently complete or timely for inclusion in EIA's Natural Gas Monthly (NGM), EIA has developed estimation methodologies to generate monthly production estimates that are described in this document.

  5. Guidelines for Estimating Unmetered Industrial Water Use

    Energy.gov [DOE]

    Document describes a systematic approach to estimate industrial water use in evaporative cooling systems, steam boiler systems, and facility wash applications.

  6. Structure Learning and Statistical Estimation in Distribution...

    Office of Scientific and Technical Information (OSTI)

    Citation Details In-Document Search Title: Structure Learning and Statistical Estimation ... Part I of this paper discusses the problem of learning the operational structure of the ...

  7. An Estimator of Propagation of Cascading Failure

    SciTech Connect

    Dobson, Ian; Wierzbicki, Kevin; Carreras, Benjamin A; Lynch, Vickie E; Newman, David E

    2006-01-01

    The authors suggest a statistical estimator to measure the extent to which failures propagate in cascading failures such as large blackouts.

  8. ,"U.S. Weekly Supply Estimates"

    Energy Information Administration (EIA) (indexed site)

    Supply Estimates" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Crude Oil Production",1,"...

  9. Interruption Cost Estimate Calculator | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Cost Estimate (ICE) Calculator This calculator is a tool designed for electric reliability planners at utilities, government organizations or other entities that are...

  10. Adjusted Estimates of Texas Natural Gas Production

    Reports and Publications

    2005-01-01

    The Energy Information Administration (EIA) is adjusting its estimates of natural gas production in Texas for 2004 and 2005 to correctly account for carbon dioxide (CO2) production.

  11. Cost Estimating Handbook for Environmental Restoration

    SciTech Connect

    1990-09-01

    Environmental restoration (ER) projects have presented the DOE and cost estimators with a number of properties that are not comparable to the normal estimating climate within DOE. These properties include: An entirely new set of specialized expressions and terminology. A higher than normal exposure to cost and schedule risk, as compared to most other DOE projects, due to changing regulations, public involvement, resource shortages, and scope of work. A higher than normal percentage of indirect costs to the total estimated cost due primarily to record keeping, special training, liability, and indemnification. More than one estimate for a project, particularly in the assessment phase, in order to provide input into the evaluation of alternatives for the cleanup action. While some aspects of existing guidance for cost estimators will be applicable to environmental restoration projects, some components of the present guidelines will have to be modified to reflect the unique elements of these projects. The purpose of this Handbook is to assist cost estimators in the preparation of environmental restoration estimates for Environmental Restoration and Waste Management (EM) projects undertaken by DOE. The DOE has, in recent years, seen a significant increase in the number, size, and frequency of environmental restoration projects that must be costed by the various DOE offices. The coming years will show the EM program to be the largest non-weapons program undertaken by DOE. These projects create new and unique estimating requirements since historical cost and estimating precedents are meager at best. It is anticipated that this Handbook will enhance the quality of cost data within DOE in several ways by providing: The basis for accurate, consistent, and traceable baselines. Sound methodologies, guidelines, and estimating formats. Sources of cost data/databases and estimating tools and techniques available at DOE cost professionals.

  12. Guidance on Utility Rate Estimations and Weather Normalization...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Utility Rate Estimations and Weather Normalization in an ESPC Guidance on Utility Rate Estimations and Weather Normalization in an ESPC Document explains how to use estimated ...

  13. Florida Dry Natural Gas Reserves Estimated Production (Billion...

    Energy Information Administration (EIA) (indexed site)

    Estimated Production (Billion Cubic Feet) Florida Dry Natural Gas Reserves Estimated ... Dry Natural Gas Reserves Estimated Production Florida Dry Natural Gas Proved Reserves Dry ...

  14. West Virginia Dry Natural Gas Reserves Estimated Production ...

    Energy Information Administration (EIA) (indexed site)

    Estimated Production (Billion Cubic Feet) West Virginia Dry Natural Gas Reserves Estimated ... Dry Natural Gas Reserves Estimated Production West Virginia Dry Natural Gas Proved ...

  15. Virginia Dry Natural Gas Reserves Estimated Production (Billion...

    Energy Information Administration (EIA) (indexed site)

    Estimated Production (Billion Cubic Feet) Virginia Dry Natural Gas Reserves Estimated ... Dry Natural Gas Reserves Estimated Production Virginia Dry Natural Gas Proved Reserves Dry ...

  16. Cost and Schedule Estimate and Analysis (FPM 207), Amarillo ...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Course topics include: identifying cost and schedule estimates; Basic estimating methods; Group analysis techniques; Applying life-cycle costing technique; Validating estimates; ...

  17. Request for Retirement Annuity Estimates | Department of Energy

    Office of Environmental Management (EM)

    Request for Retirement Annuity Estimates Request for Retirement Annuity Estimates Upon request, Office of the Chief Human Capital Officer provides retirement estimates for ...

  18. Property:Estimated End Date | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Estimated End Date Jump to: navigation, search Property Name Estimated End Date Property Type String Pages using the property "Estimated End Date" Showing 4 pages using this...

  19. New York Dry Natural Gas Reserves Estimated Production (Billion...

    Gasoline and Diesel Fuel Update

    Estimated Production (Billion Cubic Feet) New York Dry Natural Gas Reserves Estimated ... Dry Natural Gas Reserves Estimated Production New York Dry Natural Gas Proved Reserves Dry ...

  20. New Mexico Dry Natural Gas Reserves Estimated Production (Billion...

    Gasoline and Diesel Fuel Update

    Estimated Production (Billion Cubic Feet) New Mexico Dry Natural Gas Reserves Estimated ... Dry Natural Gas Reserves Estimated Production New Mexico Dry Natural Gas Proved Reserves ...

  1. North Dakota Dry Natural Gas Reserves Estimated Production (Billion...

    Energy Information Administration (EIA) (indexed site)

    Estimated Production (Billion Cubic Feet) North Dakota Dry Natural Gas Reserves Estimated ... Dry Natural Gas Reserves Estimated Production North Dakota Dry Natural Gas Proved Reserves ...

  2. Power, Optimization, Waste Estimating, Resourcing Tool

    Energy Science and Technology Software Center

    2009-08-13

    Planning, Optimization, Waste Estimating, Resourcing tool (POWERtool) is a comprehensive relational database software tool that can be used to develop and organize a detailed project scope, plan work tasks, develop bottoms-up field cost and waste estimates for facility Deactivation and Decommissioning (D&D), equipment, and environmental restoration (ER) projects and produces resource-loaded schedules.

  3. Systematic Approach for Decommissioning Planning and Estimating

    SciTech Connect

    Dam, A. S.

    2002-02-26

    Nuclear facility decommissioning, satisfactorily completed at the lowest cost, relies on a systematic approach to the planning, estimating, and documenting the work. High quality information is needed to properly perform the planning and estimating. A systematic approach to collecting and maintaining the needed information is recommended using a knowledgebase system for information management. A systematic approach is also recommended to develop the decommissioning plan, cost estimate and schedule. A probabilistic project cost and schedule risk analysis is included as part of the planning process. The entire effort is performed by a experienced team of decommissioning planners, cost estimators, schedulers, and facility knowledgeable owner representatives. The plant data, work plans, cost and schedule are entered into a knowledgebase. This systematic approach has been used successfully for decommissioning planning and cost estimating for a commercial nuclear power plant. Elements of this approach have been used for numerous cost estimates and estimate reviews. The plan and estimate in the knowledgebase should be a living document, updated periodically, to support decommissioning fund provisioning, with the plan ready for use when the need arises.

  4. Hydrogen Station Cost Estimates: Comparing Hydrogen Station Cost Calculator Results with other Recent Estimates

    SciTech Connect

    Melaina, M.; Penev, M.

    2013-09-01

    This report compares hydrogen station cost estimates conveyed by expert stakeholders through the Hydrogen Station Cost Calculation (HSCC) to a select number of other cost estimates. These other cost estimates include projections based upon cost models and costs associated with recently funded stations.

  5. State energy data report 1993: Consumption estimates

    SciTech Connect

    1995-07-01

    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.

  6. State Energy Data Report, 1991: Consumption estimates

    SciTech Connect

    Not Available

    1993-05-01

    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.

  7. Parallel State Estimation Assessment with Practical Data

    SciTech Connect

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

    2014-10-31

    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.

  8. State energy data report 1995 - consumption estimates

    SciTech Connect

    1997-12-01

    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.

  9. Hydrogen Production Cost Estimate Using Biomass Gasification...

    Energy.gov [DOE] (indexed site)

    2011 and the technical potential of Hydrogen Production Cost Estimate Using Biomass Gasification The Panel reviewed the current H2A case (Version 2.12, Case 01D) for hydrogen ...

  10. Forward estimation for game-tree search

    SciTech Connect

    Zhang, Weixiong

    1996-12-31

    It is known that bounds on the minimax values of nodes in a game tree can be used to reduce the computational complexity of minimax search for two-player games. We describe a very simple method to estimate bounds on the minimax values of interior nodes of a game tree, and use the bounds to improve minimax search. The new algorithm, called forward estimation, does not require additional domain knowledge other than a static node evaluation function, and has small constant overhead per node expansion. We also propose a variation of forward estimation, which provides a tradeoff between computational complexity and decision quality. Our experimental results show that forward estimation outperforms alpha-beta pruning on random game trees and the game of Othello.

  11. Lensed CMB simulation and parameter estimation

    SciTech Connect

    Lewis, Antony

    2005-04-15

    Modelling of the weak lensing of the CMB will be crucial to obtain correct cosmological parameter constraints from forthcoming precision CMB anisotropy observations. The lensing affects the power spectrum as well as inducing non-Gaussianities. We discuss the simulation of full-sky CMB maps in the weak lensing approximation and describe a fast numerical code. The series expansion in the deflection angle cannot be used to simulate accurate CMB maps, so a pixel remapping must be used. For parameter estimation accounting for the change in the power spectrum but assuming Gaussianity is sufficient to obtain accurate results up to Planck sensitivity using current tools. A fuller analysis may be required to obtain accurate error estimates and for more sensitive observations. We demonstrate a simple full-sky simulation and subsequent parameter estimation at Planck-like sensitivity. The lensed CMB simulation and parameter estimation codes are publicly available.

  12. Preliminary CBECS End-Use Estimates

    Energy Information Administration (EIA) (indexed site)

    For the past three CBECS (1989, 1992, and 1995), we used a statistically-adjusted engineering (SAE) methodology to estimate end-use consumption. The core of the SAE methodology...

  13. A simple method to estimate interwell autocorrelation

    SciTech Connect

    Pizarro, J.O.S.; Lake, L.W.

    1997-08-01

    The estimation of autocorrelation in the lateral or interwell direction is important when performing reservoir characterization studies using stochastic modeling. This paper presents a new method to estimate the interwell autocorrelation based on parameters, such as the vertical range and the variance, that can be estimated with commonly available data. We used synthetic fields that were generated from stochastic simulations to provide data to construct the estimation charts. These charts relate the ratio of areal to vertical variance and the autocorrelation range (expressed variously) in two directions. Three different semivariogram models were considered: spherical, exponential and truncated fractal. The overall procedure is demonstrated using field data. We find that the approach gives the most self-consistent results when it is applied to previously identified facies. Moreover, the autocorrelation trends follow the depositional pattern of the reservoir, which gives confidence in the validity of the approach.

  14. Estimating Temperature Distributions In Geothermal Areas Using...

    OpenEI (Open Energy Information) [EERE & EIA]

    "education level" (which depends on the amount and structure of information used for teaching) and (b) the distance of the point at which the estimate is made from the area for...

  15. Adjoint Error Estimation for Linear Advection

    SciTech Connect

    Connors, J M; Banks, J W; Hittinger, J A; Woodward, C S

    2011-03-30

    An a posteriori error formula is described when a statistical measurement of the solution to a hyperbolic conservation law in 1D is estimated by finite volume approximations. This is accomplished using adjoint error estimation. In contrast to previously studied methods, the adjoint problem is divorced from the finite volume method used to approximate the forward solution variables. An exact error formula and computable error estimate are derived based on an abstractly defined approximation of the adjoint solution. This framework allows the error to be computed to an arbitrary accuracy given a sufficiently well resolved approximation of the adjoint solution. The accuracy of the computable error estimate provably satisfies an a priori error bound for sufficiently smooth solutions of the forward and adjoint problems. The theory does not currently account for discontinuities. Computational examples are provided that show support of the theory for smooth solutions. The application to problems with discontinuities is also investigated computationally.

  16. Buildings GHG Mitigation Estimator Worksheet, Version 1

    Energy.gov [DOE]

    Xcel document describes Version 1 of the the Buildings GHG Mitigation Estimator tool. This tool assists federal agencies in estimating the greenhouse gas mitigation reduction from implementing energy efficiency measures across a portfolio of buildings. It is designed to be applied to groups of office buildings, for example, at a program level (regional or site) that can be summarized at the agency level. While the default savings and cost estimates apply to office buildings, users can define their own efficiency measures, costs, and savings estimates for inclusion in the portfolio assessment. More information on user-defined measures can be found in Step 2 of the buildings emission reduction guidance. The output of this tool is a prioritized set of activities that can help the agency to achieve its greenhouse gas reduction targets most cost-effectively.

  17. Estimating electron drift velocities in magnetron discharges...

    Office of Scientific and Technical Information (OSTI)

    Citation Details In-Document Search Title: Estimating ... OSTI Identifier: 1172974 Report Number(s): LBNL-5865E DOE Contract Number: DE-AC02-05CH11231 Resource Type: Journal ...

  18. Budget estimates, fiscal year 1997. Volume 12

    SciTech Connect

    1996-03-01

    This report contains the fiscal year budget justification to Congress. The budget provides estimates for salaries and expenses and for the Office of the Inspector General for fiscal year 1997.

  19. Budget estimates, fiscal years 1994--1995

    SciTech Connect

    Not Available

    1993-04-01

    This report contains the fiscal year budget justification to Congress. The budget provides estimates for salaries and expenses and for the Office of the Inspector General for fiscal years 1994 and 1995.

  20. gtp_flow_power_estimator.xlsx

    Energy.gov [DOE]

    This simple spreadsheet model estimates either the flow rate required to produce a specified level of power output, or the power output that can be produced from a specified flow rate.

  1. ARM - Lesson Plans: Estimating Local Sea Level

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Estimating Local Sea Level Outreach Home Room News Publications Traditional Knowledge Kiosks Barrow, Alaska Tropical Western Pacific Site Tours Contacts Students Study Hall About ARM Global Warming FAQ Just for Fun Meet our Friends Cool Sites Teachers Teachers' Toolbox Lesson Plans Lesson Plans: Estimating Local Sea Level Objective The objective is to train students' skills in observing the local environment based upon the sea level variations. Materials Each student or group of students will

  2. Chapter 3: FY 2006 benefits estimates

    SciTech Connect

    None, None

    2009-01-18

    The Office of Energy Efficiency and Renewable Energy (EERE) estimates expected benefits for its overall portfolio and for each of its 11 programs. Benefits for the FY 2006 budget request are estimated for the midterm (2010-2025) and long term (2030-2050). Two separate models suited to these periods are employed–NEMS-GPRA06 for the midterm and MARKAL-GPRA06 for the long term.

  3. Estimates of US biomass energy consumption 1992

    SciTech Connect

    Not Available

    1994-05-06

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass-derived primary energy used by the US economy. It presents estimates of 1991 and 1992 consumption. The objective of this report is to provide updated estimates of biomass energy consumption for use by Congress, Federal and State agencies, biomass producers and end-use sectors, and the public at large.

  4. Chapter 3: FY 2005 benefits estimates

    SciTech Connect

    None, None

    2009-01-18

    The Office of Energy Efficiency and Renewable Energy (EERE) estimates expected benefits for its overall portfolio and for each of its 11 programs. Benefits for the FY 2005 budget request are estimated for the midterm (2010-2025) and long term (2030-2050). Two separate models suited to these periods are employed—NEMS-GPRA05 for the midterm and MARKAL-GPRA05 for the long term.

  5. Thermal Hydraulic Simulations, Error Estimation and Parameter

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Thermal Hydraulic Simulations, Error Estimation and Parameter Sensitivity Studies in Drekar::CFD Thomas M. Smith, John N. Shadid, Roger P. Pawlowski, Eric C. Cyr and Timothy M. Wildey Sandia National Laboratories September, 2013 CASL-U-2013-0203-001 SANDIA REPORT SAND2013-XXXX Unlimited Release Printed September 2013 Thermal Hydraulic Simulations, Error Estimation and Parameter Sensitivity Studies in Drekar::CFD Thomas M. Smith, John N. Shadid, Roger P. Pawlowski, Eric C. Cyr and Timothy M.

  6. Guidelines for Estimating Unmetered Industrial Water Use

    SciTech Connect

    Boyd, Brian K.

    2010-08-01

    The document provides a methodology to estimate unmetered industrial water use for evaporative cooling systems, steam generating boiler systems, batch process applications, and wash systems. For each category standard mathematical relationships are summarized and provided in a single resource to assist Federal agencies in developing an initial estimate of their industrial water use. The approach incorporates industry norms, general rules of thumb, and industry survey information to provide methodologies for each section.

  7. Estimated recharge rates at the Hanford Site

    SciTech Connect

    Fayer, M.J.; Walters, T.B.

    1995-02-01

    The Ground-Water Surveillance Project monitors the distribution of contaminants in ground water at the Hanford Site for the U.S. Department of Energy. A subtask called {open_quotes}Water Budget at Hanford{close_quotes} was initiated in FY 1994. The objective of this subtask was to produce a defensible map of estimated recharge rates across the Hanford Site. Methods that have been used to estimate recharge rates at the Hanford Site include measurements (of drainage, water contents, and tracers) and computer modeling. For the simulations of 12 soil-vegetation combinations, the annual rates varied from 0.05 mm/yr for the Ephrata sandy loam with bunchgrass to 85.2 mm/yr for the same soil without vegetation. Water content data from the Grass Site in the 300 Area indicated that annual rates varied from 3.0 to 143.5 mm/yr during an 8-year period. The annual volume of estimated recharge was calculated to be 8.47 {times} 10{sup 9} L for the potential future Hanford Site (i.e., the portion of the current Site bounded by Highway 240 and the Columbia River). This total volume is similar to earlier estimates of natural recharge and is 2 to 10x higher than estimates of runoff and ground-water flow from higher elevations. Not only is the volume of natural recharge significant in comparison to other ground-water inputs, the distribution of estimated recharge is highly skewed to the disturbed sandy soils (i.e., the 200 Areas, where most contaminants originate). The lack of good estimates of the means and variances of the supporting data (i.e., the soil map, the vegetation/land use map, the model parameters) translates into large uncertainties in the recharge estimates. When combined, the significant quantity of estimated recharge, its high sensitivity to disturbance, and the unquantified uncertainty of the data and model parameters suggest that the defensibility of the recharge estimates should be improved.

  8. Robust Optical Richness Estimation with Reduced Scatter

    SciTech Connect

    Rykoff, E.S.; Koester, B.P.; Rozo, E.; Annis, J.; Evrard, A.E.; Hansen, S.M.; Hao, J.; Johnston, D.E.; McKay, T.A.; Wechsler, R.H.; /KIPAC, Menlo Park /SLAC

    2012-06-07

    Reducing the scatter between cluster mass and optical richness is a key goal for cluster cosmology from photometric catalogs. We consider various modifications to the red-sequence matched filter richness estimator of Rozo et al. (2009b), and evaluate their impact on the scatter in X-ray luminosity at fixed richness. Most significantly, we find that deeper luminosity cuts can reduce the recovered scatter, finding that {sigma}{sub ln L{sub X}|{lambda}} = 0.63 {+-} 0.02 for clusters with M{sub 500c} {approx}> 1.6 x 10{sup 14} h{sub 70}{sup -1} M{sub {circle_dot}}. The corresponding scatter in mass at fixed richness is {sigma}{sub ln M|{lambda}} {approx} 0.2-0.3 depending on the richness, comparable to that for total X-ray luminosity. We find that including blue galaxies in the richness estimate increases the scatter, as does weighting galaxies by their optical luminosity. We further demonstrate that our richness estimator is very robust. Specifically, the filter employed when estimating richness can be calibrated directly from the data, without requiring a-priori calibrations of the red-sequence. We also demonstrate that the recovered richness is robust to up to 50% uncertainties in the galaxy background, as well as to the choice of photometric filter employed, so long as the filters span the 4000 {angstrom} break of red-sequence galaxies. Consequently, our richness estimator can be used to compare richness estimates of different clusters, even if they do not share the same photometric data. Appendix A includes 'easy-bake' instructions for implementing our optimal richness estimator, and we are releasing an implementation of the code that works with SDSS data, as well as an augmented maxBCG catalog with the {lambda} richness measured for each cluster.

  9. Sub-Second Parallel State Estimation

    SciTech Connect

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

    2014-10-31

    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

  10. Building unbiased estimators from non-gaussian likelihoods with application to shear estimation

    SciTech Connect

    Madhavacheril, Mathew S.; McDonald, Patrick; Sehgal, Neelima; Slosar, Anze

    2015-01-15

    We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the work of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrongs estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors ?g/g for shears up to |g| = 0.2.

  11. Building unbiased estimators from non-Gaussian likelihoods with application to shear estimation

    SciTech Connect

    Madhavacheril, Mathew S.; Sehgal, Neelima; McDonald, Patrick; Slosar, Ane E-mail: pvmcdonald@lbl.gov E-mail: anze@bnl.gov

    2015-01-01

    We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the work of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrong's estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors ?g/g for shears up to |g|=0.2.

  12. Building unbiased estimators from non-gaussian likelihoods with application to shear estimation

    SciTech Connect

    Madhavacheril, Mathew S.; Slosar, Anze; McDonald, Patrick; Sehgal, Neelima

    2015-01-01

    We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the work of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrongs estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors ?g/g for shears up to |g| = 0.2.

  13. Building unbiased estimators from non-gaussian likelihoods with application to shear estimation

    DOE PAGES [OSTI]

    Madhavacheril, Mathew S.; McDonald, Patrick; Sehgal, Neelima; Slosar, Anze

    2015-01-15

    We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the workmore » of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrong’s estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors Δg/g for shears up to |g| = 0.2.« less

  14. Estimating exposure of terrestrial wildlife to contaminants

    SciTech Connect

    Sample, B.E.; Suter, G.W. II

    1994-09-01

    This report describes generalized models for the estimation of contaminant exposure experienced by wildlife on the Oak Ridge Reservation. The primary exposure pathway considered is oral ingestion, e.g. the consumption of contaminated food, water, or soil. Exposure through dermal absorption and inhalation are special cases and are not considered hereIN. Because wildlife mobile and generally consume diverse diets and because environmental contamination is not spatial homogeneous, factors to account for variation in diet, movement, and contaminant distribution have been incorporated into the models. To facilitate the use and application of the models, life history parameters necessary to estimate exposure are summarized for 15 common wildlife species. Finally, to display the application of the models, exposure estimates were calculated for four species using data from a source operable unit on the Oak Ridge Reservation.

  15. Reionization history and CMB parameter estimation

    SciTech Connect

    Dizgah, Azadeh Moradinezhad; Kinney, William H.; Gnedin, Nickolay Y. E-mail: gnedin@fnal.edu

    2013-05-01

    We study how uncertainty in the reionization history of the universe affects estimates of other cosmological parameters from the Cosmic Microwave Background. We analyze WMAP7 data and synthetic Planck-quality data generated using a realistic scenario for the reionization history of the universe obtained from high-resolution numerical simulation. We perform parameter estimation using a simple sudden reionization approximation, and using the Principal Component Analysis (PCA) technique proposed by Mortonson and Hu. We reach two main conclusions: (1) Adopting a simple sudden reionization model does not introduce measurable bias into values for other parameters, indicating that detailed modeling of reionization is not necessary for the purpose of parameter estimation from future CMB data sets such as Planck. (2) PCA analysis does not allow accurate reconstruction of the actual reionization history of the universe in a realistic case.

  16. Robust estimation procedure in panel data model

    SciTech Connect

    Shariff, Nurul Sima Mohamad; Hamzah, Nor Aishah

    2014-06-19

    The panel data modeling has received a great attention in econometric research recently. This is due to the availability of data sources and the interest to study cross sections of individuals observed over time. However, the problems may arise in modeling the panel in the presence of cross sectional dependence and outliers. Even though there are few methods that take into consideration the presence of cross sectional dependence in the panel, the methods may provide inconsistent parameter estimates and inferences when outliers occur in the panel. As such, an alternative method that is robust to outliers and cross sectional dependence is introduced in this paper. The properties and construction of the confidence interval for the parameter estimates are also considered in this paper. The robustness of the procedure is investigated and comparisons are made to the existing method via simulation studies. Our results have shown that robust approach is able to produce an accurate and reliable parameter estimates under the condition considered.

  17. State energy data report 1996: Consumption estimates

    SciTech Connect

    1999-02-01

    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.

  18. Estimating vehicle height using homographic projections

    DOEpatents

    Cunningham, Mark F; Fabris, Lorenzo; Gee, Timothy F; Ghebretati, Jr., Frezghi H; Goddard, James S; Karnowski, Thomas P; Ziock, Klaus-peter

    2013-07-16

    Multiple homography transformations corresponding to different heights are generated in the field of view. A group of salient points within a common estimated height range is identified in a time series of video images of a moving object. Inter-salient point distances are measured for the group of salient points under the multiple homography transformations corresponding to the different heights. Variations in the inter-salient point distances under the multiple homography transformations are compared. The height of the group of salient points is estimated to be the height corresponding to the homography transformation that minimizes the variations.

  19. CONTAMINATED SOIL VOLUME ESTIMATE TRACKING METHODOLOGY

    SciTech Connect

    Durham, L.A.; Johnson, R.L.; Rieman, C.; Kenna, T.; Pilon, R.

    2003-02-27

    The U.S. Army Corps of Engineers (USACE) is conducting a cleanup of radiologically contaminated properties under the Formerly Utilized Sites Remedial Action Program (FUSRAP). The largest cost element for most of the FUSRAP sites is the transportation and disposal of contaminated soil. Project managers and engineers need an estimate of the volume of contaminated soil to determine project costs and schedule. Once excavation activities begin and additional remedial action data are collected, the actual quantity of contaminated soil often deviates from the original estimate, resulting in cost and schedule impacts to the project. The project costs and schedule need to be frequently updated by tracking the actual quantities of excavated soil and contaminated soil remaining during the life of a remedial action project. A soil volume estimate tracking methodology was developed to provide a mechanism for project managers and engineers to create better project controls of costs and schedule. For the FUSRAP Linde site, an estimate of the initial volume of in situ soil above the specified cleanup guidelines was calculated on the basis of discrete soil sample data and other relevant data using indicator geostatistical techniques combined with Bayesian analysis. During the remedial action, updated volume estimates of remaining in situ soils requiring excavation were calculated on a periodic basis. In addition to taking into account the volume of soil that had been excavated, the updated volume estimates incorporated both new gamma walkover surveys and discrete sample data collected as part of the remedial action. A civil survey company provided periodic estimates of actual in situ excavated soil volumes. By using the results from the civil survey of actual in situ volumes excavated and the updated estimate of the remaining volume of contaminated soil requiring excavation, the USACE Buffalo District was able to forecast and update project costs and schedule. The soil volume

  20. Process Equipment Cost Estimation, Final Report

    SciTech Connect

    H.P. Loh; Jennifer Lyons; Charles W. White, III

    2002-01-01

    This report presents generic cost curves for several equipment types generated using ICARUS Process Evaluator. The curves give Purchased Equipment Cost as a function of a capacity variable. This work was performed to assist NETL engineers and scientists in performing rapid, order of magnitude level cost estimates or as an aid in evaluating the reasonableness of cost estimates submitted with proposed systems studies or proposals for new processes. The specific equipment types contained in this report were selected to represent a relatively comprehensive set of conventional chemical process equipment types.

  1. Agricultural Irrigation Demand Response Estimation Tool

    Energy Science and Technology Software Center

    2014-02-01

    This program is used to model the energy demand of agricultural irrigation pumps, used to maintain soil moisture levels in irrigated fields. This modeling is accomplished using historical data from evapotranspirationmeasuring weather stations (from the California Irrigation Management Information System) as well as irrigation system characteristics for the field(s) to be modeled. The modelled energy demand is used to estimate the achievable demand response (DR) potential of the field(s), for use in assessing the valuemore » of the DR for the utility company. The program can accept input data with varying degrees of rigor, and estimate the uncertainty of the output accordingly.« less

  2. January 12, 2009, Visiting Speakers Program - Status of a Key...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Sources: IMF WEO (October '08), OECD, NSF Data, Battelle R&D Report, SPIE data *estimates ... Top 10 High-Tech Exporters Billions of 1997 USD: Council on Competitiveness 1986 2005 USA ...

  3. Renewable Energy RFPs | OpenEI Community

    OpenEI (Open Energy Information) [EERE & EIA]

    Energy Concerns to Push Global Market to Grow at 8.1% CAGR from 2013 to 2019 Oil Shale Market is Estimated to Reach USD 7,400.70 Million by 2022 more Group members (32)...

  4. Wind Energy Timeline - From Persian Windmills Crushing Grains...

    OpenEI (Open Energy Information) [EERE & EIA]

    Energy Concerns to Push Global Market to Grow at 8.1% CAGR from 2013 to 2019 Oil Shale Market is Estimated to Reach USD 7,400.70 Million by 2022 more Group members (32)...

  5. Circulating Fluidized Bed (CFB) Boilers Market will grow due...

    OpenEI (Open Energy Information) [EERE & EIA]

    Energy Concerns to Push Global Market to Grow at 8.1% CAGR from 2013 to 2019 Oil Shale Market is Estimated to Reach USD 7,400.70 Million by 2022 more Group members (32)...

  6. Lucrative Opportunities in Asia Pacific to Help Global Bunker...

    OpenEI (Open Energy Information) [EERE & EIA]

    Energy Concerns to Push Global Market to Grow at 8.1% CAGR from 2013 to 2019 Oil Shale Market is Estimated to Reach USD 7,400.70 Million by 2022 more Group members (32)...

  7. Multi-model Estimates of Intercontinental Source-Receptor Relationships for Ozone Pollution

    SciTech Connect

    Fiore, A M; Dentener, F J; Wild, O; Cuvelier, C; Schultz, M G; Hess, P; Textor, C; Schulz, M; Doherty, R; Horowitz, L W; MacKenzie, I A; Sanderson, M G; Shindell, D T; Stevenson, D S; Szopa, S; Van Dingenen, R; Zeng, G; Atherton, C; Bergmann, D; Bey, I; Carmichael, G; Collins, W J; Duncan, B N; Faluvegi, G; Folberth, G; Gauss, M; Gong, S; Hauglustaine, D; Holloway, T; Isaksen, I A; Jacob, D J; Jonson, J E; Kaminski, J W; Keating, T J; Lupu, A; Marmer, E; Montanaro, V; Park, R; Pitari, G; Pringle, K J; Pyle, J A; Schroeder, S; Vivanco, M G; Wind, P; Wojcik, G; Wu, S; Zuber, A

    2008-10-16

    , and by the weaker relative response of annual incidences of daily maximum 8-hour average O{sub 3} above 60 ppb to emission reductions in a foreign region (<10-20% of that to domestic) as compared to the annual mean response (up to 50% of that to domestic). Applying the ensemble annual mean results to changes in anthropogenic emissions from 1996 to 2002, we estimate a Northern Hemispheric increase in background surface O{sub 3} of about 0.1 ppb yr{sup -1}, at the low end of the 0.1-0.5 ppb yr{sup -1} derived from observations. From an additional simulation in which global atmospheric methane was reduced, we infer that 20% reductions in anthropogenic methane emissions from a foreign source region would yield an O{sub 3} response in a receptor region that roughly equals that produced by combined 20% reductions of anthropogenic NO{sub x}, NMVOC and CO emissions from the foreign source region.

  8. Estimating the uncertainty in underresolved nonlinear dynamics

    SciTech Connect

    Chorin, Alelxandre; Hald, Ole

    2013-06-12

    The Mori-Zwanzig formalism of statistical mechanics is used to estimate the uncertainty caused by underresolution in the solution of a nonlinear dynamical system. A general approach is outlined and applied to a simple example. The noise term that describes the uncertainty turns out to be neither Markovian nor Gaussian. It is argued that this is the general situation.

  9. Guidelines for Estimating Unmetered Landscaping Water Use

    SciTech Connect

    McMordie Stoughton, Kate

    2010-07-28

    The document lays-out step by step instructions to estimate landscaping water using two alternative approaches: evapotranspiration method and irrigation audit method. The evapotranspiration method option calculates the amount of water needed to maintain a healthy turf or landscaped area for a given location based on the amount of water transpired and evaporated from the plants. The evapotranspiration method offers a relatively easy “one-stop-shop” for Federal agencies to develop an initial estimate of annual landscape water use. The document presents annual irrigation factors for 36 cities across the U.S. that represents the gallons of irrigation required per square foot for distinct landscape types. By following the steps outlined in the document, the reader can choose a location that is a close match their location and landscape type to provide a rough estimate of annual irrigation needs without the need to research specific data on their site. The second option presented in the document is the irrigation audit method, which is the physical measurement of water applied to landscaped areas through irrigation equipment. Steps to perform an irrigation audit are outlined in the document, which follow the Recommended Audit Guidelines produced by the Irrigation Association.[5] An irrigation audit requires some knowledge on the specific procedures to accurately estimate how much water is being consumed by the irrigation equipment.

  10. DOE Zero Energy Ready Home Savings and Cost Estimate Summary...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Savings and Cost Estimate Summary DOE Zero Energy Ready Home Savings and Cost Estimate Summary The U.S. Department of Energy Zero Energy Ready Home Savings and Cost Estimate ...

  11. Report Now Available: DC Microgrids Scoping Study--Estimate of...

    Office of Environmental Management (EM)

    Report Now Available: DC Microgrids Scoping Study--Estimate of Technical and Economic Benefits (March 2015) Report Now Available: DC Microgrids Scoping Study--Estimate of Technical ...

  12. Parameter Estimation for Single Diode Models of Photovoltaic...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Estimation for Single Diode Models of Photovoltaic Modules Clifford W. Hansen Prepared by ... Estimation for Single Diode Models of Photovoltaic Modules Clifford W. Hansen ...

  13. Time Adaptive Conditional Kernel Density Estimation for Wind...

    Office of Scientific and Technical Information (OSTI)

    Time Adaptive Conditional Kernel Density Estimation for Wind Power Forecasting Citation Details In-Document Search Title: Time Adaptive Conditional Kernel Density Estimation for ...

  14. ,"Florida Dry Natural Gas Reserves Estimated Production (Billion...

    Energy Information Administration (EIA) (indexed site)

    Data for" ,"Data 1","Florida Dry Natural Gas Reserves Estimated ... 10:36:58 AM" "Back to Contents","Data 1: Florida Dry Natural Gas Reserves Estimated ...

  15. The ARM Best Estimate 2-dimensional Gridded Surface (Dataset...

    Office of Scientific and Technical Information (OSTI)

    2-dimensional Gridded Surface Title: The ARM Best Estimate 2-dimensional Gridded Surface The ARM Best Estimate 2-dimensional Gridded Surface (ARMBE2DGRID) data set merges together ...

  16. Estimating the Benefits and Costs of Distributed Energy Technologies...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Estimating the Benefits and Costs of Distributed Energy Technologies Workshop - Agenda and Summary Estimating the Benefits and Costs of Distributed Energy Technologies Workshop -...

  17. Contribution to the development of DOE ARM Climate Best Estimate...

    Office of Scientific and Technical Information (OSTI)

    Contribution to the development of DOE ARM Climate Best Estimate Data (ARMBE) products: ... Title: Contribution to the development of DOE ARM Climate Best Estimate Data (ARMBE) ...

  18. Error estimates for fission neutron outputs (Conference) | SciTech...

    Office of Scientific and Technical Information (OSTI)

    Error estimates for fission neutron outputs Citation Details In-Document Search Title: Error estimates for fission neutron outputs You are accessing a document from the...

  19. A Review of Geothermal Resource Estimation Methodology | Open...

    OpenEI (Open Energy Information) [EERE & EIA]

    Geothermal Resource Estimation Methodology Jump to: navigation, search OpenEI Reference LibraryAdd to library Conference Paper: A Review of Geothermal Resource Estimation...

  20. Estimating the Value of Electricity Storage Resources in Electricity...

    Office of Environmental Management (EM)

    Estimating the Value of Electricity Storage Resources in Electricity Markets - EAC 2011 Estimating the Value of Electricity Storage Resources in Electricity Markets - EAC 2011 The ...

  1. Estimating the system price of redox flow batteries for grid...

    Office of Scientific and Technical Information (OSTI)

    Estimating the system price of redox flow batteries for grid storage Citation Details ... Title: Estimating the system price of redox flow batteries for grid storage Authors: Ha, ...

  2. Error Estimation for Fault Tolerance in Numerical Integration...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Error Estimation for Fault Tolerance in Numerical Integration Solvers Event Sponsor: ... In numerical integration solvers, approximation error can be estimated at a low cost. We ...

  3. Process Equipment Cost Estimation, Final Report (Technical Report...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Process Equipment Cost Estimation, Final Report Citation Details In-Document Search Title: Process Equipment Cost Estimation, Final Report You are accessing a document from the ...

  4. Property:Number of Plants included in Capacity Estimate | Open...

    OpenEI (Open Energy Information) [EERE & EIA]

    Plants included in Capacity Estimate Jump to: navigation, search Property Name Number of Plants included in Capacity Estimate Property Type Number Retrieved from "http:...

  5. Property:Number of Plants Included in Planned Estimate | Open...

    OpenEI (Open Energy Information) [EERE & EIA]

    Number of Plants Included in Planned Estimate Jump to: navigation, search Property Name Number of Plants Included in Planned Estimate Property Type String Description Number of...

  6. Estimating the Impact (Energy, Emissions and Economics) of the...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Estimating the Impact (Energy, Emissions and Economics) of the US Fluid Power Industry Citation Details In-Document Search Title: Estimating the Impact (Energy, ...

  7. Estimating Carbon Supply Curves for Global Forests and Other...

    OpenEI (Open Energy Information) [EERE & EIA]

    Estimating Carbon Supply Curves for Global Forests and Other Land Uses Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Estimating Carbon Supply Curves for Global Forests...

  8. A Review of Cost Estimation in New Technologies - Implications...

    Energy Saver

    A Review of Cost Estimation in New Technologies - Implications for Energy Process Plants A Review of Cost Estimation in New Technologies - Implications for Energy Process Plants ...

  9. Estimating Costs and Efficiency of Storage, Demand, and Heat...

    Energy Saver

    Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters A water heater's ...

  10. ARM Climate Modeling Best Estimate Lamont, OK Statistical Summary...

    Office of Scientific and Technical Information (OSTI)

    Climate Modeling Best Estimate Lamont, OK Statistical Summary (ARMBE-CLDRAD SGPC1) Title: ARM Climate Modeling Best Estimate Lamont, OK Statistical Summary (ARMBE-CLDRAD SGPC1) ...

  11. Estimation of Anisotoropy from Total Cross Section and Optical...

    Office of Scientific and Technical Information (OSTI)

    Conference: Estimation of Anisotoropy from Total Cross Section and Optical Model Citation Details In-Document Search Title: Estimation of Anisotoropy from Total Cross Section and ...

  12. Estimation of 1945 to 1957 food consumption

    SciTech Connect

    Anderson, D.M.; Bates, D.J.; Marsh, T.L.

    1993-03-01

    This report details the methods used and the results of the study on the estimated historic levels of food consumption by individuals in the Hanford Environmental Dose Reconstruction (HEDR) study area from 1945--1957. This period includes the time of highest releases from Hanford and is the period for which data are being collected in the Hanford Thyroid Disease Study. These estimates provide the food-consumption inputs for the HEDR database of individual diets. This database will be an input file in the Hanford Environmental Dose Reconstruction Integrated Code (HEDRIC) computer model that will be used to calculate the radiation dose. The report focuses on fresh milk, eggs, lettuce, and spinach. These foods were chosen because they have been found to be significant contributors to radiation dose based on the Technical Steering Panel dose decision level.

  13. CosmoSIS: Modular cosmological parameter estimation

    SciTech Connect

    Zuntz, J.; Paterno, M.; Jennings, E.; Rudd, D.; Manzotti, A.; Dodelson, S.; Bridle, S.; Sehrish, S.; Kowalkowski, J.

    2015-06-09

    Cosmological parameter estimation is entering a new era. Large collaborations need to coordinate high-stakes analyses using multiple methods; furthermore such analyses have grown in complexity due to sophisticated models of cosmology and systematic uncertainties. In this paper we argue that modularity is the key to addressing these challenges: calculations should be broken up into interchangeable modular units with inputs and outputs clearly defined. Here we present a new framework for cosmological parameter estimation, CosmoSIS, designed to connect together, share, and advance development of inference tools across the community. We describe the modules already available in CosmoSIS, including CAMB, Planck, cosmic shear calculations, and a suite of samplers. Lastly, we illustrate it using demonstration code that you can run out-of-the-box with the installer available at http://bitbucket.org/joezuntz/cosmosis

  14. CosmoSIS: Modular cosmological parameter estimation

    DOE PAGES [OSTI]

    Zuntz, J.; Paterno, M.; Jennings, E.; Rudd, D.; Manzotti, A.; Dodelson, S.; Bridle, S.; Sehrish, S.; Kowalkowski, J.

    2015-06-09

    Cosmological parameter estimation is entering a new era. Large collaborations need to coordinate high-stakes analyses using multiple methods; furthermore such analyses have grown in complexity due to sophisticated models of cosmology and systematic uncertainties. In this paper we argue that modularity is the key to addressing these challenges: calculations should be broken up into interchangeable modular units with inputs and outputs clearly defined. Here we present a new framework for cosmological parameter estimation, CosmoSIS, designed to connect together, share, and advance development of inference tools across the community. We describe the modules already available in CosmoSIS, including CAMB, Planck, cosmicmore » shear calculations, and a suite of samplers. Lastly, we illustrate it using demonstration code that you can run out-of-the-box with the installer available at http://bitbucket.org/joezuntz/cosmosis« less

  15. Generalized REGression Package for Nonlinear Parameter Estimation

    Energy Science and Technology Software Center

    1995-05-15

    GREG computes modal (maximum-posterior-density) and interval estimates of the parameters in a user-provided Fortran subroutine MODEL, using a user-provided vector OBS of single-response observations or matrix OBS of multiresponse observations. GREG can also select the optimal next experiment from a menu of simulated candidates, so as to minimize the volume of the parametric inference region based on the resulting augmented data set.

  16. Numerical Estimation of the Spent Fuel Ratio

    SciTech Connect

    Lindgren, Eric R.; Durbin, Samuel; Wilke, Jason; Margraf, J.; Dunn, T. A.

    2016-01-01

    Sabotage of spent nuclear fuel casks remains a concern nearly forty years after attacks against shipment casks were first analyzed and has a renewed relevance in the post-9/11 environment. A limited number of full-scale tests and supporting efforts using surrogate materials, typically depleted uranium dioxide (DUO 2 ), have been conducted in the interim to more definitively determine the source term from these postulated events. However, the validity of these large- scale results remain in question due to the lack of a defensible spent fuel ratio (SFR), defined as the amount of respirable aerosol generated by an attack on a mass of spent fuel compared to that of an otherwise identical surrogate. Previous attempts to define the SFR in the 1980's have resulted in estimates ranging from 0.42 to 12 and include suboptimal experimental techniques and data comparisons. Because of the large uncertainty surrounding the SFR, estimates of releases from security-related events may be unnecessarily conservative. Credible arguments exist that the SFR does not exceed a value of unity. A defensible determination of the SFR in this lower range would greatly reduce the calculated risk associated with the transport and storage of spent nuclear fuel in dry cask systems. In the present work, the shock physics codes CTH and ALE3D were used to simulate spent nuclear fuel (SNF) and DUO 2 targets impacted by a high-velocity jet at an ambient temperature condition. These preliminary results are used to illustrate an approach to estimate the respirable release fraction for each type of material and ultimately, an estimate of the SFR. This page intentionally blank

  17. Low-Temperature Hydrothermal Resource Potential Estimate

    DOE Data Explorer

    Katherine Young

    2016-06-30

    Compilation of data (spreadsheet and shapefiles) for several low-temperature resource types, including isolated springs and wells, delineated area convection systems, sedimentary basins and coastal plains sedimentary systems. For each system, we include estimates of the accessible resource base, mean extractable resource and beneficial heat. Data compiled from USGS and other sources. The paper (submitted to GRC 2016) describing the methodology and analysis is also included.

  18. Knowledge Based Estimation of Material Release Transients

    Energy Science and Technology Software Center

    1998-07-29

    KBERT is an easy to use desktop decision support tool for estimating public and in-facility worker doses and consequences of radioactive material releases in non-reactort nuclear facilities. It automatically calculates release and respirable fractions based on published handbook data, and calculates material transport concurrently with personnel evacuation simulations. Any facility layout can be modeled easily using the intuitive graphical user interface.

  19. State energy data report 1992: Consumption estimates

    SciTech Connect

    Not Available

    1994-05-01

    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.

  20. Communications circuit including a linear quadratic estimator

    SciTech Connect

    Ferguson, Dennis D.

    2015-07-07

    A circuit includes a linear quadratic estimator (LQE) configured to receive a plurality of measurements a signal. The LQE is configured to weight the measurements based on their respective uncertainties to produce weighted averages. The circuit further includes a controller coupled to the LQE and configured to selectively adjust at least one data link parameter associated with a communication channel in response to receiving the weighted averages.

  1. Notices Total Estimated Number of Annual

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    372 Federal Register / Vol. 78, No. 181 / Wednesday, September 18, 2013 / Notices Total Estimated Number of Annual Burden Hours: 10,128. Abstract: Enrollment in the Federal Student Aid (FSA) Student Aid Internet Gateway (SAIG) allows eligible entities to securely exchange Title IV, Higher Education Act (HEA) assistance programs data electronically with the Department of Education processors. Organizations establish Destination Point Administrators (DPAs) to transmit, receive, view and update

  2. Budget estimates fiscal year 1995: Volume 10

    SciTech Connect

    Not Available

    1994-02-01

    This report contains the Nuclear Regulatory Commission (NRC) fiscal year budget justification to Congress. The budget provides estimates for salaries and expenses and for the Office of the Inspector General for fiscal year 1995. The NRC 1995 budget request is $546,497,000. This is an increase of $11,497,000 above the proposed level for FY 1994. The NRC FY 1995 budget request is 3,218 FTEs. This is a decrease of 75 FTEs below the 1994 proposed level.

  3. Guidelines for Estimating Unmetered Industrial Water Use

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Guidelines for Estimating Unmetered Industrial Water Use Prepared for U.S. Department of Energy Federal Energy Management Program By Pacific Northwest National Laboratory Brian Boyd Revised September 2011 Source: Michael Kauffmann 2 Contacts Will Lintner Federal Energy Management Program 1000 Independence Ave., S.W. Washington, D.C. 20585-0121 Phone: (202) 586-3120 E-mail: William.Lintner@ee.doe.gov Brian Boyd Pacific Northwest National Laboratory 902 Battelle Boulevard Richland, WA 99352 Phone:

  4. Guidelines for Estimating Unmetered Landscapting Water Use

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Estimating Unmetered Landscaping Water Use July 2010 i Summary Executive Order 13514 requires Federal agencies to develop a baseline for industrial, landscaping, and agricultural water use in fiscal year 2010. Measuring actual water use through flow meters is the best method to develop this baseline. But there are instances where Federal sites do not meter these applications, so developing a baseline will be problematic. Therefore the intent of this document is to assist Federal agencies in the

  5. Cost estimate of initial SSC experimental equipment

    SciTech Connect

    1986-06-01

    The cost of the initial detector complement at recently constructed colliding beam facilities (or at those under construction) has been a significant fraction of the cost of the accelerator complex. Because of the complexity of large modern-day detectors, the time-scale for their design and construction is comparable to the time-scale needed for accelerator design and construction. For these reasons it is appropriate to estimate the cost of the anticipated detector complement in parallel with the cost estimates of the collider itself. The fundamental difficulty with this procedure is that, whereas a firm conceptual design of the collider does exist, comparable information is unavailable for the detectors. Traditionally, these have been built by the high energy physics user community according to their perception of the key scientific problems that need to be addressed. The role of the accelerator laboratory in that process has involved technical and managerial coordination and the allocation of running time and local facilities among the proposed experiments. It seems proper that the basic spirit of experimentation reflecting the scientific judgment of the community should be preserved at the SSC. Furthermore, the formal process of initiation of detector proposals can only start once the SSC has been approved as a construction project and a formal laboratory administration put in place. Thus an ad hoc mechanism had to be created to estimate the range of potential detector needs, potential detector costs, and associated computing equipment.

  6. TRENDS IN ESTIMATED MIXING DEPTH DAILY MAXIMUMS

    SciTech Connect

    Buckley, R; Amy DuPont, A; Robert Kurzeja, R; Matt Parker, M

    2007-11-12

    Mixing depth is an important quantity in the determination of air pollution concentrations. Fireweather forecasts depend strongly on estimates of the mixing depth as a means of determining the altitude and dilution (ventilation rates) of smoke plumes. The Savannah River United States Forest Service (USFS) routinely conducts prescribed fires at the Savannah River Site (SRS), a heavily wooded Department of Energy (DOE) facility located in southwest South Carolina. For many years, the Savannah River National Laboratory (SRNL) has provided forecasts of weather conditions in support of the fire program, including an estimated mixing depth using potential temperature and turbulence change with height at a given location. This paper examines trends in the average estimated mixing depth daily maximum at the SRS over an extended period of time (4.75 years) derived from numerical atmospheric simulations using two versions of the Regional Atmospheric Modeling System (RAMS). This allows for differences to be seen between the model versions, as well as trends on a multi-year time frame. In addition, comparisons of predicted mixing depth for individual days in which special balloon soundings were released are also discussed.

  7. Groundwater Treatment Resin Saves an Estimated $2 Million More Than

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Expected - Annual efficiency three times higher than original estimates | Department of Energy Groundwater Treatment Resin Saves an Estimated $2 Million More Than Expected - Annual efficiency three times higher than original estimates Groundwater Treatment Resin Saves an Estimated $2 Million More Than Expected - Annual efficiency three times higher than original estimates July 28, 2016 - 12:15pm Addthis There are four groundwater treatment facilities located along the Columbia River at the

  8. Estimating radiological background using imaging spectroscopy

    SciTech Connect

    Bernacki, Bruce E.; Schweppe, John E.; Stave, Sean C.; Jordan, David V.; Kulisek, Jonathan A.; Stewart, Trevor N.; Seifert, Carolyn E.

    2014-06-13

    Optical imaging spectroscopy is investigated as a method to estimate radiological background by spectral identification of soils, sediments, rocks, minerals and building materials derived from natural materials and assigning tabulated radiological emission values to these materials. Radiological airborne surveys are undertaken by local, state and federal agencies to identify the presence of radiological materials out of regulatory compliance. Detection performance in such surveys is determined by (among other factors) the uncertainty in the radiation background; increased knowledge of the expected radiation background will improve the ability to detect low-activity radiological materials. Radiological background due to naturally occurring radiological materials (NORM) can be estimated by reference to previous survey results, use of global 40K, 238U, and 232Th (KUT) values, reference to existing USGS radiation background maps, or by a moving average of the data as it is acquired. Each of these methods has its drawbacks: previous survey results may not include recent changes, the global average provides only a zero-order estimate, the USGS background radiation map resolutions are coarse and are accurate only to 1 km – 25 km sampling intervals depending on locale, and a moving average may essentially low pass filter the data to obscure small changes in radiation counts. Imaging spectroscopy from airborne or spaceborne platforms can offer higher resolution identification of materials and background, as well as provide imaging context information. AVIRIS hyperspectral image data is analyzed using commercial exploitation software to determine the usefulness of imaging spectroscopy to identify qualitative radiological background emissions when compared to airborne radiological survey data.

  9. Estimated United States Transportation Energy Use 2005

    SciTech Connect

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

    2011-11-09

    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.

  10. Position estimation of transceivers in communication networks

    DOEpatents

    Kent, Claudia A.; Dowla, Farid

    2008-06-03

    This invention provides a system and method using wireless communication interfaces coupled with statistical processing of time-of-flight data to locate by position estimation unknown wireless receivers. Such an invention can be applied in sensor network applications, such as environmental monitoring of water in the soil or chemicals in the air where the position of the network nodes is deemed critical. Moreover, the present invention can be arranged to operate in areas where a Global Positioning System (GPS) is not available, such as inside buildings, caves, and tunnels.

  11. Microsphere estimates of blood flow: Methodological considerations

    SciTech Connect

    von Ritter, C.; Hinder, R.A.; Womack, W.; Bauerfeind, P.; Fimmel, C.J.; Kvietys, P.R.; Granger, D.N.; Blum, A.L. Louisianna State Univ. Medical Center, Shreveport Universitaire Vaudois )

    1988-02-01

    The microsphere technique is a standard method for measuring blood flow in experimental animals. Sporadic reports have appeared outlining the limitations of this method. In this study the authors have systematically assessed the effect of blood withdrawals for reference sampling, microsphere numbers, and anesthesia on blood flow estimates using radioactive microspheres in dogs. Experiments were performed on 18 conscious and 12 anesthetized dogs. Four blood flow estimates were performed over 120 min using 1 {times} 10{sup 6} microspheres each time. The effects of excessive numbers of microspheres pentobarbital sodium anesthesia, and replacement of volume loss for reference samples with dextran 70 were assessed. In both conscious and anesthetized dogs a progressive decrease in gastric mucosal blood flow and cardiac output was observed over 120 min. This was also observed in the pancreas in conscious dogs. The major factor responsible for these changes was the volume loss due to the reference sample withdrawals. Replacement of the withdrawn blood with dextran 70 led to stable blood flows to all organs. The injection of excessive numbers of microspheres did not modify hemodynamics to a greater extent than did the injection of 4 million microspheres. Anesthesia exerted no influence on blood flow other than raising coronary flow. The authors conclude that although blood flow to the gastric mucosa and the pancreas is sensitive to the minor hemodynamic changes associated with the microsphere technique, replacement of volume loss for reference samples ensures stable blood flow to all organs over a 120-min period.

  12. Risk Estimation Methodology for Launch Accidents.

    SciTech Connect

    Clayton, Daniel James; Lipinski, Ronald J.; Bechtel, Ryan D.

    2014-02-01

    As compact and light weight power sources with reliable, long lives, Radioisotope Power Systems (RPSs) have made space missions to explore the solar system possible. Due to the hazardous material that can be released during a launch accident, the potential health risk of an accident must be quantified, so that appropriate launch approval decisions can be made. One part of the risk estimation involves modeling the response of the RPS to potential accident environments. Due to the complexity of modeling the full RPS response deterministically on dynamic variables, the evaluation is performed in a stochastic manner with a Monte Carlo simulation. The potential consequences can be determined by modeling the transport of the hazardous material in the environment and in human biological pathways. The consequence analysis results are summed and weighted by appropriate likelihood values to give a collection of probabilistic results for the estimation of the potential health risk. This information is used to guide RPS designs, spacecraft designs, mission architecture, or launch procedures to potentially reduce the risk, as well as to inform decision makers of the potential health risks resulting from the use of RPSs for space missions.

  13. Estimates of Savings Achievable from Irrigation Controller

    SciTech Connect

    Williams, Alison; Fuchs, Heidi; Whitehead, Camilla Dunham

    2014-03-28

    This paper performs a literature review and meta-analysis of water savings from several types of advanced irrigation controllers: rain sensors (RS), weather-based irrigation controllers (WBIC), and soil moisture sensors (SMS).The purpose of this work is to derive average water savings per controller type, based to the extent possible on all available data. After a preliminary data scrubbing, we utilized a series of analytical filters to develop our best estimate of average savings. We applied filters to remove data that might bias the sample such as data self-reported by manufacturers, data resulting from studies focusing on high-water users, or data presented in a non-comparable format such as based on total household water use instead of outdoor water use. Because the resulting number of studies was too small to be statistically significant when broken down by controller type, this paper represents a survey and synthesis of available data rather than a definitive statement regarding whether the estimated water savings are representative.

  14. Development of surface mine cost estimating equations

    SciTech Connect

    Not Available

    1980-09-26

    Cost estimating equations were developed to determine capital and operating costs for five surface coal mine models in Central Appalachia, Northern Appalachia, Mid-West, Far-West, and Campbell County, Wyoming. Engineering equations were used to estimate equipment costs for the stripping function and for the coal loading and hauling function for the base case mine and for several mines with different annual production levels and/or different overburden removal requirements. Deferred costs were then determined through application of the base case depreciation schedules, and direct labor costs were easily established once the equipment quantities (and, hence, manpower requirements) were determined. The data points were then fit with appropriate functional forms, and these were then multiplied by appropriate adjustment factors so that the resulting equations yielded the model mine costs for initial and deferred capital and annual operating cost. (The validity of this scaling process is based on the assumption that total initial and deferred capital costs are proportional to the initial and deferred costs for the primary equipment types that were considered and that annual operating cost is proportional to the direct labor costs that were determined based on primary equipment quantities.) Initial capital costs ranged from $3,910,470 in Central Appalachia to $49,296,785; deferred capital costs ranged from $3,220,000 in Central Appalachia to $30,735,000 in Campbell County, Wyoming; and annual operating costs ranged from $2,924,148 in Central Appalachia to $32,708,591 in Campbell County, Wyoming. (DMC)

  15. Estimating Terrorist Risk with Possibility Theory

    SciTech Connect

    J.L. Darby

    2004-11-30

    This report summarizes techniques that use possibility theory to estimate the risk of terrorist acts. These techniques were developed under the sponsorship of the Department of Homeland Security (DHS) as part of the National Infrastructure Simulation Analysis Center (NISAC) project. The techniques have been used to estimate the risk of various terrorist scenarios to support NISAC analyses during 2004. The techniques are based on the Logic Evolved Decision (LED) methodology developed over the past few years by Terry Bott and Steve Eisenhawer at LANL. [LED] The LED methodology involves the use of fuzzy sets, possibility theory, and approximate reasoning. LED captures the uncertainty due to vagueness and imprecision that is inherent in the fidelity of the information available for terrorist acts; probability theory cannot capture these uncertainties. This report does not address the philosophy supporting the development of nonprobabilistic approaches, and it does not discuss possibility theory in detail. The references provide a detailed discussion of these subjects. [Shafer] [Klir and Yuan] [Dubois and Prade] Suffice to say that these approaches were developed to address types of uncertainty that cannot be addressed by a probability measure. An earlier report discussed in detail the problems with using a probability measure to evaluate terrorist risk. [Darby Methodology]. Two related techniques are discussed in this report: (1) a numerical technique, and (2) a linguistic technique. The numerical technique uses traditional possibility theory applied to crisp sets, while the linguistic technique applies possibility theory to fuzzy sets. Both of these techniques as applied to terrorist risk for NISAC applications are implemented in software called PossibleRisk. The techniques implemented in PossibleRisk were developed specifically for use in estimating terrorist risk for the NISAC program. The LEDTools code can be used to perform the same linguistic evaluation as

  16. New developments in capital cost estimating

    SciTech Connect

    Stutz, R.A.; Zocher, M.A.

    1988-01-01

    The new developments in cost engineering revolve around the ability to capture information that in the past could not be automated. The purpose of automation is not to eliminate the expert cost engineer. The goal is to use available technology to have more information available to the professionals in the cost engineering field. In that sense, the demand for expertise increases in order to produce the highest quality estimate and project possible from all levels of cost engineers. We cannot overemphasize the importance of using a good source of expert information in building these types of programs. ''Garbage in, garbage out'' still applies in this form of programming. Expert systems technology will become commonplace in many vertical markets; it is important to undersand what can and cannot be accomplished in our field, and where this technology will lead us in the future.

  17. Estimated Water Flows in 2005: United States

    SciTech Connect

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

    2011-03-16

    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.

  18. Chapter 17: Estimating Net Savings: Common Practices

    SciTech Connect

    Violette, D. M.; Rathbun, P.

    2014-09-01

    This chapter focuses on the methods used to estimate net energy savings in evaluation, measurement, and verification (EM&V) studies for energy efficiency (EE) programs. The chapter provides a definition of net savings, which remains an unsettled topic both within the EE evaluation community and across the broader public policy evaluation community, particularly in the context of attribution of savings to particular program. The chapter differs from the measure-specific Uniform Methods Project (UMP) chapters in both its approach and work product. Unlike other UMP resources that provide recommended protocols for determining gross energy savings, this chapter describes and compares the current industry practices for determining net energy savings, but does not prescribe particular methods.

  19. FUZZY SUPERNOVA TEMPLATES. II. PARAMETER ESTIMATION

    SciTech Connect

    Rodney, Steven A.; Tonry, John L. E-mail: jt@ifa.hawaii.ed

    2010-05-20

    Wide-field surveys will soon be discovering Type Ia supernovae (SNe) at rates of several thousand per year. Spectroscopic follow-up can only scratch the surface for such enormous samples, so these extensive data sets will only be useful to the extent that they can be characterized by the survey photometry alone. In a companion paper we introduced the Supernova Ontology with Fuzzy Templates (SOFT) method for analyzing SNe using direct comparison to template light curves, and demonstrated its application for photometric SN classification. In this work we extend the SOFT method to derive estimates of redshift and luminosity distance for Type Ia SNe, using light curves from the Sloan Digital Sky Survey (SDSS) and Supernova Legacy Survey (SNLS) as a validation set. Redshifts determined by SOFT using light curves alone are consistent with spectroscopic redshifts, showing an rms scatter in the residuals of rms{sub z} = 0.051. SOFT can also derive simultaneous redshift and distance estimates, yielding results that are consistent with the currently favored {Lambda}CDM cosmological model. When SOFT is given spectroscopic information for SN classification and redshift priors, the rms scatter in Hubble diagram residuals is 0.18 mag for the SDSS data and 0.28 mag for the SNLS objects. Without access to any spectroscopic information, and even without any redshift priors from host galaxy photometry, SOFT can still measure reliable redshifts and distances, with an increase in the Hubble residuals to 0.37 mag for the combined SDSS and SNLS data set. Using Monte Carlo simulations, we predict that SOFT will be able to improve constraints on time-variable dark energy models by a factor of 2-3 with each new generation of large-scale SN surveys.

  20. Uncertainty in gridded CO2 emissions estimates

    DOE PAGES [OSTI]

    Hogue, Susannah; Marland, Eric; Andres, Robert J.; Marland, Gregg; Woodard, Dawn

    2016-05-19

    We are interested in the spatial distribution of fossil-fuel-related emissions of CO2 for both geochemical and geopolitical reasons, but it is important to understand the uncertainty that exists in spatially explicit emissions estimates. Working from one of the widely used gridded data sets of CO2 emissions, we examine the elements of uncertainty, focusing on gridded data for the United States at the scale of 1° latitude by 1° longitude. Uncertainty is introduced in the magnitude of total United States emissions, the magnitude and location of large point sources, the magnitude and distribution of non-point sources, and from the use ofmore » proxy data to characterize emissions. For the United States, we develop estimates of the contribution of each component of uncertainty. At 1° resolution, in most grid cells, the largest contribution to uncertainty comes from how well the distribution of the proxy (in this case population density) represents the distribution of emissions. In other grid cells, the magnitude and location of large point sources make the major contribution to uncertainty. Uncertainty in population density can be important where a large gradient in population density occurs near a grid cell boundary. Uncertainty is strongly scale-dependent with uncertainty increasing as grid size decreases. In conclusion, uncertainty for our data set with 1° grid cells for the United States is typically on the order of ±150%, but this is perhaps not excessive in a data set where emissions per grid cell vary over 8 orders of magnitude.« less

  1. The ARM Best Estimate Station-based Surface (ARMBESTNS) Data...

    Office of Scientific and Technical Information (OSTI)

    Station-based Surface (ARMBESTNS) Data set Title: The ARM Best Estimate Station-based Surface (ARMBESTNS) Data set The ARM Best Estimate Station-based Surface (ARMBESTNS) data set ...

  2. ARM Climate Modeling Best Estimate Data - A new data product...

    Office of Scientific and Technical Information (OSTI)

    ARM Climate Modeling Best Estimate Data - A new data product for climate modelers Citation Details In-Document Search Title: ARM Climate Modeling Best Estimate Data - A new data ...

  3. Microsoft PowerPoint - 15.1615_Cost Estimating Panel

    Energy Saver

    Cost Estimate (ICE) - Same Basis as Project Cost Estimate (PCE) Sa e as s as ojec Cos s a e ( C ) - Reconcilable with PCE to Facilitate Validation * Independent Cost Review...

  4. Estimating Motor Efficiency in the Field | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Estimating Motor Efficiency in the Field Estimating Motor Efficiency in the Field Some utility companies and public agencies offer rebates to encourage customers to upgrade their existing standard efficiency motors to premium efficiency motors. It is important to know the efficiency of the existing motor and how it is being used to accurately estimate potential annual energy and dollar savings. This tip sheet provides suggested actions and estimates of savings from improved efficiency. Motor

  5. Estimating Waste Inventory and Waste Tank Characterization | Department of

    Office of Environmental Management (EM)

    Energy Estimating Waste Inventory and Waste Tank Characterization Estimating Waste Inventory and Waste Tank Characterization Summary Notes from 28 May 2008 Generic Technical Issue Discussion on Estimating Waste Inventory and Waste Tank Characterization Summary Notes from 28 May 2008 Generic Technical Issue Discussion on Estimating Waste Inventory and Waste Tank Characterization (36.64 KB) More Documents & Publications Removal to Maximum Extent Practical Basis for Section 3116

  6. Buildings Greenhouse Gas Mitigation Estimator Worksheet | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy Buildings Greenhouse Gas Mitigation Estimator Worksheet Buildings Greenhouse Gas Mitigation Estimator Worksheet Excel tool helps agencies estimate the greenhouse gas (GHG) mitigation reduction from implementing energy efficiency measures across a portfolio of buildings. It is designed to be applied to groups of office buildings. For example, at a program level (regional or site) that can be summarized at the agency level. While the default savings and cost estimates apply to office

  7. Estimating Appliance and Home Electronic Energy Use | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Electricity & Fuel » Appliances & Electronics » Estimating Appliance and Home Electronic Energy Use Estimating Appliance and Home Electronic Energy Use Our appliance and electronic energy use calculator allows you to estimate your annual energy use and cost to operate specific products. The wattage values provided are samples only; actual wattage of products varies depending on product age and features. Enter a wattage value for your own product for the most accurate estimate. Wattage

  8. Best-Estimate Analysis PWR LOCA.

    Energy Science and Technology Software Center

    2005-11-11

    Version: 00 TRAC‑PF1 performs best estimate analyses of loss of coolant accidents and other transients in pressurized light water reactors. The program can also be used to model a wide range of thermal hydraulic experiments in reduced scale facilities. Models employed include reflood, multi‑dimensional two‑phase flow, nonequilibrium thermodynamics, generalized heat transfer, and reactor kinetics. Automatic steady‑state and dump/restart capabilities are provided. The changes reported in TRACNEWS issues through Number 7 are incorporated in this release.more » TRAC-PF1 was developed on a CDC computer at Los Alamos National Laboratory. The PC version of TRAC‑PF1 was converted at CNEN in 1989 and has not been updated since that time. The NRC no longer supports the TRAC codes. They currently develop and maintain the TRACE code system, which is the TRAC/RELAP Advanced Computational Engine. TRACE is a modernized thermal-hydraulics code designed to consolidate the capabilities of NRC's 3 legacy safety codes - TRAC-P, TRAC-B and RELAP. This is NRC's flagship thermal-hydraulics analysis tool. See the website for more information http://www.nrccodes.com/.« less

  9. Theoretical Estimate of Maximum Possible Nuclear Explosion

    DOE R&D Accomplishments

    Bethe, H. A.

    1950-01-31

    The maximum nuclear accident which could occur in a Na-cooled, Be moderated, Pu and power producing reactor is estimated theoretically. (T.R.H.) 2O82 Results of nuclear calculations for a variety of compositions of fast, heterogeneous, sodium-cooled, U-235-fueled, plutonium- and power-producing reactors are reported. Core compositions typical of plate-, pin-, or wire-type fuel elements and with uranium as metal, alloy, and oxide were considered. These compositions included atom ratios in the following range: U-23B to U-235 from 2 to 8; sodium to U-235 from 1.5 to 12; iron to U-235 from 5 to 18; and vanadium to U-235 from 11 to 33. Calculations were performed to determine the effect of lead and iron reflectors between the core and blanket. Both natural and depleted uranium were evaluated as the blanket fertile material. Reactors were compared on a basis of conversion ratio, specific power, and the product of both. The calculated results are in general agreement with the experimental results from fast reactor assemblies. An analysis of the effect of new cross-section values as they became available is included. (auth)

  10. Residential Lighting End-Use Consumption Study: Estimation Framework and Initial Estimates

    SciTech Connect

    Gifford, Will R.; Goldberg, Miriam L.; Tanimoto, Paulo M.; Celnicker, Dane R.; Poplawski, Michael E.

    2012-12-01

    The U.S. DOE Residential Lighting End-Use Consumption Study is an initiative of the U.S. Department of Energy’s (DOE’s) Solid-State Lighting Program that aims to improve the understanding of lighting energy usage in residential dwellings. The study has developed a regional estimation framework within a national sample design that allows for the estimation of lamp usage and energy consumption 1) nationally and by region of the United States, 2) by certain household characteristics, 3) by location within the home, 4) by certain lamp characteristics, and 5) by certain categorical cross-classifications (e.g., by dwelling type AND lamp type or fixture type AND control type).

  11. IDC RP2 & 3 US Industry Standard Cost Estimate Summary.

    SciTech Connect

    Harris, James M.; Huelskamp, Robert M.

    2015-01-01

    Sandia National Laboratories has prepared a ROM cost estimate for budgetary planning for the IDC Reengineering Phase 2 & 3 effort, using a commercial software cost estimation tool calibrated to US industry performance parameters. This is not a cost estimate for Sandia to perform the project. This report provides the ROM cost estimate and describes the methodology, assumptions, and cost model details used to create the ROM cost estimate. ROM Cost Estimate Disclaimer Contained herein is a Rough Order of Magnitude (ROM) cost estimate that has been provided to enable initial planning for this proposed project. This ROM cost estimate is submitted to facilitate informal discussions in relation to this project and is NOT intended to commit Sandia National Laboratories (Sandia) or its resources. Furthermore, as a Federally Funded Research and Development Center (FFRDC), Sandia must be compliant with the Anti-Deficiency Act and operate on a full-cost recovery basis. Therefore, while Sandia, in conjunction with the Sponsor, will use best judgment to execute work and to address the highest risks and most important issues in order to effectively manage within cost constraints, this ROM estimate and any subsequent approved cost estimates are on a 'full-cost recovery' basis. Thus, work can neither commence nor continue unless adequate funding has been accepted and certified by DOE.

  12. Parameter estimation with Sandage-Loeb test

    SciTech Connect

    Geng, Jia-Jia; Zhang, Jing-Fei; Zhang, Xin E-mail: jfzhang@mail.neu.edu.cn

    2014-12-01

    The Sandage-Loeb (SL) test directly measures the expansion rate of the universe in the redshift range of 2 ∼< z ∼< 5 by detecting redshift drift in the spectra of Lyman-α forest of distant quasars. We discuss the impact of the future SL test data on parameter estimation for the ΛCDM, the wCDM, and the w{sub 0}w{sub a}CDM models. To avoid the potential inconsistency with other observational data, we take the best-fitting dark energy model constrained by the current observations as the fiducial model to produce 30 mock SL test data. The SL test data provide an important supplement to the other dark energy probes, since they are extremely helpful in breaking the existing parameter degeneracies. We show that the strong degeneracy between Ω{sub m} and H{sub 0} in all the three dark energy models is well broken by the SL test. Compared to the current combined data of type Ia supernovae, baryon acoustic oscillation, cosmic microwave background, and Hubble constant, the 30-yr observation of SL test could improve the constraints on Ω{sub m} and H{sub 0} by more than 60% for all the three models. But the SL test can only moderately improve the constraint on the equation of state of dark energy. We show that a 30-yr observation of SL test could help improve the constraint on constant w by about 25%, and improve the constraints on w{sub 0} and w{sub a} by about 20% and 15%, respectively. We also quantify the constraining power of the SL test in the future high-precision joint geometric constraints on dark energy. The mock future supernova and baryon acoustic oscillation data are simulated based on the space-based project JDEM. We find that the 30-yr observation of SL test would help improve the measurement precision of Ω{sub m}, H{sub 0}, and w{sub a} by more than 70%, 20%, and 60%, respectively, for the w{sub 0}w{sub a}CDM model.

  13. AN OVERVIEW OF TOOL FOR RESPONSE ACTION COST ESTIMATING (TRACE)

    SciTech Connect

    FERRIES SR; KLINK KL; OSTAPKOWICZ B

    2012-01-30

    Tools and techniques that provide improved performance and reduced costs are important to government programs, particularly in current times. An opportunity for improvement was identified for preparation of cost estimates used to support the evaluation of response action alternatives. As a result, CH2M HILL Plateau Remediation Company has developed Tool for Response Action Cost Estimating (TRACE). TRACE is a multi-page Microsoft Excel{reg_sign} workbook developed to introduce efficiencies into the timely and consistent production of cost estimates for response action alternatives. This tool combines costs derived from extensive site-specific runs of commercially available remediation cost models with site-specific and estimator-researched and derived costs, providing the best estimating sources available. TRACE also provides for common quantity and key parameter links across multiple alternatives, maximizing ease of updating estimates and performing sensitivity analyses, and ensuring consistency.

  14. Matrix Methods for Estimating the Coherence Functions from Estimates of the Cross-Spectral Density Matrix

    DOE PAGES [OSTI]

    Smallwood, D. O.

    1996-01-01

    It is shown that the usual method for estimating the coherence functions (ordinary, partial, and multiple) for a general multiple-input! multiple-output problem can be expressed as a modified form of Cholesky decomposition of the cross-spectral density matrix of the input and output records. The results can be equivalently obtained using singular value decomposition (SVD) of the cross-spectral density matrix. Using SVD suggests a new form of fractional coherence. The formulation as a SVD problem also suggests a way to order the inputs when a natural physical order of the inputs is absent.

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

    SciTech Connect

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

    2013-12-31

    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

  16. ARM - Evaluation Product - Radiatively Important Parameters Best Estimate

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    (RIPBE) ProductsRadiatively Important Parameters Best Estimate (RIPBE) ARM Data Discovery Browse Data Documentation Use the Data File Inventory tool to view data availability at the file level. Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Evaluation Product : Radiatively Important Parameters Best Estimate (RIPBE) The Radiatively Important Parameters Best Estimate (RIPBE) VAP combines multiple input datastreams, each with their own temporal

  17. Estimating Methods for Determining End-Use Water Consumption | Department

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    of Energy Facilities » Water Efficiency » Estimating Methods for Determining End-Use Water Consumption Estimating Methods for Determining End-Use Water Consumption The Federal Building Metering Guidance specifies buildings with water using processes and whole building water consumption that exceeds 1,000 gallons per day must have a water meter installed. Below are methods for estimating daily water use for typical end-uses that drive building-level, end-use water consumption. Plumbing

  18. Estimating the Benefits and Costs of Distributed Energy Technologies

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Workshop - Agenda and Summary | Department of Energy DOE Grid Tech Team » Activities/Outreach » GTT Activities » Estimating the Benefits and Costs of Distributed Energy Technologies Workshop - Agenda and Summary Estimating the Benefits and Costs of Distributed Energy Technologies Workshop - Agenda and Summary On September 30 and October 1, 2014, the Department of Energy hosted a 2-day workshop on "Estimating the Benefits and Costs of Distributed Energy Technologies." The purpose

  19. Hydrogen Production Cost Estimate Using Biomass Gasification: Independent

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Review | Department of Energy Cost Estimate Using Biomass Gasification: Independent Review Hydrogen Production Cost Estimate Using Biomass Gasification: Independent Review This independent review is the conclusion arrived at from data collection, document reviews, interviews and deliberation from December 2010 through April 2011 and the technical potential of Hydrogen Production Cost Estimate Using Biomass Gasification The Panel reviewed the current H2A case (Version 2.12, Case 01D) for

  20. Independent Cost Review (ICR) and Independent Cost Estimate (ICE) Standard

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Operating Procedures, Revision 2 | Department of Energy Independent Cost Review (ICR) and Independent Cost Estimate (ICE) Standard Operating Procedures, Revision 2 Independent Cost Review (ICR) and Independent Cost Estimate (ICE) Standard Operating Procedures, Revision 2 This Standard Operating Procedures (SOP) provides guidance for Department of Energy (DOE) Project Management Oversight and Assessment (PM) staff and contractors performing either an Independent Cost Estimate (ICE) or an

  1. Guidelines for Estimating Unmetered Landscaping Water Use | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy Landscaping Water Use Guidelines for Estimating Unmetered Landscaping Water Use Document describes the step-by-step instructions to estimate landscaping water using two alternative approaches: the evapotranspiration method and the irrigation audit method. This report presents annual irrigation factors for 36 cities across the United States that represent the gallons of irrigation required per square foot for distinct landscape types. Download the Guidelines for Estimating Unmetered

  2. Nebraska Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Nebraska Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) No Data Available For This Series - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Nonassociated Natural Gas Estimated

  3. The ARM Best Estimate 2-dimensional Gridded Surface (Dataset) | Data

    Office of Scientific and Technical Information (OSTI)

    Explorer 2-dimensional Gridded Surface Title: The ARM Best Estimate 2-dimensional Gridded Surface The ARM Best Estimate 2-dimensional Gridded Surface (ARMBE2DGRID) data set merges together key surface measurements at the Southern Great Plains (SGP) sites and interpolates the data to a regular 2D grid to facilitate data application. Data from the original site locations can be found in the ARM Best Estimate Station-based Surface (ARMBESTNS) data set. Authors: Xie,Shaocheng ; Qi, Tang

  4. Battery Calendar Life Estimator Manual Modeling and Simulation

    SciTech Connect

    Jon P. Christophersen; Ira Bloom; Ed Thomas; Vince Battaglia

    2012-10-01

    The Battery Life Estimator (BLE) Manual has been prepared to assist developers in their efforts to estimate the calendar life of advanced batteries for automotive applications. Testing requirements and procedures are defined by the various manuals previously published under the United States Advanced Battery Consortium (USABC). The purpose of this manual is to describe and standardize a method for estimating calendar life based on statistical models and degradation data acquired from typical USABC battery testing.

  5. Using Photogrammetry to Estimate Tank Waste Volumes from Video

    SciTech Connect

    Field, Jim G.

    2013-03-27

    Washington River Protection Solutions (WRPS) contracted with HiLine Engineering & Fabrication, Inc. to assess the accuracy of photogrammetry tools as compared to video Camera/CAD Modeling System (CCMS) estimates. This test report documents the results of using photogrammetry to estimate the volume of waste in tank 241-C-I04 from post-retrieval videos and results using photogrammetry to estimate the volume of waste piles in the CCMS test video.

  6. Battery Life Estimator Manual Linear Modeling and Simulation

    SciTech Connect

    Jon P. Christophersen; Ira Bloom; Ed Thomas; Vince Battaglia

    2009-08-01

    The Battery Life Estimator (BLE) Manual has been prepared to assist developers in their efforts to estimate the calendar life of advanced batteries for automotive applications. Testing requirements and procedures are defined by the various manuals previously published under the United States Advanced Battery Consortium (USABC). The purpose of this manual is to describe and standardize a method for estimating calendar life based on statistical models and degradation data acquired from typical USABC battery testing.

  7. Methodology for EIA Weekly Underground Natural Gas Storage Estimates

    Weekly Natural Gas Storage Report

    Methodology for EIA Weekly Underground Natural Gas Storage Estimates Latest Update: November 16, 2015 This report consists of the following sections: Survey and Survey Processing - a description of the survey and an overview of the program Sampling - a description of the selection process used to identify companies in the survey Estimation - how the regional estimates are prepared from the collected data Computing the Five-year Averages, Maxima, Minima, and Year-Ago Values for the Weekly Natural

  8. NREL Raises Rooftop Photovoltaic Technical Potential Estimate - News

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Releases | NREL NREL Raises Rooftop Photovoltaic Technical Potential Estimate New analysis nearly doubles previous estimates and shows U.S. building rooftops could generate close to 40 percent of national electricity sales March 24, 2016 Analysts at the Energy Department's National Renewable Energy Laboratory (NREL) have used detailed light detection and ranging (LiDAR) data for 128 cities nationwide, along with improved data analysis methods and simulation tools, to update its estimate of

  9. Radiological Source Term Estimates for the February 14, 2014...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    This document corresponds to Appendix D: Modeling Integrated Summary Report of the Technical Assessment Team Report. Radiological Source Term Estimates for the February 14, 2014 ...

  10. Retrofit Energy Savings Estimation Model | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Desktop Application Website: btech.lbl.govtoolsresemresem.htm Cost: Free Language: English References: Retrofit Energy Savings Estimation Model1 Logo: Retrofit...

  11. Reconciling estimates of the contemporary North American carbon...

    Office of Scientific and Technical Information (OSTI)

    of carbon stocks and flux, and the uncertainties inherent in each approach. The alternative approaches to estimating continental scale carbon fluxes that we explored here can...

  12. RADIATION DOSE ESTIMATES TO ADULTS AND CHILDREN FROM VARIOUS

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    RADIATION DOSE ESTIMATES TO ADULTS AND CHILDREN FROM VARIOUS RADIOPHARMACEUTICALS Latest Revision Date: 43096 Radiation Internal Dose Information Center Oak Ridge Institute for ...

  13. On parameterization of the inverse problem for estimating aquifer...

    Office of Scientific and Technical Information (OSTI)

    Title: On parameterization of the inverse problem for estimating aquifer properties using tracer data Authors: Kowalsky, M. B. ; Finsterle, S. ; Commer, M. ; Williams, K. H. ; ...

  14. Quality Guidline for Cost Estimation Methodology for NETL Assessments...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    and Benefits 2 Power Plant Cost Estimation Methodology Quality Guidelines for Energy System Studies April 2011 Disclaimer This report was prepared as an account of work...

  15. NREL Report Estimates Market Potential of Shared Solar and Discusses...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Report Estimates Market Potential of Shared Solar and Discusses Relevant Securities Regulations April 27, 2015 Analysis from the Energy Department's National Renewable Energy ...

  16. Wind Resource Estimation and Mapping at the National Renewable...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Resource Estimation and Mapping at the National Renewable Energy Laboratory April 1999 * NRELCP-500-26245 M. Schwartz Presented at the ASES Solar '99 Conference Portland, Maine...

  17. Natural Ventilation in California Offices: Estimated Health Effects...

    Office of Scientific and Technical Information (OSTI)

    Effects and Economic Consequences Citation Details In-Document Search Title: Natural Ventilation in California Offices: Estimated Health Effects and Economic Consequences ...

  18. Issues and Methods for Estimating the Percentage Share of Ethanol...

    Annual Energy Outlook

    Energy Information Administration 1 Issues and Methods for Estimating the Share of Ethanol in the Motor Gasoline Supply U.S. Energy Information Administration October 6, 2011...

  19. A simplified procedure for estimation of mixture permeances from...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    simplified procedure for estimation of mixture permeances from unary permeation data Previous Next List Rajamani Krishna, Jasper M. van Baten, J. Membr. Sci., 367, 204-210 (2011)...

  20. Energy savings estimates and cost benefit calculations for high...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Energy savings estimates and cost benefit calculations for high performance relocatable classrooms Citation Details In-Document Search Title: Energy savings ...

  1. SMART BRIDGE: A Tool for Estimating the Military Load

    Office of Scientific and Technical Information (OSTI)

    D. SMART BRIDGE: A Tool for Estimating the Military Load Classification of Bridges Charles ... consideration in planning and executing military deployments is determining the routes ...

  2. Estimating global and North American methane emissions with high...

    Office of Scientific and Technical Information (OSTI)

    methane emissions with high spatial resolution using GOSAT satellite data Citation Details In-Document Search Title: Estimating global and North American methane emissions ...

  3. A Simple, Fast Method of Estimating Fractured Reservoir Geometry...

    OpenEI (Open Energy Information) [EERE & EIA]

    Fractured Reservoir Geometry from Tracer Tests Abstract A simple method of estimating flow geometry and pore geometry from conservative tracer tests in single phase geothermal...

  4. Uncertainty Estimates for SIRS, SKYRAD, & GNDRAD Data and Reprocessing...

    Office of Scientific and Technical Information (OSTI)

    Title: Uncertainty Estimates for SIRS, SKYRAD, & GNDRAD Data and Reprocessing the Pyrgeometer Data (Presentation) The National Renewable Energy Laboratory (NREL) and the ...

  5. Estimating atmospheric parameters and reducing noise for multispectral imaging

    DOEpatents

    Conger, James Lynn

    2014-02-25

    A method and system for estimating atmospheric radiance and transmittance. An atmospheric estimation system is divided into a first phase and a second phase. The first phase inputs an observed multispectral image and an initial estimate of the atmospheric radiance and transmittance for each spectral band and calculates the atmospheric radiance and transmittance for each spectral band, which can be used to generate a "corrected" multispectral image that is an estimate of the surface multispectral image. The second phase inputs the observed multispectral image and the surface multispectral image that was generated by the first phase and removes noise from the surface multispectral image by smoothing out change in average deviations of temperatures.

  6. Derivative-free optimization for parameter estimation in computational...

    Office of Scientific and Technical Information (OSTI)

    Journal Article: Derivative-free optimization for parameter estimation in computational nuclear physics Citation Details ... RADIATION PHYSICS; 97 MATHEMATICS, COMPUTING, AND ...

  7. Geothermal reservoir temperatures estimated from the oxygen isotope...

    OpenEI (Open Energy Information) [EERE & EIA]

    applied to thermal systems of Yellowstone Park, Wyoming, Long Valley, California, and Raft River, Idaho to estimate deep reservoir temperatures of 360, 240, and 142C,...

  8. Output-Based Error Estimation and Adaptation for Uncertainty...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Output-Based Error Estimation and Adaptation for Uncertainty Quantification Isaac M. Asher and Krzysztof J. Fidkowski University of Michigan US National Congress on Computational...

  9. Derivative-free optimization for parameter estimation in computational...

    Office of Scientific and Technical Information (OSTI)

    nuclear physics Citation Details In-Document Search Title: Derivative-free optimization for parameter estimation in computational nuclear physics Authors: Wild, S ; ...

  10. Estimating the Opportunity Cost of REDD+: A Training Manual ...

    OpenEI (Open Energy Information) [EERE & EIA]

    the Opportunity Cost of REDD+: A Training Manual Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Estimating the Opportunity Cost of REDD+: A Training Manual Agency...

  11. Cost Estimating Guide - DOE Directives, Delegations, and Requirements

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    1, Cost Estimating Guide by Ruben Sanchez Functional areas: Budget and Financial Management, Financial Management This Guide provides uniform guidance and best practices that...

  12. Estimating the system price of redox flow batteries for grid...

    Office of Scientific and Technical Information (OSTI)

    Estimating the system price of redox flow batteries for grid storage Citation Details ... Subject: energy storage; flow battery; grid storage; lithium-ion battery; manufacturing ...

  13. Estimation and modeling of coal pore accessibility using small...

    Office of Scientific and Technical Information (OSTI)

    Title: Estimation and modeling of coal pore accessibility using small angle neutron scattering Authors: Zhang, Rui ; Liu, Shimin ; Bahadur, Jitendra ; Elsworth, Derek ; ...

  14. Adaptive Wavenumber Estimation for Mode Tracking in a Shallow...

    Office of Scientific and Technical Information (OSTI)

    Tracking in a Shallow Ocean Environment Citation Details In-Document Search Title: Adaptive Wavenumber Estimation for Mode Tracking in a Shallow Ocean Environment You are ...

  15. Cost and Schedule Estimate and Analysis | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Cost and Schedule Estimate and Analysis Cost and Schedule Estimate and Analysis October 31, 2016 9:00AM EDT to November 4, 2016 5:00PM EDT Cost and Schedule Estimate and Analysis; Classroom Training; 5 days/40 CLPs; Lexington, KY; October 31 - November 4, 2016 Level 2 Core Course 5 days / 40 CLPs PMCDP is offering instructor-led deliveries of the 5-day course, Cost and Schedule Estimate and Analysis, October 31 - November 4, 2016, Lexington, KY. This course provides participants with a

  16. Estimating Bacteria Emissions from Inversion of Atmospheric Transport...

    Office of Scientific and Technical Information (OSTI)

    Bacteria Emissions from Inversion of Atmospheric Transport: Sensitivity to Modelled Particle Characteristics Citation Details In-Document Search Title: Estimating Bacteria ...

  17. Estimating the Benefits and Costs of Distributed Energy Technologies...

    Energy.gov [DOE] (indexed site)

    PDF icon Presentation - Robert Jeffers, Sandia PDF icon Presentation - Carl Imhoff, PNNL More Documents & Publications Estimating the Benefits and Costs of Distributed Energy ...

  18. Estimating the Benefits and Costs of Distributed Energy Technologies...

    Office of Environmental Management (EM)

    Benefits and Costs of Distributed Energy Technologies Workshop - Agenda and Summary Estimating the Benefits and Costs of Distributed Energy Technologies Workshop - Agenda and ...

  19. Estimating Appliance and Home Electronic Energy Use | Department...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    and electronic energy use calculator allows you to estimate your annual energy use and cost to operate specific products. The wattage values provided are samples only; actual...

  20. Fast Reactor Fuel Cycle Cost Estimates for Advanced Fuel Cycle...

    Office of Scientific and Technical Information (OSTI)

    Title: Fast Reactor Fuel Cycle Cost Estimates for Advanced Fuel Cycle Studies Authors: Harrison, Thomas J 1 + Show Author Affiliations ORNL ORNL Publication Date: 2013-01-01 ...

  1. Estimated Maintenance Cost Savings from a Geothermal Heat Pump...

    Office of Scientific and Technical Information (OSTI)

    Contract at Fort Polk, LA Citation Details In-Document Search Title: Estimated Maintenance Cost Savings from a Geothermal Heat Pump Energy Savings Performance Contract at ...

  2. Source term estimation during incident response to severe nuclear...

    Office of Scientific and Technical Information (OSTI)

    response to severe nuclear power plant accidents Citation Details In-Document Search Title: Source term estimation during incident response to severe nuclear power plant ...

  3. Estimation of the relationship between remotely sensed anthropogenic...

    Office of Scientific and Technical Information (OSTI)

    of Indianapolis, Indiana, USA. Anthropogenic heat discharge was estimated based on a remote sensing-based surface energy balance model, which was parameterized using land ...

  4. A Protocol for Estimating and Mapping Global EGS Potential |...

    OpenEI (Open Energy Information) [EERE & EIA]

    with public Reporting Codes * Present results using common visualization and data architecture The goal of the Protocol is the production of regional estimates and maps of EGS...

  5. New DOE Modeling Tool Estimates Economic Benefits of Offshore...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Modeling Tool Estimates Economic Benefits of Offshore Wind Plants New DOE Modeling Tool ... of Energy (DOE) recently released a new version of the Jobs and Economic ...

  6. Estimation and Control of Diesel Engine Processes Utilizing Variable...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Estimation and Control of Diesel Engine Processes Utilizing Variable Intake Valve Actuation Air handling system model for multi-cylinder variable geometry turbocharged diesel ...

  7. Estimating the System Price of Redox Flow Batteries for Grid...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Estimating the System Price of Redox Flow Batteries for Grid Storage VRFB system price ... Significance and Impact Redox flow batteries have potential advantages to meet the ...

  8. Estimation and Uncertainty Analysis of Impacts of Future Heat...

    Office of Scientific and Technical Information (OSTI)

    However, the estimation of excess mortality attributable to future heat waves is subject to large uncertainties, which have not been examined under the latest greenhouse gas ...

  9. Autocorrelation Function Statistics and Implication to Decay Ratio Estimation

    SciTech Connect

    March-Leuba, Jose A.

    2016-01-01

    This document summarizes the results of a series of computer simulations to attempt to identify the statistics of the autocorrelation function, and implications for decay ratio estimation.

  10. Energy Savings Estimates of Light Emitting Diodes in Niche Lighting...

    Energy.gov [DOE] (indexed site)

    Estimates of Light Emitting Diodes in Niche Lighting Applications Prepared for: Building Technologies Program Office of Energy Efficiency and Renewable Energy U.S. Department of ...

  11. Estimating Costs and Efficiency of Storage, Demand, and Heat...

    Energy Saver

    Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters A water heater's energy ...

  12. Mass Production Cost Estimation of Direct Hydrogen PEM Fuel Cell...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    of Direct Hydrogen PEM Fuel Cell Systems for Transportation Applications: 2012 Update Mass Production Cost Estimation of Direct Hydrogen PEM Fuel Cell Systems for Transportation ...

  13. Direct Hydrogen PEMFC Manufacturing Cost Estimation for Automotive...

    Energy.gov [DOE] (indexed site)

    and Fuel Cells Program Record 14014: Fuel Cell System Cost - 2014 Mass Production Cost Estimation of Direct H2 PEM Fuel Cell Systems for Transportation Applications: 2013 Update

  14. ARM - PI Product - Climate Modeling Best Estimate (CMBE)

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    govDataPI Data ProductsClimate Modeling Best Estimate (CMBE) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Climate Modeling Best Estimate (CMBE) The ARM Climate Modeling Best Estimate (CMBE) product is now available as ARM Best Estimate products (ARMBE). Please refer to the Data Directory link below to access ARMBE data. Data Details Contact Shaocheng Xie Lawrence Livermore National Laboratory

  15. Constrained Shortest Path Estimation on the D-Wave 2X: Accelerating Ionospheric Parameter Estimation Through Quantum Annealing

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    2/9/16 | 1 Operated by Los Alamos National Security, LLC for the U.S. Department of Energy's NNSA Constrained Shortest Path Estimation on the D-Wave 2X: Accelerating Ionospheric Parameter Estimation Through Quantum Annealing Zachary Baker CCS-7 Applied Computer Science Los Alamos National Laboratory 2/9/16 | 2 Problem: in heavy RF background noise, find wide band events, then estimate dispersion * Large transmitters can overwhelm the wideband events * Convert to frequency/time view * Shape of

  16. Performance of internal covariance estimators for cosmic shear correlation functions

    DOE PAGES [OSTI]

    Friedrich, O.; Seitz, S.; Eifler, T. F.; Gruen, D.

    2015-12-31

    Data re-sampling methods such as the delete-one jackknife are a common tool for estimating the covariance of large scale structure probes. In this paper we investigate the concepts of internal covariance estimation in the context of cosmic shear two-point statistics. We demonstrate how to use log-normal simulations of the convergence field and the corresponding shear field to carry out realistic tests of internal covariance estimators and find that most estimators such as jackknife or sub-sample covariance can reach a satisfactory compromise between bias and variance of the estimated covariance. In a forecast for the complete, 5-year DES survey we show that internally estimated covariance matrices can provide a large fraction of the true uncertainties on cosmological parameters in a 2D cosmic shear analysis. The volume inside contours of constant likelihood in themore » $$\\Omega_m$$-$$\\sigma_8$$ plane as measured with internally estimated covariance matrices is on average $$\\gtrsim 85\\%$$ of the volume derived from the true covariance matrix. The uncertainty on the parameter combination $$\\Sigma_8 \\sim \\sigma_8 \\Omega_m^{0.5}$$ derived from internally estimated covariances is $$\\sim 90\\%$$ of the true uncertainty.« less

  17. Performance of internal covariance estimators for cosmic shear correlation functions

    SciTech Connect

    Friedrich, O.; Seitz, S.; Eifler, T. F.; Gruen, D.

    2015-12-31

    Data re-sampling methods such as the delete-one jackknife are a common tool for estimating the covariance of large scale structure probes. In this paper we investigate the concepts of internal covariance estimation in the context of cosmic shear two-point statistics. We demonstrate how to use log-normal simulations of the convergence field and the corresponding shear field to carry out realistic tests of internal covariance estimators and find that most estimators such as jackknife or sub-sample covariance can reach a satisfactory compromise between bias and variance of the estimated covariance. In a forecast for the complete, 5-year DES survey we show that internally estimated covariance matrices can provide a large fraction of the true uncertainties on cosmological parameters in a 2D cosmic shear analysis. The volume inside contours of constant likelihood in the $\\Omega_m$-$\\sigma_8$ plane as measured with internally estimated covariance matrices is on average $\\gtrsim 85\\%$ of the volume derived from the true covariance matrix. The uncertainty on the parameter combination $\\Sigma_8 \\sim \\sigma_8 \\Omega_m^{0.5}$ derived from internally estimated covariances is $\\sim 90\\%$ of the true uncertainty.

  18. Cost estimating issues in the Russian integrated system planning context

    SciTech Connect

    Allentuck, J.

    1996-03-01

    An important factor in the credibility of an optimal capacity expansion plan is the accuracy of cost estimates given the uncertainty of future economic conditions. This paper examines the problems associated with estimating investment and operating costs in the Russian nuclear power context over the period 1994 to 2010.

  19. The ARM Best Estimate 2-dimensional Gridded Surface

    SciTech Connect

    Xie,Shaocheng; Qi, Tang

    2015-06-15

    The ARM Best Estimate 2-dimensional Gridded Surface (ARMBE2DGRID) data set merges together key surface measurements at the Southern Great Plains (SGP) sites and interpolates the data to a regular 2D grid to facilitate data application. Data from the original site locations can be found in the ARM Best Estimate Station-based Surface (ARMBESTNS) data set.

  20. Sensitivity of health risk estimates to air quality adjustment procedure

    SciTech Connect

    Whitfield, R.G.

    1997-06-30

    This letter is a summary of risk results associated with exposure estimates using two-parameter Weibull and quadratic air quality adjustment procedures (AQAPs). New exposure estimates were developed for children and child-occurrences, six urban areas, and five alternative air quality scenarios. In all cases, the Weibull and quadratic results are compared to previous results, which are based on a proportional AQAP.

  1. Concurrent signal combining and channel estimation in digital communications

    SciTech Connect

    Ormesher, Richard C.; Mason, John J.

    2011-08-30

    In the reception of digital information transmitted on a communication channel, a characteristic exhibited by the communication channel during transmission of the digital information is estimated based on a communication signal that represents the digital information and has been received via the communication channel. Concurrently with the estimating, the communication signal is used to decide what digital information was transmitted.

  2. The ARM Best Estimate 2-dimensional Gridded Surface

    DOE Data Explorer

    Xie,Shaocheng; Qi, Tang

    The ARM Best Estimate 2-dimensional Gridded Surface (ARMBE2DGRID) data set merges together key surface measurements at the Southern Great Plains (SGP) sites and interpolates the data to a regular 2D grid to facilitate data application. Data from the original site locations can be found in the ARM Best Estimate Station-based Surface (ARMBESTNS) data set.

  3. Cost estimate guidelines for advanced nuclear power technologies

    SciTech Connect

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

    1990-03-01

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

  4. How to Estimate the Value of Service Reliability Improvements

    SciTech Connect

    Sullivan, Michael J.; Mercurio, Matthew G.; Schellenberg, Josh A.; Eto, Joseph H.

    2010-06-08

    A robust methodology for estimating the value of service reliability improvements is presented. Although econometric models for estimating value of service (interruption costs) have been established and widely accepted, analysts often resort to applying relatively crude interruption cost estimation techniques in assessing the economic impacts of transmission and distribution investments. This paper first shows how the use of these techniques can substantially impact the estimated value of service improvements. A simple yet robust methodology that does not rely heavily on simplifying assumptions is presented. When a smart grid investment is proposed, reliability improvement is one of the most frequently cited benefits. Using the best methodology for estimating the value of this benefit is imperative. By providing directions on how to implement this methodology, this paper sends a practical, usable message to the industry.

  5. Kalman filter data assimilation: Targeting observations and parameter estimation

    SciTech Connect

    Bellsky, Thomas Kostelich, Eric J.; Mahalov, Alex

    2014-06-15

    This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.

  6. Improving Estimation Accuracy of Aggregate Queries on Data Cubes

    SciTech Connect

    Pourabbas, Elaheh; Shoshani, Arie

    2008-08-15

    In this paper, we investigate the problem of estimation of a target database from summary databases derived from a base data cube. We show that such estimates can be derived by choosing a primary database which uses a proxy database to estimate the results. This technique is common in statistics, but an important issue we are addressing is the accuracy of these estimates. Specifically, given multiple primary and multiple proxy databases, that share the same summary measure, the problem is how to select the primary and proxy databases that will generate the most accurate target database estimation possible. We propose an algorithmic approach for determining the steps to select or compute the source databases from multiple summary databases, which makes use of the principles of information entropy. We show that the source databases with the largest number of cells in common provide the more accurate estimates. We prove that this is consistent with maximizing the entropy. We provide some experimental results on the accuracy of the target database estimation in order to verify our results.

  7. Estimation of economic parameters of U.S. hydropower resources

    SciTech Connect

    Hall, Douglas G.; Hunt, Richard T.; Reeves, Kelly S.; Carroll, Greg R.

    2003-06-01

    Tools for estimating the cost of developing and operating and maintaining hydropower resources in the form of regression curves were developed based on historical plant data. Development costs that were addressed included: licensing, construction, and five types of environmental mitigation. It was found that the data for each type of cost correlated well with plant capacity. A tool for estimating the annual and monthly electric generation of hydropower resources was also developed. Additional tools were developed to estimate the cost of upgrading a turbine or a generator. The development and operation and maintenance cost estimating tools, and the generation estimating tool were applied to 2,155 U.S. hydropower sites representing a total potential capacity of 43,036 MW. The sites included totally undeveloped sites, dams without a hydroelectric plant, and hydroelectric plants that could be expanded to achieve greater capacity. Site characteristics and estimated costs and generation for each site were assembled in a database in Excel format that is also included within the EERE Library under the title, “Estimation of Economic Parameters of U.S. Hydropower Resources - INL Hydropower Resource Economics Database.”

  8. Estimating pixel variances in the scenes of staring sensors

    DOEpatents

    Simonson, Katherine M. (Cedar Crest, NM); Ma, Tian J. (Albuquerque, NM)

    2012-01-24

    A technique for detecting changes in a scene perceived by a staring sensor is disclosed. The technique includes acquiring a reference image frame and a current image frame of a scene with the staring sensor. A raw difference frame is generated based upon differences between the reference image frame and the current image frame. Pixel error estimates are generated for each pixel in the raw difference frame based at least in part upon spatial error estimates related to spatial intensity gradients in the scene. The pixel error estimates are used to mitigate effects of camera jitter in the scene between the current image frame and the reference image frame.

  9. Monitored Geologic Repository Life Cycle Cost Estimate Assumptions Document

    SciTech Connect

    R. Sweeney

    2000-03-08

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

  10. MONITORED GEOLOGIC REPOSITORY LIFE CYCLE COST ESTIMATE ASSUMPTIONS DOCUMENT

    SciTech Connect

    R.E. Sweeney

    2001-02-08

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

  11. Model Year 2011 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect

    2010-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles.

  12. Model Year 2012 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect

    2011-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles.

  13. Model Year 2013 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect

    2012-12-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles.

  14. Estimates of particulate mass in multi-canister overpacks

    SciTech Connect

    SLOUGHTER, J.P.

    1999-02-25

    High, best estimate, and low values are developed for particulate inventories within MCO baskets that have been loaded with freshly cleaned fuel assemblies and scrap. These per-basket estimates are then applied to all anticipated MCO payload configurations to identify which configurations are bounding for each type of particulate. Finally the resulting bounding and nominal values for residual particulates are combined with corresponding values [from other documents] for particulate that may be generated by corrosion of exposed uranium after the fuel has been cleaned. The resulting rounded nominal estimate for a typical MCO after 40 years of storage is 8 kg. The estimate for a bounding total particulate case MCO is that it may contain up to 64 kg of particulate after 40 years of storage.

  15. Neptunium estimation in dissolver and high-level-waste solutions

    SciTech Connect

    Pathak, P.N.; Prabhu, D.R.; Kanekar, A.S.; Manchanda, V.K.

    2008-07-01

    This papers deals with the optimization of the experimental conditions for the estimation of {sup 237}Np in spent-fuel dissolver/high-level waste solutions using thenoyltrifluoroacetone as the extractant. (authors)

  16. ARM Climate Modeling Best Estimate From Manus Island, PNG (ARMBE...

    Office of Scientific and Technical Information (OSTI)

    From Manus Island, PNG (ARMBE-ATM TWPC1) Title: ARM Climate Modeling Best Estimate From Manus Island, PNG (ARMBE-ATM TWPC1) The ARM CMBE-ATM Xie, McCoy, Klein et al. data file ...

  17. Chapter 1: Estimating prospective benefits of EERE's portfolio

    SciTech Connect

    None, None

    2009-01-18

    Document summarizes the results of the benefits analysis of EERE’s programs, as described in the FY 2008 Budget Request. EERE estimates benefits for its overall portfolio and nine Research, Development, Demonstration, and Deployment (RD3) programs.

  18. ARM - Evaluation Product - Climate Modeling Best Estimate (CMBE...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    ProductsClimate Modeling Best Estimate (CMBE) Documentation Use the Data File Inventory tool to view data availability at the file level. Comments? We would love to hear from you...

  19. Preliminary relative permeability estimates of methanehydrate-bearing sand

    SciTech Connect

    Seol, Yongkoo; Kneafsey, Timothy J.; Tomutsa, Liviu; Moridis,George J.

    2006-05-08

    The relative permeability to fluids in hydrate-bearingsediments is an important parameter for predicting natural gas productionfrom gas hydrate reservoirs. We estimated the relative permeabilityparameters (van Genuchten alpha and m) in a hydrate-bearing sand by meansof inverse modeling, which involved matching water saturation predictionswith observations from a controlled waterflood experiment. We used x-raycomputed tomography (CT) scanning to determine both the porosity and thehydrate and aqueous phase saturation distributions in the samples. X-rayCT images showed that hydrate and aqueous phase saturations arenon-uniform, and that water flow focuses in regions of lower hydratesaturation. The relative permeability parameters were estimated at twolocations in each sample. Differences between the estimated parametersets at the two locations were attributed to heterogeneity in the hydratesaturation. Better estimates of the relative permeability parametersrequire further refinement of the experimental design, and betterdescription of heterogeneity in the numerical inversions.

  20. Biomass Power Generation Market Capacity is Estimated to Reach...

    OpenEI (Open Energy Information) [EERE & EIA]

    Biomass Power Generation Market Capacity is Estimated to Reach 122,331.6 MW by 2022 Home > Groups > Renewable Energy RFPs Wayne31jan's picture Submitted by Wayne31jan(150)...

  1. Temperature estimates from zircaloy oxidation kinetics and microstructures. [PWR

    SciTech Connect

    Olsen, C.S.

    1982-10-01

    This report reviews state-of-the-art capability to determine peak zircaloy fuel rod cladding temperatures following an abnormal temperature excursion in a nuclear reactor, based on postirradiation metallographic analysis of zircaloy microstructural and oxidation characteristics. Results of a comprehensive literature search are presented to evaluate the suitability of available zircaloy microstructural and oxidation data for estimating anticipated reactor fuel rod cladding temperatures. Additional oxidation experiments were conducted to evaluate low-temperature zircaloy oxidation characteristics for postirradiation estimation of cladding temperature by metallographic examination. Results of these experiments were used to calculate peak cladding temperatures of electrical heater rods and nuclear fuel rods that had been subjected to reactor temperature transients. Comparison of the calculated and measured peak cladding temperatures for these rods indicates that oxidation kinetics is a viable technique for estimating peak cladding temperatures over a broad temperature range. However, further improvement in zircaloy microstructure technology is necessary for precise estimation of peak cladding temperatures by microstructural examination.

  2. Methodology for Estimating Ingestion Dose for Emergency Response at SRS

    SciTech Connect

    Simpkins, A.A.

    2002-04-22

    At the Savannah River Site (SRS), emergency response models estimate dose for inhalation and ground shine pathways. A methodology has been developed to incorporate ingestion doses into the emergency response models. The methodology follows a two-phase approach. The first phase estimates site-specific derived response levels (DRLs) which can be compared with predicted ground-level concentrations to determine if intervention is needed to protect the public. This phase uses accepted methods with little deviation from recommended guidance. The second phase uses site-specific data to estimate a 'best estimate' dose to offsite individuals from ingestion of foodstuffs. While this method deviates from recommended guidance, it is technically defensibly and more realistic. As guidance is updated, these methods also will need to be updated.

  3. Estimates of U.S. Biomass Energy Consumption 1992

    Reports and Publications

    1994-01-01

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass derived primary energy used by the U.S. economy. It presents estimates of 1991 and 1992 consumption.

  4. Estimating Appliance and Home Electronic Energy Use | Department...

    Energy.gov [DOE] (indexed site)

    Estimate the energy consumption and cost to operate an appliance when making a purchase. Investing in an energy-efficient product may save you money in the long run. | Photo...

  5. Table 4. Estimation Results for PAD District Regions

    Energy Information Administration (EIA) (indexed site)

    Estimation Results for PAD District Regions Dependent Variable: D(RETPAD1) Dependent Variable: D(RETPAD2) Dependent Variable: D(RETPAD3) Dependent Variable: D(RETPAD4) Dependent...

  6. Estimates of Particulate Mass in Multi Canister Overpacks (MCO)

    SciTech Connect

    SLOUGHTER, J.P.

    2000-02-16

    High, best estimate, and low values are developed for particulate inventories within MCO baskets that have been loaded with freshly cleaned fuel assemblies and scrap. These per-basket estimates are then applied to all anticipated MCO payload configurations to identify which configurations are bounding for each type of particulate. Finally the resulting bounding and nominal values for residual particulates are combined with corresponding values [from other documents] for particulates that may be generated by corrosion of exposed uranium after the fuel has been cleaned. The resulting rounded nominal estimate for a typical MCO after 40 years of storage is 8 kg. The estimate for a bounding total particulate case MCO is that it may contain up to 64 kg of particulate after 40 years of storage.

  7. Appendix C: Biomass Program inputs for FY 2008 benefits estimates

    SciTech Connect

    None, None

    2009-01-18

    Document summarizes the results of the benefits analysis of EERE’s programs, as described in the FY 2008 Budget Request. EERE estimates benefits for its overall portfolio and nine Research, Development, Demonstration, and Deployment (RD3) programs.

  8. U.S. Uranium Reserves Estimates - Energy Information Administration

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    all Nuclear Reports U.S. Uranium Reserves Estimates Data for: 2008 | Release Date: July 2010 | Next Release Date: Discontinued The U.S. Energy Information Administration (EIA) has...

  9. Performance Measure Unit Lifecycle Total Estimate Pre-2016 Lifecycle...

    Office of Environmental Management (EM)

    Measure Unit Lifecycle Total Estimate Pre-2016 Lifecycle Values 2016 Target 2017 Target Pu packaged for long-term disposition Number of Containers 5,089 5,089 5,089 5,089 eU ...

  10. Preliminary relative permeability estimates of methanehydrate-bearing sand

    SciTech Connect

    Seol, Yongkoo; Kneafsey, Timothy J.; Tomutsa, Liviu; Moridis,George J.

    2006-05-08

    The relative permeability to fluids in hydrate-bearing sediments is an important parameter for predicting natural gas production from gas hydrate reservoirs. We estimated the relative permeability parameters (van Genuchten alpha and m) in a hydrate-bearing sand by means of inverse modeling, which involved matching water saturation predictions with observations from a controlled waterflood experiment. We used x-ray computed tomography (CT) scanning to determine both the porosity and the hydrate and aqueous phase saturation distributions in the samples. X-ray CT images showed that hydrate and aqueous phase saturations are non-uniform, and that water flow focuses in regions of lower hydrate saturation. The relative permeability parameters were estimated at two locations in each sample. Differences between the estimated parameter sets at the two locations were attributed to heterogeneity in the hydrate saturation. Better estimates of the relative permeability parameters require further refinement of the experimental design, and better description of heterogeneity in the numerical inversions.

  11. Budget estimates, fiscal years 1994--1995. Volume 9

    SciTech Connect

    Not Available

    1993-04-01

    This report contains the fiscal year budget justification to Congress. The budget provides estimates for salaries and expenses and for the Office of the Inspector General for fiscal years 1994 and 1995.

  12. Property:EstimatedTimeMedian | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    week,w,Week,Weeks,W,WEEK,WEEKS 12 months,month,m,Month,Months,M,MONTH,MONTHS 1 years,year,y,Year,Years,Y,YEAR,YEARS Pages using the property "EstimatedTimeMedian" Showing 25 pages...

  13. Property:EstimatedTimeLow | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    week,w,Week,Weeks,W,WEEK,WEEKS 12 months,month,m,Month,Months,M,MONTH,MONTHS 1 years,year,y,Year,Years,Y,YEAR,YEARS Pages using the property "EstimatedTimeLow" Showing 25 pages...

  14. Property:EstimatedTimeHigh | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    week,w,Week,Weeks,W,WEEK,WEEKS 12 months,month,m,Month,Months,M,MONTH,MONTHS 1 years,year,y,Year,Years,Y,YEAR,YEARS Pages using the property "EstimatedTimeHigh" Showing 25 pages...

  15. Emissions Tool Estimates the Impact of Emissions on Smart Grid...

    Energy Saver

    The free, web-based calculator aims to estimate the impact of NOx, SO2 and CO2 emissions on smart grid infrastructure investments, taking into account specific context and project ...

  16. Summary and Presentations from "Estimating the Benefits and Costs...

    Energy.gov [DOE] (indexed site)

    Energy hosted a two-day workshop on "Estimating the Benefits and Costs of Distributed Energy Technologies" in Washington DC. The purpose of the workshop was to foster discussion...

  17. Estimating demolition cost of plutonium buildings for dummies

    SciTech Connect

    Tower, S.E.

    2000-07-01

    The primary purpose of the Rocky Flats Field Office of the US Department of Energy is to decommission the entire plant. In an effort to improve the basis and the accuracy of the future decommissioning cost, Rocky Flats has developed a powerful but easy-to-use tool to determine budget cost estimates to characterize, decontaminate, and demolish all its buildings. The parametric cost-estimating tool is called the Facilities Disposition Cost Model (FDCM).

  18. Emissions Tool Estimates the Impact of Emissions on Smart Grid

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Infrastructure Investments | Department of Energy Emissions Tool Estimates the Impact of Emissions on Smart Grid Infrastructure Investments Emissions Tool Estimates the Impact of Emissions on Smart Grid Infrastructure Investments July 28, 2016 - 2:59pm Addthis In the face of extreme weather events, states, utilities, and other companies are increasingly seeking ways to boost resiliency while reducing their carbon footprint. The Emissions Quantification Tool (EQT), which was conceived of and

  19. Estimating the Value of Electricity Storage Resources in Electricity

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Markets - EAC 2011 | Department of Energy Estimating the Value of Electricity Storage Resources in Electricity Markets - EAC 2011 Estimating the Value of Electricity Storage Resources in Electricity Markets - EAC 2011 The purpose of this report is to assist the U.S. Department of Energy (DOE) in 1) establishing a framework for understanding the role electricity storage resources (storage) can play in wholesale and retail electricity markets, 2) assessing the value of electricity storage in a

  20. Estimating the National Carbon Abatement Potential of City Policies: A

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Data- Driven Approach | Department of Energy Estimating the National Carbon Abatement Potential of City Policies: A Data- Driven Approach Estimating the National Carbon Abatement Potential of City Policies: A Data- Driven Approach Cities are increasingly taking actions such as building code enforcement, urban planning, and public transit expansion to reduce emissions of carbon dioxide in their communities and municipal operations. However, many cities lack the quantitative information needed

  1. Estimates of State Energy-Related Carbon Dioxide Emissions

    Energy Information Administration (EIA) (indexed site)

    November 2016 Estimates of State Energy-Related Carbon Dioxide Emissions Because energy-related carbon dioxide (CO2) constitutes over 80% of total emissions, the state energy- related CO2 emission levels provide a good indicator of the relative contribution of individual states to total greenhouse gas emissions. The U.S. Energy Information Administration (EIA) emissions estimates at the state level for energy-related CO2 are based on data contained in the State Energy Data System (SEDS). 1 The

  2. Estimating propagation velocity through a surface acoustic wave sensor

    DOEpatents

    Xu, Wenyuan; Huizinga, John S.

    2010-03-16

    Techniques are described for estimating the propagation velocity through a surface acoustic wave sensor. In particular, techniques which measure and exploit a proper segment of phase frequency response of the surface acoustic wave sensor are described for use as a basis of bacterial detection by the sensor. As described, use of velocity estimation based on a proper segment of phase frequency response has advantages over conventional techniques that use phase shift as the basis for detection.

  3. Using doppler radar images to estimate aircraft navigational heading error

    DOEpatents

    Doerry, Armin W.; Jordan, Jay D.; Kim, Theodore J.

    2012-07-03

    A yaw angle error of a motion measurement system carried on an aircraft for navigation is estimated from Doppler radar images captured using the aircraft. At least two radar pulses aimed at respectively different physical locations in a targeted area are transmitted from a radar antenna carried on the aircraft. At least two Doppler radar images that respectively correspond to the at least two transmitted radar pulses are produced. These images are used to produce an estimate of the yaw angle error.

  4. US Low-Temperature EGS Resource Potential Estimate

    DOE Data Explorer

    Katherine Young

    2016-06-30

    Shapefile of shallow, low-temperature EGS resources for the United States, and accompanying paper (submitted to GRC 2016) describing the methodology and analysis. These data are part of a very rough estimate created for use in the U.S. Department of Energy Geothermal Technology Office's Vision Study. They are not a robust estimate of low-temperature EGS resources in the U.S, and should be used accordingly.

  5. Unmanned Aircraft Systems Used to Improve Methods for Estimating

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Groundwater Discharge by Plants | Department of Energy Unmanned Aircraft Systems Used to Improve Methods for Estimating Groundwater Discharge by Plants Unmanned Aircraft Systems Used to Improve Methods for Estimating Groundwater Discharge by Plants October 6, 2016 - 12:00pm Addthis What does this project do? Goal 1: Protect human health and the environment The U.S. Department of Energy (DOE) Office of Legacy Management (LM) uses mathematical models and monitoring-well data to understand and

  6. UWB channel estimation using new generating TR transceivers

    DOEpatents

    Nekoogar, Faranak; Dowla, Farid U.; Spiridon, Alex; Haugen, Peter C.; Benzel, Dave M.

    2011-06-28

    The present invention presents a simple and novel channel estimation scheme for UWB communication systems. As disclosed herein, the present invention maximizes the extraction of information by incorporating a new generation of transmitted-reference (Tr) transceivers that utilize a single reference pulse(s) or a preamble of reference pulses to provide improved channel estimation while offering higher Bit Error Rate (BER) performance and data rates without diluting the transmitter power.

  7. New DOE Report Estimates LED Savings in Common Lighting Applications |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Report Estimates LED Savings in Common Lighting Applications New DOE Report Estimates LED Savings in Common Lighting Applications July 24, 2015 - 11:00am Addthis The U.S. Department of Energy (DOE) has released its latest report in a series analyzing markets where LEDs compete with traditional lighting sources. The new report, Adoption of Light-Emitting Diodes in Common Lighting Applications, reveals a wealth of insights into promising pathways for SSL technology

  8. DC Microgrids Scoping Study: Estimate of Technical and Economic Benefits

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    (March 2015) | Department of Energy Microgrids Scoping Study: Estimate of Technical and Economic Benefits (March 2015) DC Microgrids Scoping Study: Estimate of Technical and Economic Benefits (March 2015) Microgrid demonstrations and deployments have shown the ability of microgrids to provide higher reliability and higher power quality than utility power systems and improved energy utilization. The vast majority of these microgrids are based on AC power, but some manufacturers, power system

  9. Revision Policy for EIA Weekly Underground Natural Gas Storage Estimates

    Weekly Natural Gas Storage Report

    Revision Policy for EIA Weekly Underground Natural Gas Storage Estimates Latest Update: November 16, 2015 This report consists of the following sections: General EIA Weekly Natural Gas Storage Report Revisions Policy - a description of how revisions to the Weekly Natural Gas Storage Report estimates may occur EIA Weekly Natural Gas Storage Report Policy to Allow Unscheduled Release of Revisions - a description of the policy that will be implemented in the event of an out-of-cycle release

  10. WIPP - Freedom of Information Act (FOIA) Requests Received and Estimated

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Completion Dates Requests Received and Estimated Completion Dates Requesters who have submitted Freedom of Information (FOIA) requests to the Carlsbad Field Office on or after December 31, 2008, may obtain the date received by this office and the estimated completion date by clicking here. You will need to know your FOIA control number to identify your request on the listing. If you would like additional information related to your request you should contact the FOIA Requester Service

  11. Determining Best Estimates and Uncertainties in Cloud Microphysical

    Office of Scientific and Technical Information (OSTI)

    Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions (Technical Report) | SciTech Connect Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions Citation Details In-Document Search Title: Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for

  12. Hydrogen Supply: Cost Estimate for Hydrogen Pathways-Scoping Analysis.

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    January 22, 2002-July 22, 2002 | Department of Energy Supply: Cost Estimate for Hydrogen Pathways-Scoping Analysis. January 22, 2002-July 22, 2002 Hydrogen Supply: Cost Estimate for Hydrogen Pathways-Scoping Analysis. January 22, 2002-July 22, 2002 A report showing a comparative scooping economic analysis of 19 pathways for producing, handling, distributing, and dispensing hydrogen for fuel cell vehicle applications. 32525.pdf (1.48 MB) More Documents & Publications Analysis of a Cluster

  13. Updated Capital Cost Estimates for Utility Scale Electricity Generating Plants

    Energy Information Administration (EIA) (indexed site)

    Updated Capital Cost Estimates for Utility Scale Electricity Generating Plants April 2013 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Updated Capital Cost Estimates for Utility Scale Electricity Generating Plants ii This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and

  14. Verification of unfold error estimates in the unfold operator code

    SciTech Connect

    Fehl, D.L.; Biggs, F.

    1997-01-01

    Spectral unfolding is an inverse mathematical operation that attempts to obtain spectral source information from a set of response functions and data measurements. Several unfold algorithms have appeared over the past 30 years; among them is the unfold operator (UFO) code written at Sandia National Laboratories. In addition to an unfolded spectrum, the UFO code also estimates the unfold uncertainty (error) induced by estimated random uncertainties in the data. In UFO the unfold uncertainty is obtained from the error matrix. This built-in estimate has now been compared to error estimates obtained by running the code in a Monte Carlo fashion with prescribed data distributions (Gaussian deviates). In the test problem studied, data were simulated from an arbitrarily chosen blackbody spectrum (10 keV) and a set of overlapping response functions. The data were assumed to have an imprecision of 5{percent} (standard deviation). One hundred random data sets were generated. The built-in estimate of unfold uncertainty agreed with the Monte Carlo estimate to within the statistical resolution of this relatively small sample size (95{percent} confidence level). A possible 10{percent} bias between the two methods was unresolved. The Monte Carlo technique is also useful in underdetermined problems, for which the error matrix method does not apply. UFO has been applied to the diagnosis of low energy x rays emitted by Z-pinch and ion-beam driven hohlraums. {copyright} {ital 1997 American Institute of Physics.}

  15. Development on electromagnetic impedance function modeling and its estimation

    SciTech Connect

    Sutarno, D.

    2015-09-30

    Today the Electromagnetic methods such as magnetotellurics (MT) and controlled sources audio MT (CSAMT) is used in a broad variety of applications. Its usefulness in poor seismic areas and its negligible environmental impact are integral parts of effective exploration at minimum cost. As exploration was forced into more difficult areas, the importance of MT and CSAMT, in conjunction with other techniques, has tended to grow continuously. However, there are obviously important and difficult problems remaining to be solved concerning our ability to collect process and interpret MT as well as CSAMT in complex 3D structural environments. This talk aim at reviewing and discussing the recent development on MT as well as CSAMT impedance functions modeling, and also some improvements on estimation procedures for the corresponding impedance functions. In MT impedance modeling, research efforts focus on developing numerical method for computing the impedance functions of three dimensionally (3-D) earth resistivity models. On that reason, 3-D finite elements numerical modeling for the impedances is developed based on edge element method. Whereas, in the CSAMT case, the efforts were focused to accomplish the non-plane wave problem in the corresponding impedance functions. Concerning estimation of MT and CSAMT impedance functions, researches were focused on improving quality of the estimates. On that objective, non-linear regression approach based on the robust M-estimators and the Hilbert transform operating on the causal transfer functions, were used to dealing with outliers (abnormal data) which are frequently superimposed on a normal ambient MT as well as CSAMT noise fields. As validated, the proposed MT impedance modeling method gives acceptable results for standard three dimensional resistivity models. Whilst, the full solution based modeling that accommodate the non-plane wave effect for CSAMT impedances is applied for all measurement zones, including near-, transition

  16. Atmospheric Inverse Estimates of Methane Emissions from Central California

    SciTech Connect

    Zhao, Chuanfeng; Andrews, Arlyn E.; Bianco, Laura; Eluszkiewicz, Janusz; Hirsch, Adam; MacDonald, Clinton; Nehrkorn, Thomas; Fischer, Marc L.

    2008-11-21

    Methane mixing ratios measured at a tall-tower are compared to model predictions to estimate surface emissions of CH{sub 4} in Central California for October-December 2007 using an inverse technique. Predicted CH{sub 4} mixing ratios are calculated based on spatially resolved a priori CH{sub 4} emissions and simulated atmospheric trajectories. The atmospheric trajectories, along with surface footprints, are computed using the Weather Research and Forecast (WRF) coupled to the Stochastic Time-Inverted Lagrangian Transport (STILT) model. An uncertainty analysis is performed to provide quantitative uncertainties in estimated CH{sub 4} emissions. Three inverse model estimates of CH{sub 4} emissions are reported. First, linear regressions of modeled and measured CH{sub 4} mixing ratios obtain slopes of 0.73 {+-} 0.11 and 1.09 {+-} 0.14 using California specific and Edgar 3.2 emission maps respectively, suggesting that actual CH{sub 4} emissions were about 37 {+-} 21% higher than California specific inventory estimates. Second, a Bayesian 'source' analysis suggests that livestock emissions are 63 {+-} 22% higher than the a priori estimates. Third, a Bayesian 'region' analysis is carried out for CH{sub 4} emissions from 13 sub-regions, which shows that inventory CH{sub 4} emissions from the Central Valley are underestimated and uncertainties in CH{sub 4} emissions are reduced for sub-regions near the tower site, yielding best estimates of flux from those regions consistent with 'source' analysis results. The uncertainty reductions for regions near the tower indicate that a regional network of measurements will be necessary to provide accurate estimates of surface CH{sub 4} emissions for multiple regions.

  17. Estimation of uncertainty for contour method residual stress measurements

    SciTech Connect

    Olson, Mitchell D.; DeWald, Adrian T.; Prime, Michael B.; Hill, Michael R.

    2014-12-03

    This paper describes a methodology for the estimation of measurement uncertainty for the contour method, where the contour method is an experimental technique for measuring a two-dimensional map of residual stress over a plane. Random error sources including the error arising from noise in displacement measurements and the smoothing of the displacement surfaces are accounted for in the uncertainty analysis. The output is a two-dimensional, spatially varying uncertainty estimate such that every point on the cross-section where residual stress is determined has a corresponding uncertainty value. Both numerical and physical experiments are reported, which are used to support the usefulness of the proposed uncertainty estimator. The uncertainty estimator shows the contour method to have larger uncertainty near the perimeter of the measurement plane. For the experiments, which were performed on a quenched aluminum bar with a cross section of 51 76 mm, the estimated uncertainty was approximately 5 MPa (?/E = 7 10??) over the majority of the cross-section, with localized areas of higher uncertainty, up to 10 MPa (?/E = 14 10??).

  18. SECPOP90: Sector population, land fraction, and economic estimation program

    SciTech Connect

    Humphreys, S.L.; Rollstin, J.A.; Ridgely, J.N.

    1997-09-01

    In 1973 Mr. W. Athey of the Environmental Protection Agency wrote a computer program called SECPOP which calculated population estimates. Since that time, two things have changed which suggested the need for updating the original program - more recent population censuses and the widespread use of personal computers (PCs). The revised computer program uses the 1990 and 1992 Population Census information and runs on current PCs as {open_quotes}SECPOP90.{close_quotes} SECPOP90 consists of two parts: site and regional. The site provides population and economic data estimates for any location within the continental United States. Siting analysis is relatively fast running. The regional portion assesses site availability for different siting policy decisions; i.e., the impact of available sites given specific population density criteria within the continental United States. Regional analysis is slow. This report compares the SECPOP90 population estimates and the nuclear power reactor licensee-provided information. Although the source, and therefore the accuracy, of the licensee information is unknown, this comparison suggests SECPOP90 makes reasonable estimates. Given the total uncertainty in any current calculation of severe accidents, including the potential offsite consequences, the uncertainty within SECPOP90 population estimates is expected to be insignificant. 12 refs., 55 figs., 7 tabs.

  19. New Methodology for Estimating Fuel Economy by Vehicle Class

    SciTech Connect

    Chin, Shih-Miao; Dabbs, Kathryn; Hwang, Ho-Ling

    2011-01-01

    Office of Highway Policy Information to develop a new methodology to generate annual estimates of average fuel efficiency and number of motor vehicles registered by vehicle class for Table VM-1 of the Highway Statistics annual publication. This paper describes the new methodology developed under this effort and compares the results of the existing manual method and the new systematic approach. The methodology developed under this study takes a two-step approach. First, the preliminary fuel efficiency rates are estimated based on vehicle stock models for different classes of vehicles. Then, a reconciliation model is used to adjust the initial fuel consumption rates from the vehicle stock models and match the VMT information for each vehicle class and the reported total fuel consumption. This reconciliation model utilizes a systematic approach that produces documentable and reproducible results. The basic framework utilizes a mathematical programming formulation to minimize the deviations between the fuel economy estimates published in the previous year s Highway Statistics and the results from the vehicle stock models, subject to the constraint that fuel consumptions for different vehicle classes must sum to the total fuel consumption estimate published in Table MF-21 of the current year Highway Statistics. The results generated from this new approach provide a smoother time series for the fuel economies by vehicle class. It also utilizes the most up-to-date and best available data with sound econometric models to generate MPG estimates by vehicle class.

  20. Surface daytime net radiation estimation using artificial neural networks

    DOE PAGES [OSTI]

    Jiang, Bo; Zhang, Yi; Liang, Shunlin; Zhang, Xiaotong; Xiao, Zhiqiang

    2014-11-11

    Net all-wave surface radiation (Rn) is one of the most important fundamental parameters in various applications. However, conventional Rn measurements are difficult to collect because of the high cost and ongoing maintenance of recording instruments. Therefore, various empirical Rn estimation models have been developed. This study presents the results of two artificial neural network (ANN) models (general regression neural networks (GRNN) and Neuroet) to estimate Rn globally from multi-source data, including remotely sensed products, surface measurements, and meteorological reanalysis products. Rn estimates provided by the two ANNs were tested against in-situ radiation measurements obtained from 251 global sites between 1991–2010more » both in global mode (all data were used to fit the models) and in conditional mode (the data were divided into four subsets and the models were fitted separately). Based on the results obtained from extensive experiments, it has been proved that the two ANNs were superior to linear-based empirical models in both global and conditional modes and that the GRNN performed better and was more stable than Neuroet. The GRNN estimates had a determination coefficient (R2) of 0.92, a root mean square error (RMSE) of 34.27 W·m–2 , and a bias of –0.61 W·m–2 in global mode based on the validation dataset. In conclusion, ANN methods are a potentially powerful tool for global Rn estimation.« less

  1. CALIBRATING C-IV-BASED BLACK HOLE MASS ESTIMATORS

    SciTech Connect

    Park, Daeseong; Woo, Jong-Hak; Shin, Jaejin [Astronomy Program, Department of Physics and Astronomy, Seoul National University, Seoul 151-742 (Korea, Republic of); Denney, Kelly D., E-mail: pds2001@astro.snu.ac.kr, E-mail: woo@astro.snu.ac.kr, E-mail: jjshin@astro.snu.ac.kr, E-mail: kelly@dark-cosmology.dk [Dark Cosmology Centre, Niels Bohr Institute, Juliane Maries Vej 30, DK-2100 Copenhagen O (Denmark)

    2013-06-20

    We present the single-epoch black hole mass estimators based on the C IV {lambda}1549 broad emission line, using the updated sample of the reverberation-mapped active galactic nuclei and high-quality UV spectra. By performing multi-component spectral fitting analysis, we measure the C IV line widths (FWHM{sub C{sub IV}} and line dispersion, {sigma}{sub C{sub IV}}) and the continuum luminosity at 1350 A (L{sub 1350}) to calibrate the C-IV-based mass estimators. By comparing with the H{beta} reverberation-based masses, we provide new mass estimators with the best-fit relationships, i.e., M{sub BH}{proportional_to}L{sub 1350}{sup 0.50{+-}0.07}{sigma}{sub C{sub IV}{sup 2}} and M{sub BH}{proportional_to}L{sub 1350}{sup 0.52{+-}0.09} FWHM{sub C{sub IV}{sup 0.56{+-}0.48}}. The new C-IV-based mass estimators show significant mass-dependent systematic difference compared to the estimators commonly used in the literature. Using the published Sloan Digital Sky Survey QSO catalog, we show that the black hole mass of high-redshift QSOs decreases on average by {approx}0.25 dex if our recipe is adopted.

  2. Estimation of uncertainty for contour method residual stress measurements

    SciTech Connect

    Olson, Mitchell D.; DeWald, Adrian T.; Prime, Michael B.; Hill, Michael R.

    2014-12-03

    This paper describes a methodology for the estimation of measurement uncertainty for the contour method, where the contour method is an experimental technique for measuring a two-dimensional map of residual stress over a plane. Random error sources including the error arising from noise in displacement measurements and the smoothing of the displacement surfaces are accounted for in the uncertainty analysis. The output is a two-dimensional, spatially varying uncertainty estimate such that every point on the cross-section where residual stress is determined has a corresponding uncertainty value. Both numerical and physical experiments are reported, which are used to support the usefulness of the proposed uncertainty estimator. The uncertainty estimator shows the contour method to have larger uncertainty near the perimeter of the measurement plane. For the experiments, which were performed on a quenched aluminum bar with a cross section of 51 × 76 mm, the estimated uncertainty was approximately 5 MPa (σ/E = 7 · 10⁻⁵) over the majority of the cross-section, with localized areas of higher uncertainty, up to 10 MPa (σ/E = 14 · 10⁻⁵).

  3. Estimation of uncertainty for contour method residual stress measurements

    DOE PAGES [OSTI]

    Olson, Mitchell D.; DeWald, Adrian T.; Prime, Michael B.; Hill, Michael R.

    2014-12-03

    This paper describes a methodology for the estimation of measurement uncertainty for the contour method, where the contour method is an experimental technique for measuring a two-dimensional map of residual stress over a plane. Random error sources including the error arising from noise in displacement measurements and the smoothing of the displacement surfaces are accounted for in the uncertainty analysis. The output is a two-dimensional, spatially varying uncertainty estimate such that every point on the cross-section where residual stress is determined has a corresponding uncertainty value. Both numerical and physical experiments are reported, which are used to support the usefulnessmore » of the proposed uncertainty estimator. The uncertainty estimator shows the contour method to have larger uncertainty near the perimeter of the measurement plane. For the experiments, which were performed on a quenched aluminum bar with a cross section of 51 × 76 mm, the estimated uncertainty was approximately 5 MPa (σ/E = 7 · 10⁻⁵) over the majority of the cross-section, with localized areas of higher uncertainty, up to 10 MPa (σ/E = 14 · 10⁻⁵).« less

  4. Iterative methods for distributed parameter estimation in parabolic PDE

    SciTech Connect

    Vogel, C.R.; Wade, J.G.

    1994-12-31

    The goal of the work presented is the development of effective iterative techniques for large-scale inverse or parameter estimation problems. In this extended abstract, a detailed description of the mathematical framework in which the authors view these problem is presented, followed by an outline of the ideas and algorithms developed. Distributed parameter estimation problems often arise in mathematical modeling with partial differential equations. They can be viewed as inverse problems; the `forward problem` is that of using the fully specified model to predict the behavior of the system. The inverse or parameter estimation problem is: given the form of the model and some observed data from the system being modeled, determine the unknown parameters of the model. These problems are of great practical and mathematical interest, and the development of efficient computational algorithms is an active area of study.

  5. Model Year 2006 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect

    2005-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  6. Model Year 2008 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect

    2007-10-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  7. Model Year 2007 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect

    2007-10-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  8. Model Year 2016 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect

    2015-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  9. Model Year 2015 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect

    2014-12-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  10. Variational reactivity estimates: new analyses and new results

    SciTech Connect

    Favorite, Jeffrey A

    2009-01-01

    A modified form of the variational estimate of the reactivity worth ofa perturbation was previously developed to extend the range of applicability of variational perturbation theory for perturbations leading to negative reactivity worths. Recent numerical results challenged the assumptions behind the modified form. In this paper, more results are obtained, leading to the conclusion that sometimes the modified form extends the range ofapplicability of variational perturbation theory for positive reactivity worths as well, and sometimes the standard variational form is more accurate for negative-reactivity perturbations. In addition, this paper proves that using the exact generalized adjoint function would lead to an inaccurate variational reactivity estimate when the error in the first-order estimate is large; the standard generalized adjoint function, an approximation to the exact one, leads to Lore accurate results. This conclusion is also demonstrated numerically. Transport calculations use the PARTISN multi group discrete ordinates code

  11. Model Year 2005 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect

    2004-11-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  12. A Testbed for Deploying Distributed State Estimation in Power Grid

    SciTech Connect

    Jin, Shuangshuang; Chen, Yousu; Rice, Mark J.; Liu, Yan; Gorton, Ian

    2012-07-22

    Abstract—With the increasing demand, scale and data information of power systems, fast distributed applications are becoming more important in power system operation and control. This paper proposes a testbed for evaluating power system distributed applications, considering data exchange among distributed areas. A high-performance computing (HPC) version of distributed state estimation is implemented and used as a distributed application example. The IEEE 118-bus system is used to deploy the parallel distributed state estimation, and the MeDICi middleware is used for data communication. The performance of the testbed demonstrates its capability to evaluate parallel distributed state estimation by leveraging the HPC paradigm. This testbed can also be applied to evaluate other distributed applications.

  13. Estimation of fast transient overvoltage in gas-insulated substation

    SciTech Connect

    Yanabu, S.; Murase, H.; Aoyagi, H.; Okubo, H.; Kawaguchi, Y. )

    1990-10-01

    By using a commercial 550kV GIS to measure disconnector-induced FTO (fast transient overvoltages) on site, extensive data were obtained. The maximum FTO estimated from observation was 2.7 pu. Such a high FTO was observed infrequently and occurred only at the open end of bus bars. Through a comparison between simulation and measurement by employing a 1-GHz surge sensor, the authors demonstrate that when estimating the level of FTO by EMPT, no large errors are likely to be involved even without strict simulation of such GIS components as spacers, disconnectors, and short bus branches. Thus, the estimated FTO levels analytically obtained agree well with measured values within an error of 0.1 pu.

  14. Model Year 2010 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect

    2009-10-14

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  15. Model Year 2009 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect

    2008-10-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  16. Model Year 2014 Fuel Economy Guide: EPA Fuel Economy Estimates

    SciTech Connect

    2013-12-01

    The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.

  17. The Federal Highway Administration Gasohol Consumption Estimation Model

    SciTech Connect

    Hwang, HL

    2003-08-28

    The Federal Highway Administration (FHWA) is responsible for estimating the portion of Federal highway funds attributable to each State. The process involves use of State-reported data (gallons) and a set of estimation models when accurate State data is unavailable. To ensure that the distribution of funds is equitable, FHWA periodically reviews the estimation models. Estimation of the use of gasohol is difficult because of State differences in the definition of gasohol, inability of many States to separate and report gasohol usage from other fuel types, changes in fuel composition in nonattainment areas to address concerns over the use of certain fuel additives, and the lack of a valid State-level surrogate data set for gasohol use. Under the sponsorship of FHWA, Oak Ridge National Laboratory (ORNL) reviewed the regression-based gasohol estimation model that has been in use for several years. Based on an analytical assessment of that model and an extensive review of potential data sets, ORNL developed an improved rule-based model. The new model uses data from Internal Revenue Service, Energy Information Administration, Environmental Protection Agency, Department of Energy, ORNL, and FHWA sources. The model basically consists of three parts: (1) development of a controlled total of national gasohol usage, (2) determination of reliable State gasohol consumption data, and (3) estimation of gasohol usage for all other States. The new model will be employed for the 2004 attribution process. FHWA is currently soliciting comments and inputs from interested parties. Relevant data, as identified, will be pursued and refinements will be made by the research team if warranted.

  18. Estimating Externalities of Natural Gas Fuel Cycles, Report 4

    SciTech Connect

    Barnthouse, L.W.; Cada, G.F.; Cheng, M.-D.; Easterly, C.E.; Kroodsma, R.L.; Lee, R.; Shriner, D.S.; Tolbert, V.R.; Turner, R.S.

    1998-01-01

    This report describes methods for estimating the external costs (and possibly benefits) to human health and the environment that result from natural gas fuel cycles. Although the concept of externalities is far from simple or precise, it generally refers to effects on individuals' well being, that result from a production or market activity in which the individuals do not participate, or are not fully compensated. In the past two years, the methodological approach that this report describes has quickly become a worldwide standard for estimating externalities of fuel cycles. The approach is generally applicable to any fuel cycle in which a resource, such as coal, hydro, or biomass, is used to generate electric power. This particular report focuses on the production activities, pollution, and impacts when natural gas is used to generate electric power. In the 1990s, natural gas technologies have become, in many countries, the least expensive to build and operate. The scope of this report is on how to estimate the value of externalities--where value is defined as individuals' willingness to pay for beneficial effects, or to avoid undesirable ones. This report is about the methodologies to estimate these externalities, not about how to internalize them through regulations or other public policies. Notwithstanding this limit in scope, consideration of externalities can not be done without considering regulatory, insurance, and other considerations because these institutional factors affect whether costs (and benefits) are in fact external, or whether they are already somehow internalized within the electric power market. Although this report considers such factors to some extent, much analysis yet remains to assess the extent to which estimated costs are indeed external. This report is one of a series of reports on estimating the externalities of fuel cycles. The other reports are on the coal, oil, biomass, hydro, and nuclear fuel cycles, and on general methodology.

  19. Bounded limit for the Monte Carlo point-flux-estimator

    SciTech Connect

    Grimesey, R.A.

    1981-01-01

    In a Monte Carlo random walk the kernel K(R,E) is used as an expected value estimator at every collision for the collided flux phi/sub c/ r vector,E) at the detector point. A limiting value for the kernel is derived from a diffusion approximation for the probability current at a radius R/sub 1/ from the detector point. The variance of the collided flux at the detector point is thus bounded using this asymptotic form for K(R,E). The bounded point flux estimator is derived. (WHK)

  20. ARM - Evaluation Product - Quantitative Precipitation Estimates (QPE) from

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    the CSAPR ProductsQuantitative Precipitation Estimates (QPE) from the CSAPR ARM Data Discovery Browse Data Documentation Use the Data File Inventory tool to view data availability at the file level. Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Evaluation Product : Quantitative Precipitation Estimates (QPE) from the CSAPR Precipitation rates from cloud systems can give a fundamental insight into the processes occurring in-cloud. While rain

  1. Pennsylvania Dry Natural Gas Reserves Estimated Production (Billion Cubic

    Energy Information Administration (EIA) (indexed site)

    Feet) Estimated Production (Billion Cubic Feet) Pennsylvania Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 52 69 117 1980's 68 94 102 121 134 123 116 128 162 136 1990's 160 140 139 138 141 113 132 129 131 130 2000's 117 114 133 165 155 181 176 183 211 273 2010's 591 1,248 2,241 3,283 4,197 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  2. Mississippi Dry Natural Gas Reserves Estimated Production (Billion Cubic

    Energy Information Administration (EIA) (indexed site)

    Feet) Estimated Production (Billion Cubic Feet) Mississippi Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 88 121 154 1980's 170 196 198 159 181 151 165 178 181 155 1990's 141 143 109 111 82 91 88 93 79 79 2000's 78 94 98 94 93 86 83 100 110 100 2010's 87 75 64 61 54 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  3. Montana Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet)

    Energy Information Administration (EIA) (indexed site)

    Estimated Production (Billion Cubic Feet) Montana Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 49 44 47 1980's 61 86 45 49 46 49 42 42 60 43 1990's 48 48 52 50 49 51 52 55 51 41 2000's 67 73 77 86 95 100 117 112 114 113 2010's 93 75 65 62 58 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015

  4. Louisiana - South Onshore Crude Oil + Lease Condensate Estimated Production

    Energy Information Administration (EIA) (indexed site)

    from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Louisiana - South Onshore Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 48 2010's 47 47 47 47 46 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring

  5. Louisiana Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Louisiana Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 68 2010's 66 68 70 71 69 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease

  6. Louisiana State Offshore Crude Oil + Lease Condensate Estimated Production

    Energy Information Administration (EIA) (indexed site)

    from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Louisiana State Offshore Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 9 2010's 9 10 11 11 10 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages:

  7. Louisiana State Offshore Dry Natural Gas Reserves Estimated Production

    Energy Information Administration (EIA) (indexed site)

    (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) Louisiana State Offshore Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 407 188 200 196 195 1990's 145 127 117 137 144 152 177 161 128 117 2000's 127 158 122 126 99 68 83 86 95 83 2010's 74 49 84 66 52 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  8. Lower 48 States Crude Oil + Lease Condensate Estimated Production from

    Energy Information Administration (EIA) (indexed site)

    Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Lower 48 States Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 1,719 2010's 1,796 1,859 2,195 2,543 3,018 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring

  9. Michigan Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Michigan Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 6 2010's 6 6 7 7 8 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate

  10. Michigan Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Michigan Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 96 1980's 111 94 81 69 81 69 68 68 76 85 1990's 76 114 110 111 115 130 179 192 215 208 2000's 300 218 218 195 194 198 183 170 145 151 2010's 151 137 130 120 112 - = No Data Reported; -- =

  11. Miscellaneous States Crude Oil + Lease Condensate Estimated Production from

    Energy Information Administration (EIA) (indexed site)

    Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Miscellaneous States Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 2 2010's 2 2 3 3 2 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus

  12. Miscellaneous States Dry Natural Gas Reserves Estimated Production (Billion

    Energy Information Administration (EIA) (indexed site)

    Cubic Feet) Estimated Production (Billion Cubic Feet) Miscellaneous States Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 11 12 11 1980's 18 15 7 8 7 11 6 7 10 7 1990's 7 7 6 10 10 11 6 3 3 3 2000's 6 5 7 12 8 18 10 14 20 30 2010's 16 24 14 12 11 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  13. Mississippi Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Mississippi Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 24 2010's 24 24 28 24 25 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease

  14. Montana Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Montana Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 29 2010's 25 24 27 30 30 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease

  15. Montana Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Montana Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 42 1980's 51 74 36 39 38 41 31 32 47 36 1990's 40 42 46 44 43 45 47 51 46 35 2000's 62 67 70 79 86 86 100 92 88 80 2010's 70 57 45 39 35 - = No Data Reported; -- = Not Applicable; NA = Not

  16. Nebraska Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Nebraska Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 2 2010's 2 3 3 3 3 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate

  17. New Mexico - East Crude Oil + Lease Condensate Estimated Production from

    Energy Information Administration (EIA) (indexed site)

    Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) New Mexico - East Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 58 2010's 63 70 83 98 117 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil

  18. New Mexico - East Dry Natural Gas Reserves Estimated Production (Billion

    Energy Information Administration (EIA) (indexed site)

    Cubic Feet) Estimated Production (Billion Cubic Feet) New Mexico - East Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 604 553 596 1980's 515 531 498 424 439 429 325 382 359 396 1990's 392 424 437 456 466 418 432 418 427 491 2000's 447 518 526 507 516 522 480 462 459 454 2010's 392 377 404 447 464 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  19. New Mexico - West Crude Oil + Lease Condensate Estimated Production from

    Energy Information Administration (EIA) (indexed site)

    Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) New Mexico - West Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 2 2010's 2 2 3 4 7 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus

  20. New Mexico - West Dry Natural Gas Reserves Estimated Production (Billion

    Energy Information Administration (EIA) (indexed site)

    Cubic Feet) Estimated Production (Billion Cubic Feet) New Mexico - West Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 523 546 553 1980's 549 555 444 375 417 414 303 346 372 364 1990's 495 589 706 881 896 979 991 1,129 1,022 1,048 2000's 1,061 1,018 998 908 1,011 971 946 887 890 896 2010's 828 793 765 708 710 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  1. Alabama Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet)

    Energy Information Administration (EIA) (indexed site)

    Estimated Production (Billion Cubic Feet) Alabama Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 24 42 46 1980's 64 85 1990's 104 146 256 281 391 360 373 376 394 376 2000's 359 345 365 350 327 300 287 274 257 254 2010's 223 218 214 175 176 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next

  2. Alaska Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet)

    Energy Information Administration (EIA) (indexed site)

    Estimated Production (Billion Cubic Feet) Alaska Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 206 216 228 1980's 213 235 261 273 324 312 324 349 400 401 1990's 339 353 414 393 423 396 446 475 513 459 2000's 506 461 460 478 478 469 408 388 354 358 2010's 317 327 299 285 304 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  3. Arkansas Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet)

    Energy Information Administration (EIA) (indexed site)

    Estimated Production (Billion Cubic Feet) Arkansas Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 109 120 100 1980's 117 121 158 206 188 175 123 129 159 166 1990's 164 173 204 188 186 182 200 189 170 163 2000's 154 160 157 166 170 174 188 269 456 698 2010's 951 1,079 1,151 1,140 1,142 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  4. California Dry Natural Gas Reserves Estimated Production (Billion Cubic

    Energy Information Administration (EIA) (indexed site)

    Feet) Estimated Production (Billion Cubic Feet) California Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 301 313 347 1980's 294 372 345 335 306 1990's 293 308 285 252 244 216 217 212 246 266 2000's 282 336 291 265 247 268 255 253 237 239 2010's 243 311 200 188 176 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  5. Alabama Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Alabama Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 7 2010's 7 8 10 10 9 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate

  6. Alabama Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Alabama Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 44 1980's 63 85 1990's 104 147 254 276 385 354 367 372 391 380 2000's 365 345 365 347 325 298 286 273 262 256 2010's 225 218 204 174 167 - = No Data Reported; -- = Not Applicable; NA = Not

  7. Alaska Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Alaska Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 210 2010's 195 206 191 186 182 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease

  8. Alaska Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Alaska Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 176 1980's 161 181 188 193 189 200 179 179 184 192 1990's 158 184 219 184 201 195 211 207 204 202 2000's 198 213 200 204 206 213 192 164 149 136 2010's 145 152 129 108 101 - = No Data

  9. Arkansas Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Arkansas Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 6 2010's 5 6 6 4 6 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate

  10. Arkansas Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Arkansas Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 91 1980's 90 94 150 196 178 173 119 124 154 161 1990's 152 152 180 167 167 160 178 173 157 159 2000's 150 157 153 161 166 171 183 265 454 694 2010's 948 1,074 1,143 1,132 1,133 - = No Data

  11. California - Coastal Region Onshore Crude Oil + Lease Condensate Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) California - Coastal Region Onshore Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 18 2010's 18 20 22 23 23 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date:

  12. California - Coastal Region Onshore Dry Natural Gas Reserves Estimated

    Energy Information Administration (EIA) (indexed site)

    Production (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) California - Coastal Region Onshore Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 29 28 28 1980's 27 31 34 34 28 28 26 24 23 23 1990's 23 20 20 17 16 14 13 17 12 8 2000's 10 12 11 11 10 18 9 12 11 12 2010's 12 11 11 12 13 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure

  13. California - Los Angeles Basin Onshore Dry Natural Gas Reserves Estimated

    Energy Information Administration (EIA) (indexed site)

    Production (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) California - Los Angeles Basin Onshore Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 30 22 23 1980's 19 22 13 16 26 22 17 17 15 15 1990's 10 11 10 9 9 8 10 10 9 9 2000's 8 9 9 10 10 9 8 8 6 7 2010's 6 6 6 6 7 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  14. California - San Joaquin Basin Onshore Dry Natural Gas Reserves Estimated

    Energy Information Administration (EIA) (indexed site)

    Production (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) California - San Joaquin Basin Onshore Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 235 252 285 1980's 238 310 290 307 342 323 313 292 286 259 1990's 252 270 245 219 213 188 186 178 217 237 2000's 256 307 264 238 220 234 232 227 217 214 2010's 220 289 178 165 150 - = No Data Reported; -- = Not Applicable; NA = Not

  15. California Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) California Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 208 2010's 198 196 198 199 203 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease

  16. California Federal Offshore Crude Oil + Lease Condensate Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) California Federal Offshore Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 22 2010's 19 22 15 20 20 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016

  17. California Federal Offshore Dry Natural Gas Reserves Estimated Production

    Energy Information Administration (EIA) (indexed site)

    (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) California Federal Offshore Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 4 4 5 1980's 5 53 46 37 36 1990's 41 47 48 45 47 47 49 37 37 37 2000's 46 44 46 47 47 33 37 40 36 37 2010's 28 31 22 21 20 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release

  18. California Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) California Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 160 1980's 152 180 151 144 115 1990's 117 140 131 107 98 98 81 65 51 47 2000's 80 94 88 87 77 85 88 101 88 80 2010's 69 64 59 46 42 - = No Data Reported; -- = Not Applicable; NA = Not

  19. California State Offshore Crude Oil + Lease Condensate Estimated Production

    Energy Information Administration (EIA) (indexed site)

    from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) California State Offshore Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 14 2010's 13 12 13 14 14 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring

  20. California State Offshore Dry Natural Gas Reserves Estimated Production

    Energy Information Administration (EIA) (indexed site)

    (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) California State Offshore Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 7 11 11 1980's 10 16 12 11 9 1990's 8 7 10 7 6 6 8 7 8 12 2000's 8 8 7 6 7 7 6 6 3 6 2010's 5 5 5 5 6 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next

  1. Colorado Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Colorado Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 30 2010's 33 41 52 70 102 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease

  2. Methodology for Estimating Ingestion Dose for Emergency Response at SRS

    SciTech Connect

    Simpkins, A.A.

    2003-07-21

    At the Savannah River Site (SRS), emergency response computer models are used to estimate dose following releases of radioactive materials to the environment. Downwind air and ground concentrations and their associated doses from inhalation and ground shine pathways are estimated. The emergency response model (PUFF-PLUME) uses real-time data to track either instantaneous (puff) or continuous (plume) releases. A site-specific ingestion dose model was developed for use with PUFF-PLUME that includes the following ingestion dose pathways pertinent to the surrounding SRS area: milk, beef, water, and fish. The model is simplistic and can be used with existing code output.

  3. Utah Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet)

    Energy Information Administration (EIA) (indexed site)

    Estimated Production (Billion Cubic Feet) Utah Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 62 58 54 1980's 61 79 87 68 76 73 60 60 40 64 1990's 71 81 111 165 184 165 180 177 216 220 2000's 226 288 286 278 282 308 349 365 417 447 2010's 432 449 478 456 433 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  4. Wyoming Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Wyoming Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 51 2010's 53 55 57 64 75 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease

  5. Synchrophasor Measurement-Based Wind Plant Inertia Estimation: Preprint

    SciTech Connect

    Zhang, Y.; Bank, J.; Wan, Y. H.; Muljadi, E.; Corbus, D.

    2013-05-01

    The total inertia stored in all rotating masses that are connected to power systems, such as synchronous generations and induction motors, is an essential force that keeps the system stable after disturbances. To ensure bulk power system stability, there is a need to estimate the equivalent inertia available from a renewable generation plant. An equivalent inertia constant analogous to that of conventional rotating machines can be used to provide a readily understandable metric. This paper explores a method that utilizes synchrophasor measurements to estimate the equivalent inertia that a wind plant provides to the system.

  6. New Mexico Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) New Mexico Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 60 2010's 65 72 86 102 124 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease

  7. New York Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) New York Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 11 1980's 10 11 9 12 18 18 27 23 19 22 1990's 18 19 22 22 21 16 21 18 16 15 2000's 14 28 35 35 44 51 49 44 46 35 2010's 35 30 26 22 19 - = No Data Reported; -- = Not Applicable; NA = Not

  8. North Dakota Crude Oil + Lease Condensate Estimated Production from

    Energy Information Administration (EIA) (indexed site)

    Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) North Dakota Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 84 2010's 114 152 251 314 394 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil

  9. Ohio Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Ohio Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 4 2010's 5 4 5 7 14 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate

  10. Ohio Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Ohio Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 32 1980's 26 19 19 30 51 51 47 45 69 62 1990's 83 77 68 67 79 67 57 48 42 52 2000's 48 48 60 62 63 61 63 63 70 69 2010's 65 68 65 144 486 - = No Data Reported; -- = Not Applicable; NA = Not

  11. Oklahoma Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Oklahoma Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 63 2010's 63 79 85 113 132 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease

  12. Pennsylvania Crude Oil + Lease Condensate Estimated Production from

    Energy Information Administration (EIA) (indexed site)

    Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Pennsylvania Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 2 2010's 3 3 5 6 7 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease

  13. $100 billion mistake: is the windfall revenue estimate too high

    SciTech Connect

    Samuelson, R.J.

    1980-04-26

    An economic analysis of the Windfall Profits Tax (as proposed at the time) suggests that the estimate of a $227 billion revenue over the next decade may be as much as $100 billion too high. This judgment is based on provisions in the law allowing states to deduct severance taxes up to 15 percent on oil before federal taxes are paid and offering tax incentives for tertiary projects. The arithmetic, particularly in the case of enhanced oil recovery, illustrates how the incentives could shift more production from a 70% to a 30% tax rate than the Federal government had estimated. (DCK)

  14. Bayesian Estimator of Protein-Protein Association Probabilities

    Energy Science and Technology Software Center

    2008-05-28

    The Bayesian Estimator of Protein-Protein Association Probabilities (BEPro3) is a software tool for estimating probabilities of protein-protein association between bait and prey protein pairs using data from multiple-bait, multiple-replicate, protein LC-MS/MS affinity isolation experiments. BEPro3 is public domain software, has been tested on Windows XP and version 10.4 or newer of the Mac OS 10.4, and is freely available. A user guide, example dataset with analysis and additional documentation are included with the BEPro3 download.

  15. Texas - RRC District 1 Crude Oil + Lease Condensate Estimated Production

    Energy Information Administration (EIA) (indexed site)

    from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Texas - RRC District 1 Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 10 2010's 15 44 112 192 263 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring

  16. Texas - RRC District 1 Dry Natural Gas Reserves Estimated Production

    Energy Information Administration (EIA) (indexed site)

    (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) Texas - RRC District 1 Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 119 110 124 1980's 112 139 100 87 94 114 116 130 161 206 1990's 161 159 141 112 97 89 86 105 113 107 2000's 86 104 98 100 120 128 109 92 85 82 2010's 113 218 422 678 854 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  17. Texas - RRC District 10 Crude Oil + Lease Condensate Estimated Production

    Energy Information Administration (EIA) (indexed site)

    from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Texas - RRC District 10 Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 16 2010's 22 30 40 43 40 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages:

  18. Texas - RRC District 10 Dry Natural Gas Reserves Estimated Production

    Energy Information Administration (EIA) (indexed site)

    (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) Texas - RRC District 10 Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1,033 948 896 1980's 854 808 734 621 587 549 489 471 515 515 1990's 492 472 509 470 500 455 457 387 418 408 2000's 386 373 337 338 375 398 450 482 574 553 2010's 569 650 698 686 632 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  19. Texas - RRC District 2 Onshore Crude Oil + Lease Condensate Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Texas - RRC District 2 Onshore Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 10 2010's 15 46 107 170 234 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date:

  20. Texas - RRC District 2 Onshore Dry Natural Gas Reserves Estimated

    Energy Information Administration (EIA) (indexed site)

    Production (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) Texas - RRC District 2 Onshore Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 396 349 413 1980's 366 404 374 343 320 328 341 349 318 291 1990's 254 244 246 232 224 189 190 214 219 306 2000's 361 322 288 282 296 305 323 301 310 259 2010's 237 306 430 534 673 - = No Data Reported; -- = Not Applicable; NA = Not

  1. Texas - RRC District 3 Onshore Crude Oil + Lease Condensate Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Texas - RRC District 3 Onshore Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 40 2010's 44 40 42 48 60 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016

  2. Texas - RRC District 3 Onshore Dry Natural Gas Reserves Estimated

    Energy Information Administration (EIA) (indexed site)

    Production (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) Texas - RRC District 3 Onshore Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1,063 1,003 955 1980's 865 796 782 740 752 673 639 569 533 517 1990's 474 470 502 532 600 701 856 886 781 813 2000's 883 741 588 576 582 558 532 512 505 509 2010's 508 409 350 317 321 - = No Data Reported; -- = Not Applicable; NA = Not

  3. Texas - RRC District 4 Onshore Crude Oil + Lease Condensate Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Texas - RRC District 4 Onshore Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 14 2010's 15 17 21 23 25 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016

  4. Texas - RRC District 5 Crude Oil + Lease Condensate Estimated Production

    Energy Information Administration (EIA) (indexed site)

    from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Texas - RRC District 5 Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 3 2010's 3 4 5 6 6 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude

  5. Texas - RRC District 6 Crude Oil + Lease Condensate Estimated Production

    Energy Information Administration (EIA) (indexed site)

    from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Texas - RRC District 6 Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 18 2010's 18 18 19 19 20 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages:

  6. Texas - RRC District 6 Dry Natural Gas Reserves Estimated Production

    Energy Information Administration (EIA) (indexed site)

    (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) Texas - RRC District 6 Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 252 275 321 1980's 352 365 381 341 402 396 415 395 416 453 1990's 534 522 532 619 596 620 583 599 594 591 2000's 575 644 624 642 683 752 774 896 983 1,004 2010's 1,017 1,079 1,124 1,057 1,002 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  7. Texas - RRC District 8 Crude Oil + Lease Condensate Estimated Production

    Energy Information Administration (EIA) (indexed site)

    from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Texas - RRC District 8 Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 121 2010's 158 156 205 228 283 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring

  8. Texas - RRC District 8 Dry Natural Gas Reserves Estimated Production

    Energy Information Administration (EIA) (indexed site)

    (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) Texas - RRC District 8 Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1,401 1,265 1,214 1980's 1,159 1,008 832 713 643 646 619 633 734 654 1990's 663 691 693 660 688 631 583 572 541 559 2000's 547 533 524 484 493 464 480 538 541 545 2010's 549 470 564 662 767 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  9. Texas - RRC District 9 Crude Oil + Lease Condensate Estimated Production

    Energy Information Administration (EIA) (indexed site)

    from Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Texas - RRC District 9 Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 15 2010's 17 21 22 21 21 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages:

  10. Texas - RRC District 9 Dry Natural Gas Reserves Estimated Production

    Energy Information Administration (EIA) (indexed site)

    (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) Texas - RRC District 9 Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 108 130 108 1980's 99 119 149 122 130 141 128 112 117 107 1990's 106 104 99 104 100 103 104 106 101 104 2000's 144 185 258 332 412 361 407 519 650 687 2010's 733 613 611 603 616 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  11. Texas Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Texas Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 401 2010's 460 534 742 931 1,160 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease

  12. Texas State Offshore Crude Oil + Lease Condensate Estimated Production from

    Energy Information Administration (EIA) (indexed site)

    Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Texas State Offshore Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 1 2010's 1 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus

  13. Texas State Offshore Dry Natural Gas Reserves Estimated Production (Billion

    Energy Information Administration (EIA) (indexed site)

    Cubic Feet) Estimated Production (Billion Cubic Feet) Texas State Offshore Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 282 222 134 110 116 103 1990's 108 110 74 86 73 62 72 77 59 63 2000's 60 65 67 67 65 60 32 33 50 40 2010's 27 21 22 14 10 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015

  14. Kentucky Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet)

    Energy Information Administration (EIA) (indexed site)

    Estimated Production (Billion Cubic Feet) Kentucky Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 48 52 49 1980's 60 52 44 38 54 53 56 58 60 65 1990's 62 78 61 66 64 67 58 79 63 59 2000's 67 73 79 78 83 85 66 80 93 108 2010's 96 101 83 81 70 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next

  15. Utah Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Utah Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 23 2010's 25 27 31 36 43 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate

  16. Utah Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Utah Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 29 1980's 37 58 65 49 59 59 46 36 30 41 1990's 42 49 77 137 160 151 166 169 204 208 2000's 218 276 275 266 268 286 323 340 393 423 2010's 405 413 441 414 374 - = No Data Reported; -- = Not

  17. Virginia Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Virginia Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 6 4 8 15 15 19 18 18 1990's 7 12 25 36 51 52 55 46 61 66 2000's 71 78 75 82 72 70 102 109 126 178 2010's 172 156 153 142 145 - = No Data Reported; -- = Not Applicable; NA = Not Available; W

  18. West Virginia Crude Oil + Lease Condensate Estimated Production from

    Energy Information Administration (EIA) (indexed site)

    Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) West Virginia Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 1 2010's 1 2 3 7 9 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease

  19. BatPRO: Battery Manufacturing Cost Estimation | Argonne National Laboratory

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    BatPRO: Battery Manufacturing Cost Estimation BatPRO models a stiff prismatic pouch-type cell battery pack with cells linked in series. BatPRO models a stiff prismatic pouch-type cell battery pack with cells linked in series. BatPRO is the user-friendly, Windows-based version of BatPaC, a software modeling tool designed for policymakers and researchers who are interested in estimating the cost of lithium-ion batteries after they have reached a mature state of development and are being

  20. Florida Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Florida Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 1 2010's 2 2 3 2 4 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate

  1. Florida Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Florida Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 0 1980's 0 0 0 0 0 0 0 0 0 0 1990's 0 0 0 0 0 0 0 0 0 0 2000's 0 0 0 0 0 0 0 0 0 0 2010's 7 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  2. Illinois Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Illinois Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 5 2010's 4 4 4 3 2 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate

  3. Indiana Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Indiana Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 1 2010's 1 1 1 1 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate

  4. Kansas Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Kansas Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 40 2010's 41 41 43 46 48 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate

  5. Kansas Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Kansas Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 755 1980's 647 602 439 374 455 509 465 441 551 553 1990's 525 597 610 675 697 702 730 647 577 520 2000's 519 460 495 446 396 396 365 377 368 346 2010's 316 294 273 266 253 - = No Data

  6. Kentucky Crude Oil + Lease Condensate Estimated Production from Reserves

    Energy Information Administration (EIA) (indexed site)

    (Million Barrels) Estimated Production from Reserves (Million Barrels) Kentucky Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 2 2010's 1 1 1 1 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil plus Lease Condensate

  7. Kentucky Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Kentucky Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 52 1980's 61 53 46 40 55 53 56 58 60 65 1990's 63 80 63 68 65 69 60 81 65 60 2000's 69 77 83 80 87 88 70 84 97 113 2010's 102 107 88 87 74 - = No Data Reported; -- = Not Applicable; NA = Not

  8. Louisiana - North Crude Oil + Lease Condensate Estimated Production from

    Energy Information Administration (EIA) (indexed site)

    Reserves (Million Barrels) Estimated Production from Reserves (Million Barrels) Louisiana - North Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 11 2010's 10 11 12 13 13 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Crude Oil

  9. Louisiana - North Dry Natural Gas Reserves Estimated Production (Billion

    Energy Information Administration (EIA) (indexed site)

    Cubic Feet) Estimated Production (Billion Cubic Feet) Louisiana - North Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 317 344 335 1980's 338 402 336 335 362 311 334 316 353 362 1990's 381 366 334 327 328 343 387 424 400 377 2000's 384 390 395 401 453 498 552 553 685 992 2010's 1,721 2,563 2,614 1,899 1,561 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  10. Hydrogen Production Cost Estimate Using Biomass Gasification: Independent Review

    SciTech Connect

    Ruth, M.

    2011-10-01

    This independent review is the conclusion arrived at from data collection, document reviews, interviews and deliberation from December 2010 through April 2011 and the technical potential of Hydrogen Production Cost Estimate Using Biomass Gasification. The Panel reviewed the current H2A case (Version 2.12, Case 01D) for hydrogen production via biomass gasification and identified four principal components of hydrogen levelized cost: CapEx; feedstock costs; project financing structure; efficiency/hydrogen yield. The panel reexamined the assumptions around these components and arrived at new estimates and approaches that better reflect the current technology and business environments.

  11. Fuel Cell System for Transportation -- 2005 Cost Estimate

    SciTech Connect

    Wheeler, D.

    2006-10-01

    Independent review report of the methodology used by TIAX to estimate the cost of producing PEM fuel cells using 2005 cell stack technology. The U.S. Department of Energy (DOE) Hydrogen, Fuel Cells and Infrastructure Technologies Program Manager asked the National Renewable Energy Laboratory (NREL) to commission an independent review of the 2005 TIAX cost analysis for fuel cell production. The NREL Systems Integrator is responsible for conducting independent reviews of progress toward meeting the DOE Hydrogen Program (the Program) technical targets. An important technical target of the Program is the proton exchange membrane (PEM) fuel cell cost in terms of dollars per kilowatt ($/kW). The Program's Multi-Year Program Research, Development, and Demonstration Plan established $125/kW as the 2005 technical target. Over the last several years, the Program has contracted with TIAX, LLC (TIAX) to produce estimates of the high volume cost of PEM fuel cell production for transportation use. Since no manufacturer is yet producing PEM fuel cells in the quantities needed for an initial hydrogen-based transportation economy, these estimates are necessary for DOE to gauge progress toward meeting its targets. For a PEM fuel cell system configuration developed by Argonne National Laboratory, TIAX estimated the total cost to be $108/kW, based on assumptions of 500,000 units per year produced with 2005 cell stack technology, vertical integration of cell stack manufacturing, and balance-of-plant (BOP) components purchased from a supplier network. Furthermore, TIAX conducted a Monte Carlo analysis by varying ten key parameters over a wide range of values and estimated with 98% certainty that the mean PEM fuel cell system cost would be below DOE's 2005 target of $125/kW. NREL commissioned DJW TECHNOLOGY, LLC to form an Independent Review Team (the Team) of industry fuel cell experts and to evaluate the cost estimation process and the results reported by TIAX. The results of this

  12. Impedance-estimation methods, modeling methods, articles of manufacture, impedance-modeling devices, and estimated-impedance monitoring systems

    DOEpatents

    Richardson, John G.

    2009-11-17

    An impedance estimation method includes measuring three or more impedances of an object having a periphery using three or more probes coupled to the periphery. The three or more impedance measurements are made at a first frequency. Three or more additional impedance measurements of the object are made using the three or more probes. The three or more additional impedance measurements are made at a second frequency different from the first frequency. An impedance of the object at a point within the periphery is estimated based on the impedance measurements and the additional impedance measurements.

  13. Derived annual estimates of manufacturing energy consumption, 1974--1988

    SciTech Connect

    Not Available

    1992-08-05

    This report presents a complete series of annual estimates of purchased energy used by the manufacturing sector of the US economy, for the years 1974 to 1988. These estimates interpolate over gaps in the actual data collections, by deriving estimates for the missing years 1982--1984 and 1986--1987. For the purposes of this report, ``purchased`` energy is energy brought from offsite for use at manufacturing establishments, whether the energy is purchased from an energy vendor or procured from some other source. The actual data on purchased energy comes from two sources, the US Department of Commerce Bureau of the Census`s Annual Survey of Manufactures (ASM) and EIA`s Manufacturing Energy Consumption Survey (MECS). The ASM provides annual estimates for the years 1974 to 1981. However, in 1982 (and subsequent years) the scope of the ASM energy data was reduced to collect only electricity consumption and expenditures and total expenditures for other purchased energy. In 1985, EIA initiated the triennial MECS collecting complete energy data. The series equivalent to the ASM is referred to in the MECS as ``offsite-produced fuels.``

  14. Estimation of solar radiation from Australian meteorological observations

    SciTech Connect

    Moriarty, W.W. )

    1991-01-01

    A carefully prepared set of Australian radiation and meteorological data was used to develop a system for estimating hourly or instantaneous broad direct, diffuse and global radiation from meteorological observations. For clear sky conditions relationships developed elsewhere were adapted to Australian data. For cloudy conditions the clouds were divided into two groups, high clouds and opaque (middle and low) clouds, and corrections were made to compensate for the bias due to reporting practices for almost clear and almost overcast skies. Careful consideration was given to the decrease of visible sky toward the horizon caused by the vertical extent of opaque clouds. Equations relating cloud and other meteorological observations to the direct and diffuse radiation contained four unknown quantities, functions of cloud amount and of solar elevation, which were estimated from the data. These were proportions of incident solar radiation passed on as direct and as diffuse radiation by high clouds, and as diffuse radiation by opaque clouds. When the resulting relationships were used to estimate global, direct and diffuse radiation on a horizontal surface, the results were good, especially for global radiation. Some discrepancies between estimates and measurements of diffuse and direct radiation were probably due to erroneously high measurements of diffuse radiation.

  15. EIA Corrects Errors in Its Drilling Activity Estimates Series

    Reports and Publications

    1998-01-01

    The Energy Information Administration (EIA) has published monthly and annual estimates of oil and gas drilling activity since 1978. These data are key information for many industry analysts, serving as a leading indicator of trends in the industry and a barometer of general industry status.

  16. EIA Completes Corrections to Drilling Activity Estimates Series

    Reports and Publications

    1999-01-01

    The Energy Information Administration (EIA) has published monthly and annual estimates of oil and gas drilling activity since 1978. These data are key information for many industry analysts, serving as a leading indicator of trends in the industry and a barometer of general industry status.

  17. Estimating the potential of greenhouse gas mitigation in Kazakhstan

    SciTech Connect

    Monacrovich, E.; Pilifosova, O.; Danchuck, D.

    1996-09-01

    As part of the studies related to the obligations of the UN Framework Convention on Climate Change, the Republic of Kazakhstan started activities to inventory greenhouse gas (GHG) emissions and assess of GHG mitigation options, The objective of this paper is to present an estimate of the possibility of mitigating GHG emissions and determine the mitigation priorities. It presents a compilation of the possible options and their assessment in terms of major criteria and implementation feasibility. Taking into account the structure of GHG emissions in Kazakhstan in 1990, preliminary estimates of the potential for mitigation are presented for eight options for the energy sector and agriculture and forestry sector. The reference scenario prepared by expert assessments assumes a reduction of CO{sub 2} emissions in 1996-1998 by about 26% from the 1990 level due to general economic decline, but then emissions increase. It is estimated that the total potential for the mitigation of CO{sub 2} emissions for the year 2000 is 3% of the CO{sub 2} emissions in the reference scenario. The annual reduction in methane emissions due to the estimated options can amount to 5%-6% of the 1990 level. 10 refs., 1 fig., 4 tabs.

  18. Anisotropic parameter estimation using velocity variation with offset analysis

    SciTech Connect

    Herawati, I.; Saladin, M.; Pranowo, W.; Winardhie, S.; Priyono, A.

    2013-09-09

    Seismic anisotropy is defined as velocity dependent upon angle or offset. Knowledge about anisotropy effect on seismic data is important in amplitude analysis, stacking process and time to depth conversion. Due to this anisotropic effect, reflector can not be flattened using single velocity based on hyperbolic moveout equation. Therefore, after normal moveout correction, there will still be residual moveout that relates to velocity information. This research aims to obtain anisotropic parameters, ? and ?, using two proposed methods. The first method is called velocity variation with offset (VVO) which is based on simplification of weak anisotropy equation. In VVO method, velocity at each offset is calculated and plotted to obtain vertical velocity and parameter ?. The second method is inversion method using linear approach where vertical velocity, ?, and ? is estimated simultaneously. Both methods are tested on synthetic models using ray-tracing forward modelling. Results show that ? value can be estimated appropriately using both methods. Meanwhile, inversion based method give better estimation for obtaining ? value. This study shows that estimation on anisotropic parameters rely on the accuracy of normal moveout velocity, residual moveout and offset to angle transformation.

  19. Reassessing Wind Potential Estimates for India: Economic and Policy Implications

    SciTech Connect

    Phadke, Amol; Bharvirkar, Ranjit; Khangura, Jagmeet

    2011-09-15

    We assess developable on-shore wind potential in India at three different hub-heights and under two sensitivity scenarios – one with no farmland included, the other with all farmland included. Under the “no farmland included” case, the total wind potential in India ranges from 748 GW at 80m hub-height to 976 GW at 120m hub-height. Under the “all farmland included” case, the potential with a minimum capacity factor of 20 percent ranges from 984 GW to 1,549 GW. High quality wind energy sites, at 80m hub-height with a minimum capacity factor of 25 percent, have a potential between 253 GW (no farmland included) and 306 GW (all farmland included). Our estimates are more than 15 times the current official estimate of wind energy potential in India (estimated at 50m hub height) and are about one tenth of the official estimate of the wind energy potential in the US.

  20. Parameter Estimation for Single Diode Models of Photovoltaic Modules

    SciTech Connect

    Hansen, Clifford

    2015-03-01

    Many popular models for photovoltaic system performance employ a single diode model to compute the I - V curve for a module or string of modules at given irradiance and temperature conditions. A single diode model requires a number of parameters to be estimated from measured I - V curves. Many available parameter estimation methods use only short circuit, o pen circuit and maximum power points for a single I - V curve at standard test conditions together with temperature coefficients determined separately for individual cells. In contrast, module testing frequently records I - V curves over a wide range of irradi ance and temperature conditions which, when available , should also be used to parameterize the performance model. We present a parameter estimation method that makes use of a fu ll range of available I - V curves. We verify the accuracy of the method by recov ering known parameter values from simulated I - V curves . We validate the method by estimating model parameters for a module using outdoor test data and predicting the outdoor performance of the module.

  1. Estimating vehicle roadside encroachment frequency using accident prediction models

    SciTech Connect

    Miaou, S.-P.

    1996-07-01

    The existing data to support the development of roadside encroachment- based accident models are extremely limited and largely outdated. Under the sponsorship of the Federal Highway Administration and Transportation Research Board, several roadside safety projects have attempted to address this issue by providing rather comprehensive data collection plans and conducting pilot data collection efforts. It is clear from the results of these studies that the required field data collection efforts will be expensive. Furthermore, the validity of any field collected encroachment data may be questionable because of the technical difficulty to distinguish intentional from unintentional encroachments. This paper proposes an alternative method for estimating the basic roadside encroachment data without actually field collecting them. The method is developed by exploring the probabilistic relationships between a roadside encroachment event and a run-off-the-road event With some mild assumptions, the method is capable of providing a wide range of basic encroachment data from conventional accident prediction models. To illustrate the concept and use of such a method, some basic encroachment data are estimated for rural two-lane undivided roads. In addition, the estimated encroachment data are compared with the existing collected data. The illustration shows that the method described in this paper can be a viable approach to estimating basic encroachment data without actually collecting them which can be very costly.

  2. Microsoft PowerPoint - 15.1615_Cost Estimating Panel | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    615Cost Estimating Panel Microsoft PowerPoint - 15.1615Cost Estimating Panel PDF icon Microsoft PowerPoint - 15.1615Cost Estimating Panel More Documents & Publications ...

  3. Surface daytime net radiation estimation using artificial neural networks

    SciTech Connect

    Jiang, Bo; Zhang, Yi; Liang, Shunlin; Zhang, Xiaotong; Xiao, Zhiqiang

    2014-11-11

    Net all-wave surface radiation (Rn) is one of the most important fundamental parameters in various applications. However, conventional Rn measurements are difficult to collect because of the high cost and ongoing maintenance of recording instruments. Therefore, various empirical Rn estimation models have been developed. This study presents the results of two artificial neural network (ANN) models (general regression neural networks (GRNN) and Neuroet) to estimate Rn globally from multi-source data, including remotely sensed products, surface measurements, and meteorological reanalysis products. Rn estimates provided by the two ANNs were tested against in-situ radiation measurements obtained from 251 global sites between 1991–2010 both in global mode (all data were used to fit the models) and in conditional mode (the data were divided into four subsets and the models were fitted separately). Based on the results obtained from extensive experiments, it has been proved that the two ANNs were superior to linear-based empirical models in both global and conditional modes and that the GRNN performed better and was more stable than Neuroet. The GRNN estimates had a determination coefficient (R2) of 0.92, a root mean square error (RMSE) of 34.27 W·m–2 , and a bias of –0.61 W·m–2 in global mode based on the validation dataset. In conclusion, ANN methods are a potentially powerful tool for global Rn estimation.

  4. SCoPE: an efficient method of Cosmological Parameter Estimation

    SciTech Connect

    Das, Santanu; Souradeep, Tarun E-mail: tarun@iucaa.ernet.in

    2014-07-01

    Markov Chain Monte Carlo (MCMC) sampler is widely used for cosmological parameter estimation from CMB and other data. However, due to the intrinsic serial nature of the MCMC sampler, convergence is often very slow. Here we present a fast and independently written Monte Carlo method for cosmological parameter estimation named as Slick Cosmological Parameter Estimator (SCoPE), that employs delayed rejection to increase the acceptance rate of a chain, and pre-fetching that helps an individual chain to run on parallel CPUs. An inter-chain covariance update is also incorporated to prevent clustering of the chains allowing faster and better mixing of the chains. We use an adaptive method for covariance calculation to calculate and update the covariance automatically as the chains progress. Our analysis shows that the acceptance probability of each step in SCoPE is more than 95% and the convergence of the chains are faster. Using SCoPE, we carry out some cosmological parameter estimations with different cosmological models using WMAP-9 and Planck results. One of the current research interests in cosmology is quantifying the nature of dark energy. We analyze the cosmological parameters from two illustrative commonly used parameterisations of dark energy models. We also asses primordial helium fraction in the universe can be constrained by the present CMB data from WMAP-9 and Planck. The results from our MCMC analysis on the one hand helps us to understand the workability of the SCoPE better, on the other hand it provides a completely independent estimation of cosmological parameters from WMAP-9 and Planck data.

  5. Estimating externalities of biomass fuel cycles, Report 7

    SciTech Connect

    Barnthouse, L.W.; Cada, G.F.; Cheng, M.-D.; Easterly, C.E.; Kroodsma, R.L.; Lee, R.; Shriner, D.S.; Tolbert, V.R.; Turner, R.S.

    1998-01-01

    This report documents the analysis of the biomass fuel cycle, in which biomass is combusted to produce electricity. The major objectives of this study were: (1) to implement the methodological concepts which were developed in the Background Document (ORNL/RFF 1992) as a means of estimating the external costs and benefits of fuel cycles, and by so doing, to demonstrate their application to the biomass fuel cycle; (2) to develop, given the time and resources, a range of estimates of marginal (i.e., the additional or incremental) damages and benefits associated with selected impact-pathways from a new wood-fired power plant, using a representative benchmark technology, at two reference sites in the US; and (3) to assess the state of the information available to support energy decision making and the estimation of externalities, and by so doing, to assist in identifying gaps in knowledge and in setting future research agendas. The demonstration of methods, modeling procedures, and use of scientific information was the most important objective of this study. It provides an illustrative example for those who will, in the future, undertake studies of actual energy options and sites. As in most studies, a more comprehensive analysis could have been completed had budget constraints not been as severe. Particularly affected were the air and water transport modeling, estimation of ecological impacts, and economic valuation. However, the most important objective of the study was to demonstrate methods, as a detailed example for future studies. Thus, having severe budget constraints was appropriate from the standpoint that these studies could also face similar constraints. Consequently, an important result of this study is an indication of what can be done in such studies, rather than the specific numerical estimates themselves.

  6. Estimating Price Elasticity using Market-Level Appliance Data

    SciTech Connect

    Fujita, K. Sydny

    2015-08-04

    This report provides and update to and expansion upon our 2008 LBNL report “An Analysis of the Price Elasticity of Demand for Appliances,” in which we estimated an average relative price elasticity of -0.34 for major household appliances (Dale and Fujita 2008). Consumer responsiveness to price change is a key component of energy efficiency policy analysis; these policies influence consumer purchases through price both explicitly and implicitly. However, few studies address appliance demand elasticity in the U.S. market and public data sources are generally insufficient for rigorous estimation. Therefore, analysts have relied on a small set of outdated papers focused on limited appliance types, assuming long-term elasticities estimated for other durables (e.g., vehicles) decades ago are applicable to current and future appliance purchasing behavior. We aim to partially rectify this problem in the context of appliance efficiency standards by revisiting our previous analysis, utilizing data released over the last ten years and identifying additional estimates of durable goods price elasticities in the literature. Reviewing the literature, we find the following ranges of market-level price elasticities: -0.14 to -0.42 for appliances; -0.30 to -1.28 for automobiles; -0.47 to -2.55 for other durable goods. Brand price elasticities are substantially higher for these product groups, with most estimates -2.0 or more elastic. Using market-level shipments, sales value, and efficiency level data for 1989-2009, we run various iterations of a log-log regression model, arriving at a recommended range of short run appliance price elasticity between -0.4 and -0.5, with a default value of -0.45.

  7. Sub-Second Parallel State Estimation (Technical Report) | SciTech...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Sub-Second Parallel State Estimation Citation Details In-Document Search Title: Sub-Second Parallel State Estimation This report describes the performance of ...

  8. Impact of mesophyll diffusion on estimated global land CO2 fertilizati...

    Office of Scientific and Technical Information (OSTI)

    Impact of mesophyll diffusion on estimated global land CO2 fertilization Citation Details In-Document Search Title: Impact of mesophyll diffusion on estimated global land CO2 ...

  9. ARM Climate Modeling Best Estimate Data, A New Data Product for...

    Office of Scientific and Technical Information (OSTI)

    Journal Article: ARM Climate Modeling Best Estimate Data, A New Data Product for Climate Studies Citation Details In-Document Search Title: ARM Climate Modeling Best Estimate Data, ...

  10. NREL-How to Estimate the Economic Impacts from Renewable Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    NREL-How to Estimate the Economic Impacts from Renewable Energy Webinar Jump to: navigation, search Tool Summary LAUNCH TOOL Name: How to Estimate the Economic Impacts from...

  11. NREL-How to Estimate the Economic Impacts from Renewable Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    NREL-How to Estimate the Economic Impacts from Renewable Energy Webinar (Redirected from How to Estimate the Economic Impacts from Renewable Energy) Jump to: navigation, search...

  12. 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 Electrolysis ...

  13. Estimate of Geothermal Energy Resource in Major U.S. Sedimentary...

    Office of Scientific and Technical Information (OSTI)

    Estimate of Geothermal Energy Resource in Major U.S. Sedimentary Basins (Presentation) Citation Details In-Document Search Title: Estimate of Geothermal Energy Resource in Major ...

  14. Estimating U.S. Methane Emissions from the Natural Gas Supply...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    is to develop the empirical foundation for activity factor uncertainty estimation. 6. Transparency and credibility of inventory estimates can be improved by bolstering...

  15. U.S. Crude Oil + Lease Condensate Estimated Production from Reserves...

    Energy Information Administration (EIA) (indexed site)

    Estimated Production from Reserves (Million Barrels) U.S. Crude Oil + Lease Condensate Estimated Production from Reserves (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 ...

  16. Mass Production Cost Estimation for Direct H2 PEM Fuel Cell Systems...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Applications: 2007 Update Mass Production Cost Estimation for Direct H2 PEM Fuel Cell Systems for Automotive Applications: 2007 Update This report estimates fuel cell system cost ...

  17. Texas Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet)

    Energy Information Administration (EIA) (indexed site)

    Estimated Production (Billion Cubic Feet) Texas Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,567 5,151 4,620 4,517 4,590 4,568 1990's 4,478 4,480 4,545 4,645 4,775 4,724 4,889 4,942 4,855 4,897 2000's 5,072 5,138 5,038 5,166 5,318 5,424 5,608 6,263 7,009 7,017 2010's 6,974 7,139 7,570 7,607 7,877 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  18. CosmoSIS: A System for MC Parameter Estimation

    SciTech Connect

    Zuntz, Joe; Paterno, Marc; Jennings, Elise; Rudd, Douglas; Manzotti, Alessandro; Dodelson, Scott; Bridle, Sarah; Sehrish, Saba; Kowalkowski, James

    2015-01-01

    Cosmological parameter estimation is entering a new era. Large collaborations need to coordinate high-stakes analyses using multiple methods; furthermore such analyses have grown in complexity due to sophisticated models of cosmology and systematic uncertainties. In this paper we argue that modularity is the key to addressing these challenges: calculations should be broken up into interchangeable modular units with inputs and outputs clearly defined. We present a new framework for cosmological parameter estimation, CosmoSIS, designed to connect together, share, and advance development of inference tools across the community. We describe the modules already available in Cosmo- SIS, including camb, Planck, cosmic shear calculations, and a suite of samplers. We illustrate it using demonstration code that you can run out-of-the-box with the installer available at http://bitbucket.org/joezuntz/cosmosis.

  19. Estimating the releasable source term for Type B packages

    SciTech Connect

    Anderson, B.L.; Carlson, R.W.; Osgood, N.

    1995-11-01

    The release rate criteria for Type B packages designed to transport radioactive materials is given in Title 10 of the Code of Federal Regulations (10 CFR 71). Before the maximum allowable volumetric leakage rate that corresponds to the regulatory release rate can be calculated, estimation of the releasable source term activity density (concentration of releasable radioactive material) is required. This work provides methods for estimating the releasable source term for packages holding various contents types. The contents types considered include: (1) radioactive liquids; (2) radioactive gases; (3) radioactive powders and dispersible solids; (4) non-dispersible radioactive solids and (5) irradiated nuclear fuel rods. The numbers given, especially as related to the source term for packages transporting irradiated fuel rods, are preliminary and are subject to change upon development of improved methods and/or upon review of additional experimental data.

  20. Estimates of health risk from exposure to radioactive pollutants

    SciTech Connect

    Sullivan, R.E.; Nelson, N.S.; Ellett, W.H.; Dunning, D.E. Jr.; Leggett, R.W.; Yalcintas, M.G.; Eckerman, K.F.

    1981-11-01

    A dosimetric and health effects analysis has been performed for the Office of Radiation Programs of the Environmental Protection Agency (EPA) to assess potential hazards from radioactive pollutants. Contemporary dosimetric methods were used to obtain estimates of dose rates to reference organs from internal exposures due to either inhalation of contaminated air or ingestion of contaminated food, or from external exposures due to either immersion in contaminated air or proximity to contaminated ground surfaces. These dose rates were then used to estimate the number of premature cancer deaths arising from such exposures and the corresponding number of years of life lost in a cohort of 100,000 persons, all simultaneously liveborn and all going through life with the same risks of dying from competing causes. The risk of dying from a competing cause for a given year was taken to be the probability of dying from all causes as given in a recent actuarial life table for the total US population.

  1. Estimating Externalities of Coal Fuel Cycles, Report 3

    SciTech Connect

    Barnthouse, L.W.; Cada, G.F.; Cheng, M.-D.; Easterly, C.E.; Kroodsma, R.L.; Lee, R.; Shriner, D.S.; Tolbert, V.R.; Turner, R.S.

    1994-09-01

    The agreement between the US DOE and the EC established the specific objectives of the study: (a) to develop a methodological framework that uses existing data and models to quantify the external costs and benefits of energy; (b) to demonstrate the application of the framework to estimate the externalities of the coal, biomass, oil, natural gas, hydro, nuclear, photovoltaic, and wind fuel cycles (by agreement with the EC, the US addressed the first six of these); and (c) to identify major gaps in the availability of information to quantify impacts, damages, benefits, and externalities of fuel cycles; and to suggest priorities for future research. The main consideration in defining these objectives was a desire to have more information about externalities, and a better method for estimating them.

  2. Louisiana Dry Natural Gas Reserves Estimated Production (Billion Cubic

    Energy Information Administration (EIA) (indexed site)

    Feet) Estimated Production (Billion Cubic Feet) Louisiana Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,482 1,741 1,625 1,691 1,687 1990's 1,596 1,527 1,494 1,457 1,453 1,403 1,521 1,496 1,403 1,421 2000's 1,443 1,479 1,338 1,280 1,322 1,206 1,309 1,257 1,319 1,544 2010's 2,189 2,985 3,057 2,344 1,960 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  3. Louisiana - South Onshore Dry Natural Gas Reserves Estimated Production

    Energy Information Administration (EIA) (indexed site)

    (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) Louisiana - South Onshore Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 2,367 2,203 2,005 1980's 1,860 1,673 1,472 1,293 1,327 1,243 1,219 1,109 1,142 1,130 1990's 1,070 1,034 1,043 993 981 908 957 911 875 927 2000's 932 931 821 753 770 640 674 618 539 469 2010's 394 373 359 379 347 - = No Data Reported; -- = Not Applicable;

  4. Louisiana Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Louisiana Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,254 1,464 1,404 1,525 1,522 1990's 1,464 1,412 1,358 1,375 1,363 1,346 1,459 1,386 1,285 1,323 2000's 1,348 1,379 1,283 1,227 1,283 1,167 1,282 1,230 1,246 1,462 2010's 2,107 2,909 2,974

  5. Lower 48 States Dry Natural Gas Reserves Estimated Production (Billion

    Energy Information Administration (EIA) (indexed site)

    Cubic Feet) Estimated Production (Billion Cubic Feet) Lower 48 States Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 18,637 18,589 19,029 1980's 18,486 18,502 17,245 15,515 16,869 15,673 15,286 15,765 16,270 16,582 1990's 16,894 16,849 17,009 17,396 17,899 17,570 18,415 18,736 18,207 18,469 2000's 18,713 19,318 18,893 18,947 18,690 17,989 18,137 19,078 20,169 21,236 2010's 21,922 23,228

  6. Structure Learning and Statistical Estimation in Distribution Networks - Part II

    SciTech Connect

    Deka, Deepjyoti; Backhaus, Scott N.; Chertkov, Michael

    2015-02-13

    Limited placement of real-time monitoring devices in the distribution grid, recent trends notwithstanding, has prevented the easy implementation of demand-response and other smart grid applications. Part I of this paper discusses the problem of learning the operational structure of the grid from nodal voltage measurements. In this work (Part II), the learning of the operational radial structure is coupled with the problem of estimating nodal consumption statistics and inferring the line parameters in the grid. Based on a Linear-Coupled(LC) approximation of AC power flows equations, polynomial time algorithms are designed to identify the structure and estimate nodal load characteristics and/or line parameters in the grid using the available nodal voltage measurements. Then the structure learning algorithm is extended to cases with missing data, where available observations are limited to a fraction of the grid nodes. The efficacy of the presented algorithms are demonstrated through simulations on several distribution test cases.

  7. Colorado Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet)

    Energy Information Administration (EIA) (indexed site)

    Estimated Production (Billion Cubic Feet) Colorado Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 174 167 156 1980's 163 165 196 156 171 166 188 159 188 220 1990's 229 282 320 387 447 514 540 562 676 719 2000's 759 882 964 1,142 1,050 1,104 1,174 1,326 1,441 1,524 2010's 1,590 1,694 1,681 1,527 1,561 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  8. Papuan reserves estimated at 340-411 million bbl

    SciTech Connect

    Not Available

    1992-08-31

    This paper reports that proved and probable reserves of Papua New Guinea's potentially viable fields are placed at 340 million st-tk bbl recoverable of an estimated 791 million bbl of proved and probable oil in place. If the possible category were included, the same fields contain 411 million st-tk bbl recoverable out of 1.034 billion bbl in place, a consulting firm estimated. scientific Software-Intercomp, Denver, carried out an audit for the country's Department of Minerals and Energy in 1990, 1991, and 1992. SSI used recent Society of Petroleum Engineers definitions of proved, probable, and possible. However, the economic concept was not applied to reserve categories because PNG is examining possible changes in regulations to encourage development.

  9. Wyoming Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet)

    Energy Information Administration (EIA) (indexed site)

    Estimated Production (Billion Cubic Feet) Wyoming Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 315 329 355 1980's 416 423 391 414 484 433 402 456 510 591 1990's 583 639 714 713 780 806 782 891 838 1,213 2000's 1,070 1,286 1,388 1,456 1,524 1,642 1,695 1,825 2,026 2,233 2010's 2,218 2,088 2,001 1,992 1,718 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  10. Wyoming Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Wyoming Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 295 1980's 352 354 334 346 400 381 325 385 411 510 1990's 485 544 619 683 747 740 720 854 793 1,173 2000's 1,050 1,275 1,375 1,458 1,537 1,648 1,714 1,828 2,066 2,288 2010's 2,271 2,151 2,051

  11. New Mexico Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) New Mexico Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 961 1980's 896 925 802 677 724 700 499 607 608 649 1990's 794 879 1,027 1,212 1,220 1,242 1,272 1,423 1,339 1,421 2000's 1,400 1,415 1,397 1,284 1,397 1,383 1,332 1,264 1,274 1,264 2010's

  12. Oklahoma Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Oklahoma Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1,354 1980's 1,296 1,425 1,381 1,321 1,517 1,432 1,394 1,558 1,682 1,792 1990's 1,874 1,855 1,767 1,663 1,636 1,506 1,538 1,532 1,506 1,278 2000's 1,412 1,420 1,442 1,501 1,520 1,570 1,604

  13. Texas - RRC District 4 Onshore Dry Natural Gas Reserves Estimated

    Energy Information Administration (EIA) (indexed site)

    Production (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) Texas - RRC District 4 Onshore Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 1,319 1,188 1,208 1980's 1,117 1,053 969 926 1,065 1,044 1,169 1,158 1,089 1,117 1990's 1,075 1,114 1,124 1,213 1,226 1,264 1,263 1,292 1,323 1,236 2000's 1,289 1,395 1,398 1,381 1,295 1,232 1,157 1,172 1,156 1,013 2010's 893 886 926 819

  14. Texas - RRC District 5 Dry Natural Gas Reserves Estimated Production

    Energy Information Administration (EIA) (indexed site)

    (Billion Cubic Feet) Estimated Production (Billion Cubic Feet) Texas - RRC District 5 Dry Natural Gas Reserves Estimated Production (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 83 89 153 1980's 125 139 129 131 164 167 165 171 162 156 1990's 160 170 171 175 185 167 187 210 224 219 2000's 303 335 377 457 490 650 783 1,130 1,521 1,718 2010's 1,771 1,904 1,752 1,582 1,412 - = No Data Reported; -- = Not Applicable; NA = Not Available; W

  15. Texas Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Texas Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 4,672 4,265 3,877 3,860 3,966 3,954 1990's 3,928 3,879 3,917 4,161 4,296 4,284 4,466 4,525 4,396 4,438 2000's 4,577 4,776 4,727 4,815 4,992 5,146 5,370 6,029 6,729 6,716 2010's 6,641 6,748

  16. Estimating Fuel Cycle Externalities: Analytical Methods and Issues, Report 2

    SciTech Connect

    Barnthouse, L.W.; Cada, G.F.; Cheng, M.-D.; Easterly, C.E.; Kroodsma, R.L.; Lee, R.; Shriner, D.S.; Tolbert, V.R.; Turner, R.S.

    1994-07-01

    The activities that produce electric power typically range from extracting and transporting a fuel, to its conversion into electric power, and finally to the disposition of residual by-products. This chain of activities is called a fuel cycle. A fuel cycle has emissions and other effects that result in unintended consequences. When these consequences affect third parties (i.e., those other than the producers and consumers of the fuel-cycle activity) in a way that is not reflected in the price of electricity, they are termed ''hidden'' social costs or externalities. They are the economic value of environmental, health and any other impacts, that the price of electricity does not reflect. How do you estimate the externalities of fuel cycles? Our previous report describes a methodological framework for doing so--called the damage function approach. This approach consists of five steps: (1) characterize the most important fuel cycle activities and their discharges, where importance is based on the expected magnitude of their externalities, (2) estimate the changes in pollutant concentrations or other effects of those activities, by modeling the dispersion and transformation of each pollutant, (3) calculate the impacts on ecosystems, human health, and any other resources of value (such as man-made structures), (4) translate the estimates of impacts into economic terms to estimate damages and benefits, and (5) assess the extent to which these damages and benefits are externalities, not reflected in the price of electricity. Each step requires a different set of equations, models and analysis. Analysts generally believe this to be the best approach for estimating externalities, but it has hardly been used! The reason is that it requires considerable analysis and calculation, and to this point in time, the necessary equations and models have not been assembled. Equally important, the process of identifying and estimating externalities leads to a number of complex issues

  17. RSMASS: A simple model for estimating reactor and shield masses

    SciTech Connect

    Marshall, A.C.; Aragon, J.; Gallup, D.

    1987-01-01

    A simple mathematical model (RSMASS) has been developed to provide rapid estimates of reactor and shield masses for space-based reactor power systems. Approximations are used rather than correlations or detailed calculations to estimate the reactor fuel mass and the masses of the moderator, structure, reflector, pressure vessel, miscellaneous components, and the reactor shield. The fuel mass is determined either by neutronics limits, thermal/hydraulic limits, or fuel damage limits, whichever yields the largest mass. RSMASS requires the reactor power and energy, 24 reactor parameters, and 20 shield parameters to be specified. This parametric approach should be applicable to a very broad range of reactor types. Reactor and shield masses calculated by RSMASS were found to be in good agreement with the masses obtained from detailed calculations.

  18. Colorado Nonassociated Natural Gas, Wet After Lease Separation, Estimated

    Energy Information Administration (EIA) (indexed site)

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) Colorado Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 132 1980's 143 143 173 135 153 148 166 131 163 199 1990's 208 243 271 303 378 436 494 533 647 687 2000's 725 834 914 1,085 995 1,048 1,115 1,260 1,370 1,458 2010's 1,546 1,625 1,563 1,372

  19. NREL Estimates Economically Viable U.S. Renewable Generation - News

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Releases | NREL Estimates Economically Viable U.S. Renewable Generation November 19, 2015 Analysts at the Energy Department's National Renewable Energy Laboratory (NREL) are providing, for the first time, a method for measuring the economic potential of renewable energy across the United States. A study applying this new method found that renewable energy generation is economically viable in many parts of the United States largely due to rapidly declining technology costs. The report,

  20. NREL Releases Estimate of National Offshore Wind Energy Potential - News

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Releases | NREL Releases Estimate of National Offshore Wind Energy Potential September 10, 2010 The U.S. Department of Energy's National Renewable Energy Laboratory (NREL) announces the release of a new report that assesses the electricity generating potential of offshore wind resources in the United States. According to the Assessment of Offshore Wind Energy Resources for the United States, 4,150 gigawatts of potential wind turbine nameplate capacity (maximum turbine capacity) from offshore