National Library of Energy BETA

Sample records for over estimated gross

  1. Gross error detection and stage efficiency estimation in a separation process

    SciTech Connect (OSTI)

    Serth, R.W.; Srikanth, B. . Dept. of Chemical and Natural Gas Engineering); Maronga, S.J. . Dept. of Chemical and Process Engineering)

    1993-10-01

    Accurate process models are required for optimization and control in chemical plants and petroleum refineries. These models involve various equipment parameters, such as stage efficiencies in distillation columns, the values of which must be determined by fitting the models to process data. Since the data contain random and systematic measurement errors, some of which may be large (gross errors), they must be reconciled to obtain reliable estimates of equipment parameters. The problem thus involves parameter estimation coupled with gross error detection and data reconciliation. MacDonald and Howat (1988) studied the above problem for a single-stage flash distillation process. Their analysis was based on the definition of stage efficiency due to Hausen, which has some significant disadvantages in this context, as discussed below. In addition, they considered only data sets which contained no gross errors. The purpose of this article is to extend the above work by considering alternative definitions of state efficiency and efficiency estimation in the presence of gross errors.

  2. "Variable","Average Absolute Percent Differences","Percent of Projections Over- Estimated"

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

    Annual Energy Outlook Retrospective Review, 2014" "Variable","Average Absolute Percent Differences","Percent of Projections Over- Estimated" "Gross Domestic Product" "Real Gross Domestic Product (Average Cumulative Growth)* (Table 2)",0.9204312786,45.77777778 "Petroleum" "Imported Refiner Acquisition Cost of Crude Oil (Constant $) (Table 3a)",37.71300779,17.33333333 "Imported Refiner Acquisition Cost of Crude Oil

  3. Chapter 12, Survey Design and Implementation Cross-Cutting Protocols for Estimating Gross Savings: The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures

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

    12: Survey Design and Implementation Cross-Cutting Protocols for Estimating Gross Savings Robert Baumgartner, Tetra Tech Subcontract Report NREL/SR-7A30-53827 April 2013 The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures 12 - 1 Chapter 12 - Table of Contents 1 Introduction ............................................................................................................................ 2 2 The Total Survey Error Framework

  4. grossWCI.dvi

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

    Nuclear multifragmentation, Its relation to general physics A rich test-ground of the fundamentals of statistical mechanics. D.H.E. Gross 1 Hahn-Meitner Institute Glienickerstr. 100 14109 Berlin, Germany gross@hmi.de; http://www.hmi.de/people/gross/ 2 Freie Universit¨ at Berlin, Fachbereich Physik. Received: date / Revised version: date Abstract. Heat can flow from cold to hot at any phase separation, even in macroscopic systems. Therefore also Lynden-Bell's famous gravo-thermal catastrophe [1]

  5. Samantha Gross | Department of Energy

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

    Samantha Gross About Us Samantha Gross - Director, Office of International Climate and Clean Energy Samantha Gross Samantha Gross is the Director for International Climate and Clean Energy at the Office of International Affairs in the U.S. Department of Energy. She directs U.S. activities under the Clean Energy Ministerial, including the secretariat and initiatives focusing on clean energy implementation and access and energy efficiency. Her office also supports the Assistant Secretary and

  6. Quantification of the Potential Gross Economic Impacts of Five Methane

    Energy Savers [EERE]

    Reduction Scenarios | Department of Energy Quantification of the Potential Gross Economic Impacts of Five Methane Reduction Scenarios Quantification of the Potential Gross Economic Impacts of Five Methane Reduction Scenarios This study assessed five potential methane reduction scenarios from natural gas transmission, storage, and distribution (TS&D) infrastructure using published literature on the costs and the estimated quantity of methane reduced. The results show that implementation

  7. Michael Gross | Photosynthetic Antenna Research Center

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

    Michael Gross Michael Gross Michael Gross Principal Investigator E-mail: mgross@wustl.edu Phone: (314) 935-4814 Website: Washington University in St. Louis Principal Investigator Dr. Gross's research interests include analytical chemistry, biological chemistry, biophysical chemistry, FT-ICR instrument development, MALDI matrix development, mass spectrometry for protein biochemistry and biophysics, modified DNA and cancer, physical organic chemistry, protein and peptide analysis, and proteomics.

  8. LARGE-SCALE MAGNETIC HELICITY FLUXES ESTIMATED FROM MDI MAGNETIC SYNOPTIC CHARTS OVER THE SOLAR CYCLE 23

    SciTech Connect (OSTI)

    Yang Shangbin; Zhang Hongqi

    2012-10-10

    To investigate the characteristics of large-scale and long-term evolution of magnetic helicity with solar cycles, we use the method of Local Correlation Tracking to estimate the magnetic helicity evolution over solar cycle 23 from 1996 to 2009 using 795 MDI magnetic synoptic charts. The main results are as follows: the hemispheric helicity rule still holds in general, i.e., the large-scale negative (positive) magnetic helicity dominates the northern (southern) hemisphere. However, the large-scale magnetic helicity fluxes show the same sign in both hemispheres around 2001 and 2005. The global, large-scale magnetic helicity flux over the solar disk changes from a negative value at the beginning of solar cycle 23 to a positive value at the end of the cycle, while the net accumulated magnetic helicity is negative in the period between 1996 and 2009.

  9. David J. Gross and the Strong Force

    Office of Scientific and Technical Information (OSTI)

    published their proposal simultaneously with H. David Politzer, a graduate student at Harvard University who independently came up with the same idea. ... The discovery of Gross,...

  10. ,"Texas Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  11. ,"Kansas Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  12. ,"Pennsylvania Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  13. ,"Kentucky Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  14. ,"Oregon Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oregon Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301979" ,"Release...

  15. ,"Virginia Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Virginia Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  16. ,"Missouri Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Missouri Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  17. ,"Illinois Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  18. ,"Florida Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  19. ,"Utah Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  20. ,"Indiana Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Indiana Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  1. ,"Nevada Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Nevada Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301991" ,"Release...

  2. ,"Montana Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  3. ,"Ohio Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  4. ,"California Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  5. ,"Mississippi Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  6. ,"Nebraska Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Nebraska Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  7. ,"Michigan Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  8. ,"Tennessee Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Tennessee Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  9. ,"Oklahoma Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  10. ,"Wyoming Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  11. ,"Maryland Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Maryland Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  12. ,"Louisiana Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  13. ,"Colorado Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  14. David J. Gross and the Strong Force

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

    David J. Gross and the Strong Force Resources with Additional Information The 2004 Nobel Prize in Physics was awarded to David Gross for "the discovery of asymptotic freedom in the theory of the strong interaction". 'Gross, who obtained his PhD in physics in 1966, currently is a professor of physics and director of the Kavli Institute for Theoretical Physics at UC Santa Barbara. ... David Gross Courtesy of UC Santa Barbara [When on the faculty at Princeton University,] he and

  15. Fact #768: February 25, 2013 New Light Vehicle Sales and Gross Domestic

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

    Product | Department of Energy 8: February 25, 2013 New Light Vehicle Sales and Gross Domestic Product Fact #768: February 25, 2013 New Light Vehicle Sales and Gross Domestic Product Over the last four decades, new light vehicle sales have gone from a low of 9.9 million vehicles in 1970 to a high of 17.1 million vehicles sold in 2001, but along the way, there have been significant ups and downs. Those ups and downs are also reflected in the change in Gross Domestic Product (GDP) over time

  16. Estimation of the mixing layer height over a high altitude site in Central Himalayan region by using Doppler lidar

    SciTech Connect (OSTI)

    Shukla, K. K.; Phanikumar, D. V.; Newsom, Rob K.; Kumar, Niranjan; Ratnam, Venkat; Naja, M.; Singh, Narendra

    2014-03-01

    A Doppler lidar was installed at Manora Peak, Nainital (29.4 N; 79.2 E, 1958 amsl) to estimate mixing layer height for the first time by using vertical velocity variance as basic measurement parameter for the period September-November 2011. Mixing layer height is found to be located ~0.57 +/- 0.1and 0.45 +/- 0.05km AGL during day and nighttime, respectively. The estimation of mixing layer height shows good correlation (R>0.8) between different instruments and with different methods. Our results show that wavelet co-variance transform is a robust method for mixing layer height estimation.

  17. Quantification of the Potential Gross Economic Impacts of Five...

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

    Quantification of the Potential Gross Economic Impacts of Five Methane Reduction Scenarios Quantification of the Potential Gross Economic Impacts of Five Methane Reduction ...

  18. Property:DailyOpWaterUseGross | Open Energy Information

    Open Energy Info (EERE)

    Property Name DailyOpWaterUseGross Property Type Number Description Daily Operation Water Use (afday) Gross. Retrieved from "http:en.openei.orgwindex.php?titleProperty:...

  19. Fact #564: March 30, 2009 Transportation and the Gross Domestic...

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

    4: March 30, 2009 Transportation and the Gross Domestic Product, 2007 Fact 564: March 30, 2009 Transportation and the Gross Domestic Product, 2007 Transportation plays a major ...

  20. ,"West Virginia Natural Gas Gross Withdrawals (MMcf)"

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

    ,,"(202) 586-8800",,,"01042016 7:36:01 AM" "Back to Contents","Data 1: West Virginia Natural Gas Gross Withdrawals (MMcf)" "Sourcekey","N9010WV2" "Date","West...

  1. ,"New Mexico Natural Gas Gross Withdrawals (MMcf)"

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

    ,,"(202) 586-8800",,,"1292016 12:20:48 AM" "Back to Contents","Data 1: New Mexico Natural Gas Gross Withdrawals (MMcf)" "Sourcekey","N9010NM2" "Date","New Mexico...

  2. ,"Alaska Natural Gas Gross Withdrawals and Production"

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

    ,,"(202) 586-8800",,,"01042016 7:35:06 AM" "Back to Contents","Data 1: Alaska Natural Gas Gross Withdrawals and Production" "Sourcekey","N9010AK2","N9011AK2","N9012AK2"...

  3. ,"Alaska Natural Gas Gross Withdrawals and Production"

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

    ,,"(202) 586-8800",,,"01042016 7:35:07 AM" "Back to Contents","Data 1: Alaska Natural Gas Gross Withdrawals and Production" "Sourcekey","N9010AK2","N9011AK2","N9012AK2"...

  4. ,"New York Natural Gas Gross Withdrawals (MMcf)"

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

    ,,"(202) 586-8800",,,"12152015 12:10:48 PM" "Back to Contents","Data 1: New York Natural Gas Gross Withdrawals (MMcf)" "Sourcekey","N9010NY2" "Date","New York...

  5. Montana Natural Gas Gross Withdrawals (Million Cubic Feet per...

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet per Day) Montana Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 317 313...

  6. California Natural Gas Gross Withdrawals (Million Cubic Feet...

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet per Day) California Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 998...

  7. Virginia Natural Gas Gross Withdrawals (Million Cubic Feet per...

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

    Gross Withdrawals (Million Cubic Feet per Day) Virginia Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 271 275...

  8. Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals...

    Gasoline and Diesel Fuel Update (EIA)

    Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals (Million Cubic Feet per...

  9. Arizona Natural Gas Gross Withdrawals (Million Cubic Feet per...

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

    Arizona Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Arizona Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct...

  10. New Mexico Natural Gas Gross Withdrawals (Million Cubic Feet...

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

    Gross Withdrawals (Million Cubic Feet per Day) New Mexico Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 4,406...

  11. Texas--onshore Natural Gas Gross Withdrawals (Million Cubic Feet...

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

    Gross Withdrawals (Million Cubic Feet) Texas--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  12. Kansas Natural Gas Gross Withdrawals (Million Cubic Feet per...

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

    Gross Withdrawals (Million Cubic Feet per Day) Kansas Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 1,049...

  13. West Virginia Natural Gas Gross Withdrawals (Million Cubic Feet...

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet per Day) West Virginia Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006...

  14. New York Natural Gas Gross Withdrawals (Million Cubic Feet per...

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet per Day) New York Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 149 147...

  15. Estimating the supply and demand for deep geologic CO2 storage capacity over the course of the 21st Century: A meta-analysis of the literature

    SciTech Connect (OSTI)

    Dooley, James J.

    2013-08-05

    Whether there is sufficient geologic CO2 storage capacity to allow CCS to play a significant role in mitigating climate change has been the subject of debate since the 1990s. This paper presents a meta- analysis of a large body of recently published literature to derive updated estimates of the global deep geologic storage resource as well as the potential demand for this geologic CO2 storage resource over the course of this century. This analysis reveals that, for greenhouse gas emissions mitigation scenarios that have end-of-century atmospheric CO2 concentrations of between 350 ppmv and 725 ppmv, the average demand for deep geologic CO2 storage over the course of this century is between 410 GtCO2 and 1,670 GtCO2. The literature summarized here suggests that -- depending on the stringency of criteria applied to calculate storage capacity global geologic CO2 storage capacity could be: 35,300 GtCO2 of theoretical capacity; 13,500 GtCO2 of effective capacity; 3,900 GtCO2, of practical capacity; and 290 GtCO2 of matched capacity for the few regions where this narrow definition of capacity has been calculated. The cumulative demand for geologic CO2 storage is likely quite small compared to global estimates of the deep geologic CO2 storage capacity, and therefore, a lack of deep geologic CO2 storage capacity is unlikely to be an impediment for the commercial adoption of CCS technologies in this century.

  16. A Continuous Measure of Gross Primary Production for the Conterminous U.S. Derived from MODIS and AmeriFlux Data

    SciTech Connect (OSTI)

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

    2009-01-28

    The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide range of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000-2004, and was validated using observed GPP over the period 2005-2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km x 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr{sup -1} for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual variability of U.S. GPP were dominated by these extreme climate events and disturbances.

  17. Gross national happiness as a framework for health impact assessment

    SciTech Connect (OSTI)

    Pennock, Michael; Ura, Karma

    2011-01-15

    The incorporation of population health concepts and health determinants into Health Impact Assessments has created a number of challenges. The need for intersectoral collaboration has increased; the meaning of 'health' has become less clear; and the distinctions between health impacts, environmental impacts, social impacts and economic impacts have become increasingly blurred. The Bhutanese concept of Gross National Happiness may address these issues by providing an over-arching evidence-based framework which incorporates health, social, environmental and economic contributors as well as a number of other key contributors to wellbeing such as culture and governance. It has the potential to foster intersectoral collaboration by incorporating a more limited definition of health which places the health sector as one of a number of contributors to wellbeing. It also allows for the examination of the opportunity costs of health investments on wellbeing, is consistent with whole-of-government approaches to public policy and emerging models of social progress.

  18. ,"Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals...

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

    Gulf of Mexico Natural Gas Gross Withdrawals and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest...

  19. ,"New Mexico Natural Gas Gross Withdrawals and Production"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  20. ,"New Mexico Natural Gas Gross Withdrawals from Oil Wells (MMcf...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from Oil Wells (MMcf)",1,"Annual",2014 ,"Release...

  1. ,"New Mexico Natural Gas Gross Withdrawals from Gas Wells (MMcf...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from Gas Wells (MMcf)",1,"Annual",2014 ,"Release...

  2. ,"Texas Natural Gas Gross Withdrawals Total Offshore (MMcf)"

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

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals Total Offshore (MMcf)",1,"Annual",2014 ,"Release...

  3. ,"Alabama--State Offshore Natural Gas Gross Withdrawals (MMcf...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Alabama--State Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","129...

  4. ,"Louisiana--State Offshore Natural Gas Gross Withdrawals (MMcf...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana--State Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","129...

  5. ,"Texas--State Offshore Natural Gas Gross Withdrawals (MMcf)...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas--State Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","129...

  6. ,"Alaska--State Offshore Natural Gas Gross Withdrawals (MMcf...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Alaska--State Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","129...

  7. ,"US--State Offshore Natural Gas Gross Withdrawals (MMcf)"

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

    State Offshore Natural Gas Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

  8. ,"California--State Offshore Natural Gas Gross Withdrawals (MMcf...

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","California--State Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","129...

  9. Nebraska Natural Gas Gross Withdrawals and Production

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

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 2,916 2,255 1,980 1,328 1,032 402 1967-2014 From Gas Wells 2,734 2,092 1,854 1,317 1,027 400 1967-2014 From Oil Wells 182 163 126 11 5 1 1967-2014 From Shale Gas Wells 0 0 0 0 0 0 2007-2014 From Coalbed Wells 0 0 0 0 0 0 2006-2014 Repressuring 0 0 0 0 0 0 1967-2014 Vented and Flared 9 24 21 0 NA NA 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 0 2006-2014 Marketed Production 2,908 2,231 1,959 1,328 1,032 402 1967-2014 Dry Production

  10. Oregon Natural Gas Gross Withdrawals and Production

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

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 821 1,407 1,344 770 770 950 1979-2014 From Gas Wells 821 1,407 1,344 770 770 950 1979-2014 From Oil Wells 0 0 0 0 0 0 1996-2014 From Shale Gas Wells 0 0 0 0 0 0 2007-2014 From Coalbed Wells 0 0 0 0 0 0 2002-2014 Repressuring 0 0 0 0 0 0 1994-2014 Vented and Flared 0 0 0 0 0 0 1996-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 0 1994-2014 Marketed Production 821 1,407 1,344 770 770 950 1979-2014 Dry Production 821 1,407 1,344 770 770 950

  11. Pennsylvania Natural Gas Gross Withdrawals and Production

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

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 572,902 1,310,592 2,256,696 3,259,042 4,214,643 4,765,305 1967-2015 From Gas Wells 173,450 242,305 210,609 207,872 174,576 1967-2014 From Oil Wells 0 0 3,456 2,987 3,564 1967-2014 From Shale Gas Wells 399,452 1,068,288 2,042,632 3,048,182 4,036,504 2007-2014 From Coalbed Wells 0 0 0 0 0 2006-2014 Repressuring 0 0 0 0 0 1967-2014 Vented and Flared 0 0 0 0 0 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 1997-2014 Marketed Production

  12. Virginia Natural Gas Gross Withdrawals and Production

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

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 140,738 147,255 151,094 146,405 139,382 131,885 1967-2014 From Gas Wells 16,046 23,086 20,375 21,802 26,815 27,052 1967-2014 From Oil Wells 0 0 0 9 9 9 2006-2014 From Shale Gas Wells 18,284 16,433 18,501 17,212 13,016 12,226 2007-2014 From Coalbed Wells 106,408 107,736 112,219 107,383 99,542 92,599 2006-2014 Repressuring 0 0 0 0 0 0 2003-2014 Vented and Flared NA NA NA 0 NA NA 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 0 1997-2014

  13. Kansas Natural Gas Gross Withdrawals and Production

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

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 325,591 309,952 296,299 292,467 286,080 292,219 1967-2015 From Gas Wells 247,651 236,834 264,610 264,223 260,715 1967-2014 From Oil Wells 39,071 37,194 0 0 0 1967-2014 From Shale Gas Wells 0 0 0 0 0 2007-2014 From Coalbed Wells 38,869 35,924 31,689 28,244 25,365 2002-2014 Repressuring 548 521 0 NA NA 1967-2014 Vented and Flared 323 307 0 NA NA 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 2002-2014 Marketed Production 324,720 309,124

  14. Kentucky Natural Gas Gross Withdrawals and Production

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

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 113,300 135,330 124,243 106,122 94,665 78,737 1967-2014 From Gas Wells 111,782 133,521 122,578 106,122 94,665 78,737 1967-2014 From Oil Wells 1,518 1,809 1,665 0 0 0 1967-2014 From Shale Gas Wells 0 0 0 0 0 0 2007-2014 From Coalbed Wells 0 0 0 0 0 0 2006-2014 Repressuring 0 0 0 0 0 0 2006-2014 Vented and Flared 0 0 0 0 0 0 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 0 2006-2014 Marketed Production 113,300 135,330 124,243 106,122

  15. Louisiana Natural Gas Gross Withdrawals and Production

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

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 2,218,283 3,040,523 2,955,437 2,366,943 1,987,630 1,943,739 1967-2015 From Gas Wells 911,967 883,712 775,506 780,623 737,185 1967-2014 From Oil Wells 63,638 68,505 49,380 51,948 50,638 1967-2014 From Shale Gas Wells 1,242,678 2,088,306 2,130,551 1,534,372 1,199,807 2007-2014 From Coalbed Wells 0 0 0 0 0 2002-2014 Repressuring 3,606 5,015 0 2,829 3,199 1967-2014 Vented and Flared 4,578 6,302 0 3,912 4,143 1967-2014 Nonhydrocarbon Gases

  16. Contribution to the development of DOE ARM Climate Modeling Best Estimate Data (CMBE) products: Satellite data over the ARM permanent and AMF sites: Final Report

    SciTech Connect (OSTI)

    Xie, B; Dong, X; Xie, S

    2012-05-18

    To support the LLNL ARM infrastructure team Climate Modeling Best Estimate (CMBE) data development, the University of North Dakota (UND)'s group will provide the LLNL team the NASA CERES and ISCCP satellite retrieved cloud and radiative properties for the periods when they are available over the ARM permanent research sites. The current available datasets, to date, are as follows: the CERES/TERRA during 200003-200812; the CERES/AQUA during 200207-200712; and the ISCCP during 199601-200806. The detailed parameters list below: (1) CERES Shortwave radiative fluxes (net and downwelling); (2) CERES Longwave radiative fluxes (upwelling) - (items 1 & 2 include both all-sky and clear-sky fluxes); (3) CERES Layered clouds (total, high, middle, and low); (4) CERES Cloud thickness; (5) CERES Effective cloud height; (6) CERES cloud microphysical/optical properties; (7) ISCCP optical depth cloud top pressure matrix; (8) ISCCP derived cloud types (r.g., cirrus, stratus, etc.); and (9) ISCCP infrared derived cloud top pressures. (10) The UND group shall apply necessary quality checks to the original CERES and ISCCP data to remove suspicious data points. The temporal resolution for CERES data should be all available satellite overpasses over the ARM sites; for ISCCP data, it should be 3-hourly. The spatial resolution is the closest satellite field of view observations to the ARM surface sites. All the provided satellite data should be in a format that is consistent with the current ARM CMBE dataset so that the satellite data can be easily merged into the CMBE dataset.

  17. Nebraska Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

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

    Feet) Coalbed Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Coalbed Wells Nebraska Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from Coalbed

  18. Kentucky Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

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

    Feet) Coalbed Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Coalbed Wells Kentucky Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from Coalbed

  19. Maryland Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

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

    Feet) Coalbed Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Coalbed Wells Maryland Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from Coalbed

  20. Property:CoolingTowerWaterUseSummerGross | Open Energy Information

    Open Energy Info (EERE)

    Property Name CoolingTowerWaterUseSummerGross Property Type Number Description Cooling Tower Water use (summer average) (afday) Gross. Retrieved from "http:en.openei.orgw...

  1. Fact# 904: December 21, 2015 Gross Domestic Product and Vehicle...

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

    GDP and VMT Trends, 1960-2015 Graph showing gross national product and vehicle travel trends during 2015. Note: Data for the last quarter of 2015 were not available and were ...

  2. Physics Nobel winner David Gross gives public lecture at Jefferson...

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

    Physics Nobel winner David Gross gives public lecture at Jefferson Lab on June 12 (Monday) ... "The Coming Revolutions in Fundamental Physics" beginning at 8 p.m. at Jefferson Lab on ...

  3. ,"Alabama Natural Gas Gross Withdrawals from Shale Gas (Million...

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

    2015 12:34:05 PM" "Back to Contents","Data 1: Alabama Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)" "Sourcekey","NGMEPG0FGSSALMMCF" "Date","Alabama...

  4. Nevada Natural Gas Gross Withdrawals from Gas Wells (Million...

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

    from Gas Wells (Million Cubic Feet) Nevada Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  5. Other States Natural Gas Gross Withdrawals from Coalbed Wells...

    Gasoline and Diesel Fuel Update (EIA)

    Coalbed Wells (Million Cubic Feet) Other States Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2002 0 0...

  6. Other States Natural Gas Gross Withdrawals from Oil Wells (Million...

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

    Oil Wells (Million Cubic Feet) Other States Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 3,459 3,117...

  7. Gross alpha analytical modifications that improve wastewater treatment compliance

    SciTech Connect (OSTI)

    Tucker, B.J.; Arndt, S.

    2007-07-01

    This paper will propose an improvement to the gross alpha measurement that will provide more accurate gross alpha determinations and thus allow for more efficient and cost-effective treatment of site wastewaters. To evaluate the influence of salts that may be present in wastewater samples from a potentially broad range of environmental conditions, two types of efficiency curves were developed, each using a thorium-230 (Th-230) standard spike. Two different aqueous salt solutions were evaluated, one using sodium chloride, and one using salts from tap water drawn from the Bergen County, New Jersey Publicly Owned Treatment Works (POTW). For each curve, 13 to 17 solutions were prepared, each with the same concentration of Th-230 spike, but differing in the total amount of salt in the range of 0 to 100 mg. The attenuation coefficients were evaluated for the two salt types by plotting the natural log of the counted efficiencies vs. the weight of the sample's dried residue retained on the planchet. The results show that the range of the slopes for each of the attenuation curves varied by approximately a factor of 2.5. In order to better ensure the accuracy of results, and thus verify compliance with the gross alpha wastewater effluent criterion, projects depending on gross alpha measurements of environmental waters and wastewaters should employ gross alpha efficiency curves prepared with salts that mimic, as closely as possible, the salt content of the aqueous environmental matrix. (authors)

  8. Gross Gamma-Ray Calibration Blocks (May 1978) | Department of Energy

    Office of Environmental Management (EM)

    Gross Gamma-Ray Calibration Blocks (May 1978) Gross Gamma-Ray Calibration Blocks (May 1978) Gross Gamma-Ray Calibration Blocks (May 1978) PDF icon Gross Gamma-Ray Calibration Blocks (May 1978) More Documents & Publications Grade Assignments for Models Used for Calibration of Gross-Count Gamma-Ray Logging Systems (December 1983) A Brief Review of the Basis for, and the Procedures Currently Utilized in, Gross Gamma-Ray Log Calibration (October 1976) Parameter Assignments for Spectral Gamma-Ray

  9. Property:CoolingTowerWaterUseAnnlAvgGross | Open Energy Information

    Open Energy Info (EERE)

    Property Name CoolingTowerWaterUseAnnlAvgGross Property Type Number Description Cooling Tower Water use (annual average) (afday) Gross. Retrieved from "http:en.openei.orgw...

  10. Property:CoolingTowerWaterUseWinterGross | Open Energy Information

    Open Energy Info (EERE)

    lingTowerWaterUseWinterGross Property Type Number Description Cooling Tower Water use (winter average) (afday) Gross. Retrieved from "http:en.openei.orgwindex.php?titleProper...

  11. Federal Offshore California Natural Gas Gross Withdrawals (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Gross Withdrawals (Million Cubic Feet) Federal Offshore California Natural Gas Gross Withdrawals (Million 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 5,417 5,166 5,431 1980's 5,900 12,763 17,751 24,168 46,363 64,558 59,078 54,805 49,167 50,791 1990's 49,972 51,855 55,231 52,150 53,561 54,790 66,784 73,345 74,985 77,809 2000's 76,075 70,947 67,816 58,095 54,655 54,088 40,407 45,516 44,902 41,229 2010's 41,200 36,579 27,262 27,454

  12. Federal Offshore--Alabama Natural Gas Gross Withdrawals (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Offshore--Alabama Natural Gas Gross Withdrawals (Million Cubic Feet) Federal Offshore--Alabama Natural Gas Gross Withdrawals (Million 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 0 0 0 1990's 0 0 79,294 86,515 120,502 143,703 152,055 194,677 170,320 163,763 2000's 160,208 NA NA NA NA NA NA NA NA NA 2010's NA NA 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  13. Federal Offshore--Louisiana Natural Gas Gross Withdrawals (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Gross Withdrawals (Million Cubic Feet) Federal Offshore--Louisiana Natural Gas Gross Withdrawals (Million 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 3,838,521 4,101,321 4,262,607 1980's 4,200,273 4,202,553 3,879,918 3,313,354 3,750,641 3,286,091 3,071,900 3,384,442 3,418,949 3,373,680 1990's 3,549,524 3,401,801 3,304,336 3,351,101 3,513,981 3,460,103 3,689,170 3,760,953 3,759,040 3,732,046 2000's 3,671,424 NA NA NA NA NA NA NA NA NA

  14. Louisiana Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals Total Offshore (Million Cubic Feet) Louisiana Natural Gas Gross Withdrawals Total Offshore (Million 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 3,838,521 4,600,197 4,750,119 1980's 4,617,585 4,584,491 4,246,464 3,635,942 4,070,279 3,542,827 3,279,165 3,610,041 3,633,594 3,577,685 1990's 3,731,764 3,550,230 3,442,437 3,508,112 3,673,494 3,554,147 3,881,697 3,941,802 3,951,997 3,896,569 2000's 3,812,991 153,871 137,192 133,456

  15. Louisiana--State Offshore Natural Gas Gross Withdrawals (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Gross Withdrawals (Million Cubic Feet) Louisiana--State Offshore Natural Gas Gross Withdrawals (Million 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 498,876 487,512 1980's 417,312 381,938 366,546 322,588 319,638 256,736 207,265 225,599 214,645 204,005 1990's 182,240 148,429 138,101 157,011 159,513 94,044 192,527 180,848 192,956 164,523 2000's 141,567 153,871 137,192 133,456 129,245 107,584 97,479 72,868 86,198 76,386 2010's 69,836

  16. Louisiana--onshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet) Louisiana--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 1,535,033 1,538,511 1,552,603 1,608,633 1,469,698 1,357,155 1,386,478 1,434,389 2000's 1,342,963 1,370,802 1,245,270 1,244,672 1,248,050 1,202,328 1,280,758 1,309,960 1,301,523 1,482,252 2010's 2,148,447 2,969,297 2,882,193 2,289,193 1,925,968 - = No Data Reported; -- = Not Applicable; NA = Not Available;

  17. Alabama Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals Total Offshore (Million Cubic Feet) Alabama Natural Gas Gross Withdrawals Total Offshore (Million 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 0 9 13 1990's 19,861 32,603 191,605 218,023 349,380 356,598 361,068 409,091 392,320 376,435 2000's 361,289 200,862 202,002 194,339 165,630 152,902 145,762 134,451 125,502 109,214 2010's 101,487 84,270 87,398 75,660 70,827 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  18. Alabama--onshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet) Alabama--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 222,009 228,298 229,483 223,527 221,233 220,674 212,470 207,863 2000's 200,255 191,119 184,500 176,571 173,106 164,304 160,381 155,167 152,051 146,751 2010's 139,215 134,305 128,312 120,666 110,226 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  19. Alaska Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals Total Offshore (Million Cubic Feet) Alaska Natural Gas Gross Withdrawals Total Offshore (Million 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 72,813 71,946 1980's 63,355 71,477 66,852 68,776 68,315 62,454 63,007 69,656 101,440 122,595 1990's 144,064 171,665 216,377 233,198 224,301 113,552 126,051 123,854 133,111 125,841 2000's 263,958 262,937 293,580 322,010 334,125 380,568 354,816 374,204 388,188 357,490 2010's 370,148 364,702

  20. Alaska--onshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet) Alaska--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 2,409,336 2,545,144 2,861,599 3,256,352 3,247,533 3,257,096 3,245,736 3,236,241 2000's 3,265,436 3,164,843 3,183,857 3,256,295 3,309,960 3,262,379 2,850,934 3,105,086 3,027,696 2,954,896 2010's 2,826,952 2,798,220 2,857,485 2,882,956 2,803,429 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  1. Calif--onshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet) Calif--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 386,382 346,733 334,987 322,544 326,919 317,137 315,701 347,667 2000's 334,983 336,629 322,138 303,480 287,205 291,271 301,921 286,584 281,088 258,983 2010's 273,136 237,388 214,509 219,386 218,512 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  2. California Natural Gas Gross Withdrawals Total Offshore (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Gross Withdrawals Total Offshore (Million Cubic Feet) California Natural Gas Gross Withdrawals Total Offshore (Million 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 5,417 19,929 20,394 1980's 19,980 26,692 31,904 38,084 60,207 84,062 77,355 67,835 60,308 59,889 1990's 58,055 59,465 62,473 58,635 60,765 60,694 73,092 80,516 81,868 84,547 2000's 83,882 78,209 74,884 64,961 61,622 60,773 47,217 52,805 51,931 47,281 2010's 46,755 41,742

  3. Texas Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet)

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

    Gross Withdrawals Total Offshore (Million Cubic Feet) Texas Natural Gas Gross Withdrawals Total Offshore (Million 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 88,258 418,474 760,566 1980's 949,177 1,010,772 1,120,830 992,041 1,021,260 942,413 1,169,038 1,330,604 1,376,093 1,457,841 1990's 1,555,568 1,494,494 1,411,147 1,355,333 1,392,727 1,346,674 1,401,753 1,351,067 1,241,264 1,206,045 2000's 1,177,257 53,649 57,063 53,569 44,946 36,932 24,785

  4. Louisiana Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) Louisiana Natural Gas Gross Withdrawals (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 475,615 415,395 446,189 427,529 421,558 394,184 392,974 396,947 399,564 436,848 434,276 458,989 1992 453,270 402,327 420,967 411,917 431,327 417,000 427,388 382,708 381,170 414,845 406,315 428,235 1993 423,076 382,554 406,496 395,723 411,114 394,868 412,879 420,433 417,563 440,892 458,579 482,445 1994 441,368 402,280 436,425 423,914 438,127

  5. Illinois Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) Illinois Natural Gas Gross Withdrawals (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 41 38 40 39 38 37 37 38 37 40 40 41 1992 31 28 30 29 28 27 28 28 28 30 30 31 1993 30 29 29 27 27 27 27 28 28 29 27 30 1994 30 29 29 27 27 27 26 28 27 28 26 29 1995 30 29 29 27 27 27 27 28 27 28 26 29 1996 29 28 28 26 27 27 21 22 22 23 21 24 1997 23 22 22 20 21 21 17 17 17 18 16 18 1998 21 20 20 18 19 19 15 16 15 16 15 17 1999 19 18 18 17 17

  6. Indiana Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) Indiana Natural Gas Gross Withdrawals (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 21 18 20 19 19 19 19 18 19 20 19 21 1992 15 14 15 14 14 14 14 14 14 15 15 15 1993 17 15 16 16 16 15 15 15 15 17 17 17 1994 9 8 9 9 9 8 9 9 8 9 9 10 1995 4 34 22 42 21 13 22 18 8 21 28 16 1996 14 15 28 33 34 30 30 29 27 33 45 41 1997 38 40 34 34 40 29 30 40 34 39 115 52 1998 37 52 51 45 11 21 85 75 74 69 66 28 1999 76 69 79 70 82 70 66 75 59

  7. Federal Offshore Louisiana Natural Gas Gross Withdrawals and Production

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

    Annual-Million Cubic Feet Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2009 2010 2011 2012 2013 2014 View History Gross Withdrawals NA NA NA 0 0 0 1977-2014 From Gas Wells NA NA NA 0 0 0 1977-2014 From Oil Wells NA NA NA 0 0 0 1977-2014 Repressuring 1992-1998 Marketed Production 1992-1998

  8. Physics Nobel winner David Gross gives public lecture at Jefferson Lab on

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

    June 12 (Monday) | Jefferson Lab Physics Nobel winner David Gross gives public lecture at Jefferson Lab on June 12 (Monday) June 6, 2006 David Gross David Gross, Nobel Prize recipient and lecturer David Gross, Nobel Prize recipient is scheduled to give a free, public lecture titled "The Coming Revolutions in Fundamental Physics" beginning at 8 p.m. at Jefferson Lab on (Monday) June 12. He is one of three men - Frank Wilczek, H. David Politzer and Gross - to have their work

  9. Gross Input to Atmospheric Crude Oil Distillation Units

    Gasoline and Diesel Fuel Update (EIA)

    Day) Process: Gross Input to Atmospheric Crude Oil Dist. Units Operable Capacity (Calendar Day) Operating Capacity Idle Operable Capacity Operable Utilization Rate Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Process Area Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History U.S. 17,178 16,963 16,394 15,690 16,673 16,848 1985-2015 PADD 1 1,192 1,196 1,063 1,133 1,190 1,136 1985-2015 East

  10. California--State Offshore Natural Gas Gross Withdrawals (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Gross Withdrawals (Million Cubic Feet) California--State Offshore Natural Gas Gross Withdrawals (Million 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 14,763 14,963 1980's 14,080 13,929 14,153 13,916 13,844 19,504 18,277 13,030 11,141 9,098 1990's 8,083 7,610 7,242 6,484 7,204 5,904 6,309 7,171 6,883 6,738 2000's 7,808 7,262 7,068 6,866 6,966 6,685 6,809 7,289 7,029 6,052 2010's 5,554 5,163 5,051 5,470 5,961 - = No Data Reported; -- =

  11. Colorado Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) Colorado Natural Gas Gross Withdrawals (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 21,103 24,172 24,435 25,590 23,263 23,548 23,557 24,550 23,440 24,584 25,178 31,698 1992 28,269 26,307 25,490 26,125 27,205 27,139 26,396 27,842 27,128 28,391 29,527 34,175 1993 32,694 29,383 33,718 34,380 36,385 33,931 32,995 34,802 33,910 35,488 36,448 39,870 1994 39,207 35,941 38,103 38,734 41,588 36,686 38,457 39,010 39,176 40,396 39,810

  12. Kansas Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) Kansas Natural Gas Gross Withdrawals (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 64,057 54,742 58,012 52,088 50,888 46,821 45,032 42,868 43,595 50,514 58,127 63,441 1992 65,091 56,523 53,640 47,570 50,404 48,717 49,180 48,695 47,944 56,453 64,486 71,039 1993 68,326 59,556 61,876 55,016 56,230 53,159 53,089 51,079 47,670 54,487 60,596 67,071 1994 70,958 61,850 64,259 57,135 58,396 55,207 55,134 53,046 49,506 56,586 62,930

  13. Kentucky Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) Kentucky Natural Gas Gross Withdrawals (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 7,021 6,303 6,870 6,515 6,458 6,272 6,394 6,382 6,194 6,740 6,739 7,017 1992 5,425 7,142 6,716 7,270 7,191 6,365 6,320 7,295 6,011 6,813 6,684 6,458 1993 7,343 7,269 6,783 6,309 6,962 9,647 6,801 7,537 5,997 6,422 6,163 9,732 1994 6,171 6,109 5,700 5,302 5,850 8,107 5,715 6,333 5,040 5,397 5,179 8,179 1995 6,312 6,249 5,831 5,423 5,984 8,293

  14. Mississippi Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) Mississippi Natural Gas Gross Withdrawals (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 16,689 14,603 15,913 14,873 14,762 14,321 14,814 14,777 13,871 15,072 15,320 15,756 1992 15,037 13,554 14,071 13,563 13,972 13,882 13,992 13,905 11,566 14,054 14,043 13,898 1993 13,573 12,177 12,578 12,247 12,462 12,188 12,879 11,849 11,949 11,652 10,841 10,630 1994 10,324 9,474 10,554 9,984 10,227 9,886 10,159 10,675 10,780 10,098 9,632

  15. Missouri Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) Missouri Natural Gas Gross Withdrawals (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 0 0 1 2 1 1 1 1 1 2 3 2 1992 4 4 3 2 1 1 1 1 1 2 4 3 1993 2 2 2 1 0 0 0 0 0 2 3 2 1994 1 1 1 1 0 0 0 0 0 0 2 2 1995 2 1 2 2 1 1 1 0 0 1 3 3 1996 2 2 2 1 1 1 1 0 0 3 3 11 1997 2 2 0 0 0 0 0 0 0 0 0 0 1998 0 0 0 0 0 0 0 0 0 0 0 0 1999 0 0 0 0 0 0 0 0 0 0 0 0 2000 0 0 0 0 0 0 0 0 0 0 0 0 2001 0 0 0 0 0 0 0 0 0 0 2002 0 0 0 0 0 0 0 0 0 0 0 2003

  16. Montana Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) Montana Natural Gas Gross Withdrawals (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 5,317 4,533 4,861 4,866 4,600 3,543 3,583 4,173 4,023 4,479 4,241 4,783 1992 5,106 4,902 5,332 4,653 4,504 3,734 3,938 3,854 3,842 4,583 5,144 5,218 1993 5,335 4,826 5,124 4,790 4,693 4,058 3,995 3,454 4,095 5,064 4,920 5,163 1994 4,998 4,529 4,625 4,439 4,132 3,399 3,440 3,797 3,970 4,512 4,533 4,698 1995 4,965 4,316 4,752 4,417 4,186 3,459

  17. Maryland Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) Maryland Natural Gas Gross Withdrawals (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 0 0 5 0 0 5 0 0 3 0 0 16 1992 4 4 3 2 2 2 2 3 3 2 2 2 1993 2 2 2 2 1 2 3 3 3 3 3 2 1994 2 2 2 2 2 2 2 3 3 3 2 2 1995 2 2 2 2 2 2 2 2 2 2 2 2 1996 2 15 21 9 11 11 11 6 10 22 6 11 1997 2 13 18 8 10 10 9 5 9 20 5 9 1998 5 4 3 4 5 7 6 6 5 6 5 6 1999 2 1 2 2 1 2 2 2 2 1 1 1 2000 3 2 3 4 3 3 3 3 3 2 2 2 2001 3 2 3 3 3 3 3 3 3 2 2 2 2002 2 1 1 1 1

  18. Michigan Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) Michigan Natural Gas Gross Withdrawals (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 15,965 14,322 17,792 18,491 19,993 16,466 16,940 16,169 16,512 15,527 15,816 17,420 1992 14,533 13,052 16,483 15,598 13,484 21,140 16,680 17,672 19,682 18,086 14,749 19,320 1993 19,565 10,672 25,042 20,172 14,793 18,282 21,131 17,417 18,866 16,233 14,930 13,195 1994 28,151 3,543 36,182 8,227 26,191 18,882 21,165 18,682 20,799 15,884 19,038

  19. Table 6.4 Natural Gas Gross Withdrawals and Natural Gas Well Productivity, 1960-2011

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

    Natural Gas Gross Withdrawals and Natural Gas Well Productivity, 1960-2011 Year Natural Gas Gross Withdrawals From Crude Oil, Natural Gas, Coalbed, and Shale Gas Wells Natural Gas Well Productivity Texas 1 Louisiana 1 Oklahoma Other States 1 Federal Gulf of Mexico 2 Total Onshore Offshore Total Gross With- drawals From Natural Gas Wells 3 Producing Wells 4 Average Productivity Federal State Total Million Cubic Feet Million Cubic Feet Million Cubic Feet Number Cubic Feet per Well 1960 6,964,900

  20. Fact# 904: December 21, 2015 Gross Domestic Product and Vehicle Travel:

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

    Both Increased during 2015 | Department of Energy 4: December 21, 2015 Gross Domestic Product and Vehicle Travel: Both Increased during 2015 Fact# 904: December 21, 2015 Gross Domestic Product and Vehicle Travel: Both Increased during 2015 SUBSCRIBE to the Fact of the Week The nation's highway vehicle miles of travel (VMT) and the U.S. gross domestic product (GDP) reflect strikingly similar patterns, indicating the strong relationship between the nation's economy and its travel. Beginning in

  1. Spatial confinement and thermal deconfinement in the Gross-Neveu model

    SciTech Connect (OSTI)

    Malbouisson, J. M. C.; Khanna, F. C.; Malbouisson, A. P. C.

    2007-06-19

    We discuss the occurrence of spatial confinement and thermal deconfinement in the massive, D-dimensional, Gross-Neveu model with compactified spatial dimensions.

  2. Grade Assignments for Models Used for Calibration of Gross-Count Gamma-Ray

    Office of Environmental Management (EM)

    Logging Systems (December 1983) | Department of Energy Grade Assignments for Models Used for Calibration of Gross-Count Gamma-Ray Logging Systems (December 1983) Grade Assignments for Models Used for Calibration of Gross-Count Gamma-Ray Logging Systems (December 1983) Grade Assignments for Models Used for Calibration of Gross-Count Gamma-Ray Logging Systems (December 1983) PDF icon Grade Assignments for Models Used for Calibration of Gross-Count Gamma-Ray Logging Systems (December 1983) More

  3. New Mexico Natural Gas Gross Withdrawals and Production

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

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 1,341,475 1,287,682 1,276,296 1,247,394 1,265,579 1,290,139 1967-2015 From Gas Wells 616,134 556,024 653,057 588,127 535,181 1967-2014 From Oil Wells 238,580 252,326 127,009 160,649 204,054 1967-2014 From Shale Gas Wells 71,867 93,071 127,548 167,961 214,502 2007-2014 From Coalbed Wells 414,894 386,262 368,682 330,658 311,842 2002-2014 Repressuring 7,513 6,687 9,906 12,583 16,701 1967-2014 Vented and Flared 1,586 4,360 12,259 21,053

  4. Other States Total Natural Gas Gross Withdrawals and Production

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

    Monthly-Million Cubic Feet Monthly-Million Cubic Feet per Day Annual-Million Cubic Feet Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010 2011 2012 2013 2014 2015 View History Gross Withdrawals 5,864,402 6,958,125 8,225,321 689,082 633,853 595,158 1991-2015 From Gas Wells 2,523,173 2,599,172 3,177,021 362,605 328,809 1991-2014 From Oil Wells 691,643 728,857 279,627 23,391 22,817 1991-2014 From

  5. Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals and

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

    Production Monthly-Million Cubic Feet Monthly-Million Cubic Feet per Day Annual-Million Cubic Feet Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010 2011 2012 2013 2014 2015 View History Gross Withdrawals 2,259,144 1,830,913 1,527,875 1,326,697 1,275,213 1,346,074 1997-2015 From Gas Wells 1,699,908 1,353,929 1,013,914 817,340 706,413 1997-2014 From Oil Wells 559,235 476,984 513,961 509,357

  6. Estimating Methods

    Broader source: Directives, Delegations, and 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.

  7. Quantification of the Potential Gross Economic Impacts of Five Methane Reduction Scenarios

    SciTech Connect (OSTI)

    Keyser, David; Warner, Ethan; Curley, Christina

    2015-04-23

    Methane (CH4) is a potent greenhouse gas that is released from the natural gas supply chain into the atmosphere as a result of fugitive emissions1 and venting2 . We assess five potential CH4 reduction scenarios from transmission, storage, and distribution (TS&D) using published literature on the costs and the estimated quantity of CH4 reduced. We utilize cost and methane inventory data from ICF (2014) and Warner et al. (forthcoming) as well as data from Barrett and McCulloch (2014) and the American Gas Association (AGA) (2013) to estimate that the implementation of these measures could support approximately 85,000 jobs annually from 2015 to 2019 and reduce CH4 emissions from natural gas TS&D by over 40%. Based on standard input/output analysis methodology, measures are estimated to support over $8 billion in GDP annually over the same time period and allow producers to recover approximately $912 million annually in captured gas.

  8. Missouri Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet)

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

    from Oil Wells (Million Cubic Feet) Missouri Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 NA NA 2010's NA NA NA 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Oil Wells Missouri Natural Gas Gross Withdrawals

  9. Missouri Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet)

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

    from Oil Wells (Million Cubic Feet) Missouri Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 NA NA 2010's NA NA NA 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Oil Wells Missouri Natural Gas Gross Withdrawals

  10. Nevada Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet)

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

    from Gas Wells (Million Cubic Feet) Nevada Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 2010's 0 0 0 0 3 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Gas Wells Nevada Natural Gas Gross Withdrawals and

  11. Nevada Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)

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

    Shale Gas (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Shale Gas Wells Nevada Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from Shale

  12. Oregon Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)

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

    Shale Gas (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 2/29/2016 Next Release Date: 3/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Shale Gas Wells Oregon Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from Shale Gas

  13. Fact #621: May 3, 2010 Gross Vehicle Weight vs. Empty Vehicle Weight |

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

    Department of Energy 1: May 3, 2010 Gross Vehicle Weight vs. Empty Vehicle Weight Fact #621: May 3, 2010 Gross Vehicle Weight vs. Empty Vehicle Weight The gross weight of a vehicle (GVW) is the weight of the empty vehicle plus the weight of the maximum payload that the vehicle was designed to carry. In cars and small light trucks, the difference between the empty weight of the vehicle and the GVW is not significantly different (1,000 to 1,500 lbs). The largest trucks and tractor-trailers,

  14. EIA Energy Efficiency-Table 4e. Gross Output by Selected Industries...

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

    e Page Last Modified: May 2010 Table 4e. Gross Output1by Selected Industries, 1998, 2002, and 2006 (Billion 2000 Dollars 2) MECS Survey Years NAICS Subsector and Industry 1998 2002...

  15. EIA Energy Efficiency-Table 3e. Gross Output by Selected Industries...

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

    e Page Last Modified: May 2010 Table 3e. Gross Output1 by Selected Industries, 1998, 2002, and 2006 (Current Billion Dollars) MECS Survey Years NAICS Subsector and Industry 1998...

  16. 23 V.S.A. Section 1392 Gross Weight Limits on Highways | Open...

    Open Energy Info (EERE)

    Section 1392 Gross Weight Limits on HighwaysLegal Abstract Statute establishes the motor vehicle weight, load size, not to exceed 80,000 pounds without a permit. Published NA...

  17. Fact #564: March 30, 2009 Transportation and the Gross Domestic Product, 2007

    Broader source: Energy.gov [DOE]

    Transportation plays a major role in the U.S. economy. About 10% of the U.S. Gross Domestic Product (GDP) in 2007 is related to transportation. Housing, health care, and food are the only...

  18. U.S. Natural Gas Gross Withdrawals from Gas Wells (Million Cubic...

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

    Gas Wells (Million Cubic Feet) U.S. Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 1,482,053 1,363,737...

  19. U.S. Natural Gas Gross Withdrawals from Oil Wells (Million Cubic...

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

    Oil Wells (Million Cubic Feet) U.S. Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 475,614 500,196 1993...

  20. ,"Other States Total Natural Gas Gross Withdrawals and Production"

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

    Total Natural Gas Gross Withdrawals and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Other States Total Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release

  1. ,"US--Federal Offshore Natural Gas Gross Withdrawals (MMcf)"

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

    Federal Offshore Natural Gas Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","US--Federal Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  2. ,"Federal Offshore California Natural Gas Gross Withdrawals (MMcf)"

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

    Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore California Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  3. ,"Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals and Production"

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

    Gulf of Mexico Natural Gas Gross Withdrawals and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1997" ,"Release Date:","2/29/2016" ,"Next Release

  4. ,"Federal Offshore--Alabama Natural Gas Gross Withdrawals (MMcf)"

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

    Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--Alabama Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  5. ,"Federal Offshore--Louisiana Natural Gas Gross Withdrawals (MMcf)"

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

    Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--Louisiana Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  6. ,"Federal Offshore--Texas Natural Gas Gross Withdrawals (MMcf)"

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

    Natural Gas Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--Texas Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  7. "Table 2. Real Gross Domestic Product Growth Trends, Projected vs. Actual"

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

    Real Gross Domestic Product Growth Trends, Projected vs. Actual" "Projected Real GDP Growth Trend" " (cumulative average percent growth in projected real GDP from first year shown for each AEO)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO

  8. VARIATION IN EROSION/DEPOSITION RATES OVER THE LAST FIFTTY YEARS ON ALLUVIAL FAN SURFACES OF L. PLEISTOCENE-MID HOLOCENE AGE, ESTIMATIONS USING 137CS SOIL PROFILE DATA, AMARGOSA VALLEY, NEVADA

    SciTech Connect (OSTI)

    C. Harrington; R. Kelly; K.T. Ebert

    2005-08-26

    Variations in erosion and deposition for the last fifty years (based on estimates from 137Cs profiles) on surfaces (Late Pleistocene to Late Holocene in age) making up the Fortymile Wash alluvial fan south of Yucca Mountain, is a function of surface age and of desert pavement development or absence. For purposes of comparing erosion and deposition, the surfaces can be examined as three groups: (1) Late Pleistocene surfaces possess areas of desert pavement development with thin Av or sandy A horizons, formed by the trapping capabilities of the pavements. These zones of deposition are complemented by coppice dune formation on similar parts of the surface. Areas on the surface where no pavement development has occurred are erosional in nature with 0.0 +/- 0.0 cm to 1.5 +/- 0.5 cm of erosion occurring primarily by winds blowing across the surface. Overall these surfaces may show either a small net depositional gain or small erosional loss. (2) Early Holocene surfaces have no well-developed desert pavements, but may have residual gravel deposits in small areas on the surfaces. These surfaces show the most consistent erosional surface areas on which it ranges from 1.0 +/-.01 cm to 2.0+/- .01 cm. Fewer depositional forms are found on this age of surface so there is probably a net loss of 1.5 cm across these surfaces. (3) The Late Holocene surfaces show the greatest variability in erosion and deposition. Overbank deposition during floods cover many edges of these surfaces and coppice dune formation also creates depositional features. Erosion rates are highly variable and range from 0.0 +/- 0.0 to a maximum of 2.0+/-.01. Erosion occurs because of the lack of protection of the surface. However, the common areas of deposition probably result in the surface having a small net depositional gain across these surfaces. Thus, the interchannel surfaces of the Fortymile Wash fan show a variety of erosional styles as well as areas of deposition. The fan, therefore, is a dynamic system that primarily responds to the incising of the channels into the upper fan surface, and the development of protecting desert pavements with time.

  9. Federal Offshore--Texas Natural Gas Gross Withdrawals (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet) Federal Offshore--Texas Natural Gas Gross Withdrawals (Million 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 88,258 249,255 554,076 1980's 696,181 775,351 875,204 844,711 909,778 834,870 1,054,537 1,232,554 1,278,548 1,346,940 1990's 1,447,164 1,396,001 1,332,883 1,276,099 1,308,154 1,283,493 1,338,413 1,286,539 1,180,967 1,157,128 2000's 1,136,062 NA NA NA NA NA NA NA NA NA 2010's NA NA 0 0 0 - = No Data

  10. Alabama--State Offshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet) Alabama--State Offshore Natural Gas Gross Withdrawals (Million 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 0 9 13 1990's 19,861 32,603 112,311 131,508 228,878 212,895 209,013 214,414 222,000 212,673 2000's 201,081 200,862 202,002 194,339 165,630 152,902 145,762 134,451 125,502 109,214 2010's 101,487 84,270 87,398 75,660 70,827 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  11. Alaska--State Offshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet) Alaska--State Offshore Natural Gas Gross Withdrawals (Million 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 72,813 71,946 1980's 63,355 71,477 66,852 68,776 68,315 62,454 63,007 69,656 101,440 122,595 1990's 144,064 171,665 216,377 233,198 224,301 113,552 126,051 123,854 133,111 125,841 2000's 263,958 262,937 293,580 322,010 334,125 380,568 354,816 374,204 388,188 357,490 2010's 370,148 364,702 307,306

  12. Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals (Million

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

    Cubic Feet) Gross Withdrawals (Million Cubic Feet) Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1997 432,713 396,681 438,926 423,131 435,592 426,888 434,325 439,712 428,689 440,668 425,849 441,756 1998 443,757 398,519 448,486 438,144 457,815 435,237 439,093 443,144 336,241 421,315 414,058 434,518 1999 436,171 395,293 435,012 424,724 432,489 414,495 431,981 424,513 408,237 421,312 409,660 419,049 2000

  13. Texas--State Offshore Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) Texas--State Offshore Natural Gas Gross Withdrawals (Million 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 169,219 206,490 1980's 252,996 235,421 245,626 147,330 111,482 107,543 114,501 98,050 97,545 110,901 1990's 108,404 98,493 78,263 79,234 84,573 63,181 63,340 64,528 60,298 48,918 2000's 41,195 53,649 57,063 53,569 44,946 36,932 24,785 29,229 46,786 37,811 2010's 28,574 23,791 16,506 14,036 11,222 - = No

  14. U.S. Natural Gas Gross Withdrawals Offshore (Million Cubic Feet)

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

    Gross Withdrawals Offshore (Million Cubic Feet) U.S. Natural Gas Gross Withdrawals Offshore (Million 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 3,932,196 5,111,413 5,603,025 1980's 5,650,097 5,693,432 5,466,050 4,734,843 5,220,061 4,631,756 4,588,565 5,078,178 5,180,875 5,231,028 1990's 5,509,312 5,308,457 5,324,039 5,373,300 5,700,666 5,431,665 5,843,661 5,906,329 5,800,561 5,689,438 2000's 5,699,377 5,815,542 5,312,348 5,215,683 4,736,252

  15. US--Federal Offshore Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) US--Federal Offshore Natural Gas Gross Withdrawals (Million 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 3,932,196 4,355,742 4,822,114 1980's 4,902,354 4,990,667 4,772,873 4,182,233 4,706,782 4,185,519 4,185,515 4,671,801 4,746,664 4,771,411 1990's 5,046,660 4,849,657 4,771,744 4,765,865 4,996,197 4,942,089 5,246,422 5,315,514 5,185,312 5,130,746 2000's 5,043,769 5,136,962 4,615,443 4,505,443 4,055,340

  16. US--State Offshore Natural Gas Gross Withdrawals (Million Cubic Feet)

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

    Gross Withdrawals (Million Cubic Feet) US--State Offshore Natural Gas Gross Withdrawals (Million 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 755,671 780,911 1980's 747,743 702,765 693,177 552,610 513,279 446,237 403,050 406,377 434,211 459,617 1990's 462,652 458,800 552,294 607,435 704,469 489,576 597,239 590,815 615,249 558,692 2000's 655,609 678,580 696,905 710,240 680,911 684,671 629,652 618,042 653,704 586,953 2010's 575,601 549,151 489,505

  17. Quantification of the Potential Gross Economic Impacts of Five Methane Reduction Scenarios

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

    Quantification of the Potential Gross Economic Impacts of Five Methane Reduction Scenarios David Keyser and Ethan Warner National Renewable Energy Laboratory Christina Curley Colorado State University Technical Report NREL/TP-6A50-63801 April 2015 The Joint Institute for Strategic Energy Analysis is operated by the Alliance for Sustainable Energy, LLC, on behalf of the U.S. Department of Energy's National Renewable Energy Laboratory, the University of Colorado-Boulder, the Colorado School of

  18. ,"Montana Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  19. ,"Montana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  20. ,"Nebraska Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    from Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Nebraska Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  1. ,"New Mexico Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  2. ,"New Mexico Natural Gas Gross Withdrawals from Gas Wells (MMcf)"

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

    Gas Wells (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from Gas Wells (MMcf)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  3. ,"New Mexico Natural Gas Gross Withdrawals from Oil Wells (MMcf)"

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

    Oil Wells (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from Oil Wells (MMcf)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  4. ,"New Mexico Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  5. ,"New York Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    from Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New York Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  6. ,"North Dakota Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  7. ,"North Dakota Natural Gas Gross Withdrawals from Gas Wells (MMcf)"

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

    Gas Wells (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Gross Withdrawals from Gas Wells (MMcf)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  8. ,"North Dakota Natural Gas Gross Withdrawals from Oil Wells (MMcf)"

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

    Oil Wells (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Gross Withdrawals from Oil Wells (MMcf)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  9. ,"North Dakota Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  10. ,"Ohio Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1991" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  11. ,"Ohio Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  12. ,"Oklahoma Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  13. ,"Oklahoma Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  14. ,"Oregon Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oregon Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1991" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  15. ,"Pennsylvania Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1991" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  16. ,"Pennsylvania Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  17. ,"South Dakota Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","South Dakota Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  18. ,"Tennessee Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Tennessee Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  19. ,"Texas Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  20. ,"Texas Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  1. ,"U.S. Natural Gas Gross Withdrawals Offshore (MMcf)"

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

    Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Natural Gas Gross Withdrawals Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File Name:","na1090_nus_2a.xls" ,"Available

  2. ,"Utah Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  3. ,"Utah Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  4. ,"Virginia Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Virginia Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  5. ,"West Virginia Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","West Virginia Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1991" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  6. ,"West Virginia Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","West Virginia Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  7. ,"Wyoming Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  8. ,"Alabama Natural Gas Gross Withdrawals Total Offshore (MMcf)"

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

    Total Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alabama Natural Gas Gross Withdrawals Total Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File Name:","na1090_sal_2a.xls"

  9. ,"Alaska Natural Gas Gross Withdrawals Total Offshore (MMcf)"

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

    Total Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alaska Natural Gas Gross Withdrawals Total Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File Name:","na1090_sak_2a.xls"

  10. ,"California Natural Gas Gross Withdrawals Total Offshore (MMcf)"

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

    Total Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Gross Withdrawals Total Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File Name:","na1090_sca_2a.xls"

  11. ,"California Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  12. ,"California Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  13. ,"Colorado Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  14. ,"Colorado Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  15. ,"Florida Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  16. ,"Florida Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  17. ,"Illinois Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1991" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  18. ,"Illinois Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  19. ,"Indiana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Indiana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  20. ,"Kansas Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  1. ,"Kansas Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  2. ,"Kentucky Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    from Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  3. ,"Louisiana Natural Gas Gross Withdrawals Total Offshore (MMcf)"

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

    Total Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Gross Withdrawals Total Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File Name:","na1090_sla_2a.xls"

  4. ,"Louisiana Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  5. ,"Louisiana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  6. ,"Maryland Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Maryland Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  7. ,"Michigan Natural Gas Gross Withdrawals and Production"

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

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Gross Withdrawals and Production",10,"Monthly","12/2015","1/15/1989" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  8. ,"Michigan Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  9. ,"Mississippi Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  10. ,"Missouri Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

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

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Missouri Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","12/2015" ,"Release Date:","2/29/2016" ,"Next Release Date:","3/31/2016" ,"Excel File

  11. Input-output model for MACCS nuclear accident impacts estimation

    SciTech Connect (OSTI)

    Outkin, Alexander V.; Bixler, Nathan E.; Vargas, Vanessa N

    2015-01-27

    Since the original economic model for MACCS was developed, better quality economic data (as well as the tools to gather and process it) and better computational capabilities have become available. The update of the economic impacts component of the MACCS legacy model will provide improved estimates of business disruptions through the use of Input-Output based economic impact estimation. This paper presents an updated MACCS model, bases on Input-Output methodology, in which economic impacts are calculated using the Regional Economic Accounting analysis tool (REAcct) created at Sandia National Laboratories. This new GDP-based model allows quick and consistent estimation of gross domestic product (GDP) losses due to nuclear power plant accidents. This paper outlines the steps taken to combine the REAcct Input-Output-based model with the MACCS code, describes the GDP loss calculation, and discusses the parameters and modeling assumptions necessary for the estimation of long-term effects of nuclear power plant accidents.

  12. A Brief Review of the Basis for, and the Procedures Currently Utilized in, Gross Gamma-Ray Log Calibration (October 1976)

    Broader source: Energy.gov [DOE]

    A Brief Review of the Basis for, and the Procedures Currently Utilized in, Gross Gamma-Ray Log Calibration (October 1976)

  13. Chapter 17: Estimating Net Savings: Common Practices

    SciTech Connect (OSTI)

    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.

  14. Wave transmission over submerged breakwaters

    SciTech Connect (OSTI)

    Kobayashi, N.; Wurjanto, A. )

    1989-09-01

    Monochromatic wave reflection and transmission over a submerged impermeable breakwater is predicted numerically by slightly modifying the numerical model developed previously for predicting wave reflection and run-up on rough or smooth impermeable slopes. The slight modification is related to the landward boundary condition required for the transmitted wave propagating landward. In addition to the conservation equations of mass and momentum used to compute the flow field, an equation of energy is derived to estimate the rate of energy dissipation due to wave breaking. The computed reflection and transmission coefficients are shown to be in agreement with available small-scale test data. The numerical model also predicts the spatial variation of the energy dissipation, the mean water level difference, and the time-averaged volume flux per unit width, although available measurements are not sufficient for evaluating the capabilities and limitations of the numerical model for predicting these quantities.

  15. Failure of the gross theory of beta decay in neutron deficient nuclei

    SciTech Connect (OSTI)

    Firestone, R. B.; Schwengner, R.; Zuber, K.

    2015-05-28

    The neutron deficient isotopes 117-121Xe, 117-124Cs, and 122-124Ba were produced by a beam of 28Si from the LBNL SuperHILAC on a target of natMo. The isotopes were mass separated and their beta decay schemes were measured with a Total Absorption Spectrometer (TAS). The beta strengths derived from these data decreased dramatically to levels above ?1 MeV for the even-even decays; 34 MeV for even-Z, odd-N decays; 45 MeV for the odd-Z, even-N decays; and 78 MeV for the odd-Z, odd-N decays. The decreasing strength to higher excitation energies in the daughters contradicts the predictions of the Gross Theory of Beta Decay. The integrated beta strengths are instead found to be consistent with shell model predictions where the single-particle beta strengths are divided amoung many low-lying levels. The experimental beta strengths determined here have been used calculate the half-lives of 143 neutron deficient nuclei with Z=5164 to a precision of 20% with respect to the measured values.

  16. Weak decay processes in pre-supernova core evolution within the gross theory

    SciTech Connect (OSTI)

    Ferreira, R. C.; Dimarco, A. J.; Samana, A. R.; Barbero, C. A.

    2014-03-20

    The beta decay and electron capture rates are of fundamental importance in the evolution of massive stars in a pre-supernova core. The beta decay process gives its contribution by emitting electrons in the plasma of the stellar core, thereby increasing pressure, which in turn increases the temperature. From the other side, the electron capture removes free electrons from the plasma of the star core contributing to the reduction of pressure and temperature. In this work we calculate the beta decay and electron capture rates in stellar conditions for 63 nuclei of relevance in the pre-supernova stage, employing Gross Theory as the nuclear model. We use the abundances calculated with the Saha equations in the hypothesis of nuclear statistical equilibrium to evaluate the time derivative of the fraction of electrons. Our results are compared with other evaluations available in the literature. They have shown to be one order less or equal than the calculated within other models. Our results indicate that these differences may influence the evolution of the star in the later stages of pre-supernova.

  17. Table 2. Real Gross Domestic Product Growth Trends, Projected vs. Actual

    Gasoline and Diesel Fuel Update (EIA)

    Real Gross Domestic Product Growth Trends, Projected vs. Actual Projected Real GDP Growth Trend (cumulative average percent growth in projected real GDP from first year shown for each AEO) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 3.09 3.15 2.86 2.78 2.73 2.65 2.62 2.60 2.56 2.53 2.52 2.49 2.45 2.41 2.40 2.36 2.32 2.29 AEO 1995 3.66 2.77 2.53 2.71 2.67 2.61 2.55 2.48 2.46 2.45 2.45 2.43 2.39 2.35 2.31 2.27 2.24 AEO 1996 2.61

  18. Other States Natural Gas Gross Withdrawals from Gas Wells (Million Cubic

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

    Feet) Gas Wells (Million Cubic Feet) Other States Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 72,328 63,451 67,732 63,118 62,276 59,557 61,217 60,722 59,142 65,119 67,627 70,643 1992 66,374 62,007 65,284 63,487 63,488 60,701 62,949 63,036 61,442 66,259 65,974 68,514 1993 66,943 61,161 64,007 60,709 61,964 63,278 60,746 62,204 59,969 64,103 63,410 70,929 1994 65,551 60,458 63,396 60,438 60,965 61,963 60,675 62,160

  19. Other States Natural Gas Gross Withdrawals from Shale Gas (Million Cubic

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

    Feet) Shale Gas (Million Cubic Feet) Other States Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 13,204 11,926 13,204 12,778 13,204 12,778 13,204 13,204 12,778 13,204 12,778 13,204 2008 12,755 11,932 12,755 12,343 12,755 12,343 12,755 12,755 12,343 12,755 12,343 12,755 2009 12,222 11,039 12,222 11,827 12,222 11,827 12,222 12,222 11,827 12,222 11,827 12,222 2010 11,842 10,659 11,705 11,180 11,541 11,189 11,357 11,589

  20. Failure of the gross theory of beta decay in neutron deficient nuclei

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Firestone, R. B.; Schwengner, R.; Zuber, K.

    2015-05-28

    The neutron deficient isotopes 117-121Xe, 117-124Cs, and 122-124Ba were produced by a beam of 28Si from the LBNL SuperHILAC on a target of natMo. The isotopes were mass separated and their beta decay schemes were measured with a Total Absorption Spectrometer (TAS). The beta strengths derived from these data decreased dramatically to levels above ≈1 MeV for the even-even decays; 3–4 MeV for even-Z, odd-N decays; 4–5 MeV for the odd-Z, even-N decays; and 7–8 MeV for the odd-Z, odd-N decays. The decreasing strength to higher excitation energies in the daughters contradicts the predictions of the Gross Theory of Betamore » Decay. The integrated beta strengths are instead found to be consistent with shell model predictions where the single-particle beta strengths are divided amoung many low-lying levels. The experimental beta strengths determined here have been used calculate the half-lives of 143 neutron deficient nuclei with Z=51–64 to a precision of 20% with respect to the measured values.« less

  1. Cost Estimation Package

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1997-03-28

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

  2. Glass Property Models and Constraints for Estimating the Glass...

    Office of Scientific and Technical Information (OSTI)

    waste loading in HLW and LAW glasses are possible over current system planning estimates. ... be used to estimate the likely HLW and LAW glass volumes that would result if the ...

  3. Check Estimates and Independent Costs

    Broader source: Directives, Delegations, and 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.

  4. Regional Scale Surface CO2 Exchange Estimates Using a Boundary...

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

    Estimates Using a Boundary Layer Budget Method over the Southern Great Plains Williams, Ian University of Chicago Riley, William Lawrence Berkeley National Laboratory...

  5. Glass Property Models and Constraints for Estimating the Glass...

    Office of Scientific and Technical Information (OSTI)

    glass formulation and melter testing data have suggested that significant increases in waste loading in HLW and LAW glasses are possible over current system planning estimates....

  6. State Energy Production Estimates

    U.S. 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...

  7. Types of Cost Estimates

    Broader source: Directives, Delegations, and 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.

  8. Simulation of gross and net erosion of high-Z materials in the DIII-D divertor

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Wampler, William R.; Ding, R.; Stangeby, P. C.; Elder, J. D.; Tskhakaya, D.; Kirschner, A.; Guo, H. Y.; Chan, V. S.; McLean, A. G.; Snyder, P. B.; et al

    2015-12-17

    The three-dimensional Monte Carlo code ERO has been used to simulate dedicated DIII-D experiments in which Mo and W samples with different sizes were exposed to controlled and well-diagnosed divertor plasma conditions to measure the gross and net erosion rates. Experimentally, the net erosion rate is significantly reduced due to the high local redeposition probability of eroded high-Z materials, which according to the modelling is mainly controlled by the electric field and plasma density within the Chodura sheath. Similar redeposition ratios were obtained from ERO modelling with three different sheath models for small angles between the magnetic field and themore » material surface, mainly because of their similar mean ionization lengths. The modelled redeposition ratios are close to the measured value. Decreasing the potential drop across the sheath can suppress both gross and net erosion because sputtering yield is decreased due to lower incident energy while the redeposition ratio is not reduced owing to the higher electron density in the Chodura sheath. Taking into account material mixing in the ERO surface model, the net erosion rate of high-Z materials is shown to be strongly dependent on the carbon impurity concentration in the background plasma; higher carbon concentration can suppress net erosion. As a result, the principal experimental results such as net erosion rate and profile and redeposition ratio are well reproduced by the ERO simulations.« less

  9. DOE Zero Energy Ready Home Case Study: Promethean Homes Gross-Shepard Residence, Charlottesville, VA

    SciTech Connect (OSTI)

    none,

    2014-09-01

    This is the first DOE Zero Energy Ready Home for this builder, who earned a Custom Builder honor in the 2014 Housing Innovation Awards. The home included rigid mineral wool board insulation over house wrap and plywood on the 2x6 advanced framed walls, achieving HERS 33 without PV.

  10. Reservoir Temperature Estimator

    Energy Science and Technology Software Center (OSTI)

    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

  11. Geological Carbon Sequestration Storage Resource Estimates for the Ordovician St. Peter Sandstone, Illinois and Michigan Basins, USA

    SciTech Connect (OSTI)

    Barnes, David; Ellett, Kevin; Leetaru, Hannes

    2014-09-30

    The Cambro-Ordovician strata of the Midwest of the United States is a primary target for potential geological storage of CO2 in deep saline formations. The objective of this project is to develop a comprehensive evaluation of the Cambro-Ordovician strata in the Illinois and Michigan Basins above the basal Mount Simon Sandstone since the Mount Simon is the subject of other investigations including a demonstration-scale injection at the Illinois Basin Decatur Project. The primary reservoir targets investigated in this study are the middle Ordovician St Peter Sandstone and the late Cambrian to early Ordovician Knox Group carbonates. The topic of this report is a regional-scale evaluation of the geologic storage resource potential of the St Peter Sandstone in both the Illinois and Michigan Basins. Multiple deterministic-based approaches were used in conjunction with the probabilistic-based storage efficiency factors published in the DOE methodology to estimate the carbon storage resource of the formation. Extensive data sets of core analyses and wireline logs were compiled to develop the necessary inputs for volumetric calculations. Results demonstrate how the range in uncertainty of storage resource estimates varies as a function of data availability and quality, and the underlying assumptions used in the different approaches. In the simplest approach, storage resource estimates were calculated from mapping the gross thickness of the formation and applying a single estimate of the effective mean porosity of the formation. Results from this approach led to storage resource estimates ranging from 3.3 to 35.1 Gt in the Michigan Basin, and 1.0 to 11.0 Gt in the Illinois Basin at the P10 and P90 probability level, respectively. The second approach involved consideration of the diagenetic history of the formation throughout the two basins and used depth-dependent functions of porosity to derive a more realistic spatially variable model of porosity rather than applying a single estimate of porosity throughout the entire potential reservoir domains. The second approach resulted in storage resource estimates of 3.0 to 31.6 Gt in the Michigan Basin, and 0.6 to 6.1 Gt in the Illinois Basin. The third approach attempted to account for the local-scale variability in reservoir quality as a function of both porosity and permeability by using core and log analyses to calculate explicitly the net effective porosity at multiple well locations, and interpolate those results throughout the two basins. This approach resulted in storage resource estimates of 10.7 to 34.7 Gt in the Michigan Basin, and 11.2 to 36.4 Gt in the Illinois Basin. A final approach used advanced reservoir characterization as the most sophisticated means to estimating storage resource by defining reservoir properties for multiple facies within the St Peter formation. This approach was limited to the Michigan Basin since the Illinois Basin data set did not have the requisite level of data quality and sampling density to support such an analysis. Results from this approach led to storage resource estimates of 15.4 Gt to 50.1 Gt for the Michigan Basin. The observed variability in results from the four different approaches is evaluated in the context of data and methodological constraints, leading to the conclusion that the storage resource estimates from the first two approaches may be conservative, whereas the net porosity based approaches may over-estimate the resource.

  12. Estimating Specialty Costs

    Broader source: Directives, Delegations, and 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.

  13. State Energy Data Report, 1991: Consumption estimates

    SciTech Connect (OSTI)

    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.

  14. State energy data report 1993: Consumption estimates

    SciTech Connect (OSTI)

    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.

  15. Derived Annual Estimates

    U.S. 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...

  16. Cost Estimating Guide

    Broader source: Directives, Delegations, and 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.

  17. Cost Estimating Guide

    Broader source: Directives, Delegations, and 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.

  18. Assessment of model estimates of land-atmosphere CO2 exchange across Northern Eurasia

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Rawlins, M. A.; McGuire, A. D.; Kimball, J. S.; Dass, P.; Lawrence, D.; Burke, E.; Chen, X.; Delire, C.; Koven, C.; MacDougall, A.; et al

    2015-07-28

    A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climate modelmore » simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m⁻² yr⁻², equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.« less

  19. Sensitivity of Global Terrestrial Gross Primary Production to Hydrologic States Simulated by the Community Land Model Using Two Runoff Parameterizations

    SciTech Connect (OSTI)

    Lei, Huimin; Huang, Maoyi; Leung, Lai-Yung R.; Yang, Dawen; Shi, Xiaoying; Mao, Jiafu; Hayes, Daniel J.; Schwalm, C.; Wei, Yaxing; Liu, Shishi

    2014-09-01

    The terrestrial water and carbon cycles interact strongly at various spatio-temporal scales. To elucidate how hydrologic processes may influence carbon cycle processes, differences in terrestrial carbon cycle simulations induced by structural differences in two runoff generation schemes were investigated using the Community Land Model 4 (CLM4). Simulations were performed with runoff generation using the default TOPMODEL-based and the Variable Infiltration Capacity (VIC) model approaches under the same experimental protocol. The comparisons showed that differences in the simulated gross primary production (GPP) are mainly attributed to differences in the simulated leaf area index (LAI) rather than soil moisture availability. More specifically, differences in runoff simulations can influence LAI through changes in soil moisture, soil temperature, and their seasonality that affect the onset of the growing season and the subsequent dynamic feedbacks between terrestrial water, energy, and carbon cycles. As a result of a relative difference of 36% in global mean total runoff between the two models and subsequent changes in soil moisture, soil temperature, and LAI, the simulated global mean GPP differs by 20.4%. However, the relative difference in the global mean net ecosystem exchange between the two models is small (2.1%) due to competing effects on total mean ecosystem respiration and other fluxes, although large regional differences can still be found. Our study highlights the significant interactions among the water, energy, and carbon cycles and the need for reducing uncertainty in the hydrologic parameterization of land surface models to better constrain carbon cycle modeling.

  20. Magnetic nanoparticle temperature estimation

    SciTech Connect (OSTI)

    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.

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

    SciTech Connect (OSTI)

    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.

  2. Use of Cost Estimating Relationships

    Broader source: Directives, Delegations, and 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.

  3. Fixed conditions for achieving the real-valued partition function of one-dimensional Gross-Pitaevskii equation coupled with time-dependent potential

    SciTech Connect (OSTI)

    Prayitno, T. B.

    2014-03-24

    We have imposed the conditions in order to preserve the real-valued partition function in the case of onedimensional Gross-Pitaevskii equation coupled by time-dependent potential. In this case we have solved the Gross-Pitaevskii equation by means of the time-dependent perturbation theory by extending the previous work of Kivshar et al. [Phys. Lett A 278, 225–230 (2001)]. To use the method, we have treated the equation as the macroscopic quantum oscillator and found that the expression of the partition function explicitly has complex values. In fact, we have to choose not only the appropriate functions but also the suitable several values of the potential to keep the real-valued partition function.

  4. State energy data report 1996: Consumption estimates

    SciTech Connect (OSTI)

    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.

  5. What is Gross Up?

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

    reimbursement amount. You do not see the money in your pocket, but rather it offsets taxes that would have reduced the payment if we had not paid you the additional amount. For...

  6. Natural Gas Gross Withdrawals

    Gasoline and Diesel Fuel Update (EIA)

    Feet Monthly-Million Cubic Feet per Day Annual-Million Cubic Feet Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes...

  7. Natural Gas Gross Withdrawals

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

    Alaska 221,340 204,073 261,150 279,434 289,770 304,048 1991-2015 Arkansas 85,763 83,954 81,546 83,309 79,278 80,492 1991-2015 California 19,225 19,655 18,928 18,868 18,266 18,868 ...

  8. Natural Gas Gross Withdrawals

    Gasoline and Diesel Fuel Update (EIA)

    Period-Unit: Monthly-Million Cubic Feet Monthly-Million Cubic Feet per Day Annual-Million Cubic Feet Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History U.S. 2,767,207 2,765,998 2,750,252 2,817,792 2,740,123 2,822,700 1973-2015 Alaska 221,340 204,073 261,150 279,434 289,770 304,048 1991-2015 Arkansas 85,763 83,954 81,546 83,309 79,278 80,492

  9. Natural Gas Gross Withdrawals

    Gasoline and Diesel Fuel Update (EIA)

    2010 2011 2012 2013 2014 2015 View History U.S. 26,816,085 28,479,026 29,542,313 29,522,551 31,345,546 32,960,531 1936-2015 U.S. Offshore 2,875,945 2,416,644 2,044,643 1,859,469 1,818,267 1977-2014 U.S. State Offshore 575,601 549,151 489,505 505,318 514,809 1978-2014 Federal Offshore U.S. 2,300,344 1,867,492 1,555,138 1,354,151 1,303,458 1977-2014 Alaska 3,197,100 3,162,922 3,164,791 3,215,358 3,168,566 3,175,163 1967-2015 Alaska Onshore 2,826,952 2,798,220 2,857,485 2,882,956 2,803,429

  10. Natural Gas Gross Withdrawals

    Gasoline and Diesel Fuel Update (EIA)

    Monthly-Million Cubic Feet per Day Annual-Million Cubic Feet Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010 2011 2012 2013 2014 2015 View History U.S. 26,816,085 28,479,026 29,542,313 29,522,551 31,345,546 32,960,531 1936-2015 U.S. Offshore 2,875,945 2,416,644 2,044,643 1,859,469 1,818,267 1977-2014 U.S. State Offshore 575,601 549,151 489,505 505,318 514,809 1978-2014 Federal Offshore U.S.

  11. Sofia Mancheno-Gross

    Broader source: Energy.gov [DOE]

    Sofia specializes in Communications strategies on behalf of the Office of Energy Efficiency and Renewable Energy.

  12. Automated Estimating System

    Energy Science and Technology Software Center (OSTI)

    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

  13. Assessment of model estimates of land-atmosphere CO2 exchange across Northern Eurasia

    SciTech Connect (OSTI)

    Rawlins, M. A.; McGuire, A. D.; Kimball, J. S.; Dass, P.; Lawrence, D.; Burke, E.; Chen, X.; Delire, C.; Koven, C.; MacDougall, A.; Peng, S.; Rinke, A.; Saito, K.; Zhang, W.; Alkama, R.; Bohn, T. J.; Ciais, P.; Decharme, B.; Gouttevin, I.; Hajima, T.; Ji, D.; Krinner, G.; Lettenmaier, D. P.; Miller, P.; Moore, J. C.; Smith, B.; Sueyoshi, T.

    2015-07-28

    A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 19602009 at 0.5 resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m? yr?, equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (19601969 vs. 20002009), with a weakening CO2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.

  14. Fight over fuel additive rekindled

    SciTech Connect (OSTI)

    Stringer, J.

    1996-03-20

    Ethyl and EPA are trading punches over EPA`s doubts about the safety of Ethyl`s gasoline additive methylcyclopentadienyl manganese (MMT). Late last week, EPA released a statement reaffirming its position that there has not been enough research on health effects of MMT and asking gas stations to label pumps that contain the additive so consumers will be aware they are using it. Responding to that statement, Ethyl has written Administrator Carol Browner asking why she appears to be supporting the Environmental Defense Fund`s (EDF; Washington) campaign against MMT and advocating the delay of the additive use in light of its known emission-reducing characteristics. The tension began in the early `90s, when the EPA refused to allow Ethyl to market MMT and required it to perform more long-term health studies. Last October a court ordered the agency to grant Ethyl approval to use MMT in nonreformulated gasoline.

  15. Cost Estimating, Analysis, and Standardization

    Broader source: Directives, Delegations, and 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

  16. Reliability Estimates for Power Supplies

    SciTech Connect (OSTI)

    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.

  17. Gaining creative control over semiconductor nanowires

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

    Gaining creative control over semiconductor nanowires Gaining creative control over semiconductor nanowires Using a microfluidic reactor, Los Alamos researchers transformed the SLS...

  18. Robust and intelligent bearing estimation

    DOE Patents [OSTI]

    Claassen, John P. (Albuquerque, NM)

    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.

  19. Supercooled liquid water Estimation Tool

    Energy Science and Technology Software Center (OSTI)

    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.

  20. Estimating propagation velocity through a surface acoustic wave sensor

    DOE Patents [OSTI]

    Xu, Wenyuan (Oakdale, MN); Huizinga, John S. (Dellwood, MN)

    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.

  1. Examples of Cost Estimation Packages

    Broader source: Directives, Delegations, and 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.

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

    U.S. 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...

  3. GAO Cost Estimating and Assessment Guide

    Broader source: 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.

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

    Open Energy Info (EERE)

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

  5. Science On Tap - Matter over. Antimatter

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

    Science On Tap - Matter over Antimatter Science On Tap - Matter over. Antimatter WHEN: Aug 20, 2015 5:30 PM - 7:00 PM WHERE: UnQuarked Wine Room 145 Central Park Square, Los...

  6. Internal Controls Over Sensitive Compartmented Information Access...

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

    Compartmented Information Access for Selected Field Intelligence Elements, IG-0796 Internal Controls Over Sensitive Compartmented Information Access for Selected Field ...

  7. Estimate Radiological Dose for Animals

    Energy Science and Technology Software Center (OSTI)

    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

  8. Weekly Coal Production Estimation Methodology

    Gasoline and Diesel Fuel Update (EIA)

    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 ̂ () =

  9. EVMS Training Snippet: 4.1 The Over Target Baseline (OTB) and The Over

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

    Target Schedule (OTS) Implementations | Department of Energy EVMS Training Snippet: 4.1 The Over Target Baseline (OTB) and The Over Target Schedule (OTS) Implementations » EVMS Training Snippet: 4.1 The Over Target Baseline (OTB) and The Over Target Schedule (OTS) Implementations EVMS Training Snippet: 4.1 The Over Target Baseline (OTB) and The Over Target Schedule (OTS) Implementations This EVMS Training Snippet, sponsored by the Office of Project Management (PM) covers Over Target

  10. Estimates of Green potentials. Applications

    SciTech Connect (OSTI)

    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.

  11. Estimated Cost Description Determination Date:

    Office of Environmental Management (EM)

    Revised and posted 2/10/2011 *Title, Location Estimated Cost Description Determination Date: uncertain Transmittal to State: uncertain EA Approval: uncertain $50,000 FONSI: uncertain Determination Date: uncertain Transmittal to State: uncertain EA Approval: uncertain FONSI: uncertain Total Estimated Cost $70,000 Attachment: Memo, Moody to Marcinowski, III, SUBJECT: NEPA 2011 APS for DOE-SRS, Dated: Annual NEPA Planning Summary Environmental Assessments (EAs) Expected to be Initiated in the Next

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

    Office of Environmental Management (EM)

    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

  13. Weldon Spring historical dose estimate

    SciTech Connect (OSTI)

    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.

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

    SciTech Connect (OSTI)

    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.

  15. EVMS Training Snippet: 4.1 The Over Target Baseline (OTB) and The Over

    Office of Environmental Management (EM)

    Target Schedule (OTS) Implementations | Department of Energy 1 The Over Target Baseline (OTB) and The Over Target Schedule (OTS) Implementations EVMS Training Snippet: 4.1 The Over Target Baseline (OTB) and The Over Target Schedule (OTS) Implementations This EVMS Training Snippet, sponsored by the Office of Project Management (PM) covers Over Target Baseline and Over Target Schedule implementations. Link to Video Presentation | Prior Snippet (3.3) | Next Snippet (4.2) | Return to Index PDF

  16. Researchers Model Impact of Aerosols Over California

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

    Researchers Model Impact of Aerosols Over California Researchers Model Impact of Aerosols Over California Research may clarify the effectiveness of regional pollution controls May 28, 2013 Contact: Linda Vu, lvu@lbl.gov, (510) 495-2404 LosAngelesSmogv1.jpg Smog over downtown Los Angeles. Aerosols are microscopic particles-like dust, pollen and soot-that ubiquitously float around in our atmosphere. Despite their tiny stature, these particles can have a huge impact on human health, climate and the

  17. NERSC's Names and Logos over the Years

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

    names and logos over the years NERSC's Names and Logos over the Years April 16, 2014 by Francesca Verdier NERSC's name and logos have changed over the decades, reflecting the center's increasingly broad scientific mission. Founded in 1974 at Lawrence Livermore National Laboratory (LLNL) as the Controlled Thermonuclear Research Computer Center, NERSC has evolved from its early days supporting magnetic fusion research at LLNL to providing supercomputing resources across a spectrum of scientific

  18. Cladding Attachment Over Thick Exterior Rigid Insulation

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

    Cladding Attachment Over Thick Exterior Rigid Insulation Peter Baker, P.Eng. BA Webinar: High Performance Enclosure Strategies: Part II, New Construction Cladding Attachment Over Thick Exterior Rigid Insulation Background  Industry trend to using exterior rigid insulation  Increased thermal value  Condensation resistance  Increased air tightness (possibly)  Increased rainwater management (possibly)  Need to develop a means to attach cladding over thick layers of exterior

  19. Over Core Stress | Open Energy Information

    Open Energy Info (EERE)

    Analysis- Rock Over Core Stress Paleomagnetic Measurements Petrography Analysis Rock Density X-Ray Diffraction (XRD) X-Ray Fluorescence (XRF) References Page Area Activity Start...

  20. Researchers Model Impact of Aerosols Over California

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

    cooling over California using supercomputers at the Department of Energy's National Energy Research Scientific Computing Center (NERSC) and at PNNL. The scientists found that...

  1. Mandatory Photovoltaic System Cost Estimate

    Broader source: Energy.gov [DOE]

    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...

  2. Estimation of uncertainty for contour method residual stress measurements

    SciTech Connect (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 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??).

  3. Estimation of uncertainty for contour method residual stress measurements

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    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. Hydrogen Production Cost Estimate Using Biomass Gasification...

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

    Cost Estimate Using Biomass Gasification: Independent Review Hydrogen Production Cost Estimate Using Biomass Gasification: Independent Review This independent review is the ...

  5. 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...

  6. $100 billion mistake: is the windfall revenue estimate too high

    SciTech Connect (OSTI)

    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)

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

    SciTech Connect (OSTI)

    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.}

  8. Successional trajectories of rhizosphere bacterial communities over

    Office of Scientific and Technical Information (OSTI)

    consecutive seasons (Journal Article) | DOE PAGES Successional trajectories of rhizosphere bacterial communities over consecutive seasons Title: Successional trajectories of rhizosphere bacterial communities over consecutive seasons It is well known that rhizosphere microbiomes differ from those of surrounding soil, and yet we know little about how these root-associated microbial communities change through the growing season and between seasons. We analyzed the response of soil bacteria to

  9. Successional trajectories of rhizosphere bacterial communities over

    Office of Scientific and Technical Information (OSTI)

    consecutive seasons (Journal Article) | SciTech Connect Journal Article: Successional trajectories of rhizosphere bacterial communities over consecutive seasons Citation Details In-Document Search Title: Successional trajectories of rhizosphere bacterial communities over consecutive seasons It is well known that rhizosphere microbiomes differ from those of surrounding soil, and yet we know little about how these root-associated microbial communities change through the growing season and

  10. Gaining creative control over semiconductor nanowires

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

    Gaining creative control over semiconductor nanowires Gaining creative control over semiconductor nanowires Using a microfluidic reactor, Los Alamos researchers transformed the SLS process into a flow-based technique. September 26, 2013 Growth of nanowire precursors in a flowing carrier solvent Growth of nanowire precursors in a flowing carrier solvent The new "flow" solution-liquid-solid method allows scientists to slow down growth and thereby capture mechanistic details as the

  11. Guidelines for Estimating Unmetered Landscapting Water Use

    SciTech Connect (OSTI)

    None

    2010-07-30

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

  12. Estimated Cost Description Determination Date:

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

    Title, Location Estimated Cost Description Determination Date: 2010 LCLS Undulator 2 is envisioned to be a 0.2 - 2keV FEL x-ray source, capable of delivering x-rays to End Station A (ESA), located in the existing Research Yard at SLAC. It will also be configurable as a non- FEL hard x-ray source capable of delivering a chirped x-ray pulse for single-shot broad-spectrum measurements. The project would entail reconstruction of the electron beam transport to End Station A, construction and

  13. Science On Tap - Matter over. Antimatter

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

    Science On Tap - Matter over Antimatter Science On Tap - Matter over. Antimatter WHEN: Aug 20, 2015 5:30 PM - 7:00 PM WHERE: UnQuarked Wine Room 145 Central Park Square, Los Alamos, New Mexico, 87544 CONTACT: Jessica Privette 505 667-0375 CATEGORY: Bradbury INTERNAL: Calendar Login Science On Tap Event Description Science On Tap happens every third Thursday of the month, featuring a new topic each week. It begins with an informal 15-minute talk and is followed by a lively group discussion.

  14. Move Over, 'American Idol'... | Department of Energy

    Office of Environmental Management (EM)

    Over, 'American Idol'... Move Over, 'American Idol'... May 26, 2011 - 11:24am Addthis Liisa O'Neill Liisa O'Neill Former New Media Specialist, Office of Public Affairs The votes have been counted. America has spoken. 
The five finalists were so outstanding that no one cared Simon Cowell wasn't part of the action. 
 No, I'm not talking about Scotty McCreery, though we congratulate him as well. I'm talking about yesterday's "People's Choice Award" winner of the Department of Energy's

  15. Estimating Terrorist Risk with Possibility Theory

    SciTech Connect (OSTI)

    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 performed in PossibleRisk. [LEDTools] LEDTools is a general purpose linguistic evaluation tool and allows user defined universes of discourse and approximate reasoning rules, whereas PossibleRisk uses predefined universes of discourse (risk, attack, success, loss, and consequence) and rules. Also LEDTools has the capability to model a large number of threat scenarios with a graph and to integrate the scenarios (paths from the graph) into the linguistic evaluation. Example uses of PossibleRisk and LEDTools for the possibilistic evaluation of terrorist risk are provided in this report.

  16. Review of Evaluation, Measurement and Verification Approaches Used to Estimate the Load Impacts and Effectiveness of Energy Efficiency Programs

    SciTech Connect (OSTI)

    Messenger, Mike; Bharvirkar, Ranjit; Golemboski, Bill; Goldman, Charles A.; Schiller, Steven R.

    2010-04-14

    Public and private funding for end-use energy efficiency actions is expected to increase significantly in the United States over the next decade. For example, Barbose et al (2009) estimate that spending on ratepayer-funded energy efficiency programs in the U.S. could increase from $3.1 billion in 2008 to $7.5 and 12.4 billion by 2020 under their medium and high scenarios. This increase in spending could yield annual electric energy savings ranging from 0.58% - 0.93% of total U.S. retail sales in 2020, up from 0.34% of retail sales in 2008. Interest in and support for energy efficiency has broadened among national and state policymakers. Prominent examples include {approx}$18 billion in new funding for energy efficiency programs (e.g., State Energy Program, Weatherization, and Energy Efficiency and Conservation Block Grants) in the 2009 American Recovery and Reinvestment Act (ARRA). Increased funding for energy efficiency should result in more benefits as well as more scrutiny of these results. As energy efficiency becomes a more prominent component of the U.S. national energy strategy and policies, assessing the effectiveness and energy saving impacts of energy efficiency programs is likely to become increasingly important for policymakers and private and public funders of efficiency actions. Thus, it is critical that evaluation, measurement, and verification (EM&V) is carried out effectively and efficiently, which implies that: (1) Effective program evaluation, measurement, and verification (EM&V) methodologies and tools are available to key stakeholders (e.g., regulatory agencies, program administrators, consumers, and evaluation consultants); and (2) Capacity (people and infrastructure resources) is available to conduct EM&V activities and report results in ways that support program improvement and provide data that reliably compares achieved results against goals and similar programs in other jurisdictions (benchmarking). The National Action Plan for Energy Efficiency (2007) presented commonly used definitions for EM&V in the context of energy efficiency programs: (1) Evaluation (E) - The performance of studies and activities aimed at determining the effects and effectiveness of EE programs; (2) Measurement and Verification (M&V) - Data collection, monitoring, and analysis associated with the calculation of gross energy and demand savings from individual measures, sites or projects. M&V can be a subset of program evaluation; and (3) Evaluation, Measurement, and Verification (EM&V) - This term is frequently seen in evaluation literature. EM&V is a catchall acronym for determining both the effectiveness of program designs and estimates of load impacts at the portfolio, program and project level. This report is a scoping study that assesses current practices and methods in the evaluation, measurement and verification (EM&V) of ratepayer-funded energy efficiency programs, with a focus on methods and practices currently used for determining whether projected (ex-ante) energy and demand savings have been achieved (ex-post). M&V practices for privately-funded energy efficiency projects (e.g., ESCO projects) or programs where the primary focus is greenhouse gas reductions were not part of the scope of this study. We identify and discuss key purposes and uses of current evaluations of end-use energy efficiency programs, methods used to evaluate these programs, processes used to determine those methods; and key issues that need to be addressed now and in the future, based on discussions with regulatory agencies, policymakers, program administrators, and evaluation practitioners in 14 states and national experts in the evaluation field. We also explore how EM&V may evolve in a future in which efficiency funding increases significantly, innovative mechanisms for rewarding program performance are adopted, the role of efficiency in greenhouse gas mitigation is more closely linked, and programs are increasingly funded from multiple sources often with multiple program administrators and in

  17. 2007 Estimated International Energy Flows

    SciTech Connect (OSTI)

    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.

  18. Remote direct memory access over datagrams

    DOE Patents [OSTI]

    Grant, Ryan Eric; Rashti, Mohammad Javad; Balaji, Pavan; Afsahi, Ahmad

    2014-12-02

    A communication stack for providing remote direct memory access (RDMA) over a datagram network is disclosed. The communication stack has a user level interface configured to accept datagram related input and communicate with an RDMA enabled network interface card (NIC) via an NIC driver. The communication stack also has an RDMA protocol layer configured to supply one or more data transfer primitives for the datagram related input of the user level. The communication stack further has a direct data placement (DDP) layer configured to transfer the datagram related input from a user storage to a transport layer based on the one or more data transfer primitives by way of a lower layer protocol (LLP) over the datagram network.

  19. Hydrolysis of carbonyl sulfide over alumina

    SciTech Connect (OSTI)

    Polleck, R. E.; Ledley, R. E.; Scott, K. A.

    1985-01-01

    The reaction rate for the hydrolysis of carbonyl sulfide in liquid petroleum hydrocarbons over alumina, such as propylene, is greatly increased by maintaining water in the hydrocarbons in an amount of one mole of water per mole of carbonyl sulfide to an upper limit of about ten moles of water per mole of carbonyl sulfide or about 30% of saturation of the hydrocarbons, whichever upper limit provides the lesser amount of water.

  20. Estimating Waste Inventory and Waste Tank Characterization

    Broader source: Energy.gov [DOE]

    Summary Notes from 28 May 2008 Generic Technical Issue Discussion on Estimating Waste Inventory and Waste Tank Characterization

  1. Cost Model and Cost Estimating Software

    Broader source: Directives, Delegations, and 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.

  2. New Methodology for Natural Gas Production Estimates

    Reports and Publications (EIA)

    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.

  3. Looking northeast over the ITER construction site

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

    Looking northeast over the ITER construction site. A power shovel removes the first of some 230,000 cubic meters from the Tokamak Pit. Operations and Safety on the ITER Platform are being carefully coordinated by the Engage Consortium and the French company APAVE. Bulldozers and scrapers are busy leveling the 14,000 square-meter area that will host the huge PF Coils Assembly Building. Welcome to the first U.S. ITER newsletter. We have prepared this publication as part of our effort to better

  4. Robust bearing estimation for 3-component stations

    SciTech Connect (OSTI)

    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.

  5. Making web annotations persistent over time

    SciTech Connect (OSTI)

    Sanderson, Robert; Van De Sompel, Herbert

    2010-01-01

    As Digital Libraries (DL) become more aligned with the web architecture, their functional components need to be fundamentally rethought in terms of URIs and HTTP. Annotation, a core scholarly activity enabled by many DL solutions, exhibits a clearly unacceptable characteristic when existing models are applied to the web: due to the representations of web resources changing over time, an annotation made about a web resource today may no longer be relevant to the representation that is served from that same resource tomorrow. We assume the existence of archived versions of resources, and combine the temporal features of the emerging Open Annotation data model with the capability offered by the Memento framework that allows seamless navigation from the URI of a resource to archived versions of that resource, and arrive at a solution that provides guarantees regarding the persistence of web annotations over time. More specifically, we provide theoretical solutions and proof-of-concept experimental evaluations for two problems: reconstructing an existing annotation so that the correct archived version is displayed for all resources involved in the annotation, and retrieving all annotations that involve a given archived version of a web resource.

  6. Time and Resource Estimation Tool

    Energy Science and Technology Software Center (OSTI)

    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

  7. Projections of Future Summertime Ozone over the U.S.

    SciTech Connect (OSTI)

    Pfister, G. G.; Walters, Stacy; Lamarque, J. F.; Fast, Jerome D.; Barth, Mary; Wong, John; Done, James; Holland, Greg; Bruyere, Cindy

    2014-05-05

    This study uses a regional fully coupled chemistry-transport model to assess changes in surface ozone over the summertime U.S. between present and a 2050 future time period at high spatial resolution (12 km grid spacing) under the SRES A2 climate and RCP8.5 anthropogenic pre-cursor emission scenario. The impact of predicted changes in climate and global background ozone is estimated to increase surface ozone over most of the U.S; the 5th - 95th percentile range for daily 8-hour maximum surface ozone increases from 31-79 ppbV to 30-87 ppbV between the present and future time periods. The analysis of a set of meteorological drivers suggests that these mostly will add to increasing ozone, but the set of simulations conducted does not allow to separate this effect from that through enhanced global background ozone. Statistically the most robust positive feedbacks are through increased temperature, biogenic emissions and solar radiation. Stringent emission controls can counteract these feedbacks and if considered, we estimate large reductions in surface ozone with the 5th-95th percentile reduced to 27-55 ppbV. A comparison of the high-resolution projections to global model projections shows that even though the global model is biased high in surface ozone compared to the regional model and compared to observations, both the global and the regional model predict similar changes in ozone between the present and future time periods. However, on smaller spatial scales, the regional predictions show more pronounced changes between urban and rural regimes that cannot be resolved at the coarse resolution of global model. In addition, the sign of the changes in overall ozone mixing ratios can be different between the global and the regional predictions in certain regions, such as the Western U.S. This study confirms the key role of emission control strategies in future air quality predictions and demonstrates the need for considering degradation of air quality with future climate change in emission policy making. It also illustrates the need for high resolution modeling when the objective is to address regional and local air quality or establish links to human health and society.

  8. Derived annual estimates of manufacturing energy consumption, 1974--1988

    SciTech Connect (OSTI)

    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.``

  9. Parameter Estimation for Single Diode Models of Photovoltaic Modules

    SciTech Connect (OSTI)

    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.

  10. A survey of numerical cubature over triangles

    SciTech Connect (OSTI)

    Lyness, J.N.; Cools, R.

    1993-12-31

    This survey collects together theoretical results in the area of numerical cubature over triangles and is a vehicle for a current bibliography. We treat first the theory relating to regular integrands and then the corresponding theory for singular integrands with emphasis on the ``full comer singularity.`` Within these two sections we treat successively approaches based on transforming the triangle into a square, formulas based on polynomial moment fitting, and extrapolation techniques. Within each category we quote key theoretical results without proof, and relate other results and references to these. Nearly all the references we have found may be readily placed in one of these categories. This survey is theoretical in character and does not include recent work in adaptive and automatic integration.

  11. Hydrogen isotopic exchange over palladium metal

    SciTech Connect (OSTI)

    Carstens, D.H.W.; Encinias, P.D.

    1990-01-01

    We have recently developed the laser-Raman technique as a means of unambiguously measuring the partial pressures of all possible hydrogen isotopes in the gas phase. Using this technique we have investigated the hydrogen-deuterium exchange in a number of metals. This report presents detailed data for isotopic exchange in the palladium hydride system over the temperature range 26{degree}C to -100{degree}C at a pressure of 7 atm. First order kinetic rate constants and activation energies are summarized for the forward (hydride to deuteride) and reverse (deuteride to hydride) exchange processes. In addition, we have found that small amounts (100 ppm) of impurities in the exchange gases considerably slow the exchange kinetics with the effect increasing down the series CH{sub 4}, CO{sub 2}, H{sub 2}O, and CO. 9 refs., 4 figs., 1 tab.

  12. Early Internal and External Dose Magnitude Estimation

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

  13. State energy data report 1994: Consumption estimates

    SciTech Connect (OSTI)

    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.

  14. Methodology for Monthly Crude Oil Production Estimates

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

    5 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 Alaska.

  15. An Estimator of Propagation of Cascading Failure

    SciTech Connect (OSTI)

    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.

  16. Adjusted Estimates of Texas Natural Gas Production

    Reports and Publications (EIA)

    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.

  17. How EIA Estimates Natural Gas Production

    Reports and Publications (EIA)

    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.

  18. Interruption Cost Estimate Calculator | Open Energy Information

    Open Energy Info (EERE)

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

  19. ORISE: Radiation Dose Estimates and Other Compendia

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

    Nuclear Medicine" (M. Stabin, in Pediatric Nuclear Medicine, S. Treves, ed., Springer-Verlag, 1995). The compendium of dose estimates for pregnant women was published...

  20. 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 ... PNNL would like to thank the Federal Water Working Group of the Interagency Energy ...

  1. Catalyst Activity Comparison of Alcohols over Zeolites

    SciTech Connect (OSTI)

    Ramasamy, Karthikeyan K.; Wang, Yong

    2013-01-01

    Alcohol transformation to transportation fuel range hydrocarbon on HZSM-5 (SiO2 / Al2O3 = 30) catalyst was studied at 360oC and 300psig. Product distributions and catalyst life were compared using methanol, ethanol, 1-propanol or 1-butanol as a feed. The catalyst life for 1-propanol and 1-butanol was more than double compared to that for methanol and ethanol. For all the alcohols studied, the product distributions (classified to paraffin, olefin, napthene, aromatic and naphthalene compounds) varied with time on stream (TOS). At 24 hours TOS, liquid product from 1-propanol and 1-butanol transformation primarily contains higher olefin compounds. The alcohol transformation process to higher hydrocarbon involves a complex set of reaction pathways such as dehydration, oligomerization, dehydrocyclization, and hydrogenation. Compared to ethylene generated from methanol and ethanol, oligomerization of propylene and butylene has a lower activation energy and can readily take place on weaker acidic sites. On the other hand, dehydrocyclization of propylene and butylene to form the cyclic compounds requires the sits with stronger acid strength. Combination of the above mentioned reasons are the primary reasons for olefin rich product generated in the later stage of the time on stream and for the extended catalyst life time for 1 propanol and 1 butanol compared to methanol and ethanol conversion over HZSM-5.

  2. Evaluating atmospheric CO2 inversions at multiple scales over a highly-inventoried agricultural landscape.

    SciTech Connect (OSTI)

    Schuh, Andrew E.; Lauvaux, Thomas; West, Tristram O.; Denning, A.; Davis, Kenneth J.; Miles, Natasha; Richardson, S. J.; Uliasz, Marek; Lokupitiya, Erandathie; Cooley, Dan; Andrews, Arlyn; Ogle, Stephen

    2013-05-01

    An intensive regional research campaign was conducted by the North American Carbon Program (NACP) in 2005 to study the carbon cycle of the highly productive agricultural regions of the Midwestern United States. Forty-_ve di_erent associated projects were spawned across _ve U.S. agencies over the course of nearly a decade involving hundreds of researchers. The primary objective of the project was to investigate the ability of atmospheric inversion techniques to use highly calibrated CO2 mixing ratio data to estimate CO2 exchange over the major croplands of the U.S. Statistics from densely monitored crop production, consisting primarily corn and soybeans, provided the backbone of a well-studied\\bottom up"flux estimate that was used to evaluate the atmospheric inversion results. Three different inversion systems, representing spatial scales varying from high resolution mesoscale, to continental, to global, coupled to different transport models and optimization techniques were compared to the bottom up" inventory estimates. The mean annual CO2-C sink for 2007 from the inversion systems ranged from 120 TgC to 170 TgC, when viewed across a wide variety of inversion setups, with the best" point estimates ranging from 145 TgC to 155 TgC. Inversion-based mean C sink estimates were generally slightly stronger, but statistically indistinguishable,from the inventory estimate whose mean C sink was 135 TgC. The inversion results showed temporal correlations at seasonal lengths while week to week correlations remained low. Comparisons were made between atmospheric transport yields of the two regional inversion systems, which despite having different influence footprints in space and time due to differences in underlying transport models and external forcings, showed similarity when aggregated in space and time.

  3. Estimating Price Elasticity using Market-Level Appliance Data

    SciTech Connect (OSTI)

    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.

  4. Cost Estimating Handbook for Environmental Restoration

    SciTech Connect (OSTI)

    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.

  5. Selective adsorption of ethylene over ethane and propylene over propane in

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

    the metal-organic frameworks M2(dobdc) (M = Mg, Mn, Fe, Co, Ni, Zn) | Center for Gas SeparationsRelevant to Clean Energy Technologies | Blandine Jerome adsorption of ethylene over ethane and propylene over propane in the metal-organic frameworks M2(dobdc) (M = Mg, Mn, Fe, Co, Ni, Zn) Previous Next List Stephen J. Geier, Jarad A. Mason, Eric D. Bloch, Wendy L. Queen, Matthew R. Hudson, Craig M. Brown and Jeffrey R. Long, Chem. Sci., 4, 2054-2061 (2013) DOI: 10.1039/c3sc00032j Abstract: A

  6. SPECIAL ANALYSIS OF OPERATIONAL STORMWATER RUNOFF COVERS OVER SLIT TRENCHES

    SciTech Connect (OSTI)

    Collard, L; Luther Hamm, L

    2008-12-18

    Solid Waste Management (SWM) commissioned this Special Analysis (SA) to determine the effects of placing operational stormwater runoff covers (referred to as covers in the remainder of this document) over slit trench (ST) disposal units ST1 through ST7 (the center set of slit trenches). Previously the United States Department of Energy (DOE) entered into an agreement with the United States Environmental Protection Agency (EPA) and the South Carolina Department of Health and Environmental Control (SCDHEC) to place covers over Slit Trenches 1 and 2 to be able to continue disposing Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) solid waste (see USDOE 2008). Because the covers changed the operating conditions, DOE Order 435.1 (DOE 1999) required that an SA be performed to assess the impact. This Special Analysis has been prepared to determine the effects of placing covers over slit trenches at about years 5, 10 and 15 of the 30-year operational period. Because some slit trenches have already been operational for about 15 years, results from analyzing covers at 5 years and 10 years provide trend analysis information only. This SA also examined alternatives of covering Slit Trenches 1 and 2 with one cover and Slit Trenches 3 and 4 with a second cover versus covering them all with a single cover. Based on modeling results, minimal differences exist between covering Slit Trench groups 1-2 and 3-4 with two covers or one large cover. This SA demonstrates that placement of covers over slit trenches will slow the subsequent release and transport of radionuclides in the vadose zone in the early time periods (from time of placement until about 100 years). Release and transport of some radionuclides in the vadose zone beyond 100 years were somewhat higher than for the case without covers. The sums-of-fractions (SOFs) were examined for the current waste inventory in ST1 and ST2 and for estimated inventories at closure for ST3 through ST7. In all cases SOFs were less than one (except for one SOF for ST5 that remained at one), indicating that there should be no unacceptable impacts on operations from placing covers for the cover alternatives that were analyzed. Minimal operational limits provided in Table 4 should be used as the new set of limits for Slit Trenches 1 through 7. ST1 and ST2 are expected to be covered about 15 years after the first disposal in ST1. Because the time of actual placement of covers over the other slit trenches is unknown, this SA did not consider limit increases, only limit decreases. Thus, each minimal operational limit is the minimum of the Performance Assessment (PA) final limit and the limit calculated in this SA if covers were placed at about 5, 10 or 15 years. If other cover times are desired, further analysis will be required.

  7. Power, Optimization, Waste Estimating, Resourcing Tool

    Energy Science and Technology Software Center (OSTI)

    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.

  8. Systematic Approach for Decommissioning Planning and Estimating

    SciTech Connect (OSTI)

    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.

  9. Property:Estimated End Date | Open Energy Information

    Open Energy Info (EERE)

    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...

  10. 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...

  11. Building America Expert Meeting: Cladding Attachment Over Exterior...

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

    Cladding Attachment Over Exterior Insulation Building America Expert Meeting: Cladding Attachment Over Exterior Insulation Building Science Corporation (BSC) held an expert meeting...

  12. Federal Government Increases Renewable Energy Use Over 1000 Percent...

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

    Government Increases Renewable Energy Use Over 1000 Percent since 1999; Exceeds Goal Federal Government Increases Renewable Energy Use Over 1000 Percent since 1999; Exceeds Goal ...

  13. Efficiency Improvement in an Over the Road Diesel Powered Engine...

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

    in an Over the Road Diesel Powered Engine System by the Application of Advanced Thermoelectric Systems Implemented in a Hybrid Configuration Efficiency Improvement in an Over the ...

  14. DOE Announces Over $30 Million to Help Universities Train the...

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

    DOE Announces Over 30 Million to Help Universities Train the Next Generation of Industrial Energy Efficiency Experts DOE Announces Over 30 Million to Help Universities Train the...

  15. Advantages of Oxygenates Fuels over Gasoline in Direct Injection...

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

    Advantages of Oxygenates Fuels over Gasoline in Direct Injection Spark Ignition Engines Advantages of Oxygenates Fuels over Gasoline in Direct Injection Spark Ignition Engines ...

  16. Federal Government Increases Renewable Energy Use Over 1000 Percent...

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

    Government Increases Renewable Energy Use Over 1000 Percent since 1999; Exceeds Goal Federal Government Increases Renewable Energy Use Over 1000 Percent since 1999; Exceeds Goal...

  17. Atomic Energy Commission Takes Over Responsibility for all Atomic...

    National Nuclear Security Administration (NNSA)

    Takes Over Responsibility for all Atomic Energy Programs | National Nuclear Security ... Home About Us Our History NNSA Timeline Atomic Energy Commission Takes Over ...

  18. Verification of unfold error estimates in the UFO code

    SciTech Connect (OSTI)

    Fehl, D.L.; Biggs, F.

    1996-07-01

    Spectral unfolding is an inverse mathematical operation which attempts to obtain spectral source information from a set of tabulated response functions and data measurements. Several unfold algorithms have appeared over the past 30 years; among them is the UFO (UnFold Operator) code. In addition to an unfolded spectrum, UFO also estimates the unfold uncertainty (error) induced by running the code in a Monte Carlo fashion with prescribed data distributions (Gaussian deviates). In the 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% (standard deviation). 100 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% confidence level). A possible 10% bias between the two methods was unresolved. The Monte Carlo technique is also useful in underdetemined 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.

  19. Estimating the age of alleles by use of intraallelic variability

    SciTech Connect (OSTI)

    Slatkin, M.; Rannala, B.

    1997-02-01

    A method is presented for estimating the age of an allele by use of its frequency and the extent of variation among different copies. The method uses the joint distribution of the number of copies in a population sample and the coalescence times of the intraallelic gene genealogy conditioned on the number of copies. The linear birth-death process is used to approximate the dynamics of a rare allele in a finite population. A maximum-likelihood estimate of the age of the allele is obtained by Monte Carlo integration over the coalescence times. The method is applied to two alleles at the cystic fibrosis (CFTR) locus, {Delta}F508 and G542X, for which intraallelic variability at three intronic microsatellite loci has been examined. Our results indicate that G542X is somewhat older than {Delta}F508. Although absolute estimates depend on the mutation rates at the microsatellite loci, our results support the hypothesis that {Delta}F508 arose <500 generations ({approx}10,000 years) ago. 32 refs., 4 figs.

  20. Decommissioning Cost Estimating Factors And Earned Value Integration

    SciTech Connect (OSTI)

    Sanford, P.C.; Cimmarron, E.

    2008-07-01

    The Rocky Flats 771 Project progressed from the planning stage of decommissioning a plutonium facility, through the strip-out of highly-contaminated equipment, removal of utilities and structural decontamination, and building demolition. Actual cost data was collected from the strip-out activities and compared to original estimates, allowing the development of cost by equipment groupings and types and over time. Separate data was developed from the project control earned value reporting and compared with the equipment data. The paper discusses the analysis to develop the detailed factors for the different equipment types, and the items that need to be considered during characterization of a similar facility when preparing an estimate. The factors are presented based on direct labor requirements by equipment type. The paper also includes actual support costs, and examples of fixed or one-time start-up costs. The integration of the estimate and the earned value system used for the 771 Project is also discussed. The paper covers the development of the earned value system as well as its application to a facility to be decommissioned and an existing work breakdown structure. Lessons learned are provided, including integration with scheduling and craft supervision, measurement approaches, and verification of scope completion. In summary: The work of decommissioning the Rocky Flats 771 Project process equipment was completed in 2003. Early in the planning process, we had difficulty in identifying credible data and implementing processes for estimating and controlling this work. As the project progressed, we were able to collect actual data on the costs of removing plutonium contaminated equipment from various areas over the life of this work and associate those costs with individual pieces of equipment. We also were able to develop and test out a system for measuring the earned value of a decommissioning project based on an evolving estimate. These were elements that would have been useful to us in our early planning process, and we would expect that they would find application elsewhere as the DOE weapons complex and some commercial nuclear facilities move towards closure. (authors)

  1. Parallel State Estimation Assessment with Practical Data

    SciTech Connect (OSTI)

    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.

  2. State energy data report 1995 - consumption estimates

    SciTech Connect (OSTI)

    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.

  3. A simple method to estimate interwell autocorrelation

    SciTech Connect (OSTI)

    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.

  4. Preliminary CBECS End-Use Estimates

    U.S. 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...

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

    Open Energy Info (EERE)

    "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...

  6. gtp_flow_power_estimator.xlsx

    Broader source: 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.

  7. U.S. Uranium Reserves Estimates

    Gasoline and Diesel Fuel Update (EIA)

    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...

  8. Buildings GHG Mitigation Estimator Worksheet, Version 1

    Broader source: 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.

  9. Sub-Second Parallel State Estimation

    SciTech Connect (OSTI)

    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 todays 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 estimators single estimate. There are other benefits with the sub-second SE, such as that the PSE results can potentially be used in local and/or wide-area automatic corrective control actions that are currently dependent on raw measurements to minimize the impact of bad measurements, and provides opportunities to enhance the power grid reliability and efficiency. PSE also can enable other advanced tools that rely on SE outputs and could be used to further improve operators actions and automated controls to mitigate effects of severe events on the grid. The power grid continues to grow and the number of measurements is increasing at an accelerated rate due to the variety of smart grid devices being introduced. A parallel state estimation implementation will have better performance than traditional, sequential state estimation by utilizing the power of high performance computing (HPC). This increased performance positions parallel state estimators as valuable tools for operating the increasingly more complex power grid.

  10. Chapter 3: FY 2006 benefits estimates

    SciTech Connect (OSTI)

    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 employedNEMS-GPRA06 for the midterm and MARKAL-GPRA06 for the long term.

  11. Chapter 3: FY 2005 benefits estimates

    SciTech Connect (OSTI)

    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 employedNEMS-GPRA05 for the midterm and MARKAL-GPRA05 for the long term.

  12. ARM - Lesson Plans: Estimating Local Sea Level

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

  13. Estimates of US biomass energy consumption 1992

    SciTech Connect (OSTI)

    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.

  14. Estimated recharge rates at the Hanford Site

    SciTech Connect (OSTI)

    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.

  15. Home Improvement Catalyst: Sequencing Upgrades and Engaging Homeowners over

    Office of Environmental Management (EM)

    Time (201) | Department of Energy Home Improvement Catalyst: Sequencing Upgrades and Engaging Homeowners over Time (201) Home Improvement Catalyst: Sequencing Upgrades and Engaging Homeowners over Time (201) March 24

  16. A Study of Successive Over-relaxation Method Parallelization over Modern HPC Languages

    SciTech Connect (OSTI)

    Mittal, Sparsh [ORNL

    2014-01-01

    Successive over-relaxation (SOR) is a computationally intensive, yet extremely important iterative solver for solving linear systems. Due to recent trends of exponential growth in amount of data generated and increasing problem sizes, serial platforms have proved to be insucient in providing the required computational power. In this paper, we present parallel implementations of red-black SOR method using three modern programming languages namely Chapel, D and Go. We employ SOR method for solving 2D steady-state heat conduction problem. We discuss the optimizations incorporated and the features of these languages which are crucial for improving the program performance. Experiments have been performed using 2, 4, and 8 threads and performance results are compared with serial execution. The analysis of results provides important insights into working of SOR method.

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

    SciTech Connect (OSTI)

    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.

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

    SciTech Connect (OSTI)

    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.

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

    SciTech Connect (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 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.

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

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    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

  1. Variation in Hydraulic Conductivity Over Time at the Monticello Permeable

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

    Reactive Barrier | Department of Energy Variation in Hydraulic Conductivity Over Time at the Monticello Permeable Reactive Barrier Variation in Hydraulic Conductivity Over Time at the Monticello Permeable Reactive Barrier Variation in Hydraulic Conductivity Over Time at the Monticello Permeable Reactive Barrier PDF icon Variation in Hydraulic Conductivity Over Time at the Monticello Permeable Reactive Barrier More Documents & Publications Hydraulic Conductivity of the Monticello

  2. Estimating exposure of terrestrial wildlife to contaminants

    SciTech Connect (OSTI)

    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.

  3. Estimating vehicle height using homographic projections

    DOE Patents [OSTI]

    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.

  4. NREL: News - New Design Tool Analyzes Cost of Operating a Building Over its

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

    Lifetime Design Tool Analyzes Cost of Operating a Building Over its Lifetime Golden, Colo., August 2, 2002 Imagine being able to estimate the energy life-cycle costs of a new building by simply entering numbers into a software program. Thanks to the new Energy-10 design tool, this is now possible. The new software - Energy-10 Version 1.5 - is an upgrade to the original program developed at the U.S. Department of Energy's (DOE) National Renewable Energy Laboratory (NREL). The new Energy-10

  5. Estimating and mapping ecological processes influencing microbial community assembly

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Stegen, James C.; Lin, Xueju; Fredrickson, Jim K.; Konopka, Allan

    2015-05-01

    Ecological community assembly is governed by a combination of (i) selection resulting from among-taxa differences in performance; (ii) dispersal resulting from organismal movement; and (iii) ecological drift resulting from stochastic changes in population sizes. The relative importance and nature of these processes can vary across environments. Selection can be homogeneous or variable, and while dispersal is a rate, we conceptualize extreme dispersal rates as two categories; dispersal limitation results from limited exchange of organisms among communities, and homogenizing dispersal results from high levels of organism exchange. To estimate the influence and spatial variation of each process we extend a recentlymore » developed statistical framework, use a simulation model to evaluate the accuracy of the extended framework, and use the framework to examine subsurface microbial communities over two geologic formations. For each subsurface community we estimate the degree to which it is influenced by homogeneous selection, variable selection, dispersal limitation, and homogenizing dispersal. Our analyses revealed that the relative influences of these ecological processes vary substantially across communities even within a geologic formation. We further identify environmental and spatial features associated with each ecological process, which allowed mapping of spatial variation in ecological-process-influences. The resulting maps provide a new lens through which ecological systems can be understood; in the subsurface system investigated here they revealed that the influence of variable selection was associated with the rate at which redox conditions change with subsurface depth.« less

  6. Estimating and mapping ecological processes influencing microbial community assembly

    SciTech Connect (OSTI)

    Stegen, James C.; Lin, Xueju; Fredrickson, Jim K.; Konopka, Allan

    2015-05-01

    Ecological community assembly is governed by a combination of (i) selection resulting from among-taxa differences in performance; (ii) dispersal resulting from organismal movement; and (iii) ecological drift resulting from stochastic changes in population sizes. The relative importance and nature of these processes can vary across environments. Selection can be homogeneous or variable, and while dispersal is a rate, we conceptualize extreme dispersal rates as two categories; dispersal limitation results from limited exchange of organisms among communities, and homogenizing dispersal results from high levels of organism exchange. To estimate the influence and spatial variation of each process we extend a recently developed statistical framework, use a simulation model to evaluate the accuracy of the extended framework, and use the framework to examine subsurface microbial communities over two geologic formations. For each subsurface community we estimate the degree to which it is influenced by homogeneous selection, variable selection, dispersal limitation, and homogenizing dispersal. Our analyses revealed that the relative influences of these ecological processes vary substantially across communities even within a geologic formation. We further identify environmental and spatial features associated with each ecological process, which allowed mapping of spatial variation in ecological-process-influences. The resulting maps provide a new lens through which ecological systems can be understood; in the subsurface system investigated here they revealed that the influence of variable selection was associated with the rate at which redox conditions change with subsurface depth.

  7. Guidelines for Estimating Unmetered Landscaping Water Use

    SciTech Connect (OSTI)

    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.

  8. Estimating the uncertainty in underresolved nonlinear dynamics

    SciTech Connect (OSTI)

    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. Estimating Annual Precipitation in the Fenner Basin of the Eastern Mojave Desert, California

    SciTech Connect (OSTI)

    Davisson, M.L.; Rose, T.P.

    2000-05-15

    Metropolitan Water District (MWD) of southern California and Cadiz Inc. investigated the feasibility of storing Colorado River water in groundwater aquifers of the eastern Mojave Desert as a future drought mitigation strategy. This culminated in the public release of the Cadiz Groundwater Storage and Dry-Year Supply program Draft EIR, which included pilot percolation studies, groundwater modeling, and precipitation/runoff analysis in the Fenner groundwater basin, which overlies the proposed storage site. The project proposes to store and withdrawal Colorado River water over a 50-year period, but will not exceed the natural replenishment rates of the groundwater basin. Several independent analyses were conducted to estimate the rates of natural groundwater replenishment to the Fenner Groundwater Basin which was included in the Draft EIR. The US Geologic Survey, Water Resources Division (WRD) officially submitted comments during public review and concluded that the natural groundwater replenishment rates calculated for the Draft EIR were too high. In the WRD review, they provided a much lower recharge calculation based on a Maxey-Eakin estimation approach. This approach estimates annual precipitation over an entire basin as a function of elevation, followed by calibration against annual recharge rates. Previous attempts to create precipitation-elevation functions in western Nevada have been difficult and result in large uncertainty. In the WRD data analysis, the effect of geographic scale on the precipitation-elevation function was overlooked. This contributed to an erroneous Maxey-Eakin recharge estimate.

  10. WETCHIMP-WSL: Intercomparison of wetland methane emissions models over West Siberia

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Bohn, T. J.; Melton, J. R.; Ito, A.; Kleinen, T.; Spahni, R.; Stocker, B. D.; Zhang, B.; Zhu, X.; Schroeder, R.; Glagolev, M. V.; et al

    2015-06-03

    Wetlands are the world's largest natural source of methane, a powerful greenhouse gas. The strong sensitivity of methane emissions to environmental factors such as soil temperature and moisture has led to concerns about potential positive feedbacks to climate change. This risk is particularly relevant at high latitudes, which have experienced pronounced warming and where thawing permafrost could potentially liberate large amounts of labile carbon over the next 100 years. However, global models disagree as to the magnitude and spatial distribution of emissions, due to uncertainties in wetland area and emissions per unit area and a scarcity of in situ observations.more » Recent intensive field campaigns across the West Siberian Lowland (WSL) make this an ideal region over which to assess the performance of large-scale process-based wetland models in a high-latitude environment. Here we present the results of a follow-up to the Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP), focused on the West Siberian Lowland (WETCHIMP-WSL). We assessed 21 models and 5 inversions over this domain in terms of total CH4 emissions, simulated wetland areas, and CH4 fluxes per unit wetland area and compared these results to an intensive in situ CH4 flux data set, several wetland maps, and two satellite surface water products. We found that (a) despite the large scatter of individual estimates, 12-year mean estimates of annual total emissions over the WSL from forward models (5.34 ± 0.54 Tg CH4 yr⁻¹), inversions (6.06 ± 1.22 Tg CH4 yr⁻¹), and in situ observations (3.91 ± 1.29 Tg CH4 yr⁻¹) largely agreed; (b) forward models using surface water products alone to estimate wetland areas suffered from severe biases in CH4 emissions; (c) the interannual time series of models that lacked either soil thermal physics appropriate to the high latitudes or realistic emissions from unsaturated peatlands tended to be dominated by a single environmental driver (inundation or air temperature), unlike those of inversions and more sophisticated forward models; (d) differences in biogeochemical schemes across models had relatively smaller influence over performance; and (e) multiyear or multidecade observational records are crucial for evaluating models' responses to long-term climate change.« less

  11. WETCHIMP-WSL: Intercomparison of wetland methane emissions models over West Siberia

    SciTech Connect (OSTI)

    Bohn, T. J.; Melton, J. R.; Ito, A.; Kleinen, T.; Spahni, R.; Stocker, B. D.; Zhang, B.; Zhu, X.; Schroeder, R.; Glagolev, M. V.; Maksyutov, S.; Brovkin, V.; Chen, G.; Denisov, S. N.; Eliseev, A. V.; Gallego-Sala, A.; McDonald, K. C.; Rawlins, M. A.; Riley, W. J.; Subin, Z. M.; Tian, H.; Zhuang, Q.; Kaplan, J. O.

    2015-06-03

    Wetlands are the world's largest natural source of methane, a powerful greenhouse gas. The strong sensitivity of methane emissions to environmental factors such as soil temperature and moisture has led to concerns about potential positive feedbacks to climate change. This risk is particularly relevant at high latitudes, which have experienced pronounced warming and where thawing permafrost could potentially liberate large amounts of labile carbon over the next 100 years. However, global models disagree as to the magnitude and spatial distribution of emissions, due to uncertainties in wetland area and emissions per unit area and a scarcity of in situ observations. Recent intensive field campaigns across the West Siberian Lowland (WSL) make this an ideal region over which to assess the performance of large-scale process-based wetland models in a high-latitude environment. Here we present the results of a follow-up to the Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP), focused on the West Siberian Lowland (WETCHIMP-WSL). We assessed 21 models and 5 inversions over this domain in terms of total CH4 emissions, simulated wetland areas, and CH4 fluxes per unit wetland area and compared these results to an intensive in situ CH4 flux data set, several wetland maps, and two satellite surface water products. We found that (a) despite the large scatter of individual estimates, 12-year mean estimates of annual total emissions over the WSL from forward models (5.34 0.54 Tg CH4 yr?), inversions (6.06 1.22 Tg CH4 yr?), and in situ observations (3.91 1.29 Tg CH4 yr?) largely agreed; (b) forward models using surface water products alone to estimate wetland areas suffered from severe biases in CH4 emissions; (c) the interannual time series of models that lacked either soil thermal physics appropriate to the high latitudes or realistic emissions from unsaturated peatlands tended to be dominated by a single environmental driver (inundation or air temperature), unlike those of inversions and more sophisticated forward models; (d) differences in biogeochemical schemes across models had relatively smaller influence over performance; and (e) multiyear or multidecade observational records are crucial for evaluating models' responses to long-term climate change.

  12. Reasons for changes in MPG estimates, model year 1978 to the present

    SciTech Connect (OSTI)

    Patterson, P.D.; Westbrook, F.W.; Greene, D.L.; Roberts, G.F.

    1984-01-01

    In model year 1983, new car MPG declined for the first time in ten years. Accompanying this decline in MPG, the size of the average car increased, car weights and engine sized increased and diesel sales declined - all reversing their movements over the previous ten years. Using carline MPG estimates and sales figures, it is estimated that new car MPG declined 0.29 in 1983 after rising 6.70 MPG over the previous four years. Furthermore,it is estimated that actions by new car buyers would have lowered the 1983 MPG 0.40 MPG through the purchase of larger cars, cars with larger engines and fewer diesel engines if the manufacturers had not some fuel economy improvements and introduced some new high-MPG cars. A simple model of future fuel use increases as a friction of MPG levels below a specified level consistent with the CAFE standards shows that the costs of lower fuel economy will only gradually be felt, but that these costs will increase over time and persist for over a decade.

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

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

    This report reviews literature on cost estimation in several areas involving major capital ... projects, and cost estimating techniques and problems for chemical process plants. ...

  14. An Analytical Approach for Tail-Pipe Emissions Estimation with...

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

    An Analytical Approach for Tail-Pipe Emissions Estimation with Coupled Engine and Aftertreatment System An Analytical Approach for Tail-Pipe Emissions Estimation with Coupled Engine ...

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

    Open Energy Info (EERE)

    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...

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

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

    Direct Hydrogen PEMFC Manufacturing Cost Estimation for Automotive Applications: Fuel Cell Tech Team Review Direct Hydrogen PEMFC Manufacturing Cost Estimation for Automotive...

  17. DC Microgrids Scoping Study: Estimate of Technical and Economic...

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

    Microgrids Scoping Study: Estimate of Technical and Economic Benefits (March 2015) DC Microgrids Scoping Study: Estimate of Technical and Economic Benefits (March 2015) Microgrid ...

  18. INDEPENDENT COST REVIEW (ICR) and INDEPENDENT COST ESTIMATE ...

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

    INDEPENDENT COST REVIEW (ICR) and INDEPENDENT COST ESTIMATE (ICE) Standard Operating Procedures INDEPENDENT COST REVIEW (ICR) and INDEPENDENT COST ESTIMATE (ICE) Standard Operating...

  19. 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...

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

    Office of Environmental Management (EM)

    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...

  1. Statistical Surrogate Models for Estimating Probability of High...

    Office of Scientific and Technical Information (OSTI)

    Statistical Surrogate Models for Estimating Probability of High-Consequence Climate Change. Citation Details In-Document Search Title: Statistical Surrogate Models for Estimating ...

  2. Analysis Procedures to Estimate Seismic Demands of Structures...

    Office of Environmental Management (EM)

    to Estimate Seismic Demands of Structures Presentation from the May 2015 Seismic Lessons-Learned Panel Meeting. PDF icon Analysis Procedures to Estimate Seismic Demands of...

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

    Open Energy Info (EERE)

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

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

    Open Energy Info (EERE)

    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...

  5. 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 -...

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

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

    Radiological Source Term Estimates for the February 14, 2014 WIPP Release Event Radiological Source Term Estimates for the February 14, 2014 WIPP Release Event This document was...

  7. 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, ...

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

    Open Energy Info (EERE)

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

  9. 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 Estimation and Control of Diesel Engine Processes Utilizing Variable Intake Valve ...

  10. 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 ...

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

    SciTech Connect (OSTI)

    Qi,Tang; Xie,Shaocheng

    2015-08-06

    The ARM Best Estimate Station-based Surface (ARMBESTNS) data set merges together key surface measurements from the Southern Great Plains (SGP) sites. It is a twin data product of the ARM Best Estimate 2-dimensional Gridded Surface (ARMBE2DGRID) data set. Unlike the 2DGRID data set, the STNS data are reported at the original site locations and show the original information, except for the interpolation over time. Therefore, users have the flexibility to process the data with the approach more suitable for their applications.

  12. Wave like signatures in aerosol optical depth and associated radiative impacts over the central Himalayan region

    SciTech Connect (OSTI)

    Shukla, K. K.; Phanikumar, D. V.; Kumar, Niranjan; Reddy, Kishore; Kotamarthi, Veerabhadra R.; Newsom, Rob K.; Ouarda, Taha B.

    2015-10-01

    In this study, we present a case study on 16 October 2011 to show the first observational evidence of the influence of short period gravity waves in aerosol transport during daytime over the central Himalayan region. The Doppler lidar data has been utilized to address the daytime boundary layer evolution and related aerosol dynamics over the site. Mixing layer height is estimated by wavelet covariance transform method and found to be ~ 0.7 km, AGL. Aerosol optical depth observations during daytime revealed an asymmetry showing clear enhancement during afternoon hours as compared to forenoon. Interestingly, Fourier and wavelet analysis of vertical velocity and attenuated backscatter showed similar 50-90 min short period gravity wave signatures during afternoon hours. Moreover, our observations showed that gravity waves are dominant within the boundary layer implying that the daytime boundary layer dynamics is playing a vital role in transporting the aerosols from surface to the top of the boundary layer. Similar modulations are also evident in surface parameters like temperature, relative humidity and wind speed indicating these waves are associated with the dynamical aspects over Himalayan region. Finally, time evolution of range-23 height indicator snapshots during daytime showed strong upward velocities especially during afternoon hours implying that convective processes through short period gravity waves plays a significant role in transporting aerosols from the nearby valley region to boundary layer top over the site. These observations also establish the importance of wave induced daytime convective boundary layer dynamics in the lower Himalayan region.

  13. A method for estimating direct normal solar irradiation from satellite data for a tropical environment

    SciTech Connect (OSTI)

    Janjai, Serm

    2010-09-15

    In order to investigate a potential use of concentrating solar power technologies and select an optimum site for these technologies, it is necessary to obtain information on the geographical distribution of direct normal solar irradiation over an area of interest. In this work, we have developed a method for estimating direct normal irradiation from satellite data for a tropical environment. The method starts with the estimation of global irradiation on a horizontal surface from MTSAT-1R satellite data and other ground-based ancillary data. Then a satellite-based diffuse fraction model was developed and used to estimate the diffuse component of the satellite-derived global irradiation. Based on this estimated global and diffuse irradiation and the solar radiation incident angle, the direct normal irradiation was finally calculated. To evaluate its performance, the method was used to estimate the monthly average hourly direct normal irradiation at seven pyrheliometer stations in Thailand. It was found that values of monthly average hourly direct normal irradiation from the measurements and those estimated from the proposed method are in reasonable agreement, with a root mean square difference of 16% and a mean bias of -1.6%, with respect to mean measured values. After the validation, this method was used to estimate the monthly average hourly direct normal irradiation over Thailand by using MTSAT-1R satellite data for the period from June 2005 to December 2008. Results from the calculation were displayed as hourly and yearly irradiation maps. These maps reveal that the direct normal irradiation in Thailand was strongly affected by the tropical monsoons and local topography of the country. (author)

  14. Simulation of the intraseasonal variability over the Eastern Pacific ITCZ

    Office of Scientific and Technical Information (OSTI)

    in climate models (Journal Article) | SciTech Connect Simulation of the intraseasonal variability over the Eastern Pacific ITCZ in climate models Citation Details In-Document Search Title: Simulation of the intraseasonal variability over the Eastern Pacific ITCZ in climate models During boreal summer, convective activity over the eastern Pacific (EPAC) inter-tropical convergence zone (ITCZ) exhibits vigorous intraseasonal variability (ISV). Previous observational studies identified two

  15. Building America Expert Meeting: Cladding Attachment Over Exterior

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

    Insulation | Department of Energy Cladding Attachment Over Exterior Insulation Building America Expert Meeting: Cladding Attachment Over Exterior Insulation Building Science Corporation (BSC) held an expert meeting on Cladding Attachment Over Exterior Insulation on Saturday, July 28, 2012 at the Westford Regency Hotel in Westford, Massachusetts. Featured speakers included Jay Crandell of ARES Consulting, Peter Baker of BSC, Gary Parsons of DOW Chemical Company, Vladimir Kochkin of the

  16. Building America Expert Meeting: Cladding Attachment Over Exterior

    Energy Savers [EERE]

    Insulation | Department of Energy Cladding Attachment Over Exterior Insulation Building America Expert Meeting: Cladding Attachment Over Exterior Insulation Building Science Corporation (BSC) held an expert meeting on Cladding Attachment Over Exterior Insulation on Saturday, July 28, 2012 at the Westford Regency Hotel in Westford, Massachusetts. Featured speakers included Jay Crandell of ARES Consulting, Peter Baker of BSC, Gary Parsons of DOW Chemical Company, Vladimir Kochkin of the

  17. IG Investigation with DOJ Results in over $10million Settlement |

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

    Department of Energy IG Investigation with DOJ Results in over $10million Settlement IG Investigation with DOJ Results in over $10million Settlement PDF icon IG Investigation with DOJ Results in Over $10million Settlement More Documents & Publications Savannah River Site Contractor Agrees to Pay $3.8 Million to Settle False Claims Act Allegations Semiannual Report to Congress: April 1, 2015 - September 30, 2015 Sandia Corporation Agrees to Pay $4.7 Million to Resolve Allegations Related

  18. President Obama Announces Over $467 Million in Recovery Act Funding...

    Office of Environmental Management (EM)

    Announces Over 467 Million in Recovery Act Funding for Geothermal and Solar Energy Projects ... areas, as well as geothermal energy production from oil and natural gas fields, ...

  19. Further Analysis of 3D Magnetotelluric Measurements Over the...

    Open Energy Info (EERE)

    contiguous bipole array profiling over the east flank of the field (Newman et al., 2005). Motivation for this study is that electrical resistivity conductivity mapping can...

  20. Simulation of the intraseasonal variability over the Eastern...

    Office of Scientific and Technical Information (OSTI)

    exerts significant influences on regional climateweather systems, investigation of contemporary model capabilities in representing these ISV modes over the EPAC is limited. In...

  1. NDOT Over Dimensional Permits Instruction 1-08 | Open Energy...

    Open Energy Info (EERE)

    library PermittingRegulatory Guidance - Instructions: NDOT Over Dimensional Permits Instruction 1-08PermittingRegulatory GuidanceInstructions Abstract The purpose of this...

  2. NDOT Over Dimensional Permits Instruction 6-07 | Open Energy...

    Open Energy Info (EERE)

    library PermittingRegulatory Guidance - Instructions: NDOT Over Dimensional Permits Instruction 6-07PermittingRegulatory GuidanceInstructions Abstract The purpose of this...

  3. NNSA to conduct Aerial Radiation Assessment Survey over Boston...

    National Nuclear Security Administration (NNSA)

    at NNSA Blog Home Library Press Releases NNSA to conduct Aerial Radiation Assessment Survey ... NNSA to conduct Aerial Radiation Assessment Survey over Boston area Press...

  4. NNSA to conduct Aerial Radiation Assessment Survey over Phoenix...

    National Nuclear Security Administration (NNSA)

    at NNSA Blog Home Library Press Releases NNSA to conduct Aerial Radiation Assessment Survey ... NNSA to conduct Aerial Radiation Assessment Survey over Phoenix,...

  5. Audit of Internal Controls Over Special Nuclear Materials, IG...

    Energy Savers [EERE]

    0388 "Audit of Internal Controls Over Special Nuclear Materials" This report is not available electronically. However, copies may be obtained by calling the Office of Inspector...

  6. Reserving and Scheduling Transmission over the Time Change -...

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

    Customer Training Interconnection Notices Rates Standards of Conduct Tariff TF Web Based Training Notice: Reserving & Scheduling Transmission over the Time Change Posted Date: 10...

  7. Reminder Reserving and Scheduling Transmission over the Time...

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

    Customer Training Interconnection Notices Rates Standards of Conduct Tariff TF Web Based Training Notice: Reminder - Reserving & Scheduling Transmission over the Time Change...

  8. Reserving and Scheduling Transmission over the Time Change -...

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

    Customer Training Interconnection Notices Rates Standards of Conduct Tariff TF Web Based Training Notice: Reserving & Scheduling Transmission over the Time Change Reminder Posted...

  9. Reserving and Scheduling Transmission over the Time Change -...

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

    Customer Training Interconnection Notices Rates Standards of Conduct Tariff TF Web Based Training Notice: Reserving & Scheduling Transmission over the Time Change Posted Date: 2...

  10. Numerical Estimation of the Spent Fuel Ratio

    SciTech Connect (OSTI)

    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

  11. State energy data report 1992: Consumption estimates

    SciTech Connect (OSTI)

    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.

  12. Generalized REGression Package for Nonlinear Parameter Estimation

    Energy Science and Technology Software Center (OSTI)

    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.

  13. Knowledge Based Estimation of Material Release Transients

    Energy Science and Technology Software Center (OSTI)

    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.

  14. Notices Total Estimated Number of Annual

    Energy Savers [EERE]

    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

  15. Communications circuit including a linear quadratic estimator

    DOE Patents [OSTI]

    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.

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

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

    Hydrogen Station Cost Estimates Comparing Hydrogen Station Cost Calculator Results with other Recent Estimates M. Melaina and M. Penev National Renewable Energy Laboratory Technical Report NREL/TP-5400-56412 September 2013 NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency & Renewable Energy Operated by the Alliance for Sustainable Energy, LLC This report is available at no cost from the National Renewable Energy Laboratory (NREL) at

  17. US Energy Production over the Years Data | Department of Energy

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

    US Energy Production over the Years Data US Energy Production over the Years Data File total_states_link.xlsx Office spreadsheet icon total_sectors_link.xls Binary Data us_93_02_v3.json More Documents & Publications ESPC Project Performance: Supplemental Data Noise and Vibration Impact Assessment Methodology Audit Report: OAS-FS-12-06

  18. Energy Production Over the Years | Department of Energy

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

    Energy Production Over the Years Energy Production Over the Years US Energy Production Through the Years Click on each state to learn more about how much energy it produces Pick an energy source Total Energy Produced Coal Crude Oil Natural Gas Total Renewable Energy Non-Biofuel Renewable Energy Biofuels Nuclear Power Source: EIA State Energy Data Systems

  19. Pension Estimate System PIA, Bechtel Jacobs Company, LLC | Department of

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

    Energy Pension Estimate System PIA, Bechtel Jacobs Company, LLC Pension Estimate System PIA, Bechtel Jacobs Company, LLC Pension Estimate System PIA, Bechtel Jacobs Company, LLC PDF icon Pension Estimate System PIA, Bechtel Jacobs Company, LLC More Documents & Publications Electronic Document Management System PIA, BechtelJacobs Company, LLC Dosimetry Records System PIA, bechtel Jacobs Company, LLC Medgate, PIA, Bechtel Jacobs

  20. A Dynamic Programming Approach to Estimate the Capacity Value of Energy Storage

    Broader source: Energy.gov [DOE]

    We present a method to estimate the capacity value of storage. Our method uses a dynamic program to model the effect of power system outages on the operation and state of charge of storage in subsequent periods. We combine the optimized dispatch from the dynamic program with estimated system loss of load probabilities to compute a probability distribution for the state of charge of storage in each period. This probability distribution can be used as a forced outage rate for storage in standard reliability-based capacity value estimation methods. Our proposed method has the advantage over existing approximations that it explicitly captures the effect of system shortage events on the state of charge of storage in subsequent periods. We also use a numerical case study, based on five utility systems in the U.S., to demonstrate our technique and compare it to existing approximation methods.

  1. Seismic damage estimation for buried pipelines - challenges after three decades of progress

    SciTech Connect (OSTI)

    Pineda-porras, Omar Andrey; Najafi, Mohammand

    2009-01-01

    This paper analyzes the evolution over the past three decades of seismic damage estimation for buried pipelines and identifies some challenges for future research studies on the subject. The first section of this paper presents a chronological description of the evolution since the mid-1970s of pipeline fragility relations - the most common tool for pipeline damage estimation - and follows with a careful analysis of the use of several ground motion parameters as pipeline damage indicators. In the second section of the paper, four gaps on the subject are identified and proposed as challenges for future research studies. The main conclusion of this work is that enhanced fragility relations must be developed for improving pipeline damage estimation, which must consider relevant parameters that could influence the seismic response of pipelines.

  2. Estimating Parameters for the PVsyst Version 6 Photovoltaic Module Performance Model

    SciTech Connect (OSTI)

    Hansen, Clifford

    2015-10-01

    We present an algorithm to determine parameters for the photovoltaic module perf ormance model encoded in the software package PVsyst(TM) version 6. Our method operates on current - voltage (I - V) measured over a range of irradiance and temperature conditions. We describe the method and illustrate its steps using data for a 36 cell crystalli ne silicon module. We qualitatively compare our method with one other technique for estimating parameters for the PVsyst(TM) version 6 model .

  3. Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water

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

    Heaters | Department of Energy 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 efficiency is determined by the energy factor (EF), which is based on the amount of hot water produced per unit of fuel consumed over a typical day. The higher the energy factor, the more efficient the water heater. A water heater's energy efficiency is determined by the energy factor (EF),

  4. Position estimation of transceivers in communication networks

    DOE Patents [OSTI]

    Kent, Claudia A. (Pleasanton, CA); Dowla, Farid (Castro Valley, CA)

    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.

  5. Process Equipment Cost Estimation, Final Report

    Office of Scientific and Technical Information (OSTI)

    Process Equipment Cost Estimation Final Report January 2002 H.P. Loh U.S. Department of Energy National Energy Technology Laboratory P.O. Box 10940, 626 Cochrans Mill Road Pittsburgh, PA 15236-0940 and P.O. Box 880, 3610 Collins Ferry Road Morgantown, WV 26507-0880 and Jennifer Lyons and Charles W. White, III EG&G Technical Services, Inc. 3604 Collins Ferry Road, Suite 200 Morgantown, WV 26505 DOE/NETL-2002/1169 ii Disclaimer This report was prepared as an account of work sponsored by an

  6. Estimated United States Transportation Energy Use 2005

    SciTech Connect (OSTI)

    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.

  7. WEATHER PREDICTIONS AND SURFACE RADIATION ESTIMATES

    Office of Legacy Management (LM)

    ARLV - 3 51 - 4 / WEATHER PREDICTIONS AND SURFACE RADIATION ESTIMATES for the RULISON EVENT Final Report Albert H . S t o u t , Ray E . White, and V i r g i l E. Quinn Environmental Science Services Administration A i r Resources Laboratory - Las Vegas PROPERW OF U. S. GOVERNMENT Prepared Under Contract SF-54-351 f o r the Nevada Operations O f f i c e U . ' S . Atomic Energy Commission January 1970 LEGAL NOTSCCE ; L *U . . . . . - . T h i s r e p o r t w a s prepared a s an account o f

  8. Cell Total Activity Final Estimate.xls

    Office of Legacy Management (LM)

    WSSRAP Cell Total Activity Final Estimate (calculated September 2002, Fleming) (Waste streams & occupied cell volumes from spreadsheet titled "cell waste volumes-8.23.02 with macros.xls") Waste Stream a Volume (cy) Mass (g) 2 Radiological Profile 3 Nuclide Activity (Ci) 4 Total % of Total U-238 U-234 U-235 Th-228 Th-230 Th-232 Ra-226 Ra-228 Rn-222 5 Activity if > 1% Raffinate Pits Work Zone (Ci) Raffinate processed through CSS Plant 1 159990 1.49E+11 Raffinate 6.12E+01 6.12E+01

  9. Energy Department Announces Over $12 Million to Spur Solar Energy

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

    Innovation | Department of Energy Over $12 Million to Spur Solar Energy Innovation Energy Department Announces Over $12 Million to Spur Solar Energy Innovation February 8, 2012 - 1:53pm Addthis WASHINGTON, D.C. -- As part of the Obama Administration's blueprint for an American economy built to last, today U.S. Energy Secretary Steven Chu announced over $12 million to speed solar energy innovation from the lab to the marketplace through the Energy Department's SunShot Incubator program. The

  10. Development of surface mine cost estimating equations

    SciTech Connect (OSTI)

    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)

  11. Estimates of Savings Achievable from Irrigation Controller

    SciTech Connect (OSTI)

    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.

  12. Risk Estimation Methodology for Launch Accidents.

    SciTech Connect (OSTI)

    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. Geothermal Exploration Using Aviris Remote Sensing Data Over...

    Open Energy Info (EERE)

    Aviris Remote Sensing Data Over Fish Lake Valley, Nv Jump to: navigation, search OpenEI Reference LibraryAdd to library Conference Paper: Geothermal Exploration Using Aviris Remote...

  14. LG Dismisses Lawsuit against DOE over Energy Star Enforcement

    Broader source: Energy.gov [DOE]

    DOE announced today that LG Electronics voluntarily dismissed its lawsuit against DOE over the Department's decision to require LG to use the same energy efficiency tests as other manufacturers and...

  15. DOE Announces Over $8 Million to Increase Use and Availability...

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

    8 Million to Increase Use and Availability of Alternative Fuels DOE Announces Over 8 Million to Increase Use and Availability of Alternative Fuels October 25, 2006 - 9:17am ...

  16. Remote Sensing Observations from MTI Satellites and GMS Over...

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

    There are no clouds in the region on December 12, 2000. On December 13, on the other hand, an island cloud trail is formed that extends over 100 km and has cloud-free regions...

  17. Surprising Control over Photoelectrons from a Topological Insulator

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

    Surprising Control over Photoelectrons from a Topological Insulator Surprising Control over Photoelectrons from a Topological Insulator Print Tuesday, 12 March 2013 00:00 Topological insulators are insulators in the bulk but metals on the surface, and the electrons that flow swiftly across their surfaces are "spin polarized." Surface-electron spin and momentum are locked, offering new ways to control electron flow and distribution in spintronic devices. A Nature Physics paper by first

  18. Recent advances in modeling fission cross sections over intermediate

    Office of Scientific and Technical Information (OSTI)

    structures (Conference) | SciTech Connect modeling fission cross sections over intermediate structures Citation Details In-Document Search Title: Recent advances in modeling fission cross sections over intermediate structures More accurate fission cross section calculations in presence of underlying intermediate structure are strongly desired. This paper recalls the common approximations used below the fission threshold and quantifies their impact. In particular, an exact expanded R-matrix

  19. Recent advances in modeling fission cross sections over intermediate

    Office of Scientific and Technical Information (OSTI)

    structures (Conference) | SciTech Connect modeling fission cross sections over intermediate structures Citation Details In-Document Search Title: Recent advances in modeling fission cross sections over intermediate structures × You are accessing a document from the Department of Energy's (DOE) SciTech Connect. This site is a product of DOE's Office of Scientific and Technical Information (OSTI) and is provided as a public service. Visit OSTI to utilize additional information resources in

  20. Federal Government Increases Renewable Energy Use Over 1000 Percent since

    Energy Savers [EERE]

    1999; Exceeds Goal | Department of Energy Government Increases Renewable Energy Use Over 1000 Percent since 1999; Exceeds Goal Federal Government Increases Renewable Energy Use Over 1000 Percent since 1999; Exceeds Goal November 3, 2005 - 12:35pm Addthis WASHINGTON, DC - The Department of Energy (DOE) announced today that the federal government has exceeded its goal of obtaining 2.5 percent of its electricity needs from renewable energy sources by September 30, 2005. The largest energy

  1. DOE Awards Over a Billion Supercomputing Hours to Address Scientific

    Energy Savers [EERE]

    Challenges | Department of Energy Over a Billion Supercomputing Hours to Address Scientific Challenges DOE Awards Over a Billion Supercomputing Hours to Address Scientific Challenges January 26, 2010 - 12:00am Addthis Washington, DC. - The U.S. Department of Energy announced today that approximately 1.6 billion supercomputing processor hours have been awarded to 69 cutting-edge research projects through the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program.

  2. Cladding Attachment Over Thick Exterior Sheathing | Department of Energy

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

    Cladding Attachment Over Thick Exterior Sheathing Cladding Attachment Over Thick Exterior Sheathing The addition of insulation to the exterior of buildings is an effective means of increasing the thermal resistance of both wood framed walls as well as mass masonry wall assemblies. For thick layers of exterior insulation (levels greater than 1.5 inches), the use of wood furring strips attached through the insulation back to the structure has been used by many contractors and designers as a means

  3. Technical Demonstration of 2010 Emissions Regulations over Transient

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

    Operation | Department of Energy Demonstration of 2010 Emissions Regulations over Transient Operation Technical Demonstration of 2010 Emissions Regulations over Transient Operation Presentation given at DEER 2006, August 20-24, 2006, Detroit, Michigan. Sponsored by the U.S. DOE's EERE FreedomCar and Fuel Partnership and 21st Century Truck Programs. PDF icon 2006_deer_aneja.pdf More Documents & Publications Heavy-Duty Engine Technology for High Thermal Efficiency at EPA 2010 Emissions

  4. Internal Controls Over Sensitive Compartmented Information Access for

    Office of Environmental Management (EM)

    Selected Field Intelligence Elements, IG-0796 | Department of Energy Internal Controls Over Sensitive Compartmented Information Access for Selected Field Intelligence Elements, IG-0796 Internal Controls Over Sensitive Compartmented Information Access for Selected Field Intelligence Elements, IG-0796 As a member of the U.S. Government's Intelligence Community, the Department of Energy (DOE) serves as the premier technical intelligence resource in the areas of nuclear weapons,

  5. EM's First Business Opportunity Forum Draws over 70 People | Department

    Office of Environmental Management (EM)

    of Energy First Business Opportunity Forum Draws over 70 People EM's First Business Opportunity Forum Draws over 70 People September 4, 2014 - 12:00pm Addthis EM Acquisition and Project Management Deputy Assistant Secretary Jack Surash discusses EM's acquisition program during Thursday's forum. EM Acquisition and Project Management Deputy Assistant Secretary Jack Surash discusses EM's acquisition program during Thursday's forum. Surash answers questions from participants during the forum.

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

    SciTech Connect (OSTI)

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

    2014-05-01

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

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

    SciTech Connect (OSTI)

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

    2009-06-01

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

  8. Estimation of Groundwater Recharge at Pahute Mesa using the Chloride Mass-Balance Method

    SciTech Connect (OSTI)

    Cooper, Clay A; Hershey, Ronald L; Healey, John M; Lyles, Brad F

    2013-07-01

    Groundwater recharge on Pahute Mesa was estimated using the chloride mass-balance (CMB) method. This method relies on the conservative properties of chloride to trace its movement from the atmosphere as dry- and wet-deposition through the soil zone and ultimately to the saturated zone. Typically, the CMB method assumes no mixing of groundwater with different chloride concentrations; however, because groundwater is thought to flow into Pahute Mesa from valleys north of Pahute Mesa, groundwater flow rates (i.e., underflow) and chloride concentrations from Kawich Valley and Gold Flat were carefully considered. Precipitation was measured with bulk and tipping-bucket precipitation gauges installed for this study at six sites on Pahute Mesa. These data, along with historical precipitation amounts from gauges on Pahute Mesa and estimates from the PRISM model, were evaluated to estimate mean annual precipitation. Chloride deposition from the atmosphere was estimated by analyzing quarterly samples of wet- and dry-deposition for chloride in the bulk gauges and evaluating chloride wet-deposition amounts measured at other locations by the National Atmospheric Deposition Program. Mean chloride concentrations in groundwater were estimated using data from the UGTA Geochemistry Database, data from other reports, and data from samples collected from emplacement boreholes for this study. Calculations were conducted assuming both no underflow and underflow from Kawich Valley and Gold Flat. Model results estimate recharge to be 30 mm/yr with a standard deviation of 18 mm/yr on Pahute Mesa, for elevations >1800 m amsl. These estimates assume Pahute Mesa recharge mixes completely with underflow from Kawich Valley and Gold Flat. The model assumes that precipitation, chloride concentration in bulk deposition, underflow and its chloride concentration, have been constant over the length of time of recharge.

  9. Estimated Water Flows in 2005: United States

    SciTech Connect (OSTI)

    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.

  10. New developments in capital cost estimating

    SciTech Connect (OSTI)

    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.

  11. Contractor: Contract Number: Contract Type: Total Estimated

    Office of Environmental Management (EM)

    Contract Number: Contract Type: Total Estimated Contract Cost: Performance Period Total Fee Paid FY2004 $294,316 FY2005 $820,074 FY2006 $799,449 FY2007 $877,898 FY2008 $866,608 FY2009 $886,404 FY2010 $800,314 FY2011 $871,280 FY2012 $824,517 FY2013 Cumulative Fee Paid $7,040,860 $820,074 $799,449 $877,898 $916,130 $886,608 Computer Sciences Corporation DE-AC06-04RL14383 $895,358 $899,230 $907,583 Cost Plus Award Fee $134,100,336 $8,221,404 Fee Available Contract Period: Fee Information Minimum

  12. Simulation of Electron Cloud Density Distributions in RHIC Dipoles at Injection and Transition and Estimates for Scrubbing Times

    SciTech Connect (OSTI)

    He,P.; Blaskiewicz, M.; Fischer, W.

    2009-01-02

    In this report we summarize electron-cloud simulations for the RHIC dipole regions at injection and transition to estimate if scrubbing over practical time scales at injection would reduce the electron cloud density at transition to significantly lower values. The lower electron cloud density at transition will allow for an increase in the ion intensity.

  13. 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 Estimates Economic Benefits of Offshore Wind Plants October 1, 2013 - 3:28pm Addthis To help ...

  14. Property:EstimatedCostLowUSD | Open Energy Information

    Open Energy Info (EERE)

    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...

  15. Property:EstimatedCostHighUSD | Open Energy Information

    Open Energy Info (EERE)

    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...

  16. Property:EstimatedCostMedianUSD | Open Energy Information

    Open Energy Info (EERE)

    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...

  17. Microsoft PowerPoint - 15.1615_Cost Estimating Panel

    Energy Savers [EERE]

    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...

  18. Texas Dry Natural Gas Reserves Estimated Production (Billion...

    Gasoline and Diesel Fuel Update (EIA)

    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...

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

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

    Estimated Production (Billion Cubic Feet) New York 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...

  20. Evolution of Safeguards over Time: Past, Present, and Projected Facilities, Material, and Budget

    SciTech Connect (OSTI)

    Kollar, Lenka; Mathews, Caroline E.

    2009-07-01

    This study examines the past trends and evolution of safeguards over time and projects growth through 2030. The report documents the amount of nuclear material and facilities under safeguards from 1970 until present, along with the corresponding budget. Estimates for the future amount of facilities and material under safeguards are made according to non-nuclear-weapons states (NNWS) plans to build more nuclear capacity and sustain current nuclear infrastructure. Since nuclear energy is seen as a clean and economic option for base load electric power, many countries are seeking to either expand their current nuclear infrastructure, or introduce nuclear power. In order to feed new nuclear power plants and sustain existing ones, more nuclear facilities will need to be built, and thus more nuclear material will be introduced into the safeguards system. The projections in this study conclude that a zero real growth scenario for the IAEA safeguards budget will result in large resource gaps in the near future.

  1. Black Carbon Radiative Forcing over the Tibetan Plateau

    SciTech Connect (OSTI)

    He, Cenlin; Li, Qinbin; Liou, K. N.; Takano, Y.; Gu, Yu; Qi, L.; Mao, Yuhao; Leung, Lai-Yung R.

    2014-11-28

    We estimate the snow albedo forcing and direct radiative forcing (DRF) of black carbon (BC) in the Tibetan Plateau using a global chemical transport model in conjunction with a stochastic snow model and a radiative transfer model. Our best estimate of the annual BC snow albedo forcing in the Plateau is 2.9 W m-2 (uncertainty: 1.55.0 W m-226 ). We find that BC-snow internal mixing increases the albedo forcing by 40-60% compared with external mixing and coated BC increases the forcing by 30-50% compared with uncoated BC, whereas Koch snowflakes reduce the forcing by 20-40% relative to spherical snow grains. Our best estimate of the annual BC DRF at the top of the atmosphere is 2.3 W m-2 (uncertainty: 0.74.3 W m-230 ) in the Plateau after scaling the modeled BC absorption optical depth to Aerosol Robotic Network (AERONET) observations. The BC forcings are attributed to emissions from different regions.

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

    Broader source: Energy.gov [DOE]

    The U.S. Department of Energy Zero Energy Ready Home Savings and Cost Estimate Summary, October 2015

  3. Direct Hydrogen PEMFC Manufacturing Cost Estimation for Automotive

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

    Applications: Fuel Cell Tech Team Review | Department of Energy Direct Hydrogen PEMFC Manufacturing Cost Estimation for Automotive Applications: Fuel Cell Tech Team Review Direct Hydrogen PEMFC Manufacturing Cost Estimation for Automotive Applications: Fuel Cell Tech Team Review This presentation reports on direct hydrogen PEMFC manufacturing cost estimation for automotive applications. PDF icon Direct Hydrogen PEMFC Manufacturing Cost Estimation for Automotive Applications: Fuel Cell Tech

  4. 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

  5. Steady state estimation of soil organic carbon using satellite-derived canopy leaf area index

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Fang, Yilin; Liu, Chongxuan; Huang, Maoyi; Li, Hongyi; Leung, Lai-Yung R.

    2014-12-02

    Soil organic carbon (SOC) plays a key role in the global carbon cycle that is important for decadal-to-century climate prediction. Estimation of soil organic carbon stock using model-based methods typically requires spin-up (time marching transient simulation) of the carbon-nitrogen (CN) models by performing hundreds to thousands years long simulations until the carbon-nitrogen pools reach dynamic steady-state. This has become a bottleneck for global modeling and analysis, especially when testing new physical and/or chemical mechanisms and evaluating parameter sensitivity. Here we report a new numerical approach to estimate global soil carbon stock that can avoid the long term spin-up of themore » CN model. The approach uses canopy leaf area index (LAI) from satellite data and takes advantage of a reaction-based biogeochemical module NGBGC (Next Generation BioGeoChemical Module) that was recently developed and incorporated in version 4 of the Community Land Model (CLM4). Although NGBGC uses the same CN mechanisms as used in CLM4CN, it can be easily configured to run prognostic or steady state simulations. In this approach, monthly LAI from the multi-year Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to calculate potential annual average gross primary production (GPP) and leaf carbon for the period of the atmospheric forcing. The calculated potential annual average GPP and leaf C are then used by NGBGC to calculate the steady-state distributions of carbon and nitrogen in different vegetation and soil pools by solving the steady-state reaction-network in NGBGC using the Newton-Raphson method. The new approach was applied at point and global scales and compared with SOC derived from long spin-up by running NGBGC in prognostic mode, and SOC from the empirical data of the Harmonized World Soil Database (HWSD). The steady-state solution is comparable to the spin-up value when the MODIS LAI is close to the LAI from the spin-up solution, and largely captured the variability of the HWSD SOC across the different dominant plant functional types (PFTs) at global scale. The numerical correlation between the calculated and HWSD SOC was, however, weak at both point and global scales, suggesting that the models used in describing biogeochemical processes in CLM needs improvements and/or HWSD needs updating as suggested by other studies. Besides SOC, the steady state solution also includes all other state variables simulated by a spin-up run, such as NPP, GPP, total vegetation C etc., which makes the developed approach a promising tool to efficiently estimate global SOC distribution and evaluate and compare different aspects simulated by different CN mechanisms in the model.« less

  6. Steady state estimation of soil organic carbon using satellite-derived canopy leaf area index

    SciTech Connect (OSTI)

    Fang, Yilin; Liu, Chongxuan; Huang, Maoyi; Li, Hongyi; Leung, Lai-Yung R.

    2014-12-02

    Soil organic carbon (SOC) plays a key role in the global carbon cycle that is important for decadal-to-century climate prediction. Estimation of soil organic carbon stock using model-based methods typically requires spin-up (time marching transient simulation) of the carbon-nitrogen (CN) models by performing hundreds to thousands years long simulations until the carbon-nitrogen pools reach dynamic steady-state. This has become a bottleneck for global modeling and analysis, especially when testing new physical and/or chemical mechanisms and evaluating parameter sensitivity. Here we report a new numerical approach to estimate global soil carbon stock that can avoid the long term spin-up of the CN model. The approach uses canopy leaf area index (LAI) from satellite data and takes advantage of a reaction-based biogeochemical module NGBGC (Next Generation BioGeoChemical Module) that was recently developed and incorporated in version 4 of the Community Land Model (CLM4). Although NGBGC uses the same CN mechanisms as used in CLM4CN, it can be easily configured to run prognostic or steady state simulations. In this approach, monthly LAI from the multi-year Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to calculate potential annual average gross primary production (GPP) and leaf carbon for the period of the atmospheric forcing. The calculated potential annual average GPP and leaf C are then used by NGBGC to calculate the steady-state distributions of carbon and nitrogen in different vegetation and soil pools by solving the steady-state reaction-network in NGBGC using the Newton-Raphson method. The new approach was applied at point and global scales and compared with SOC derived from long spin-up by running NGBGC in prognostic mode, and SOC from the empirical data of the Harmonized World Soil Database (HWSD). The steady-state solution is comparable to the spin-up value when the MODIS LAI is close to the LAI from the spin-up solution, and largely captured the variability of the HWSD SOC across the different dominant plant functional types (PFTs) at global scale. The numerical correlation between the calculated and HWSD SOC was, however, weak at both point and global scales, suggesting that the models used in describing biogeochemical processes in CLM needs improvements and/or HWSD needs updating as suggested by other studies. Besides SOC, the steady state solution also includes all other state variables simulated by a spin-up run, such as NPP, GPP, total vegetation C etc., which makes the developed approach a promising tool to efficiently estimate global SOC distribution and evaluate and compare different aspects simulated by different CN mechanisms in the model.

  7. Total Natural Gas Gross Withdrawals (Summary)

    Gasoline and Diesel Fuel Update (EIA)

    Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 1231 Reserves...

  8. Solar Energy Gross Receipts Tax Deduction

    Broader source: Energy.gov [DOE]

    The seller must have a signed copy of Form RPD-41341 to claim the deduction or other evidence acceptable to EMNRD that the service or equipment was purchased for the sole use of the sale and...

  9. Advanced Energy Gross Receipts Tax Deduction

    Broader source: Energy.gov [DOE]

    To qualify for the exemption, the owner of a qualified generating facility must first obtain a certificate of eligibility from the Department of Environment. The owner must then present the...

  10. Property:GrossGen | Open Energy Information

    Open Energy Info (EERE)

    B Blundell 1 Geothermal Facility + 213,599 + Blundell 2 Geothermal Facility + 85,633 + G Gumuskoy Geothermal Power Plant + 104,000 + L Las Tres Virgenes Geothermal Plant + 19 +...

  11. Mississippi Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

    2-2015 Repressuring NA NA NA NA NA NA 1991-2015 Vented and Flared NA NA NA NA NA NA 1996-2015 Nonhydrocarbon Gases Removed NA NA NA NA NA NA 1991-2015 Marketed Production NA NA NA NA NA NA 1989-2015 Dry Production 2006

  12. Missouri Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

    7-2015 Repressuring NA NA NA NA NA NA 1991-2015 Vented and Flared NA NA NA NA NA NA 1991-2015 Nonhydrocarbon Gases Removed NA NA NA NA NA NA 1991-2015 Marketed Production NA NA NA NA NA NA 1991-2015 Dry Production 2007

  13. Natural Gas Gross Withdrawals from Coalbed Wells

    Gasoline and Diesel Fuel Update (EIA)

    2002-2015 Alaska NA NA NA NA NA NA 2002-2015 Arkansas NA NA NA NA NA NA 2006-2015 California NA NA NA NA NA NA 2002-2015 Colorado NA NA NA NA NA NA 2002-2015 Federal Offshore Gulf of Mexico NA NA NA NA NA NA 2002-2015 Kansas NA NA NA NA NA NA 2002-2015 Louisiana NA NA NA NA NA NA 2002-2015 Montana NA NA NA NA NA NA 2002-2015 New Mexico NA NA NA NA NA NA 2002-2015 North Dakota NA NA NA NA NA NA 2002-2015 Ohio NA NA NA NA NA NA 2006-2015 Oklahoma NA NA NA NA NA NA 2002-2015 Pennsylvania NA NA NA

  14. Nebraska Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

    NA NA NA NA NA NA 1991-2015 From Gas Wells NA NA NA NA NA NA 1991-2015 From Oil Wells NA NA NA NA NA NA 1991-2015 From Shale Gas Wells NA NA NA NA NA NA 2007-2015 From Coalbed Wells NA NA NA NA NA NA 2006-2015 Repressuring NA NA NA NA NA NA 1991-2015 Vented and Flared NA NA NA NA NA NA 1991-2015 Nonhydrocarbon Gases Removed NA NA NA NA NA NA 1991-2015 Marketed Production NA NA NA NA NA NA 1991

  15. Nevada Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

  16. Alabama Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

    U.S. Offshore U.S. State Offshore Federal Offshore U.S. Alaska Alaska Onshore Alaska Offshore Alaska State Offshore Arkansas California California Onshore California Offshore California State Offshore Federal Offshore California Colorado Federal Offshore Gulf of Mexico Federal Offshore Alabama Federal Offshore Louisiana Federal Offshore Texas Kansas Louisiana Louisiana Onshore Louisiana Offshore Louisiana State Offshore Montana New Mexico North Dakota Ohio Oklahoma Pennsylvania Texas Texas

  17. Alabama Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

    Alaska Arkansas California Colorado Federal Offshore Gulf of Mexico Kansas Louisiana Montana New Mexico North Dakota Ohio Oklahoma Pennsylvania Texas Utah West Virginia Wyoming Other States Total Alabama Arizona Florida Illinois Indiana Kentucky Maryland Michigan Mississippi Missouri Nebraska Nevada New York Oregon South Dakota Tennessee Virginia Period-Unit: Monthly-Million Cubic Feet Monthly-Million Cubic Feet per Day Annual-Million Cubic Feet Download Series History Download Series History

  18. Alaska Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

    U.S. Offshore U.S. State Offshore Federal Offshore U.S. Alaska Alaska Onshore Alaska Offshore Alaska State Offshore Arkansas California California Onshore California Offshore California State Offshore Federal Offshore California Colorado Federal Offshore Gulf of Mexico Federal Offshore Alabama Federal Offshore Louisiana Federal Offshore Texas Kansas Louisiana Louisiana Onshore Louisiana Offshore Louisiana State Offshore Montana New Mexico North Dakota Ohio Oklahoma Pennsylvania Texas Texas

  19. Alaska Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

    Alaska Arkansas California Colorado Federal Offshore Gulf of Mexico Kansas Louisiana Montana New Mexico North Dakota Ohio Oklahoma Pennsylvania Texas Utah West Virginia Wyoming Other States Total Alabama Arizona Florida Illinois Indiana Kentucky Maryland Michigan Mississippi Missouri Nebraska Nevada New York Oregon South Dakota Tennessee Virginia Period-Unit: Monthly-Million Cubic Feet Monthly-Million Cubic Feet per Day Annual-Million Cubic Feet Download Series History Download Series History

  20. Arizona Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

    U.S. Offshore U.S. State Offshore Federal Offshore U.S. Alaska Alaska Onshore Alaska Offshore Alaska State Offshore Arkansas California California Onshore California Offshore California State Offshore Federal Offshore California Colorado Federal Offshore Gulf of Mexico Federal Offshore Alabama Federal Offshore Louisiana Federal Offshore Texas Kansas Louisiana Louisiana Onshore Louisiana Offshore Louisiana State Offshore Montana New Mexico North Dakota Ohio Oklahoma Pennsylvania Texas Texas

  1. Arkansas Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

    U.S. Offshore U.S. State Offshore Federal Offshore U.S. Alaska Alaska Onshore Alaska Offshore Alaska State Offshore Arkansas California California Onshore California Offshore California State Offshore Federal Offshore California Colorado Federal Offshore Gulf of Mexico Federal Offshore Alabama Federal Offshore Louisiana Federal Offshore Texas Kansas Louisiana Louisiana Onshore Louisiana Offshore Louisiana State Offshore Montana New Mexico North Dakota Ohio Oklahoma Pennsylvania Texas Texas

  2. Arkansas Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

    Alaska Arkansas California Colorado Federal Offshore Gulf of Mexico Kansas Louisiana Montana New Mexico North Dakota Ohio Oklahoma Pennsylvania Texas Utah West Virginia Wyoming Other States Total Alabama Arizona Florida Illinois Indiana Kentucky Maryland Michigan Mississippi Missouri Nebraska Nevada New York Oregon South Dakota Tennessee Virginia Period-Unit: Monthly-Million Cubic Feet Monthly-Million Cubic Feet per Day Annual-Million Cubic Feet Download Series History Download Series History

  3. Indiana Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

  4. Kentucky Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

    NA NA NA NA NA NA 1991-2015 From Gas Wells NA NA NA NA NA NA 1991-2015 From Oil Wells NA NA NA NA NA NA 1991-2015 From Shale Gas Wells NA NA NA NA NA NA 2007-2015 From Coalbed Wells NA NA NA NA NA NA 2006-2015 Repressuring NA NA NA NA NA NA 1991-2015 Vented and Flared NA NA NA NA NA NA 1991-2015 Nonhydrocarbon Gases Removed NA NA NA NA NA NA 1991-2015 Marketed Production NA NA NA NA NA NA 1991

  5. Maryland Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

    6-2015 Repressuring NA NA NA NA NA NA 1991-2015 Vented and Flared NA NA NA NA NA NA 1991-2015 Nonhydrocarbon Gases Removed NA NA NA NA NA NA 1991-2015 Marketed Production NA NA NA NA NA NA 1991

  6. Tennessee Natural Gas Gross Withdrawals and Production

    Gasoline and Diesel Fuel Update (EIA)

  7. Louisiana Natural Gas Gross Withdrawals and Production

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

    159,456 166,570 164,270 166,973 161,280 163,799 1991-2015 From Gas Wells NA NA NA NA NA NA 1991-2015 From Oil Wells NA NA NA NA NA NA 1991-2015 From Shale Gas Wells NA NA NA NA NA ...

  8. ,"Arizona Natural Gas Gross Withdrawals and Production"

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

    Monthly","122015","1151991" ,"Release Date:","2292016" ,"Next Release Date:","3312016" ,"Excel File Name:","ngprodsumdcsazmmcfm.xls" ,"Available from Web ...

  9. Natural Gas Gross Withdrawals from Oil Wells

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

    1-2015 Illinois NA NA NA NA NA NA 1991-2015 Indiana NA NA NA NA NA NA 1991-2015 Kentucky NA NA NA NA NA NA 1991-2015 Maryland NA NA NA NA NA NA 1991-2015 Michigan NA NA NA NA NA NA ...

  10. Michigan Natural Gas Gross Withdrawals and Production

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

    NA NA NA NA NA NA 1991-2015 From Gas Wells NA NA NA NA NA NA 1991-2015 From Oil Wells NA NA NA NA NA NA 1991-2015 From Shale Gas Wells NA NA NA NA NA NA 2007-2015 From Coalbed ...

  11. Colorado Natural Gas Gross Withdrawals and Production

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

    39,822 143,397 138,325 144,845 139,698 141,947 1991-2015 From Gas Wells NA NA NA NA NA NA 1991-2015 From Oil Wells NA NA NA NA NA NA 1991-2015 From Shale Gas Wells NA NA NA NA NA ...

  12. ,"Arkansas Natural Gas Gross Withdrawals and Production"

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

    Monthly","122015","1151991" ,"Release Date:","2292016" ,"Next Release Date:","331...14,19600,16058,3542,,,156,21,0,18960 35445,19915,16196,3719,,,208,5,0,19147 ...

  13. Kansas Natural Gas Gross Withdrawals and Production

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

    24,842 24,864 23,819 23,559 22,371 22,744 1991-2015 From Gas Wells NA NA NA NA NA NA 1991-2015 From Oil Wells NA NA NA NA NA NA 1991-2015 From Shale Gas Wells NA NA NA NA NA NA ...

  14. Arizona Natural Gas Gross Withdrawals and Production

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

    NA NA NA NA NA NA 1996-2015 From Gas Wells NA NA NA NA NA NA 1991-2015 From Oil Wells NA NA NA NA NA NA 1991-2015 From Shale Gas Wells NA NA NA NA NA NA 2007-2015 From Coalbed ...

  15. Natural Gas Gross Withdrawals from Gas Wells

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

    6-2015 Illinois NA NA NA NA NA NA 1991-2015 Indiana NA NA NA NA NA NA 1991-2015 Kentucky NA NA NA NA NA NA 1991-2015 Maryland NA NA NA NA NA NA 1991-2015 Michigan NA NA NA NA NA NA ...

  16. Florida Natural Gas Gross Withdrawals and Production

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

    6-2015 From Oil Wells NA NA NA NA NA NA 1991-2015 From Shale Gas Wells NA NA NA NA NA NA 2007-2015 From Coalbed Wells NA NA NA NA NA NA 2002-2015 Repressuring NA NA NA NA NA NA ...

  17. Montana Natural Gas Gross Withdrawals and Production

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

    4,941 4,756 4,573 4,827 4,568 4,681 1991-2015 From Gas Wells NA NA NA NA NA NA 1991-2015 From Oil Wells NA NA NA NA NA NA 1991-2015 From Shale Gas Wells NA NA NA NA NA NA 2007-2015 ...

  18. California Natural Gas Gross Withdrawals and Production

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

    9,225 19,655 18,928 18,868 18,266 18,868 1991-2015 From Gas Wells NA NA NA NA NA NA 1991-2015 From Oil Wells NA NA NA NA NA NA 1991-2015 From Shale Gas Wells NA NA NA NA NA NA ...

  19. Illinois Natural Gas Gross Withdrawals and Production

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

    NA NA NA NA NA NA 1991-2015 From Shale Gas Wells NA NA NA NA NA NA 2007-2015 From Coalbed Wells NA NA NA NA NA NA 2006-2015 Repressuring NA NA NA NA NA NA 1991-2015 Vented and ...

  20. Monthly Natural Gas Gross Production Report

    Gasoline and Diesel Fuel Update (EIA)