Sample records for model output location

  1. Community Climate System Model (CCSM) Experiments and Output Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The CCSM web makes the source code of various versions of the model freely available and provides access to experiments that have been run and the resulting output data.

  2. Simple SPICE model for comparison of CMOS output driver circuits

    E-Print Network [OSTI]

    Hermann, John Karl

    1993-01-01T23:59:59.000Z

    to monitor the ground nodes of output driver circuits for noise. Both relative performance and noise levels are generated through the simulations. A test device was built to confirm that the model was effective in speed and noise comparisons. Values were... on CMOS technologies. Journal model is IEEE 'I?ansactions on Automatic Control. A. Literature Survey Research has been done in the past concerning noise generated by digital logic de- vices. In particular, Advanced CMOS Logic (ACL) integrated circuits...

  3. Modeling of passive microwave responses in convective situations using output from mesoscale models

    E-Print Network [OSTI]

    Pardo-Carrión, Juan R.

    Modeling of passive microwave responses in convective situations using output from mesoscale models using output from nonhydrostatic mesoscale atmospheric model, Meso-NH, simulations. The radiative for a systematic evaluation of the mesoscale cloud models. An overall good agreement is obtained for both

  4. Observer-Controllers for Output Regulation: the Internal Model Principle Revisited

    E-Print Network [OSTI]

    Pao, Lucy Y.

    Observer-Controllers for Output Regulation: the Internal Model Principle Revisited Jason H. Laks rejection;tracking;model predictive control;output feedback control 1 Introduction Output regulation, the design of an output regulating observer-controller is less clear. This latter approach is based

  5. Statistical post processing of model output from the air quality model LOTOS-EUROS

    E-Print Network [OSTI]

    Stoffelen, Ad

    are calculated with R, a language for statistical computing. The routine STEP in R is used to remove variablesStatistical post processing of model output from the air quality model LOTOS-EUROS Annemiek Pijnappel De Bilt, 2011 | Stageverslag #12;#12;Statistical post processing of model output from the air

  6. An Advanced simulation Code for Modeling Inductive Output Tubes

    SciTech Connect (OSTI)

    Thuc Bui; R. Lawrence Ives

    2012-04-27T23:59:59.000Z

    During the Phase I program, CCR completed several major building blocks for a 3D large signal, inductive output tube (IOT) code using modern computer language and programming techniques. These included a 3D, Helmholtz, time-harmonic, field solver with a fully functional graphical user interface (GUI), automeshing and adaptivity. Other building blocks included the improved electrostatic Poisson solver with temporal boundary conditions to provide temporal fields for the time-stepping particle pusher as well as the self electric field caused by time-varying space charge. The magnetostatic field solver was also updated to solve for the self magnetic field caused by time changing current density in the output cavity gap. The goal function to optimize an IOT cavity was also formulated, and the optimization methodologies were investigated.

  7. Use of Advanced Meteorological Model Output for Coastal Ocean Modeling in Puget Sound

    SciTech Connect (OSTI)

    Yang, Zhaoqing; Khangaonkar, Tarang; Wang, Taiping

    2011-06-01T23:59:59.000Z

    It is a great challenge to specify meteorological forcing in estuarine and coastal circulation modeling using observed data because of the lack of complete datasets. As a result of this limitation, water temperature is often not simulated in estuarine and coastal modeling, with the assumption that density-induced currents are generally dominated by salinity gradients. However, in many situations, temperature gradients could be sufficiently large to influence the baroclinic motion. In this paper, we present an approach to simulate water temperature using outputs from advanced meteorological models. This modeling approach was applied to simulate annual variations of water temperatures of Puget Sound, a fjordal estuary in the Pacific Northwest of USA. Meteorological parameters from North American Region Re-analysis (NARR) model outputs were evaluated with comparisons to observed data at real-time meteorological stations. Model results demonstrated that NARR outputs can be used to drive coastal ocean models for realistic simulations of long-term water-temperature distributions in Puget Sound. Model results indicated that the net flux from NARR can be further improved with the additional information from real-time observations.

  8. Neural Networks for Post-processing Model Output: Caren Marzban

    E-Print Network [OSTI]

    Marzban, Caren

    variables to the neural network are: Forecast hour, model forecast temperature, relative humidity, wind direction and speed, mean sea level pressure, cloud cover, and precipitation rate and amount. The single to being able to approximate a large class of functions, they are less inclined to overfit data than some

  9. Modeling the Energy Output from an In-Stream Tidal Turbine Farm

    E-Print Network [OSTI]

    Ye Li; Barbara J. Lence; Sander M. Calisal

    Abstract—This paper is based on a recent paper presented in the 2007 IEEE SMC conference by the same authors [1], discussing an approach to predicting energy output from an instream tidal turbine farm. An in-stream tidal turbine is a device for harnessing energy from tidal currents in channels, and functions in a manner similar to a wind turbine. A group of such turbines distributed in a site is called an in-stream tidal turbine farm which is similar to a wind farm. Approaches to estimating energy output from wind farms cannot be fully transferred to study tidal farms, however, because of the complexities involved in modeling turbines underwater. In this paper, we intend to develop an approach for predicting energy output of an in-stream tidal turbine farm. The mathematical formulation and basic procedure for predicting power output of a stand-alone turbine 1 is presented, which includes several highly nonlinear terms. In order to facilitate the computation and utilize the formulation for predicting power output from a turbine farm, a simplified relationship between turbine distribution and turbine farm energy output is derived. A case study is then conducted by applying the numerical procedure to predict the energy output of the farms. Various scenarios are implemented according to the environmental conditions in Seymour Narrows, British Columbia, Canada. Additionally, energy cost results are presented as an extension. Index Terms—renewable energy, in-stream turbine, tidal current, tidal power, vertical axis turbine, farm system modeling, in-stream tidal turbine farm 1 A stand-alone turbine refers to a turbine around which there is no other turbine that might potentially affect the performance of this turbine.

  10. Residential mobility and location choice: a nested logit model with sampling of alternatives

    E-Print Network [OSTI]

    Lee, Brian H.; Waddell, Paul

    2010-01-01T23:59:59.000Z

    Waddell, P. : Modeling residential location in UrbanSim. In:D. (eds. ) Modelling Residential Location Choice. Springer,based model system and a residential location model. Urban

  11. Quartz resonators thermal modelization using located constants networks

    E-Print Network [OSTI]

    Boyer, Edmond

    of quartz resonator. The designed model is tested by comparison of the experimental frequency versus235 Quartz resonators thermal modelization using located constants networks S. Galliou and J. P modelization of quartz resonators is first presented ; next, the method consisting on establishing a located

  12. Characteristic Operator Functions for Quantum Input-Plant-Output Models & Coherent Control

    E-Print Network [OSTI]

    J. E. Gough

    2015-01-09T23:59:59.000Z

    We introduce the characteristic operator as the generalization of the usual concept of a transfer function of linear input-plant-output systems to arbitrary quantum nonlinear Markovian input-output models. This is intended as a tool in the characterization of quantum feedback control systems that fits in with the general theory of networks. The definition exploits the linearity of noise differentials in both the plant Heisenberg equations of motion and the differential form of the input-output relations. Mathematically, the characteristic operator is a matrix of dimension equal to the number of outputs times the number of inputs (which must coincide), but with entries that are operators of the plant system. In this sense the characteristic operator retains details of the effective plant dynamical structure and is an essentially quantum object. We illustrate the relevance to model reduction and simplification by showing that the convergence of the characteristic operator in adiabatic elimination limit models requires the same conditions and assumptions appearing in the work on limit quantum stochastic differential theorems of Bouten and Silberfarb. This approach also shows in a natural way that the limit coefficients of the quantum stochastic differential equations in adiabatic elimination problems arise algebraically as Schur complements, and amounts to a model reduction where the fast degrees of freedom are decoupled from the slow ones, and eliminated.

  13. Bayesian Emulation of Complex Multi-Output and Dynamic Computer Models

    E-Print Network [OSTI]

    Oakley, Jeremy

    Bayesian Emulation of Complex Multi-Output and Dynamic Computer Models Stefano Conti Anthony O the case). In particular, standard Monte Carlo-based methods of sensitivity analysis (extensively reviewed'Hagan, 2002), offering substantial efficiency gains over standard Monte Carlo-based meth- ods. These authors

  14. Using Weather Data and Climate Model Output in Economic Analyses of Climate Change

    SciTech Connect (OSTI)

    Auffhammer, Maximilian [University of California at Berkeley; Hsiang, Solomon M. [Princeton University; Schlenker, Wolfram [Columbia University; Sobel, Adam H. [Columbia University

    2013-06-28T23:59:59.000Z

    Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overview of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.

  15. Model-based Lifecycle Optimization of Well Locations

    E-Print Network [OSTI]

    Van den Hof, Paul

    Model-based Lifecycle Optimization of Well Locations and Production Settings in Petroleum Reservoirs #12;#12;MODEL-BASED LIFECYCLE OPTIMIZATION OF WELL LOCATIONS AND PRODUCTION SETTINGS IN PETROLEUM System Approach Petroleum Production" (ISAPP) programme. The knowledge center is a long-term co

  16. A MODELING APPROACH FOR LOCATING LOGISTICS PLATFORMS FOR FAST PARCEL

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 29 A MODELING APPROACH FOR LOCATING LOGISTICS PLATFORMS FOR FAST PARCEL DELIVERY IN URBAN AREAS for optimizing, in a sustainable way (i.e. economical, eco-friendly and societal), the location of logistics has a logistics platform right in its centre (ARENC: 41362 m2 of warehouses and offices

  17. Models for Offender Target Location Selection with Explicit Dependency Structures

    E-Print Network [OSTI]

    O'Leary, Michael

    Models for Offender Target Location Selection with Explicit Dependency Structures Mike O'Leary April 30 - May 1, 2012 O'Leary & Tucker (Towson University) Target Location Selection QMDNS 2012 1 / 54 in this study We thank Phil Canter from the Baltimore County Police Department for his assistance. O'Leary

  18. Modeling Space-Time Dynamics of Aerosols Using Satellite Data and Atmospheric Transport Model Output

    E-Print Network [OSTI]

    Shi, Tao

    Modeling Space-Time Dynamics of Aerosols Using Satellite Data and Atmospheric Transport Model of aerosol optical depth across mainland Southeast Asia. We include a cross validation study to assess

  19. Modeling study of deposition locations in the 291-Z plenum

    SciTech Connect (OSTI)

    Mahoney, L.A.; Glissmeyer, J.A.

    1994-06-01T23:59:59.000Z

    The TEMPEST (Trent and Eyler 1991) and PART5 computer codes were used to predict the probable locations of particle deposition in the suction-side plenum of the 291-Z building in the 200 Area of the Hanford Site, the exhaust fan building for the 234-5Z, 236-Z, and 232-Z buildings in the 200 Area of the Hanford Site. The Tempest code provided velocity fields for the airflow through the plenum. These velocity fields were then used with TEMPEST to provide modeling of near-floor particle concentrations without particle sticking (100% resuspension). The same velocity fields were also used with PART5 to provide modeling of particle deposition with sticking (0% resuspension). Some of the parameters whose importance was tested were particle size, point of injection and exhaust fan configuration.

  20. Pervasive informatics and persistent actimetric information in health smart homes : From Language Model to Location Model

    E-Print Network [OSTI]

    Fouquet, Yannick

    Pervasive informatics and persistent actimetric information in health smart homes : From Language. Pervasive informatics and persistent actimetric information in health smart homes : From Language Model, this approach seems to be a good way of location modelling. Index Terms--smart flats for elderly people

  1. Grid-search event location with non-Gaussian error models

    E-Print Network [OSTI]

    Rodi, William L.

    This study employs an event location algorithm based on grid search to investigate the possibility of improving seismic event location accuracy by using non-Gaussian error models. The primary departure from the Gaussian ...

  2. Locating Pleistocene refugia: Comparing phylogeographic and ecological niche model predictions

    E-Print Network [OSTI]

    Waltari, Eric; Hijmans, Robert J.; Peterson, A. Townsend; Nyá ri, Á rpá d S.; Perkins, Susan L.; Guralnick, Robert P.

    2007-07-11T23:59:59.000Z

    , American Museum of Natural History, New York, New York, United States of America, 2 International Rice Research Institute, Los Ban˜os, Laguna, Philippines, 3Natural History Museum & Biodiversity Research Center, University of Kansas, Lawrence, Kansas.... Refugia identified in phylogeographic studies are shown as black outlines. Areas predicted to be refugia are in green, areas not predicted are in gray, and hatching indicates approximate locations of ice sheets [68]. Gray lines indicate present day...

  3. Model Validation and Spatial Interpolation by Combining Observations with Outputs from Numerical

    E-Print Network [OSTI]

    Washington at Seattle, University of

    ""r,c,rn The authors are for hel]JfuI #12;Abstract Constructing maps of pollution levels is vital for air quality concentrations. Key tlJords: air pollution, Ba~yesian inference, change of support, likelihood approaches, Matern Resolutions 2.5 Modeling a Nonstationary Covariance . 3 Estimation 3.1 Algorithm 4 Application: Air Pollution

  4. TEOS 04 Carbon Flux and C Pipe: Integrating sensor outputs to models Team Members

    E-Print Network [OSTI]

    California at Los Angeles, University of

    , Staff · Thomas Unwin, Staff · Hai Vo, Undergrad * Primary Contact Overview Our goal is to integrate model [Katul et. al. 2003] to estimate carbon and water fluxes. System(s) Description and/or Experiments] where Cw is water capacity, h is water pressure head, t is time, z is depth, K(h) is hydraulic constant

  5. Identifying damage locations under ambient vibrations utilizing vector autoregressive models and Mahalanobis distances

    E-Print Network [OSTI]

    Identifying damage locations under ambient vibrations utilizing vector autoregressive models Keywords: Damage location Ambient vibration Vector Autoregressive model Statistical pattern recognition Bridges Structural health monitoring a b s t r a c t This paper presents a study for identifying damage

  6. Effectiveness-Equity Models for Facility Location Problems on Tree ...

    E-Print Network [OSTI]

    2013-01-19T23:59:59.000Z

    pecially in situations that involve public facilities or resources. ... Department of Decision Sciences, School of Business, The George Washington University, Washington, ... First, the proposed models allow one to identify efficient (or Pareto opti-.

  7. Model for locating fluids` contracts in petroleum reservoirs

    SciTech Connect (OSTI)

    Udegbunam, E.O. [Illinois State Geological Survey, Champaign, IL (United States); Numbere, D.T. [Univ. of Missouri, Rolla, MO (United States)

    1994-12-31T23:59:59.000Z

    Direct determination of the gas-water contact (GWC) or the oil-water contact (OWC) in new wells from geophysical logs, core analysis data and/or whole core inspection is often difficult. Rapidly changing reservoir quality in the interval of interest or gradually changing saturation profiles in the vicinity of the contact can make the determination of the GWC or OWC difficult. This paper presents a model for the accurate placement of the GWC or OWC. The input data are water saturations at various well depths as interpreted from induction logs and the average residual oil saturation. When available, permeability and porosity values from core analysis may improve the result. Using a power-law equation or a Langmuir isotherm-type equation to represent the capillary pressure saturation relationship, the GWC or OWC is expressed as a function of water saturation and well depth. A nonlinear optimization technique is then used to determine the GWC or OWC. The applicability of this model is demonstrated with a field example. The calculated OWC values from all variations of the model fall within 4 feet of the actual OWC value. This model can only be applied in an oil or gas well where an equilibrium capillary curve and a hydrocarbon-water contact occur.

  8. An Electricity-focused Economic Input-output Model: Life-cycle Assessment and Policy Implications of Future Electricity Generation Scenarios

    E-Print Network [OSTI]

    , and the different means of generating power. We build a flexible framework for creating new industry sectors, supply of Future Electricity Generation Scenarios Joe Marriott Submitted in Partial Fulfillment of the Requirements in the input- output model of the U.S. economy, the power generation sector is an excellent candidate

  9. A 2D Random Walk Mobility Model for Location Management Studies in Wireless Networks

    E-Print Network [OSTI]

    Shenoy, Nirmala

    crossing rate' and `dwell time' studies using the same model with slight modifications for the square cell, namely the square cell and the hexagonal cell have been detailed. The analytical results obtained for location update rates and dwell times have been validated using simulated and published results

  10. An enhanced sector integration model for output and dose distribution calculation of irregular concave shaped electron beams

    SciTech Connect (OSTI)

    Gajewski, Romuald [Department of Medical Physics, Sydney West Cancer Network, Westmead, New South Wales 2145 (Australia)

    2009-07-15T23:59:59.000Z

    A comprehensive method of output factor and dose distribution calculation for electron beams has been developed. It allows one to calculate the output factors and isodose distributions in water of arbitrary shaped electron fields with excellent accuracy even for the cases of concaved, small, elongated beams, and extended source to surface distances (SSDs). The method requires two sets of data: Depth dose distribution per monitor unit for circular cutouts and depth dose distributions per monitor unit for circular blocks (plugs), both for two SSDs, one reference of 100 cm and second extended one. The method has been extensively tested using a combination of different irregular cutouts and various SSDs for the 6 and 9 MeV electron beams. The calculated values agreed with the measured data well within 1% for output factors and below 1 for {gamma} (gamma test) for isodose distributions. The computer program has been developed to facilitate the method for practical application. The method has been used for almost 8 years considerably cutting workload in the department.

  11. VOLUME 79, NUMBER 22 P H Y S I C A L R E V I E W L E T T E R S 1 DECEMBER 1997 Behaviors of Spike Output Jitter in the Integrate-and-Fire Model

    E-Print Network [OSTI]

    Feng, Jianfeng

    Output Jitter in the Integrate-and-Fire Model Jianfeng Feng Biomathematics Laboratory, The Babraham Institute, Cambridge CB2 4AT, United Kingdom (Received 17 April 1997) We consider behaviors of output jitter jitter is sensitive to the input distribution and can be a constant, diverge to infinity, or converge

  12. Correlation between model observer and human observer performance in CT imaging when lesion location is uncertain

    SciTech Connect (OSTI)

    Leng, Shuai; Yu, Lifeng; Zhang, Yi; McCollough, Cynthia H. [Department of Radiology, Mayo Clinic, 200 First Street Southwest, Rochester, Minnesota 55905 (United States)] [Department of Radiology, Mayo Clinic, 200 First Street Southwest, Rochester, Minnesota 55905 (United States); Carter, Rickey [Department of Biostatistics, Mayo Clinic, 200 First Street Southwest, Rochester, Minnesota 55905 (United States)] [Department of Biostatistics, Mayo Clinic, 200 First Street Southwest, Rochester, Minnesota 55905 (United States); Toledano, Alicia Y. [Biostatistics Consulting, LLC, 10606 Wheatley Street, Kensington, Maryland 20895 (United States)] [Biostatistics Consulting, LLC, 10606 Wheatley Street, Kensington, Maryland 20895 (United States)

    2013-08-15T23:59:59.000Z

    Purpose: The purpose of this study was to investigate the correlation between model observer and human observer performance in CT imaging for the task of lesion detection and localization when the lesion location is uncertain.Methods: Two cylindrical rods (3-mm and 5-mm diameters) were placed in a 35 × 26 cm torso-shaped water phantom to simulate lesions with ?15 HU contrast at 120 kV. The phantom was scanned 100 times on a 128-slice CT scanner at each of four dose levels (CTDIvol = 5.7, 11.4, 17.1, and 22.8 mGy). Regions of interest (ROIs) around each lesion were extracted to generate images with signal-present, with each ROI containing 128 × 128 pixels. Corresponding ROIs of signal-absent images were generated from images without lesion mimicking rods. The location of the lesion (rod) in each ROI was randomly distributed by moving the ROIs around each lesion. Human observer studies were performed by having three trained observers identify the presence or absence of lesions, indicating the lesion location in each image and scoring confidence for the detection task on a 6-point scale. The same image data were analyzed using a channelized Hotelling model observer (CHO) with Gabor channels. Internal noise was added to the decision variables for the model observer study. Area under the curve (AUC) of ROC and localization ROC (LROC) curves were calculated using a nonparametric approach. The Spearman's rank order correlation between the average performance of the human observers and the model observer performance was calculated for the AUC of both ROC and LROC curves for both the 3- and 5-mm diameter lesions.Results: In both ROC and LROC analyses, AUC values for the model observer agreed well with the average values across the three human observers. The Spearman's rank order correlation values for both ROC and LROC analyses for both the 3- and 5-mm diameter lesions were all 1.0, indicating perfect rank ordering agreement of the figures of merit (AUC) between the average performance of the human observers and the model observer performance.Conclusions: In CT imaging of different sizes of low-contrast lesions (?15 HU), the performance of CHO with Gabor channels was highly correlated with human observer performance for the detection and localization tasks with uncertain lesion location in CT imaging at four clinically relevant dose levels. This suggests the ability of Gabor CHO model observers to meaningfully assess CT image quality for the purpose of optimizing scan protocols and radiation dose levels in detection and localization tasks for low-contrast lesions.

  13. A Multi-Model Filter for Mobile Terminal Location M. McGuire , K.N. Plataniotis

    E-Print Network [OSTI]

    Plataniotis, Konstantinos N.

    A Multi-Model Filter for Mobile Terminal Location Tracking M. McGuire , K.N. Plataniotis The Edward's College Road, Toronto, Ontario, M5S 3G4, email: mmcguire@dsp.toronto.edu Abstract-- Mobile terminal and resource allocation. This paper presents a method for reducing the error in mobile terminal location

  14. Use of roof temperature modeling to predict necessary conditions for locating wet insulation with infrared thermography

    SciTech Connect (OSTI)

    Childs, K.W.

    1985-11-01T23:59:59.000Z

    In low-sloped roofing systems using porous insulation, the presence of water can significantly degrade thermal performance. For this reason, it is desirable to develop a reliable method for detecting the presence of water in a roofing system. Because of the different thermal characteristics of wet and dry insulation, there is often a surface temperature differential between areas containing wet insulation and areas containing dry insulation. Under the right circumstances, the areas of wet insulation can be detected by means of infrared sensing techniques. These techniques have already gained widespread acceptance, but there is still some uncertainty as to what are appropriate environmental conditions for viewing. To better define the conditions under which infrared techniques can distinguish between areas of wet and dry insulation, a one-dimensional, transient heat transfer model of a roofing system was developed. The model considers conduction through the roof, insolation on the surface, radiant exchange between the roof and sky, convective heat transfer between the roof and air, and the influence of trapped moisture on the thermal properties of the insulation. A study was undertaken using this model to develop an easily-applied technique for prediction of necessary conditions for locating wet roof insulation using infrared thermography.

  15. Comparisons of four categories of waste recycling in China's paper industry based on physical input-output life-cycle assessment model

    SciTech Connect (OSTI)

    Liang Sai [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China); Zhang, Tianzhu, E-mail: zhangtz@mail.tsinghua.edu.cn [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China); Xu Yijian [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China); China Academy of Urban Planning and Design, Beijing 100037 (China)

    2012-03-15T23:59:59.000Z

    Highlights: Black-Right-Pointing-Pointer Using crop straws and wood wastes for paper production should be promoted. Black-Right-Pointing-Pointer Bagasse and textile waste recycling should be properly limited. Black-Right-Pointing-Pointer Imports of scrap paper should be encouraged. Black-Right-Pointing-Pointer Sensitivity analysis, uncertainties and policy implications are discussed. - Abstract: Waste recycling for paper production is an important component of waste management. This study constructs a physical input-output life-cycle assessment (PIO-LCA) model. The PIO-LCA model is used to investigate environmental impacts of four categories of waste recycling in China's paper industry: crop straws, bagasse, textile wastes and scrap paper. Crop straw recycling and wood utilization for paper production have small total intensity of environmental impacts. Moreover, environmental impacts reduction of crop straw recycling and wood utilization benefits the most from technology development. Thus, using crop straws and wood (including wood wastes) for paper production should be promoted. Technology development has small effects on environmental impacts reduction of bagasse recycling, textile waste recycling and scrap paper recycling. In addition, bagasse recycling and textile waste recycling have big total intensity of environmental impacts. Thus, the development of bagasse recycling and textile waste recycling should be properly limited. Other pathways for reusing bagasse and textile wastes should be explored and evaluated. Moreover, imports of scrap paper should be encouraged to reduce large indirect impacts of scrap paper recycling on domestic environment.

  16. Sandia National Laboratories: simulating solar-power-plant output...

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

    simulating solar-power-plant output variability Sandia PV Team Publishes Book Chapter On January 21, 2014, in Computational Modeling & Simulation, Energy, Modeling & Analysis,...

  17. Treanmission Line Fault Location using Interoperability and Integration of Data and Model

    E-Print Network [OSTI]

    Dutta, Papiya

    2014-01-10T23:59:59.000Z

    . The second type is a sparse measurement based fault location scheme using phasor measurements from different substations located in the vicinity where the fault has occurred and can be applied if the measurements are not available from any of the line ends...

  18. Evaluation of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Populations

    E-Print Network [OSTI]

    Lloyd, Alun

    specific locations, the cities of Iquitos, Peru, and Buenos Aires, Argentina. These two sites differ that was averaged across all locations. In the Argentina case Skeeter Buster provides a satisfactory simulation from the Research and Policy for Infectious Disease Dynamics (RAPIDD) program of the Science

  19. Comparing urban solid waste recycling from the viewpoint of urban metabolism based on physical input-output model: A case of Suzhou in China

    SciTech Connect (OSTI)

    Liang Sai, E-mail: liangsai09@gmail.com [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China); Zhang Tianzhu, E-mail: zhangtz@mail.tsinghua.edu.cn [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China)

    2012-01-15T23:59:59.000Z

    Highlights: Black-Right-Pointing-Pointer Impacts of solid waste recycling on Suzhou's urban metabolism in 2015 are analyzed. Black-Right-Pointing-Pointer Sludge recycling for biogas is regarded as an accepted method. Black-Right-Pointing-Pointer Technical levels of reusing scrap tires and food wastes should be improved. Black-Right-Pointing-Pointer Other fly ash utilization methods should be exploited. Black-Right-Pointing-Pointer Secondary wastes from reusing food wastes and sludge should be concerned. - Abstract: Investigating impacts of urban solid waste recycling on urban metabolism contributes to sustainable urban solid waste management and urban sustainability. Using a physical input-output model and scenario analysis, urban metabolism of Suzhou in 2015 is predicted and impacts of four categories of solid waste recycling on urban metabolism are illustrated: scrap tire recycling, food waste recycling, fly ash recycling and sludge recycling. Sludge recycling has positive effects on reducing all material flows. Thus, sludge recycling for biogas is regarded as an accepted method. Moreover, technical levels of scrap tire recycling and food waste recycling should be improved to produce positive effects on reducing more material flows. Fly ash recycling for cement production has negative effects on reducing all material flows except solid wastes. Thus, other fly ash utilization methods should be exploited. In addition, the utilization and treatment of secondary wastes from food waste recycling and sludge recycling should be concerned.

  20. Treanmission Line Fault Location using Interoperability and Integration of Data and Model 

    E-Print Network [OSTI]

    Dutta, Papiya

    2014-01-10T23:59:59.000Z

    , classify and locate transmission line faults using synchronous samples of voltages and currents captured during fault transients from both ends of the transmission line of interest. The method is tested for several faults simulated on IEEE 118 bus test...

  1. Commissioning of output factors for uniform scanning proton beams

    SciTech Connect (OSTI)

    Zheng Yuanshui; Ramirez, Eric; Mascia, Anthony; Ding Xiaoning; Okoth, Benny; Zeidan, Omar; Hsi Wen; Harris, Ben; Schreuder, Andries N.; Keole, Sameer [ProCure Proton Therapy Center, 5901 West Memorial Road, Oklahoma City, Oklahoma 73142 (United States); ProCure Treatment Centers, 420 North Walnut Street, Bloomington, Indiana 47404 (United States); ProCure Proton Therapy Center, 5901 West Memorial Road, Oklahoma City, Oklahoma 73142 (United States)

    2011-04-15T23:59:59.000Z

    Purpose: Current commercial treatment planning systems are not able to accurately predict output factors and calculate monitor units for proton fields. Patient-specific field output factors are thus determined by either measurements or empirical modeling based on commissioning data. The objective of this study is to commission output factors for uniform scanning beams utilized at the ProCure proton therapy centers. Methods: Using water phantoms and a plane parallel ionization chamber, the authors first measured output factors with a fixed 10 cm diameter aperture as a function of proton range and modulation width for clinically available proton beams with ranges between 4 and 31.5 cm and modulation widths between 2 and 15 cm. The authors then measured the output factor as a function of collimated field size at various calibration depths for proton beams of various ranges and modulation widths. The authors further examined the dependence of the output factor on the scanning area (i.e., uncollimated proton field), snout position, and phantom material. An empirical model was developed to calculate the output factor for patient-specific fields and the model-predicted output factors were compared to measurements. Results: The output factor increased with proton range and field size, and decreased with modulation width. The scanning area and snout position have a small but non-negligible effect on the output factors. The predicted output factors based on the empirical modeling agreed within 2% of measurements for all prostate treatment fields and within 3% for 98.5% of all treatment fields. Conclusions: Comprehensive measurements at a large subset of available beam conditions are needed to commission output factors for proton therapy beams. The empirical modeling agrees well with the measured output factor data. This investigation indicates that it is possible to accurately predict output factors and thus eliminate or reduce time-consuming patient-specific output measurements for proton treatments.

  2. Comparison of CAISO-run Plexos output with LLNL-run Plexos output

    SciTech Connect (OSTI)

    Schmidt, A; Meyers, C; Smith, S

    2011-12-20T23:59:59.000Z

    In this report we compare the output of the California Independent System Operator (CAISO) 33% RPS Plexos model when run on various computing systems. Specifically, we compare the output resulting from running the model on CAISO's computers (Windows) and LLNL's computers (both Windows and Linux). We conclude that the differences between the three results are negligible in the context of the entire system and likely attributed to minor differences in Plexos version numbers as well as the MIP solver used in each case.

  3. Environmental Modelling & Software 15 (2000) 681692 www.elsevier.com/locate/envsoft

    E-Print Network [OSTI]

    Utah, University of

    2000-01-01T23:59:59.000Z

    -scale air pollution modelling using adaptive unstructured meshes A.S. Tomlin a,* , S. Ghorai a , G. Hart of Computer Studies, University of Leeds, Leeds LS2 9JT, UK Abstract High resolution models of air pollution but less so in meteorological and air pollution models. However, it is well known that grid resolution has

  4. Serial Input Output

    SciTech Connect (OSTI)

    Waite, Anthony; /SLAC

    2011-09-07T23:59:59.000Z

    Serial Input/Output (SIO) is designed to be a long term storage format of a sophistication somewhere between simple ASCII files and the techniques provided by inter alia Objectivity and Root. The former tend to be low density, information lossy (floating point numbers lose precision) and inflexible. The latter require abstract descriptions of the data with all that that implies in terms of extra complexity. The basic building blocks of SIO are streams, records and blocks. Streams provide the connections between the program and files. The user can define an arbitrary list of streams as required. A given stream must be opened for either reading or writing. SIO does not support read/write streams. If a stream is closed during the execution of a program, it can be reopened in either read or write mode to the same or a different file. Records represent a coherent grouping of data. Records consist of a collection of blocks (see next paragraph). The user can define a variety of records (headers, events, error logs, etc.) and request that any of them be written to any stream. When SIO reads a file, it first decodes the record name and if that record has been defined and unpacking has been requested for it, SIO proceeds to unpack the blocks. Blocks are user provided objects which do the real work of reading/writing the data. The user is responsible for writing the code for these blocks and for identifying these blocks to SIO at run time. To write a collection of blocks, the user must first connect them to a record. The record can then be written to a stream as described above. Note that the same block can be connected to many different records. When SIO reads a record, it scans through the blocks written and calls the corresponding block object (if it has been defined) to decode it. Undefined blocks are skipped. Each of these categories (streams, records and blocks) have some characteristics in common. Every stream, record and block has a name with the condition that each stream, record or block name must be unique in its category (i.e. all streams must have different names, but a stream can have the same name as a record). Each category is an arbitrary length list which is handled by a 'manager' and there is one manager for each category.

  5. Residential mobility and location choice: a nested logit model with sampling of alternatives

    E-Print Network [OSTI]

    Lee, Brian H.; Waddell, Paul

    2010-01-01T23:59:59.000Z

    empirical results from the Puget Sound region. Environ.residences from the central Puget Sound region. It usesapplication in the Central Puget Sound region The NL model

  6. OLAF _ A General Modeling System to Evaluate and Optimize the Location of an Air

    E-Print Network [OSTI]

    Fliege, Jörg

    ........................17 3.1.1The Standard Model ....................17 3.1.2Metabolism.1.2The Objective Function ..................40 5.1.3The Gradient of the Objective Function

  7. UFO - The Universal FeynRules Output

    E-Print Network [OSTI]

    Céline Degrande; Claude Duhr; Benjamin Fuks; David Grellscheid; Olivier Mattelaer; Thomas Reiter

    2012-07-31T23:59:59.000Z

    We present a new model format for automatized matrix-element generators, the so- called Universal FeynRules Output (UFO). The format is universal in the sense that it features compatibility with more than one single generator and is designed to be flexible, modular and agnostic of any assumption such as the number of particles or the color and Lorentz structures appearing in the interaction vertices. Unlike other model formats where text files need to be parsed, the information on the model is encoded into a Python module that can easily be linked to other computer codes. We then describe an interface for the Mathematica package FeynRules that allows for an automatic output of models in the UFO format.

  8. UFO - The Universal FeynRules Output

    E-Print Network [OSTI]

    Degrande, Céline; Fuks, Benjamin; Grellscheid, David; Mattelaer, Olivier; Reiter, Thomas

    2011-01-01T23:59:59.000Z

    We present a new model format for automatized matrix-element generators, the so- called Universal FeynRules Output (UFO). The format is universal in the sense that it features compatibility with more than one single generator and is designed to be flexible, modular and agnostic of any assumption such as the number of particles or the color and Lorentz structures appearing in the interaction vertices. Unlike other model formats where text files need to be parsed, the information on the model is encoded into a Python module that can easily be linked to other computer codes. We then describe an interface for the Mathematica package FeynRules that allows for an automatic output of models in the UFO format.

  9. Environmental Modelling & Software 15 (2000) 161167 www.elsevier.com/locate/envsoft

    E-Print Network [OSTI]

    Kuncheva, Ludmila I.

    2000-01-01T23:59:59.000Z

    of heavy metal loadings in Liverpool bay L.I. Kuncheva a,* , J. Wrench b , L.C. Jain c , A.S. Al of the loadings of 10 heavy metals in Liverpool bay. Each metal concentration is associated with a fuzzy set modelling; Liverpool bay; Heavy metal concentration; Index of spatial distribution 1. Introduction

  10. Verification of hourly forecasts of wind turbine power output

    SciTech Connect (OSTI)

    Wegley, H.L.

    1984-08-01T23:59:59.000Z

    A verification of hourly average wind speed forecasts in terms of hourly average power output of a MOD-2 was performed for four sites. Site-specific probabilistic transformation models were developed to transform the forecast and observed hourly average speeds to the percent probability of exceedance of an hourly average power output. (This transformation model also appears to have value in predicting annual energy production for use in wind energy feasibility studies.) The transformed forecasts were verified in a deterministic sense (i.e., as continuous values) and in a probabilistic sense (based upon the probability of power output falling in a specified category). Since the smoothing effects of time averaging are very pronounced, the 90% probability of exceedance was built into the transformation models. Semiobjective and objective (model output statistics) forecasts were made compared for the four sites. The verification results indicate that the correct category can be forecast an average of 75% of the time over a 24-hour period. Accuracy generally decreases with projection time out to approx. 18 hours and then may increase due to the fairly regular diurnal wind patterns that occur at many sites. The ability to forecast the correct power output category increases with increasing power output because occurrences of high hourly average power output (near rated) are relatively rare and are generally not forecast. The semiobjective forecasts proved superior to model output statistics in forecasting high values of power output and in the shorter time frames (1 to 6 hours). However, model output statistics were slightly more accurate at other power output levels and times. Noticeable differences were observed between deterministic and probabilistic (categorical) forecast verification results.

  11. Where is the ideal location for a US East Coast offshore grid? Michael J. Dvorak,1

    E-Print Network [OSTI]

    weather model data from 2006­2010 were used to approximate wind farm output. The offshore grid was located%, and the combined capacity factor was 48% (gross). By interconnecting offshore wind energy farms 450 km apart of no and full-power events. Offshore grids to connect offshore wind energy (OWE) farms have been proposed

  12. Output regulation problem for differentiable families of linear systems

    E-Print Network [OSTI]

    Politècnica de Catalunya, Universitat

    The output regulation problem arose as one of the main research topics in linear control theory in the 1970s regulation when modeled by a global or a local differentiable family. Partially supported by DGICYT n.PB97Output regulation problem for differentiable families of linear systems Albert Compta and Marta Pe

  13. Multi-horizon solar radiation forecasting for Mediterranean locations using time series models

    E-Print Network [OSTI]

    Voyant, Cyril; Muselli, Marc; Nivet, Marie Laure

    2013-01-01T23:59:59.000Z

    Considering the grid manager's point of view, needs in terms of prediction of intermittent energy like the photovoltaic resource can be distinguished according to the considered horizon: following days (d+1, d+2 and d+3), next day by hourly step (h+24), next hour (h+1) and next few minutes (m+5 e.g.). Through this work, we have identified methodologies using time series models for the prediction horizon of global radiation and photovoltaic power. What we present here is a comparison of different predictors developed and tested to propose a hierarchy. For horizons d+1 and h+1, without advanced ad hoc time series pre-processing (stationarity) we find it is not easy to differentiate between autoregressive moving average (ARMA) and multilayer perceptron (MLP). However we observed that using exogenous variables improves significantly the results for MLP . We have shown that the MLP were more adapted for horizons h+24 and m+5. In summary, our results are complementary and improve the existing prediction techniques ...

  14. Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output Perturbation

    E-Print Network [OSTI]

    Washington at Seattle, University of

    Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output. This is typically not feasible for mesoscale weather prediction carried out locally by organizations without by simulating realizations of the geostatistical model. The method is applied to 48-hour mesoscale forecasts

  15. Modeling, Performance Analysis and Comparison of Two Level Single Chain Pointer Forwarding Strategy For Location Management in Wireless Mobile Communication

    E-Print Network [OSTI]

    Kant, C R; Prakash, N; Kant, Chhaya Ravi; Prakash, Nupur

    2006-01-01T23:59:59.000Z

    Global wireless networks enable mobile users to communicate regardless of their locations. Location management is an important part of the emerging wireless and mobile technology. A Personal Communication System (PCS) network must have an efficient way to keep track of the mobile users to deliver services effectively. Global System for Mobile Communication (GSM) is a commonly accepted standard for mobility management of mobile users. Location management involves location tracking, and location information storage. Location management requires mobile users to register at various registration areas whenever they are on the move. The registration process may cause excessive signaling traffic and long service delays. To improve the efficiency of location tracking and avoid call set up delays, several strategies such as local anchor scheme, per-user caching scheme and several pointer forwarding schemes have been proposed in the past. In this paper, we propose a new "Two Level Single Chain Pointer Forwarding (TLSCP...

  16. Using Mesoscale Weather Model Output as Boundary Conditions for Atmospheric Large-Eddy Simulations and Wind-Plant Aerodynamic Simulations (Presentation)

    SciTech Connect (OSTI)

    Churchfield, M. J.; Michalakes, J.; Vanderwende, B.; Lee, S.; Sprague, M. A.; Lundquist, J. K.; Moriarty, P. J.

    2013-10-01T23:59:59.000Z

    Wind plant aerodynamics are directly affected by the microscale weather, which is directly influenced by the mesoscale weather. Microscale weather refers to processes that occur within the atmospheric boundary layer with the largest scales being a few hundred meters to a few kilometers depending on the atmospheric stability of the boundary layer. Mesoscale weather refers to large weather patterns, such as weather fronts, with the largest scales being hundreds of kilometers wide. Sometimes microscale simulations that capture mesoscale-driven variations (changes in wind speed and direction over time or across the spatial extent of a wind plant) are important in wind plant analysis. In this paper, we present our preliminary work in coupling a mesoscale weather model with a microscale atmospheric large-eddy simulation model. The coupling is one-way beginning with the weather model and ending with a computational fluid dynamics solver using the weather model in coarse large-eddy simulation mode as an intermediary. We simulate one hour of daytime moderately convective microscale development driven by the mesoscale data, which are applied as initial and boundary conditions to the microscale domain, at a site in Iowa. We analyze the time and distance necessary for the smallest resolvable microscales to develop.

  17. Output error identification of hydrogenerator conduit dynamics

    SciTech Connect (OSTI)

    Vogt, M.A.; Wozniak, L. (Illinois Univ., Urbana, IL (USA)); Whittemore, T.R. (Bureau of Reclamation, Denver, CO (USA))

    1989-09-01T23:59:59.000Z

    Two output error model reference adaptive identifiers are considered for estimating the parameters in a reduced order gate position to pressure model for the hydrogenerator. This information may later be useful in an adaptive controller. Gradient and sensitivity functions identifiers are discussed for the hydroelectric application and connections are made between their structural differences and relative performance. Simulations are presented to support the conclusion that the latter algorithm is more robust, having better disturbance rejection and less plant model mismatch sensitivity. For identification from recorded plant data from step gate inputs, the other algorithm even fails to converge. A method for checking the estimated parameters is developed by relating the coefficients in the reduced order model to head, an externally measurable parameter.

  18. A Framework to Determine the Probability Density Function for the Output Power of Wind Farms

    E-Print Network [OSTI]

    Liberzon, Daniel

    A Framework to Determine the Probability Density Function for the Output Power of Wind Farms Sairaj to the power output of a wind farm while factoring in the availability of the wind turbines in the farm availability model for the wind turbines, we propose a method to determine the wind-farm power output pdf

  19. Overload protection circuit for output driver

    DOE Patents [OSTI]

    Stewart, Roger G. (Neshanic Station, NJ)

    1982-05-11T23:59:59.000Z

    A protection circuit for preventing excessive power dissipation in an output transistor whose conduction path is connected between a power terminal and an output terminal. The protection circuit includes means for sensing the application of a turn on signal to the output transistor and the voltage at the output terminal. When the turn on signal is maintained for a period of time greater than a given period without the voltage at the output terminal reaching a predetermined value, the protection circuit decreases the turn on signal to, and the current conduction through, the output transistor.

  20. Simulation of one-minute power output from utility-scale photovoltaic generation systems.

    SciTech Connect (OSTI)

    Stein, Joshua S.; Ellis, Abraham; Hansen, Clifford W.

    2011-08-01T23:59:59.000Z

    We present an approach to simulate time-synchronized, one-minute power output from large photovoltaic (PV) generation plants in locations where only hourly irradiance estimates are available from satellite sources. The approach uses one-minute irradiance measurements from ground sensors in a climatically and geographically similar area. Irradiance is translated to power using the Sandia Array Performance Model. Power output is generated for 2007 in southern Nevada are being used for a Solar PV Grid Integration Study to estimate the integration costs associated with various utility-scale PV generation levels. Plant designs considered include both fixed-tilt thin-film, and single-axis-tracked polycrystalline Si systems ranging in size from 5 to 300 MW{sub AC}. Simulated power output profiles at one-minute intervals were generated for five scenarios defined by total PV capacity (149.5 MW, 222 WM, 292 MW, 492 MW, and 892 MW) each comprising as many as 10 geographically separated PV plants.

  1. Nonlinear quantum input-output analysis using Volterra series

    E-Print Network [OSTI]

    Jing Zhang; Yu-xi Liu; Re-Bing Wu; Kurt Jacobs; Sahin Kaya Ozdemir; Lan Yang; Tzyh-Jong Tarn; Franco Nori

    2014-08-04T23:59:59.000Z

    Quantum input-output theory plays a very important role for analyzing the dynamics of quantum systems, especially large-scale quantum networks. As an extension of the input-output formalism of Gardiner and Collet, we develop a new approach based on the quantum version of the Volterra series which can be used to analyze nonlinear quantum input-output dynamics. By this approach, we can ignore the internal dynamics of the quantum input-output system and represent the system dynamics by a series of kernel functions. This approach has the great advantage of modelling weak-nonlinear quantum networks. In our approach, the number of parameters, represented by the kernel functions, used to describe the input-output response of a weak-nonlinear quantum network, increases linearly with the scale of the quantum network, not exponentially as usual. Additionally, our approach can be used to formulate the quantum network with both nonlinear and nonconservative components, e.g., quantum amplifiers, which cannot be modelled by the existing methods, such as the Hudson-Parthasarathy model and the quantum transfer function model. We apply our general method to several examples, including Kerr cavities, optomechanical transducers, and a particular coherent feedback system with a nonlinear component and a quantum amplifier in the feedback loop. This approach provides a powerful way to the modelling and control of nonlinear quantum networks.

  2. DUAL-OUTPUT HOLA FIRMWARE AND TESTS

    E-Print Network [OSTI]

    another channel (thus, "dual-output" HOLA) · Another LDC+ROMB block was added to receive data from side S32PCI64 "SOLAR" mezzanine card: Provides access to S-LINK via PCI bus The first prototype of dual-outputDUAL-OUTPUT HOLA FIRMWARE AND TESTS Anton Kapliy Mel Shochet Fukun Tang Daping Weng #12;Summary

  3. 922 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 16, NO. 6, AUGUST 1998 Mobility Modeling, Location Tracking, and

    E-Print Network [OSTI]

    Hunt, Galen

    mobility management to cope with frequent mobile handoff and rerouting of connections. Although much of the key problems within this set is mobility management. Mobility management as defined in [1] entails both connection management and location management. Since ATM is a connection-oriented technology

  4. System and method for cancelling the effects of stray magnetic fields from the output of a variable reluctance sensor

    DOE Patents [OSTI]

    Chen, Chingchi (Ann Arbor, MI); Degner, Michael W. (Farmington Hills, MI)

    2002-11-19T23:59:59.000Z

    A sensor system for sensing a rotation of a sensing wheel is disclosed. The sensor system has a sensing coil in juxtaposition with the sensing wheel. Moreover, the sensing coil has a sensing coil output signal indicative of the rotational speed of the sensing wheel. Further, a cancellation coil is located remotely from the sensing coil and connected in series therewith. Additionally, the cancellation coil has a cancellation coil output signal indicative of an environmental disturbance which is effecting the sensing coil output signal. The cancellation coil output signal operates to cancel the effects of the environmental disturbance on the sensing coil output signal.

  5. Control of fuel cell power output Federico Zenith, Sigurd Skogestad *

    E-Print Network [OSTI]

    Skogestad, Sigurd

    Control of fuel cell power output Federico Zenith, Sigurd Skogestad * Department of Chemical A simplified dynamic model for fuel cells is developed, based on the concept of instantaneous characteristic, which is the set of values of current and voltage that a fuel cell can reach instantaneously

  6. OUTPUT REGULATION OF NONLINEAR NEUTRAL SYSTEMS

    E-Print Network [OSTI]

    Fridman, Emilia

    OUTPUT REGULATION OF NONLINEAR NEUTRAL SYSTEMS Emilia Fridman1 Department of Electrical Engineering, Tel-Aviv University Ramat-Aviv, Tel-Aviv 69978, Israel emilia@eng.tau.ac.il Summary. Output regulation regulation, regulator equations, center manifold 1 Introduction One of the most important problems in control

  7. Bayesian Learning of unobservable output 1 Bayesian Learning of unobservable output

    E-Print Network [OSTI]

    Provence Aix-Marseille I, Université de

    Bayesian Learning of unobservable output 1 Bayesian Learning of unobservable output aggregating the consistency of our method and illustrate its efficiency using simulations. Although up to our knowledge there are no similar algorithms for unobservable output, we compared in our simulations to supervised approaches

  8. X-ray source assembly having enhanced output stability, and fluid stream analysis applications thereof

    DOE Patents [OSTI]

    Radley, Ian (Glenmont, NY); Bievenue, Thomas J. (Delmar, NY); Burdett, John H. (Charlton, NY); Gallagher, Brian W. (Guilderland, NY); Shakshober, Stuart M. (Hudson, NY); Chen, Zewu (Schenectady, NY); Moore, Michael D. (Alplaus, NY)

    2008-06-08T23:59:59.000Z

    An x-ray source assembly and method of operation are provided having enhanced output stability. The assembly includes an anode having a source spot upon which electrons impinge and a control system for controlling position of the anode source spot relative to an output structure. The control system can maintain the anode source spot location relative to the output structure notwithstanding a change in one or more operating conditions of the x-ray source assembly. One aspect of the disclosed invention is most amenable to the analysis of sulfur in petroleum-based fuels.

  9. X-ray source assembly having enhanced output stability, and fluid stream analysis applications thereof

    DOE Patents [OSTI]

    Radley, Ian; Bievenue, Thomas J.; Burdett Jr., John H.; Gallagher, Brian W.; Shakshober, Stuart M.; Chen, Zewu; Moore, Michael D.

    2007-04-24T23:59:59.000Z

    An x-ray source assembly (2700) and method of operation are provided having enhanced output stability. The assembly includes an anode (2125) having a source spot upon which electrons (2120) impinge and a control system (2715/2720) for controlling position of the anode source spot relative to an output structure. The control system can maintain the anode source spot location relative to the output structure (2710) notwithstanding a change in one or more operating conditions of the x-ray source assembly. One aspect of the disclosed invention is most amenable to the analysis of sulfur in petroleum-based fuels.

  10. Deep groundwater flow as the main pathway for chemical outputs in a small headwater watershed (Mule Hole, South India)

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Deep groundwater flow as the main pathway for chemical outputs in a small headwater watershed (Mule of a groundwater baseflow located into the active zone of the crystalline aquifer, below the weir. These findings indicate that groundwater contributes to a large part of chemical outputs at the catchment scale

  11. Input-output multiplier distributions from probabilistic production paths

    SciTech Connect (OSTI)

    Konecny, R.T.

    1987-01-01T23:59:59.000Z

    In the standard Leontief input-output model, a single dominant technology is assumed in the production of a particular commodity. However, in the real world, quite similar commodities are produced by firms with vastly different technologies. In addressing this limitation, the Probabilistic Production Path model (PPP) is used to investigate both the method of production and identity of the producer. An important feature of the PPP model is the consideration of the effects that heterogeneous technologies and dissimilar trade patterns have on the properties of the distribution of input-output multipliers. The derivation of the distribution of output multipliers is generalized for discrete probabilities based on market shares. Due to the complexity of the generalized solution, a simulation model is used to approximate the multiplier distribution. Results of the model show that the distributional properties of the multipliers are unpredictable, with the majority of the distributions being multimodal. Typically, the mean of the multipliers lies in a trough between two modes. Multimodal multiplier distributions were found to have a tighter symmetric interval than the corresponding standard normal confidence interval. Therefore, the use of the normal confidence interval appears to be sufficient, though overstated, for the construction of confidence intervals in the PPP model.

  12. POLE PLACEMENT BY STATIC OUTPUT FEEDBACK FOR ...

    E-Print Network [OSTI]

    SIAM (#1) 1035 2001 Apr 10 12:32:38

    2002-06-04T23:59:59.000Z

    topology) subset U of such systems, where the real pole placement map is not surjective. It follows that, for ... Key words. linear systems, static output control feedback, pole placement. AMS subject .... is an integral power of 2. In the opposite ...

  13. Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs

    E-Print Network [OSTI]

    Venditti, David A.

    Anisotropic grid–adaptive strategies are presented for viscous flow simulations in which the accurate prediction of multiple aerodynamic outputs (such as the lift, drag, and moment coefficients) is required from a single ...

  14. Optimization on Solar Panels: Finding the Optimal Output Brian Y. Lu

    E-Print Network [OSTI]

    Lavaei, Javad

    Optimization on Solar Panels: Finding the Optimal Output Brian Y. Lu January 1, 2013 1 Introduction of solar panel: Routing the configuration between solar cells with a switch matrix. However, their result models and control policies for the optimal output of solar panels. The smallest unit on a solar panel

  15. Quality assurance of solar thermal systems with the ISFH-Input/Output-Procedure

    E-Print Network [OSTI]

    Quality assurance of solar thermal systems with the ISFH- Input/Output-Procedure Peter Paerisch different solar systems. The simulation model was validated with measured data. The deviation between meas * Tel. +49 (0)5151-999503, Fax: +49 (0)5151-999500, Email: paerisch@isfh.de Abstract Input/Output

  16. Efficient Algorithm for Locating and Sizing Series Compensation Devices in Large Transmission Grids: Model Implementation (PART 1)

    SciTech Connect (OSTI)

    Frolov, Vladimir [Moscow Inst. of Physics and Technology (MIPT), Moscow (Russian Federation); Backhaus, Scott N. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Chertkov, Michael [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2014-01-14T23:59:59.000Z

    We explore optimization methods for planning the placement, sizing and operations of Flexible Alternating Current Transmission System (FACTS) devices installed to relieve transmission grid congestion. We limit our selection of FACTS devices to Series Compensation (SC) devices that can be represented by modification of the inductance of transmission lines. Our master optimization problem minimizes the l1 norm of the inductance modification subject to the usual line thermal-limit constraints. We develop heuristics that reduce this non-convex optimization to a succession of Linear Programs (LP) which are accelerated further using cutting plane methods. The algorithm solves an instance of the MatPower Polish Grid model (3299 lines and 2746 nodes) in 40 seconds per iteration on a standard laptop—a speed up that allows the sizing and placement of a family of SC devices to correct a large set of anticipated congestions. We observe that our algorithm finds feasible solutions that are always sparse, i.e., SC devices are placed on only a few lines. In a companion manuscript, we demonstrate our approach on realistically-sized networks that suffer congestion from a range of causes including generator retirement. In this manuscript, we focus on the development of our approach, investigate its structure on a small test system subject to congestion from uniform load growth, and demonstrate computational efficiency on a realistically-sized network.

  17. Library Locations Locations other than Main Library

    E-Print Network [OSTI]

    Library Locations Locations other than Main Library Example: Feminist Studies HQ1410 .U54 2009 University of California, Santa Barbara Library www.library.ucsb.edu Updated 3-2014 A - B.......................................6 Central M - N..................................................Arts Library (Music Building) P

  18. Automated detection and location of indications in eddy current signals

    DOE Patents [OSTI]

    Brudnoy, David M. (Albany, NY); Oppenlander, Jane E. (Burnt Hills, NY); Levy, Arthur J. (Schenectady, NY)

    2000-01-01T23:59:59.000Z

    A computer implemented information extraction process that locates and identifies eddy current signal features in digital point-ordered signals, signals representing data from inspection of test materials, by enhancing the signal features relative to signal noise, detecting features of the signals, verifying the location of the signal features that can be known in advance, and outputting information about the identity and location of all detected signal features.

  19. Predicting the Energy Output of Wind Farms Based on Weather Data: Important Variables and their Correlation

    E-Print Network [OSTI]

    Vladislavleva, Katya; Neumann, Frank; Wagner, Markus

    2011-01-01T23:59:59.000Z

    Wind energy plays an increasing role in the supply of energy world-wide. The energy output of a wind farm is highly dependent on the weather condition present at the wind farm. If the output can be predicted more accurately, energy suppliers can coordinate the collaborative production of different energy sources more efficiently to avoid costly overproductions. With this paper, we take a computer science perspective on energy prediction based on weather data and analyze the important parameters as well as their correlation on the energy output. To deal with the interaction of the different parameters we use symbolic regression based on the genetic programming tool DataModeler. Our studies are carried out on publicly available weather and energy data for a wind farm in Australia. We reveal the correlation of the different variables for the energy output. The model obtained for energy prediction gives a very reliable prediction of the energy output for newly given weather data.

  20. PV output smoothing with energy storage.

    SciTech Connect (OSTI)

    Ellis, Abraham; Schoenwald, David Alan

    2012-03-01T23:59:59.000Z

    This report describes an algorithm, implemented in Matlab/Simulink, designed to reduce the variability of photovoltaic (PV) power output by using a battery. The purpose of the battery is to add power to the PV output (or subtract) to smooth out the high frequency components of the PV power that that occur during periods with transient cloud shadows on the PV array. The control system is challenged with the task of reducing short-term PV output variability while avoiding overworking the battery both in terms of capacity and ramp capability. The algorithm proposed by Sandia is purposely very simple to facilitate implementation in a real-time controller. The control structure has two additional inputs to which the battery can respond. For example, the battery could respond to PV variability, load variability or area control error (ACE) or a combination of the three.

  1. Single Inductor Dual Output Buck Converter

    E-Print Network [OSTI]

    Eachempatti, Haritha

    2010-07-14T23:59:59.000Z

    of value 3V. The main focus areas are low cross regulation between the outputs and supply of completely independent load current levels while maintaining desired values (1.2V,1.5V) within well controlled ripple levels. Dynamic hysteresis control is used...

  2. Porous radiant burners having increased radiant output

    DOE Patents [OSTI]

    Tong, Timothy W. (Tempe, AZ); Sathe, Sanjeev B. (Tempe, AZ); Peck, Robert E. (Tempe, AZ)

    1990-01-01T23:59:59.000Z

    Means and methods for enhancing the output of radiant energy from a porous radiant burner by minimizing the scattering and increasing the adsorption, and thus emission of such energy by the use of randomly dispersed ceramic fibers of sub-micron diameter in the fabrication of ceramic fiber matrix burners and for use therein.

  3. Bioenergy technology balancing energy output with environmental

    E-Print Network [OSTI]

    Levi, Ran

    E2.3 Bioenergy technology ­ balancing energy output with environmental benefitsbenefits John bioenergy Farmers historically used 25% land for horse feed #12;Energy crops are `solar panels' Solar energy° 50° #12;Same climate data (A1F1 scenario for 2050 - 2080) but the genotype is one which is less

  4. Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs

    E-Print Network [OSTI]

    Peraire, Jaime

    Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs David A. Venditti and David L Anisotropic grid­adaptive strategies are presented for viscous flow simulations in which the accurate estimation and Hessian-based anisotropic grid adaptation. Airfoil test cases are presented to demonstrate

  5. Investigation of the effects of cell model and subcellular location of gold nanoparticles on nuclear dose enhancement factors using Monte Carlo simulation

    SciTech Connect (OSTI)

    Cai, Zhongli; Chattopadhyay, Niladri; Kwon, Yongkyu Luke [Department of Pharmaceutical Sciences, University of Toronto, Toronto, Ontario M5S 3M2 (Canada)] [Department of Pharmaceutical Sciences, University of Toronto, Toronto, Ontario M5S 3M2 (Canada); Pignol, Jean-Philippe [Department of Radiation Oncology, University of Toronto, Toronto, Ontario M4N 3M5, Canada and Department of Medical Biophysics, University of Toronto, Toronto, Ontario M4N 3M5 (Canada)] [Department of Radiation Oncology, University of Toronto, Toronto, Ontario M4N 3M5, Canada and Department of Medical Biophysics, University of Toronto, Toronto, Ontario M4N 3M5 (Canada); Lechtman, Eli [Department of Medical Biophysics, University of Toronto, Toronto, Ontario M4N 3M5 (Canada)] [Department of Medical Biophysics, University of Toronto, Toronto, Ontario M4N 3M5 (Canada); Reilly, Raymond M. [Department of Pharmaceutical Sciences, University of Toronto, Toronto, Ontario M5S 3M2 (Canada) [Department of Pharmaceutical Sciences, University of Toronto, Toronto, Ontario M5S 3M2 (Canada); Department of Medical Imaging, University of Toronto, Toronto, Ontario M5S 3E2 (Canada); Toronto General Research Institute, University Health Network, Toronto, Ontario M5G 2C4 (Canada)

    2013-11-15T23:59:59.000Z

    Purpose: The authors’ aims were to model how various factors influence radiation dose enhancement by gold nanoparticles (AuNPs) and to propose a new modeling approach to the dose enhancement factor (DEF).Methods: The authors used Monte Carlo N-particle (MCNP 5) computer code to simulate photon and electron transport in cells. The authors modeled human breast cancer cells as a single cell, a monolayer, or a cluster of cells. Different numbers of 5, 30, or 50 nm AuNPs were placed in the extracellular space, on the cell surface, in the cytoplasm, or in the nucleus. Photon sources examined in the simulation included nine monoenergetic x-rays (10–100 keV), an x-ray beam (100 kVp), and {sup 125}I and {sup 103}Pd brachytherapy seeds. Both nuclear and cellular dose enhancement factors (NDEFs, CDEFs) were calculated. The ability of these metrics to predict the experimental DEF based on the clonogenic survival of MDA-MB-361 human breast cancer cells exposed to AuNPs and x-rays were compared.Results: NDEFs show a strong dependence on photon energies with peaks at 15, 30/40, and 90 keV. Cell model and subcellular location of AuNPs influence the peak position and value of NDEF. NDEFs decrease in the order of AuNPs in the nucleus, cytoplasm, cell membrane, and extracellular space. NDEFs also decrease in the order of AuNPs in a cell cluster, monolayer, and single cell if the photon energy is larger than 20 keV. NDEFs depend linearly on the number of AuNPs per cell. Similar trends were observed for CDEFs. NDEFs using the monolayer cell model were more predictive than either single cell or cluster cell models of the DEFs experimentally derived from the clonogenic survival of cells cultured as a monolayer. The amount of AuNPs required to double the prescribed dose in terms of mg Au/g tissue decreases as the size of AuNPs increases, especially when AuNPs are in the nucleus and the cytoplasm. For 40 keV x-rays and a cluster of cells, to double the prescribed x-ray dose (NDEF = 2) using 30 nm AuNPs, would require 5.1 ± 0.2, 9 ± 1, 10 ± 1, 10 ± 1 mg Au/g tissue in the nucleus, in the cytoplasm, on the cell surface, or in the extracellular space, respectively. Using 50 nm AuNPs, the required amount decreases to 3.1 ± 0.3, 8 ± 1, 9 ± 1, 9 ± 1 mg Au/g tissue, respectively.Conclusions: NDEF is a new metric that can predict the radiation enhancement of AuNPs for various experimental conditions. Cell model, the subcellular location and size of AuNPs, and the number of AuNPs per cell, as well as the x-ray photon energy all have effects on NDEFs. Larger AuNPs in the nucleus of cluster cells exposed to x-rays of 15 or 40 keV maximize NDEFs.

  6. Short range radio locator system

    DOE Patents [OSTI]

    McEwan, Thomas E. (Livermore, CA)

    1996-01-01T23:59:59.000Z

    A radio location system comprises a wireless transmitter that outputs two megahertz period bursts of two gigahertz radar carrier signals. A receiver system determines the position of the transmitter by the relative arrival of the radar bursts at several component receivers set up to have a favorable geometry and each one having a known location. One receiver provides a synchronizing gating pulse to itself and all the other receivers to sample the ether for the radar pulse. The rate of the synchronizing gating pulse is slightly offset from the rate of the radar bursts themselves, so that each sample collects one finely-detailed piece of information about the time-of-flight of the radar pulse to each receiver each pulse period. Thousands of sequential pulse periods provide corresponding thousand of pieces of information about the time-of-flight of the radar pulse to each receiver, in expanded, not real time. Therefore the signal processing can be done with relatively low-frequency, inexpensive components. A conventional microcomputer is then used to find the position of the transmitter by geometric triangulation based on the relative time-of-flight information.

  7. Boosting America's Hydropower Output | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny: The FutureCommentsEnergyandapproximatelyBoosting America's Hydropower Output

  8. Characterizing detonator output using dynamic witness plates

    SciTech Connect (OSTI)

    Murphy, Michael John [Los Alamos National Laboratory; Adrian, Ronald J [Los Alamos National Laboratory

    2009-01-01T23:59:59.000Z

    A sub-microsecond, time-resolved micro-particle-image velocimetry (PIV) system is developed to investigate the output of explosive detonators. Detonator output is directed into a transparent solid that serves as a dynamic witness plate and instantaneous shock and material velocities are measured in a two-dimensional plane cutting through the shock wave as it propagates through the solid. For the case of unloaded initiators (e.g. exploding bridge wires, exploding foil initiators, etc.) the witness plate serves as a surrogate for the explosive material that would normally be detonated. The velocity-field measurements quantify the velocity of the shocked material and visualize the geometry of the shocked region. Furthermore, the time-evolution of the velocity-field can be measured at intervals as small as 10 ns using the PIV system. Current experimental results of unloaded exploding bridge wire output in polydimethylsiloxane (PDMS) witness plates demonstrate 20 MHz velocity-field sampling just 300 ns after initiation of the wire.

  9. Reversible micromachining locator

    DOE Patents [OSTI]

    Salzer, L.J.; Foreman, L.R.

    1999-08-31T23:59:59.000Z

    This invention provides a device which includes a locator, a kinematic mount positioned on a conventional tooling machine, a part carrier disposed on the locator and a retainer ring. The locator has disposed therein a plurality of steel balls, placed in an equidistant position circumferentially around the locator. The kinematic mount includes a plurality of magnets which are in registry with the steel balls on the locator. In operation, a blank part to be machined is placed between a surface of a locator and the retainer ring (fitting within the part carrier). When the locator (with a blank part to be machined) is coupled to the kinematic mount, the part is thus exposed for the desired machining process. Because the locator is removably attachable to the kinematic mount, it can easily be removed from the mount, reversed, and reinserted onto the mount for additional machining. Further, the locator can likewise be removed from the mount and placed onto another tooling machine having a properly aligned kinematic mount. Because of the unique design and use of magnetic forces of the present invention, positioning errors of less than 0.25 micrometer for each machining process can be achieved. 7 figs.

  10. Reversible micromachining locator

    DOE Patents [OSTI]

    Salzer, Leander J. (Los Alamos, NM); Foreman, Larry R. (Los Alamos, NM)

    1999-01-01T23:59:59.000Z

    This invention provides a device which includes a locator, a kinematic mount positioned on a conventional tooling machine, a part carrier disposed on the locator and a retainer ring. The locator has disposed therein a plurality of steel balls, placed in an equidistant position circumferentially around the locator. The kinematic mount includes a plurality of magnets which are in registry with the steel balls on the locator. In operation, a blank part to be machined is placed between a surface of a locator and the retainer ring (fitting within the part carrier). When the locator (with a blank part to be machined) is coupled to the kinematic mount, the part is thus exposed for the desired machining process. Because the locator is removably attachable to the kinematic mount, it can easily be removed from the mount, reversed, and reinserted onto the mount for additional machining. Further, the locator can likewise be removed from the mount and placed onto another tooling machine having a properly aligned kinematic mount. Because of the unique design and use of magnetic forces of the present invention, positioning errors of less than 0.25 micrometer for each machining process can be achieved.

  11. Reversible micromachining locator

    DOE Patents [OSTI]

    Salzer, Leander J. (Los Almos, NM); Foreman, Larry R. (late of Los Alamos, NM)

    2002-01-01T23:59:59.000Z

    A locator with a part support is used to hold a part onto the kinematic mount of a tooling machine so that the part can be held in or replaced in exactly the same position relative to the cutting tool for machining different surfaces of the part or for performing different machining operations on the same or different surfaces of the part. The locator has disposed therein a plurality of steel balls placed at equidistant positions around the planar surface of the locator and the kinematic mount has a plurality of magnets which alternate with grooves which accommodate the portions of the steel balls projecting from the locator. The part support holds the part to be machined securely in place in the locator. The locator can be easily detached from the kinematic mount, turned over, and replaced onto the same kinematic mount or another kinematic mount on another tooling machine without removing the part to be machined from the locator so that there is no need to touch or reposition the part within the locator, thereby assuring exact replication of the position of the part in relation to the cutting tool on the tooling machine for each machining operation on the part.

  12. World crude output overcomes Persian Gulf disruption

    SciTech Connect (OSTI)

    Not Available

    1992-02-01T23:59:59.000Z

    Several OPEC producers made good on their promises to replace 2.7 MMbpd of oil exports that vanished from the world market after Iraq took over Kuwait. Even more incredibly, they accomplished this while a breathtaking 1.2- MMbopd reduction in Soviet output took place during the course of 1991. After Abu Dhabi, Indonesia, Iran, Libya, Nigeria, Saudi Arabia and Venezuela turned the taps wide open, their combined output rose 2.95 MMbopd. Put together with a 282,000-bopd increase by Norway and contributions from smaller producers, this enabled world oil production to remain within 400,000 bopd of its 1990 level. The 60.5-MMbopd average was off by just 0.7%. This paper reports that improvement took place in five of eight regions. Largest increases were in Western Europe and Africa. Greatest reductions occurred in Eastern Europe and the Middle East. Fifteen nations produced 1 MMbopd or more last year, compared with 17 during 1990.

  13. SARAH 3.2: Dirac Gauginos, UFO output, and more

    E-Print Network [OSTI]

    Florian Staub

    2013-02-12T23:59:59.000Z

    SARAH is a Mathematica package optimized for the fast, efficient and precise study of supersymmetric models beyond the MSSM: a new model can be defined in a short form and all vertices are derived. This allows SARAH to create model files for FeynArts/FormCalc, CalcHep/CompHep and WHIZARD/OMEGA. The newest version of SARAH now provides the possibility to create model files in the UFO format which is supported by MadGraph 5, MadAnalysis, GoSam, and soon by Herwig++. Furthermore, SARAH also calculates the mass matrices, RGEs and one-loop corrections to the mass spectrum. This information is used to write source code for SPheno in order to create a precision spectrum generator for the given model. This spectrum-generator-generator functionality as well as the output of WHIZARD and CalcHep model files have seen further improvement in this version. Also models including Dirac Gauginos are supported with the new version of SARAH, and additional checks for the consistency of model implementations have been created.

  14. Quality assurance with the ISFH-Input/Output-Procedure 6-year-experience with 14 solar thermal systems

    E-Print Network [OSTI]

    Quality assurance with the ISFH-Input/Output-Procedure 6-year-experience with 14 solar thermal the confidence in solar thermal energy. The so called Input/Output-Procedure is controlling the solar heat systems. The simulation model was validated with measured data and a lot of failures in 11 solar thermal

  15. Locating Heat Recovery Opportunities 

    E-Print Network [OSTI]

    Waterland, A. F.

    1981-01-01T23:59:59.000Z

    Basic concepts of heat recovery are defined as they apply to the industrial community. Methods for locating, ranking, and developing heat recovery opportunities are presented and explained. The needs for useful heat 'sinks' are emphasized as equal...

  16. Locating Heat Recovery Opportunities

    E-Print Network [OSTI]

    Waterland, A. F.

    1981-01-01T23:59:59.000Z

    Basic concepts of heat recovery are defined as they apply to the industrial community. Methods for locating, ranking, and developing heat recovery opportunities are presented and explained. The needs for useful heat 'sinks' are emphasized as equal...

  17. Soft-Input Soft-Output Sphere Decoding Christoph Studer

    E-Print Network [OSTI]

    Soft-Input Soft-Output Sphere Decoding Christoph Studer Integrated Systems Laboratory ETH Zurich Soft-input soft-output (SISO) detection in multiple-input multiple-output (MIMO) systems constitutes Laboratory ETH Zurich, 8092 Zurich, Switzerland Email: boelcskei@nari.ee.ethz.ch Abstract--Soft-input soft

  18. Automated Fault Location In Smart Distribution Systems 

    E-Print Network [OSTI]

    Lotfifard, Saeed

    2012-10-19T23:59:59.000Z

    ............................................................................................................................ 88 x LIST OF FIGURES Page Figure 1 Multiple possible fault location estimation for a fault at node A ........................ 7 Figure 2 Simple faulted network model [1] © [2011] IEEE ............................................ 40 Figure 3... Types C and D voltage sags for different phases [51] © [2003] IEEE .............. 42 Figure 4 Rf estimation procedure [1] © [2011] IEEE ...................................................... 45 Figure 5 Flow chart of the fault location algorithm [1...

  19. Locating and tracking assets using RFID 

    E-Print Network [OSTI]

    Kim, Gak Gyu

    2009-05-15T23:59:59.000Z

    , this research presents a math¬ematical model of using RFID (both handheld readers and stationary readers) for e?cient asset location. We derive the expected cost of locating RFID¬tagged objects in a multi¬area environment where hand¬held RF readers are used. We...

  20. The impact of upper tropospheric friction and Gill-type heating on the location and strength of the Tropical Easterly Jet: Idealized physics in a dry Atmospheric General Circulation Model

    E-Print Network [OSTI]

    Rao, Samrat

    2015-01-01T23:59:59.000Z

    An atmospheric general circulation model (AGCM) with idealized and complete physics has been used to evaluate the Tropical Easterly Jet (TEJ) jet. In idealized physics, the role of upper tropospheric friction has been found to be important in getting realistic upper tropospheric zonal wind patterns in response to heating. In idealized physics, the location and strength of the TEJ as a response to Gill heating has been studied. Though the Gill model is considered to be widely successful in capturing the lower tropospheric response, it is found to be inadequate in explaining the location and strength of the upper level TEJ. Heating from the Gill model and realistic upper tropospheric friction does not lead to the formation of a TEJ.

  1. Uncertainty and sensitivity analysis for photovoltaic system modeling.

    SciTech Connect (OSTI)

    Hansen, Clifford W.; Pohl, Andrew Phillip; Jordan, Dirk [National Center for Photovoltaics, National Renewable Energy Laboratory, Golden, CO] [National Center for Photovoltaics, National Renewable Energy Laboratory, Golden, CO

    2013-12-01T23:59:59.000Z

    We report an uncertainty and sensitivity analysis for modeling DC energy from photovoltaic systems. We consider two systems, each comprised of a single module using either crystalline silicon or CdTe cells, and located either at Albuquerque, NM, or Golden, CO. Output from a PV system is predicted by a sequence of models. Uncertainty in the output of each model is quantified by empirical distributions of each model's residuals. We sample these distributions to propagate uncertainty through the sequence of models to obtain an empirical distribution for each PV system's output. We considered models that: (1) translate measured global horizontal, direct and global diffuse irradiance to plane-of-array irradiance; (2) estimate effective irradiance from plane-of-array irradiance; (3) predict cell temperature; and (4) estimate DC voltage, current and power. We found that the uncertainty in PV system output to be relatively small, on the order of 1% for daily energy. Four alternative models were considered for the POA irradiance modeling step; we did not find the choice of one of these models to be of great significance. However, we observed that the POA irradiance model introduced a bias of upwards of 5% of daily energy which translates directly to a systematic difference in predicted energy. Sensitivity analyses relate uncertainty in the PV system output to uncertainty arising from each model. We found that the residuals arising from the POA irradiance and the effective irradiance models to be the dominant contributors to residuals for daily energy, for either technology or location considered. This analysis indicates that efforts to reduce the uncertainty in PV system output should focus on improvements to the POA and effective irradiance models.

  2. Transportation Networks and Location A Geometric Approach

    E-Print Network [OSTI]

    Palop del Río, Belén

    Transportation Networks and Location A Geometric Approach Belén Palop1,2 1Departamento de March 2009 Florida State University #12;Belén Palop, UVa, SUNY Outline Transportation Network Model;Transportation Network Model Belén Palop, UVa, SUNY Outline Transportation Network Model Network placement

  3. Method of locating underground mines fires

    DOE Patents [OSTI]

    Laage, Linneas (Eagam, MN); Pomroy, William (St. Paul, MN)

    1992-01-01T23:59:59.000Z

    An improved method of locating an underground mine fire by comparing the pattern of measured combustion product arrival times at detector locations with a real time computer-generated array of simulated patterns. A number of electronic fire detection devices are linked thru telemetry to a control station on the surface. The mine's ventilation is modeled on a digital computer using network analysis software. The time reguired to locate a fire consists of the time required to model the mines' ventilation, generate the arrival time array, scan the array, and to match measured arrival time patterns to the simulated patterns.

  4. Method and apparatus for varying accelerator beam output energy

    DOE Patents [OSTI]

    Young, Lloyd M. (Los Alamos, NM)

    1998-01-01T23:59:59.000Z

    A coupled cavity accelerator (CCA) accelerates a charged particle beam with rf energy from a rf source. An input accelerating cavity receives the charged particle beam and an output accelerating cavity outputs the charged particle beam at an increased energy. Intermediate accelerating cavities connect the input and the output accelerating cavities to accelerate the charged particle beam. A plurality of tunable coupling cavities are arranged so that each one of the tunable coupling cavities respectively connect an adjacent pair of the input, output, and intermediate accelerating cavities to transfer the rf energy along the accelerating cavities. An output tunable coupling cavity can be detuned to variably change the phase of the rf energy reflected from the output coupling cavity so that regions of the accelerator can be selectively turned off when one of the intermediate tunable coupling cavities is also detuned.

  5. Electric current locator

    DOE Patents [OSTI]

    King, Paul E. (Corvallis, OR); Woodside, Charles Rigel (Corvallis, OR)

    2012-02-07T23:59:59.000Z

    The disclosure herein provides an apparatus for location of a quantity of current vectors in an electrical device, where the current vector has a known direction and a known relative magnitude to an input current supplied to the electrical device. Mathematical constants used in Biot-Savart superposition equations are determined for the electrical device, the orientation of the apparatus, and relative magnitude of the current vector and the input current, and the apparatus utilizes magnetic field sensors oriented to a sensing plane to provide current vector location based on the solution of the Biot-Savart superposition equations. Description of required orientations between the apparatus and the electrical device are disclosed and various methods of determining the mathematical constants are presented.

  6. Optimal fault location

    E-Print Network [OSTI]

    Knezev, Maja

    2009-05-15T23:59:59.000Z

    are triggered. Protection system consisting of protection relays and circuit breakers (CBs) will operate in order to de-energize faulted line. Different Intelligent Electronic Devices (IEDs) located in substations for the purpose of monitoring... in the control center by an operator who will mark fault event in a spreadsheet and inform other staff responsible for dealing with fault analysis and repair such as protection group or maintenance respectively. Protective relaying staff will be ready...

  7. Optimal fault location

    E-Print Network [OSTI]

    Knezev, Maja

    2008-10-10T23:59:59.000Z

    are triggered. Protection system consisting of protection relays and circuit breakers (CBs) will operate in order to de-energize faulted line. Different Intelligent Electronic Devices (IEDs) located in substations for the purpose of monitoring... in the control center by an operator who will mark fault event in a spreadsheet and inform other staff responsible for dealing with fault analysis and repair such as protection group or maintenance respectively. Protective relaying staff will be ready...

  8. Alternative Fueling Station Locator

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels Data Center Home PageStation LocationsGeneseeValleyPerformance

  9. Alternative Fueling Station Locator

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels Data Center Home PageStation LocationsGeneseeValleyPerformance

  10. average power output: Topics by E-print Network

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

    in the bucket). For low Carroll, David L. 7 High power multi-output piezoelectric transformers. Open Access Theses and Dissertations Summary: ??Piezoelectric transformers have...

  11. action potential output: Topics by E-print Network

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

    HF efficiency, but does not necessarily yield a higher measurable power (power in the bucket). For low Carroll, David L. 376 A Spatial Analysis of Multivariate Output from...

  12. advisory capability output: Topics by E-print Network

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

    HF efficiency, but does not necessarily yield a higher measurable power (power in the bucket). For low Carroll, David L. 453 A Spatial Analysis of Multivariate Output from...

  13. SWAT 2012 Input/Output Documentation

    E-Print Network [OSTI]

    Arnold, J.G.; Kiniry, J.R.; Srinivasan, R.; Williams, J.R.; Haney, E.B.; Neitsch, S.L.

    2013-03-04T23:59:59.000Z

    The Soil and Water Assessment Tool (SWAT) is a comprehensive model that requires a diversity of information in order to run. Novice users may feel overwhelmed by the variety and number of inputs when they first begin to use the model. This document...

  14. Final Exam Location and Time

    E-Print Network [OSTI]

    Final Exam Location and Time. Math 162 Fall 2001. Date: Wednesday December 12, 2001. Time: 7:00 pm -9:00 pm. Location: Lambert Fieldhouse ...

  15. Final Exam Location and Time

    E-Print Network [OSTI]

    Final Exam Location and Time. Math 161 Fall 2001. Date: Friday December 14, 2001. Time: 8:00 am -10:00 am. Location: Lambert Fieldhouse ...

  16. Policy-aware sender anonymity in Location-based services

    E-Print Network [OSTI]

    Vyas, Avinash

    2011-01-01T23:59:59.000Z

    LBS Server Location Server CSP Sender Figure 1.1: LBS ModelService Provider, denoted as CSP, the Location Server,is either the MPC in the CSP’s network or an Over-The-Top (

  17. A design solution to the problem of adaptive output regulation for nonlinear minimum-phase systems

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    in the spirit of the internal model principle, the control law needed to fulfill the regulation objective. In [3 regulation and solved by using an "hybrid" control strategy. In that paper it was emphasized how persistenceA design solution to the problem of adaptive output regulation for nonlinear minimum-phase systems

  18. On output regulation in state-constrained systems: An application to polyhedral case

    E-Print Network [OSTI]

    Boyer, Edmond

    .brogliato@inria.fr Abstract: This paper deals with the problem of output regulation using the state feedback control laws of the state feedback law is based on the internal model principle. We study two types of control laws: firstly, a static control is designed assuming that the entire states of the plant and the exosystem are available

  19. Cooling output optimization of an air handling unit Andrew Kusiak *, Mingyang Li

    E-Print Network [OSTI]

    Kusiak, Andrew

    supply temperature and supply air temperature in response to the dynamic cooling load and changingCooling output optimization of an air handling unit Andrew Kusiak *, Mingyang Li Department mining Neural network Multi-objective optimization Evolutionary computation Dynamic modeling Cooling

  20. On the Impact of Partial Shading on PV Output Power DEZSO SERA YAHIA BAGHZOUZ

    E-Print Network [OSTI]

    Sera, Dezso

    @unlv.nevada.edu Abstract: - It is a well-documented fact that partial shading of a photovoltaic array reduces it output power capability. However, the relative amount of such degradation in energy production cannot on a commercial 70 W panel, and a 14.4 kW PV array. Key-Words: - photovoltaic systems, effect of shading, modeling

  1. Analytical input-output and supply chain study of China's coke and steel sectors

    E-Print Network [OSTI]

    Li, Yu, 1976-

    2004-01-01T23:59:59.000Z

    I design an input-output model to investigate the energy supply chain of coal-coke-steel in China. To study the demand, supply, and energy-intensity issues for coal and coke from a macroeconomic perspective, I apply the ...

  2. Abstract: Wind Energy Conversion Systems (WECS) produce fluctuating output power, which may cause voltage fluctuations and

    E-Print Network [OSTI]

    Gross, George

    : An approach to model the solar cell system with coupled multi-physics equations (photovoltaic, electrothermalAbstract: Wind Energy Conversion Systems (WECS) produce fluctuating output power, which may cause in a network of any size can be performed. An algorithm for flicker measurement in the frequency do- main

  3. Sandia National Laboratories: Locations

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearch > TheNuclear PressLaboratorySoftware100LifeAnnouncementsLocations

  4. Bayesian approaches for combining computational model output and physical

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041clothAdvanced Materials Advanced Materials Find More Like This Return to Search Batteryless

  5. Investigation and design of a secure, transportable fluoride-salt-cooled high-temperature reactor (TFHR) for isolated locations

    E-Print Network [OSTI]

    Macdonald, Ruaridh (Ruaridh R.)

    2014-01-01T23:59:59.000Z

    In this work we describe a preliminary design for a transportable fluoride salt cooled high temperature reactor (TFHR) intended for use as a variable output heat and electricity source for off-grid locations. The goals of ...

  6. Interactive Computing 1 Input/Output and Complex Arithmetic

    E-Print Network [OSTI]

    Verschelde, Jan

    Interactive Computing 1 Input/Output and Complex Arithmetic interactive Python scripts complex Software (MCS 507 L-3) Interactive Computing 30 August 2013 1 / 33 #12;Interactive Computing 1 Input/Output and Complex Arithmetic interactive Python scripts complex arithmetic 2 Python Coding Style and pylint coding

  7. A Note on Platt's Probabilistic Outputs for Support Vector Machines

    E-Print Network [OSTI]

    Abu-Mostafa, Yaser S.

    A Note on Platt's Probabilistic Outputs for Support Vector Machines Hsuan-Tien Lin (htlin, National Chengchi University, Taipei 116, Taiwan Abstract. Platt's probabilistic outputs for Support Vector Machines (Platt, 2000) has been popular for applications that require posterior class probabilities

  8. Challenges in Predicting Power Output from Offshore Wind Farms

    E-Print Network [OSTI]

    Pryor, Sara C.

    Challenges in Predicting Power Output from Offshore Wind Farms R. J. Barthelmie1 and S. C. Pryor2 Abstract: Offshore wind energy is developing rapidly in Europe and the trend is towards large wind farms an offshore wind farm, accurate assessment of the wind resource/power output from the wind farm is a necessity

  9. A Counterexample to Additivity of Minimum Output Entropy

    E-Print Network [OSTI]

    M. B. Hastings

    2009-12-30T23:59:59.000Z

    We present a random construction of a pair of channels which gives, with non-zero probability for sufficiently large dimensions, a counterexample to the minimum output entropy conjecture. As shown by Shor, this implies a violation of the additivity conjecture for the classical capacity of quantum channels. The violation of the minimum output entropy conjecture is relatively small.

  10. Driver expectancy in locating automotive controls

    E-Print Network [OSTI]

    Francis, Dawn Suzette

    1990-01-01T23:59:59.000Z

    Major Subject: Industrial Engineering DRIVER EXPECTANCY IN LOCATING AUTOMOTIVE CONTROLS A Thesis by DAWN SUZETTE FRANCIS Approved as to style and content by: R. Dale Huchi son (Chair of Committee) Rodger . . ppa (Member) Waymon L ohnston (M er... assessment of automotive industry practices in 1971 and concluded that only 50% of controls/displays on various models could be said to have a common location. Perel (1974) reviewed prior research and found that it would be difficult to pinpoint...

  11. Locating Boosted Kerr and Schwarzschild Apparent Horizons

    E-Print Network [OSTI]

    Mijan F. Huq; Matthew W. Choptuik; Richard A. Matzner

    2000-02-22T23:59:59.000Z

    We describe a finite-difference method for locating apparent horizons and illustrate its capabilities on boosted Kerr and Schwarzschild black holes. Our model spacetime is given by the Kerr-Schild metric. We apply a Lorentz boost to this spacetime metric and then carry out a 3+1 decomposition. The result is a slicing of Kerr/Schwarzschild in which the black hole is propagated and Lorentz contracted. We show that our method can locate distorted apparent horizons efficiently and accurately.

  12. Most efficient quantum thermoelectric at finite power output

    E-Print Network [OSTI]

    Robert S. Whitney

    2014-03-13T23:59:59.000Z

    Machines are only Carnot efficient if they are reversible, but then their power output is vanishingly small. Here we ask, what is the maximum efficiency of an irreversible device with finite power output? We use a nonlinear scattering theory to answer this question for thermoelectric quantum systems; heat engines or refrigerators consisting of nanostructures or molecules that exhibit a Peltier effect. We find that quantum mechanics places an upper bound on both power output, and on the efficiency at any finite power. The upper bound on efficiency equals Carnot efficiency at zero power output, but decays with increasing power output. It is intrinsically quantum (wavelength dependent), unlike Carnot efficiency. This maximum efficiency occurs when the system lets through all particles in a certain energy window, but none at other energies. A physical implementation of this is discussed, as is the suppression of efficiency by a phonon heat flow.

  13. SWAT 2012 Input/Output Documentation 

    E-Print Network [OSTI]

    Arnold, J.G.; Kiniry, J.R.; Srinivasan, R.; Williams, J.R.; Haney, E.B.; Neitsch, S.L.

    2013-03-04T23:59:59.000Z

    &M AgriLife Research, part of The Texas A&M University System. SWAT is a small watershed to river basin-scale model to simulate the quality and quantity of surface and ground water and predict the environmental impact of land use, land management practices...

  14. An Information Theoretic Location Verification System for Wireless Networks

    E-Print Network [OSTI]

    Yan, Shihao; Nevat, Ido; Peters, Gareth W

    2012-01-01T23:59:59.000Z

    As location-based applications become ubiquitous in emerging wireless networks, Location Verification Systems (LVS) are of growing importance. In this paper we propose, for the first time, a rigorous information-theoretic framework for an LVS. The theoretical framework we develop illustrates how the threshold used in the detection of a spoofed location can be optimized in terms of the mutual information between the input and output data of the LVS. In order to verify the legitimacy of our analytical framework we have carried out detailed numerical simulations. Our simulations mimic the practical scenario where a system deployed using our framework must make a binary Yes/No "malicious decision" to each snapshot of the signal strength values obtained by base stations. The comparison between simulation and analysis shows excellent agreement. Our optimized LVS framework provides a defence against location spoofing attacks in emerging wireless networks such as those envisioned for Intelligent Transport Systems, wh...

  15. Impurity-doped optical shock, detonation and damage location sensor

    DOE Patents [OSTI]

    Weiss, J.D.

    1995-02-07T23:59:59.000Z

    A shock, detonation, and damage location sensor providing continuous fiber-optic means of measuring shock speed and damage location, and could be designed through proper cabling to have virtually any desired crush pressure. The sensor has one or a plurality of parallel multimode optical fibers, or a singlemode fiber core, surrounded by an elongated cladding, doped along their entire length with impurities to fluoresce in response to light at a different wavelength entering one end of the fiber(s). The length of a fiber would be continuously shorted as it is progressively destroyed by a shock wave traveling parallel to its axis. The resulting backscattered and shifted light would eventually enter a detector and be converted into a proportional electrical signals which would be evaluated to determine shock velocity and damage location. The corresponding reduction in output, because of the shortening of the optical fibers, is used as it is received to determine the velocity and position of the shock front as a function of time. As a damage location sensor the sensor fiber cracks along with the structure to which it is mounted. The size of the resulting drop in detector output is indicative of the location of the crack. 8 figs.

  16. Impurity-doped optical shock, detonation and damage location sensor

    DOE Patents [OSTI]

    Weiss, Jonathan D. (Albuquerque, NM)

    1995-01-01T23:59:59.000Z

    A shock, detonation, and damage location sensor providing continuous fiber-optic means of measuring shock speed and damage location, and could be designed through proper cabling to have virtually any desired crush pressure. The sensor has one or a plurality of parallel multimode optical fibers, or a singlemode fiber core, surrounded by an elongated cladding, doped along their entire length with impurities to fluoresce in response to light at a different wavelength entering one end of the fiber(s). The length of a fiber would be continuously shorted as it is progressively destroyed by a shock wave traveling parallel to its axis. The resulting backscattered and shifted light would eventually enter a detector and be converted into a proportional electrical signals which would be evaluated to determine shock velocity and damage location. The corresponding reduction in output, because of the shortening of the optical fibers, is used as it is received to determine the velocity and position of the shock front as a function of time. As a damage location sensor the sensor fiber cracks along with the structure to which it is mounted. The size of the resulting drop in detector output is indicative of the location of the crack.

  17. Saving Output to a File (Using Codeblocks or Dev-C++) Saving Your Output to a File

    E-Print Network [OSTI]

    Sokol, Dina

    Saving Output to a File (Using Codeblocks or Dev-C++) Saving Your Output to a File To save | New | Source File. d. In the new window, right-click and select Paste. e. Then select "File | Save as" to save and name the file. i. In the window that pops up, the bottom fill-in box is labelled "Save as type

  18. VLSI implementation of output convertors for ASIC architectures based on the residual number system: an overview

    E-Print Network [OSTI]

    Godbole, Rajesh

    1992-01-01T23:59:59.000Z

    , . For example, 5 bit residues occupy only 32 locations with a word length equal to [log sM] = 18. The key to this output conversion is a quotient-remainder representation for the summands s?such that 0 & s, & M. If a particular modulus m~ is singled out... Systems 5. Mixed Radix Systems 6. Properties of Weighted and Residual Number Systems B. Algebra of Residue Classes 1. Residue Representation 2. Example: Calculation of Integer Values k Residue Digits 3. Identities Involving Residues and Integer...

  19. Furniture Models Learned from the WWW Using Web Catalogs to Locate and Categorize Unknown Furniture Pieces in 3D Laser Scans

    E-Print Network [OSTI]

    Cremers, Daniel

    , and Michael Beetz, Member, IEEE, Abstract--In this article, we address the problem of exploiting the structure@irvs.is.kyushu-u.ac.jp Zoltan Csaba Marton and Michael Beetz are with the Intelligent Au- tonomous Systems, Technische Universit¨at M¨unchen, 85748 Munich, Ger- many {marton,beetz}@cs.tum.edu Fig. 1. Using furniture models from

  20. Dose monitoring and output correction for the effects of scanning field changes with uniform scanning proton beam

    SciTech Connect (OSTI)

    Zhao, Qingya [IU Health Proton Therapy Center (IUHPTC, formerly known as Midwest Proton Radiotherapy Institute), Bloomington, Indiana 47408 and School of Health Sciences, Purdue University, West Lafayette, Indianapolis, Indiana 47907 (United States); Wu, Huanmei [Purdue School of Engineering and Technology, IUPUI, Indianapolis, Indiana 46202 (United States); Cheng, Chee-Wai; Das, Indra J. [IU Health Proton Therapy Center (IUHPTC, formerly known as Midwest Proton Radiotherapy Institute), Bloomington, Indiana 47408 and Department of Radiation Oncology, School of Medicine, Indiana University, Indianapolis, Indiana 46202 (United States)

    2011-08-15T23:59:59.000Z

    Purpose: The output of a proton beam is affected by proton energy, Spread-Out Bragg Peak (SOBP) width, aperture size, dose rate, and the point of measurement. In a uniform scanning proton beam (USPB), the scanning field size is adjusted (including the vertical length and the horizontal width) according to the treatment field size with appropriate margins to reduce secondary neutron production. Different scanning field settings result in beam output variations that are investigated in this study. Methods: The measurements are performed with a parallel plate Markus chamber at the center of SOBP under the reference condition with 16 cm range, 10 cm SOBP, and 5 cm air gap. The effect of dose rate on field output is studied by varying proton beam current from 0.5 to 7 nA. The effects of scanning field settings are studied by varying independently the field width and length from 12 x 12 to 30 x 30 cm{sup 2}. Results: The results demonstrate that scanning field variations can produce output variation up to 3.80%. In addition, larger output variation is observed with scanning field changes along the stem direction of the patient dose monitor (PDM). By investigating the underlying physics of incomplete charge collection and the stem effects of the PDM, an analytical model is proposed to calculate USPB output with consideration of the scanning field area and the PDM stem length that is irradiated. The average absolute difference between the measured output and calculated output using our new correction model are within 0.13 and 0.08% for the 20 and 30 cm snouts, respectively. Conclusions: This study proposes a correction model for accurate USPB output calculation, which takes account of scanning field settings and the PDM stem effects. This model may be used to extend the existing output calculation model from one snout size to other snout sizes with customized scanning field settings. The study is especially useful for calculating field output for treatment without individualized patient specific measurements.

  1. Steady-state bumpless transfer under controller uncertainty using the state/output feedback topology

    SciTech Connect (OSTI)

    Zheng, K.; Lee, A.H.; Bentsman, J.; Taft, C.W. [University of Illinois, Urbana, IL (United States)

    2006-01-15T23:59:59.000Z

    Linear quadratic (LQ) bumpless transfer design introduced recently by Turner and Walker gives a very convenient and straightforward computational procedure for the steady-state bumpless transfer operator synthesis. It is, however, found to be incapable of providing convergence of the output of the offline controller to that of the online controller in several industrial applications, producing bumps in the plant output in the wake of controller transfer. An examination of this phenomenon reveals that the applications in question are characterized by a significant mismatch, further referred to as controller uncertainty, between the dynamics of the implemented controllers and their models used in the transfer operator computation. To address this problem, while retaining the convenience of the Turner and Walker design, a novel state/output feedback bumpless transfer topology is introduced that employs the nominal state of the offline controller and, through the use of an additional controller/model mismatch compensator, also the offline controller output. A corresponding steady-state bumpless transfer design procedure along with the supporting theory is developed for a large class of systems. Due to these features, it is demonstrated to solve a long-standing problem of high-quality steady-state bumpless transfer from the industry standard low-order nonlinear multiloop PID-based controllers to the modern multiinput-multioutput (MIMO) robust controllers in the megawatt/throttle pressure control of a typical coal-fired boiler/turbine unit.

  2. p-facility Huff location problem on networks ?

    E-Print Network [OSTI]

    2014-10-30T23:59:59.000Z

    ing field, in problems such as location of petrol stations, shopping centers or restaurants. [14, 20, 22]. Network optimization models [5] are widely used in practice ...

  3. The Cricket indoor location system

    E-Print Network [OSTI]

    Priyantha, Nissanka Bodhi, 1968-

    2005-01-01T23:59:59.000Z

    Indoor environments present opportunities for a rich set of location-aware applications such as navigation tools for humans and robots, interactive virtual games, resource discovery, asset tracking, location-aware sensor ...

  4. Ota City : characterizing output variability from 553 homes with residential PV systems on a distribution feeder.

    SciTech Connect (OSTI)

    Stein, Joshua S.; Miyamoto, Yusuke (Kandenko, Ibaraki, Japan); Nakashima, Eichi (Kandenko, Ibaraki, Japan); Lave, Matthew

    2011-11-01T23:59:59.000Z

    This report describes in-depth analysis of photovoltaic (PV) output variability in a high-penetration residential PV installation in the Pal Town neighborhood of Ota City, Japan. Pal Town is a unique test bed of high-penetration PV deployment. A total of 553 homes (approximately 80% of the neighborhood) have grid-connected PV totaling over 2 MW, and all are on a common distribution line. Power output at each house and irradiance at several locations were measured once per second in 2006 and 2007. Analysis of the Ota City data allowed for detailed characterization of distributed PV output variability and a better understanding of how variability scales spatially and temporally. For a highly variable test day, extreme power ramp rates (defined as the 99th percentile) were found to initially decrease with an increase in the number of houses at all timescales, but the reduction became negligible after a certain number of houses. Wavelet analysis resolved the variability reduction due to geographic diversity at various timescales, and the effect of geographic smoothing was found to be much more significant at shorter timescales.

  5. Correction method for in-air output ratio for output variations occurring with changes in backscattered radiation

    SciTech Connect (OSTI)

    Tajiri, Minoru; Tokiya, Yuji; Watanabe, Kazuhiro [Research Center Hospital for Charged Particle Therapy, National Institute of Radiological Sciences, 4-9-1, Anagawa, Inage-ku, Chiba 263-8555 (Japan); International University of Health and Welfare, 1-4-3, Mita, Minato-ku, Tokyo 108-8329 (Japan); Research Center Hospital for Charged Particle Therapy, National Institute of Radiological Sciences, 4-9-1, Anagawa, Inage-ku, Chiba 263-8555 (Japan)

    2012-02-15T23:59:59.000Z

    Purpose: The in-air output ratio (S{sub c}) for a rectangular field is usually obtained using an equivalent square field formula. However, it is well-known that S{sub c} obtained using an equivalent square field formula differs slightly from the measured S{sub c}. Though several correction methods have been suggested for the monitor-backscatter effect, the authors propose a more simple correction method for a rectangular field. Methods: For rectangular fields and equivalent square fields, the authors assumed that the output variation was the product of six output variations for each backscattering area at the top of the collimator jaws, and the correction factor was the ratio of the output variation for a rectangular field to the output variation for an equivalent square field. The output variation was measured by using a telescope measurement. Results: The differences between the measured and corrected S{sub c} ranged from -0.20% to 0.28% for symmetric rectangular fields by applying the correction factor to S{sub c} obtained using an equivalent square field formula. This correction method is also available for asymmetric rectangular fields. Conclusions: The authors propose a method to correct S{sub c} obtained using an equivalent square field formula, and a method to obtain the output variation for a field defined by collimator jaws.

  6. The Effect of Signal Quality on Six Cardiac Output Estimators

    E-Print Network [OSTI]

    Mark, Roger Greenwood

    The effect of signal quality on the accuracy of cardiac output (CO) estimation from arterial blood pressure (ABP) was evaluated using data from the MIMIC II database. Thermodilution CO (TCO) was the gold standard. A total ...

  7. Development of Regional Wind Resource and Wind Plant Output Datasets...

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

    50-47676 March 2010 Development of Regional Wind Resource and Wind Plant Output Datasets Final Subcontract Report 15 October 2007 - 15 March 2009 3TIER Seattle, Washington National...

  8. Corticospinal Output to Hindlimb Muscles in the Primate

    E-Print Network [OSTI]

    Hudson, Heather M

    2011-05-31T23:59:59.000Z

    The overall goal of this study was to investigate the properties of corticospinal output to a wide range of hindlimb muscles in the primate and to map the representation of individual muscles in hindlimb motor cortex. ...

  9. Grid adaptation for functional outputs of compressible flow simulations

    E-Print Network [OSTI]

    Venditti, David Anthony, 1973-

    2002-01-01T23:59:59.000Z

    An error correction and grid adaptive method is presented for improving the accuracy of functional outputs of compressible flow simulations. The procedure is based on an adjoint formulation in which the estimated error in ...

  10. Process and Intermediate Calculations User AccessInputs Outputs

    E-Print Network [OSTI]

    Process and Intermediate Calculations User AccessInputs Outputs Fire Behavior & Probability STARFire System Flow Valuation Processing Temporal Schedules Smoke · Zones · Zone impact · Emissions Fire and compare Valuation (Structured Elicit Process) 1) Value Layers: · Point (housing, cultural trees, etc

  11. The world of quantum noise and the fundamental output process

    E-Print Network [OSTI]

    V. P. Belavkin; O. Hirota; R. Hudson

    2005-10-04T23:59:59.000Z

    A stationary theory of quantum stochastic processes of second order is outlined. It includes KMS processes in wide sense like the equilibrium finite temperature quantum noise given by the Planck's spectral formula. It is shown that for each stationary noise there exists a natural output process output process which is identical to the noise in the infinite temperature limit, and flipping with the noise if the time is reversed at finite temperature. A canonical Hilbert space representation of the quantum noise and the fundamental output process is established and a decomposition of their spectra is found. A brief explanation of quantum stochastic integration with respect to the input-output processes is given using only correlation functions. This provides a mathematical foundation for linear stationary filtering transformations of quantum stochastic processes. It is proved that the colored quantum stationary noise and its time-reversed version can be obtained in the second order theory by a linear nonadapted filtering of the standard vacuum noise uniquely defined by the canonical creation and annihilation operators on the spectrum of the input-output pair.

  12. Microwave generated electrodeless lamp for producing bright output

    SciTech Connect (OSTI)

    Wood, Ch. H.; Ury, M. G.

    1985-03-26T23:59:59.000Z

    A microwave generated electrodeless light source for producing a bright output comprising a lamp structure including a microwave chamber and a plasma medium-containing lamp envelope having a maximum dimension which is substantially less than a wavelength disposed therein. To provide the desired radiation output the interior of the chamber is coated with a UV-reflective material and the chamber has an opening for allowing UV radiation to exit, which is covered with a metallic mesh. The chamber is arranged to be near-resonant at a single wavelength, and the lamp envelope has a fill including mercury at an operating pressure of 1-2 atmospheres, while a power density of at least 250-300 (watts/cm/sup 3/) is coupled to the envelope to result in a relatively high deep UV output at a relatively high brightness.

  13. Self-consistent input-output formulation of quantum feedback

    SciTech Connect (OSTI)

    Yanagisawa, M. [Department of Engineering, The Australian National University, Canberra, ACT 0200 (Australia); Hope, J. J. [Department of Quantum Science, The Australian National University, Canberra, ACT 0200 (Australia)

    2010-12-15T23:59:59.000Z

    A simple method of analyzing quantum feedback circuits is presented. The classical analysis of feedback circuits can be generalized to apply to quantum systems by mapping the field operators of various outputs to other inputs via the standard input-output formalism. Unfortunately, this has led to unphysical results such as the violation of the Heisenberg uncertainty principle for in-loop fields. This paper shows that this general approach can be redeemed by ensuring a self-consistently Hermitian Hamiltonian. The calculations are based on a noncommutative calculus of operator derivatives. A full description of several examples of quantum linear and nonlinear feedback for optical systems is presented.

  14. Motor-output variability in a ballistic task

    E-Print Network [OSTI]

    Weeks, Douglas Lane

    1981-01-01T23:59:59.000Z

    MOTOR-OUTPUT VARIABILIT'f IN A BALLISTIC TASK A Thesis by DOUGLAS LANE WEEKS Submitted to the Graduate College of Texas ASM University in partsal fulfillment of the requirement for the degree of MASTER OF SCIENCE August 1981 Major Subject...: Physical Education MOTOR-OUTPUT VARIABILITY IN A BALLISTIC TASK A Thesis by DOUGLAS LANE WEEKS Approved as to style and content by: Chairman of Committee , ember C ee. yc ace Member )g p~ Head of Department August 1981 ADS!RACT !Notor...

  15. Mobile Alternative Fueling Station Locator

    SciTech Connect (OSTI)

    Not Available

    2009-04-01T23:59:59.000Z

    The Department of Energy's Alternative Fueling Station Locator is available on-the-go via cell phones, BlackBerrys, or other personal handheld devices. The mobile locator allows users to find the five closest biodiesel, electricity, E85, hydrogen, natural gas, and propane fueling sites using Google technology.

  16. Precision zero-home locator

    DOE Patents [OSTI]

    Stone, W.J.

    1983-10-31T23:59:59.000Z

    A zero-home locator includes a fixed phototransistor switch and a moveable actuator including two symmetrical, opposed wedges, each wedge defining a point at which switching occurs. The zero-home location is the average of the positions of the points defined by the wedges.

  17. Model Development Development of a system emulating the global carbon cycle in Earth system models

    E-Print Network [OSTI]

    K. Tachiiri; J. C. Hargreaves; J. D. Annan; A. Oka; A. Abe-ouchi; M. Kawamiya

    2010-01-01T23:59:59.000Z

    developed a loosely coupled model (LCM) which can represent the outputs of a GCMbased Earth system model

  18. Output power characteristics and performance of TOPAZ II Thermionic Fuel Element No. 24

    SciTech Connect (OSTI)

    Luchau, D.W.; Bruns, D.R. [Team Specialty Services, Inc., TOPAZ International Program, 901 University Blvd., SE, Albuquerque, New Mexico 87106 (United States); Izhvanov, O.; Androsov, V. [JV INERTEK, Scientific Industrial Association ``Luch``, 24 Zheleznodorozhnaya, Podolsk, (Russia) 142100

    1996-03-01T23:59:59.000Z

    A final report on the output power characteristics and capabilities of single cell TOPAZ II Thermionic Fuel Element (TFE) No. 24 is presented. Thermal power tests were conducted for over 3000 hours to investigate converter performance under normal and adverse operating conditions. Experiments conducted include low power testing, high power testing, air introduction to the interelectrode gap, collector temperature optimization, thermal modeling, and output power characteristic measurements. During testing, no unexpected degradation in converter performance was observed. The TFE has been removed from the test stand and returned to Scientific Industrial Association {open_quote}{open_quote}LUCH{close_quote}{close_quote} for materials analysis and report. This research was conducted at the Thermionic System Evaluation Test (TSET) Facility at the New Mexico Engineering Research Institute (NMERI) as a part of the Topaz International Program (TIP) by the Air Force Phillips Laboratory (PL). {copyright} {ital 1996 American Institute of Physics.}

  19. Development of a 402.5 MHz 140 kW Inductive Output Tube

    SciTech Connect (OSTI)

    R. Lawrence Ives; Michael Read, Robert Jackson

    2012-05-09T23:59:59.000Z

    This report contains the results of Phase I of an SBIR to develop a Pulsed Inductive Output Tube (IOT) with 140 kW at 400 MHz for powering H-proton beams. A number of sources, including single beam and multiple beam klystrons, can provide this power, but the IOT provides higher efficiency. Efficiencies exceeding 70% are routinely achieved. The gain is typically limited to approximately 24 dB; however, the availability of highly efficient, solid state drivers reduces the significance of this limitation, particularly at lower frequencies. This program initially focused on developing a 402 MHz IOT; however, the DOE requirement for this device was terminated during the program. The SBIR effort was refocused on improving the IOT design codes to more accurately simulate the time dependent behavior of the input cavity, electron gun, output cavity, and collector. Significant improvement was achieved in modeling capability and simulation accuracy.

  20. On Optimal Distributed Output-Feedback Control over Acyclic Graphs

    E-Print Network [OSTI]

    Gattami, Ather

    2012-01-01T23:59:59.000Z

    In this paper, we consider the problem of distributed optimal control of linear dynamical systems with a quadratic cost criterion. We study the case of output feedback control for two interconnected dynamical systems, and show that the linear optimal solution can be obtained from a combination of two uncoupled Riccati equations and two coupled Riccati equations.

  1. TRICOLOR LIGHT EMITTING DIODE DOT MATRIX DISPLAY SYSTEM WITHAUDIO OUTPUT

    E-Print Network [OSTI]

    Pang, Grantham

    1 TRICOLOR LIGHT EMITTING DIODE DOT MATRIX DISPLAY SYSTEM WITHAUDIO OUTPUT Grantham Pang, Chi emitting diodes; tricolor display; audio communication. I. Introduction This paper relates to a tricolor broadcasting through the visible light rays transmitted by the display panel or assembly. Keywords: light

  2. The effects of output transformers on distortion in audio amplifiers

    E-Print Network [OSTI]

    Lanier, Ross Edwin

    1949-01-01T23:59:59.000Z

    Introduction ~. . . . . . . . , . . . . . . ~. . . . . 7 Frequency Discrimination. . . . . . . . . . . . . . . . 9 Harmonic Distortion. ~ ~. . . . ~ 21 Distortion by the Intermodulationmethod. . . . . . . . 47 Comparison of Harmonic and Intermodulation... current in the primary as a function of frequency . 19 Output voltage of transformer 3 without direct current in the primary as a function of frequency 20 Block diagram for measuring distortion by the harmonic method 26 Per cent harmonic distortion...

  3. ANALOG-DIGITAL INPUT OUTPUT SYSTEM FOR APPLE CO

    E-Print Network [OSTI]

    Groppi, Christopher

    Initialization Program - ADIOS INITB Appendix 2 Test Program - ADIOS TEST Appendix 3 AND9513 Utilization Appendix HI-506A. Multiplexer F. Sprague UHP -507 Relay Driver G. Teledyne Solid-State Relays H. Advanced bus driver, a 4-bit relay driver, or two solid-state relays. Three of the digital output bits can

  4. Convergent relaxations of polynomial matrix inequalities and static output feedback

    E-Print Network [OSTI]

    Henrion, Didier

    (LMI) relaxations to solve non-convex polynomial matrix in- equality (PMI) optimization problems minimizers that satisfy the PMI. The approach is successfully applied to PMIs arising from static output- mulated as polynomial matrix inequality (PMI) optimization problems in the controller parameters

  5. Weak values and weak coupling maximizing the output of weak measurements

    SciTech Connect (OSTI)

    Di Lorenzo, Antonio, E-mail: dilorenzo.antonio@gmail.com

    2014-06-15T23:59:59.000Z

    In a weak measurement, the average output ?o? of a probe that measures an observable A{sup -hat} of a quantum system undergoing both a preparation in a state ?{sub i} and a postselection in a state E{sub f} is, to a good approximation, a function of the weak value A{sub w}=Tr[E{sub f}A{sup -hat} ?{sub i}]/Tr[E{sub f}?{sub i}], a complex number. For a fixed coupling ?, when the overlap Tr[E{sub f}?{sub i}] is very small, A{sub w} diverges, but ?o? stays finite, often tending to zero for symmetry reasons. This paper answers the questions: what is the weak value that maximizes the output for a fixed coupling? What is the coupling that maximizes the output for a fixed weak value? We derive equations for the optimal values of A{sub w} and ?, and provide the solutions. The results are independent of the dimensionality of the system, and they apply to a probe having a Hilbert space of arbitrary dimension. Using the Schrödinger–Robertson uncertainty relation, we demonstrate that, in an important case, the amplification ?o? cannot exceed the initial uncertainty ?{sub o} in the observable o{sup -hat}, we provide an upper limit for the more general case, and a strategy to obtain ?o???{sub o}. - Highlights: •We have provided a general framework to find the extremal values of a weak measurement. •We have derived the location of the extremal values in terms of preparation and postselection. •We have devised a maximization strategy going beyond the limit of the Schrödinger–Robertson relation.

  6. aid maximum output: Topics by E-print Network

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

    at a given geographic location. Taking the solar irradiation levels, the ambient temperature, and the Sun's position angles as inputs, a multilayer feed-forward neural network...

  7. Transionospheric propagation calculations for the output of two EMP (electromagnetic pulse) simulators

    SciTech Connect (OSTI)

    Roussel-Dupre, R.

    1990-11-01T23:59:59.000Z

    The Los Alamos Transionospheric Propagation Code (TIPC) was used to calculate the transionospheric signals corresponding to the computed output of two electromagnetic pulse (EMP) simulators, the NAVES II vertical polarization dipole and the TACAMO horizontal polarization dipole. The EMP calculations used as input to TIPC were performed by Mission Research Corporation. The 1986 International Reference Ionosphere code was used to generate vertical profiles of electron density over a twenty-four hour period for the geographical location of the NAVES II EMP simulator and for a solar content, used as input to TIPC, was calculated from the electron density profiles by integrating along a given line of sight. The maximum root mean square power densities to be expected in each of eight broadband receivers with bandwidths of 5 and 20 MHz centered at 200, 120, 80, and 40 MHx are presented. 5 refs., 20 figs., 1 tab.

  8. Detecting and Locating Radioactive Signals with Wireless Sensor Networks

    E-Print Network [OSTI]

    Zhang, Tonglin

    Detecting and Locating Radioactive Signals with Wireless Sensor Networks Tonglin Zhang Department-765-4940558 AbstractMethods of detecting and locating nuclear radioac- tive targets via wireless sensor networks (WSN model, radia- tion and radioactive isotopes, wireless sensor network. I. INTRODUCTION Currently, using

  9. On Hastings' counterexamples to the minimum output entropy additivity conjecture

    E-Print Network [OSTI]

    Fernando G. S. L. Brandao; Michal Horodecki

    2009-07-19T23:59:59.000Z

    Hastings recently reported a randomized construction of channels violating the minimum output entropy additivity conjecture. Here we revisit his argument, presenting a simplified proof. In particular, we do not resort to the exact probability distribution of the Schmidt coefficients of a random bipartite pure state, as in the original proof, but rather derive the necessary large deviation bounds by a concentration of measure argument. Furthermore, we prove non-additivity for the overwhelming majority of channels consisting of a Haar random isometry followed by partial trace over the environment, for an environment dimension much bigger than the output dimension. This makes Hastings' original reasoning clearer and extends the class of channels for which additivity can be shown to be violated.

  10. Optical device with conical input and output prism faces

    DOE Patents [OSTI]

    Brunsden, Barry S. (Chicago, IL)

    1981-01-01T23:59:59.000Z

    A device for radially translating radiation in which a right circular cylinder is provided at each end thereof with conical prism faces. The faces are oppositely extending and the device may be severed in the middle and separated to allow access to the central part of the beam. Radiation entering the input end of the device is radially translated such that radiation entering the input end at the perimeter is concentrated toward the output central axis and radiation at the input central axis is dispersed toward the output perimeter. Devices are disclosed for compressing beam energy to enhance drilling techniques, for beam manipulation of optical spatial frequencies in the Fourier plane and for simplification of dark field and color contrast microscopy. Both refracting and reflecting devices are disclosed.

  11. Reliable Gas Turbine Output: Attaining Temperature Independent Performance

    E-Print Network [OSTI]

    Neeley, J. E.; Patton, S.; Holder, F.

    % of the electric system, could create reliability and operational problems. This paper explores the potential for maintaining constant, reliable outputs from gas turbines by cooling ambient air temperatures before the air is used in the compressor section... strides have been made in the development of both aircraft, aircraft-derivative, and industrial gas turbines. The Basic Cycle The basic gas turbine engine consists of a compressor, a combustor, and a turbine in series. The intake air is compressed...

  12. Development of output user interface software to support analysis

    SciTech Connect (OSTI)

    Wahanani, Nursinta Adi, E-mail: sintaadi@batan.go.id; Natsir, Khairina, E-mail: sintaadi@batan.go.id; Hartini, Entin, E-mail: sintaadi@batan.go.id [Center for Development of Nuclear Informatics - National Nuclear Energy Agency, PUSPIPTEK, Serpong, Tangerang, Banten (Indonesia)

    2014-09-30T23:59:59.000Z

    Data processing software packages such as VSOP and MCNPX are softwares that has been scientifically proven and complete. The result of VSOP and MCNPX are huge and complex text files. In the analyze process, user need additional processing like Microsoft Excel to show informative result. This research develop an user interface software for output of VSOP and MCNPX. VSOP program output is used to support neutronic analysis and MCNPX program output is used to support burn-up analysis. Software development using iterative development methods which allow for revision and addition of features according to user needs. Processing time with this software 500 times faster than with conventional methods using Microsoft Excel. PYTHON is used as a programming language, because Python is available for all major operating systems: Windows, Linux/Unix, OS/2, Mac, Amiga, among others. Values that support neutronic analysis are k-eff, burn-up and mass Pu{sup 239} and Pu{sup 241}. Burn-up analysis used the mass inventory values of actinide (Thorium, Plutonium, Neptunium and Uranium). Values are visualized in graphical shape to support analysis.

  13. Ring laser having an output at a single frequency

    DOE Patents [OSTI]

    Hackell, Lloyd A. (Livermore, CA)

    1991-01-01T23:59:59.000Z

    A ring laser is disclosed that produces a single frequency of laser radiation in either the pulsed mode of operation or the continuous waveform (cw) mode of operation. The laser comprises a ring laser in a bowtie configuration, a birefringent gain material such as Nd:YLF, an improved optical diode that supports laser oscillation having a desired direction of travel and linear polarization, and a Q-switch. An output coupler (mirror) having a high reflectivity, such as 94%, is disclosed. Also disclosed is a self-seeded method of operation in which the laser can provide a pulse or a series of pulses of high power laser radiation at a consistent single frequency with a high degree of amplitude stability and temporal stability. In operation, the laser is operated in continuous waveform (cw) at a low power output with the Q-switch introducing a loss into the resonating cavity. Pumping is continued at a high level, causing the gain material to store energy. When a pulse is desired, the Q-switch is actuated to substantially reduce the losses so that a pulse can build up based on the low level cw oscillation. The pulse quickly builds, using the stored energy in the gain medium to provide a high power output pulse. The process may be repeated to provide a series of high power pulses of a consistent single frequency.

  14. A Two Stage Stochastic Equilibrium Model for Electricity Markets ...

    E-Print Network [OSTI]

    2008-12-12T23:59:59.000Z

    a monopoly, its marginal cost at output level qu or above would exceed any possible market price. ...... in an electricity markets with locational prices. See [15] for ...

  15. ambulance location monitoring: Topics by E-print Network

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

    model adds a dependence on the datatype used to derive the location. M. S. Briggs; G. N. Pendleton; J. J. Brainerd; V. Connaughton; R. M. Kippen; C. Meegan; K. Hurley...

  16. Synchronized sampling improves fault location

    SciTech Connect (OSTI)

    Kezunovic, M. [Texas A and M Univ., College Station, TX (United States)] [Texas A and M Univ., College Station, TX (United States); Perunicic, B. [Lamar Univ., Beaumont, TX (United States)] [Lamar Univ., Beaumont, TX (United States)

    1995-04-01T23:59:59.000Z

    Transmission line faults must be located accurately to allow maintenance crews to arrive at the scene and repair the faulted section as soon as possible. Rugged terrain and geographical layout cause some sections of power transmission lines to be difficult to reach. In the past, a variety of fault location algorithms were introduced as either an add-on feature in protective relays or stand-alone implementation in fault locators. In both cases, the measurements of current and voltages were taken at one terminal of a transmission line only. Under such conditions, it may become difficult to determine the fault location accurately, since data from other transmission line ends are required for more precise computations. In the absence of data from the other end, existing algorithms have accuracy problems under several circumstances, such as varying switching and loading conditions, fault infeed from the other end, and random value of fault resistance. Most of the one-end algorithms were based on estimation of voltage and current phasors. The need to estimate phasors introduces additional difficulty in high-speed tripping situations where the algorithms may not be fast enough in determining fault location accurately before the current signals disappear due to the relay operation and breaker opening. This article introduces a unique concept of high-speed fault location that can be implemented either as a simple add-on to the digital fault recorders (DFRs) or as a stand-alone new relaying function. This advanced concept is based on the use of voltage and current samples that are synchronously taken at both ends of a transmission line. This sampling technique can be made readily available in some new DFR designs incorporating receivers for accurate sampling clock synchronization using the satellite Global Positioning System (GPS).

  17. Location logistics of industrial facilities

    E-Print Network [OSTI]

    Hammack, William Eugene

    1981-01-01T23:59:59.000Z

    of company intent1ons is not made at the correct time and in the correct manner. 6. Recommend Best Areas for Further Invest1 ations. Once the on-site evaluations have been completed, the 11st of possibilities is reduced still further and only the best... location and site selection. This data was gathered through library research, atten- dance of various industr1al development conferences, sol1citation of mater1als from individuals currently involved with industrial facil1ties location, and various...

  18. Building Address Locations -Assumes entire

    E-Print Network [OSTI]

    Guenther, Frank

    Building Address Locations - Assumes entire building unless noted Designation Submit through* 560, 4 BU Crosstown Center 801 Massachusetts Ave Floor 1, 2 BMC BCD Building 800 Harrison Avenue BCD BMC Biosquare III 670 Albany Floors 2, 3, 6, 7 BMC Biosquare III 670 Albany Floors 1, 4, 5, 8 BU Building

  19. Boston, Massachusetts Location: Boston, MA

    E-Print Network [OSTI]

    Prevedouros, Panos D.

    -recovery ventilation and water-source heat pumps Each unit has fresh air ducted independently. Each residence is warmed by a heat pump that taps the Trigen Energy Corporation steam lines that run underneath the street. #12;WallsBoston, Massachusetts #12;Location: Boston, MA Building type(s): Multi-unit residential, Retail 350

  20. A Wavelet-Based Variability Model (WVM) for Solar PV Power Plants

    E-Print Network [OSTI]

    Lave, Matthew; Kleissl, Jan; Stein, Joshua S

    2013-01-01T23:59:59.000Z

    Model (WVM) for Solar PV Power Plants Matthew Lave, Jansolar photovoltaic (PV) power plant output given a singleproduce a simulated power plant output. The WVM is validated

  1. Method and system for managing an electrical output of a turbogenerator

    DOE Patents [OSTI]

    Stahlhut, Ronnie Dean (Bettendorf, IA); Vuk, Carl Thomas (Denver, IA)

    2009-06-02T23:59:59.000Z

    The system and method manages an electrical output of a turbogenerator in accordance with multiple modes. In a first mode, a direct current (DC) bus receives power from a turbogenerator output via a rectifier where turbogenerator revolutions per unit time (e.g., revolutions per minute (RPM)) or an electrical output level of a turbogenerator output meet or exceed a minimum threshold. In a second mode, if the turbogenerator revolutions per unit time or electrical output level of a turbogenerator output are less than the minimum threshold, the electric drive motor or a generator mechanically powered by the engine provides electrical energy to the direct current bus.

  2. Method and system for managing an electrical output of a turbogenerator

    DOE Patents [OSTI]

    Stahlhut, Ronnie Dean (Bettendorf, IA); Vuk, Carl Thomas (Denver, IA)

    2010-08-24T23:59:59.000Z

    The system and method manages an electrical output of a turbogenerator in accordance with multiple modes. In a first mode, a direct current (DC) bus receives power from a turbogenerator output via a rectifier where turbogenerator revolutions per unit time (e.g., revolutions per minute (RPM)) or an electrical output level of a turbogenerator output meet or exceed a minimum threshold. In a second mode, if the turbogenerator revolutions per unit time or electrical output level of a turbogenerator output are less than the minimum threshold, the electric drive motor or a generator mechanically powered by the engine provides electrical energy to the direct current bus.

  3. Joint microseismic event location with uncertain velocity

    E-Print Network [OSTI]

    Poliannikov, Oleg V.

    2013-01-01T23:59:59.000Z

    We study the problem of the joint location of seismic events using an array of receivers. We show that locating multiple seismic events simultaneously is advantageous compared to the more traditional approaches of locating ...

  4. Enhancing e-waste estimates: Improving data quality by multivariate Input–Output Analysis

    SciTech Connect (OSTI)

    Wang, Feng, E-mail: fwang@unu.edu [Institute for Sustainability and Peace, United Nations University, Hermann-Ehler-Str. 10, 53113 Bonn (Germany); Design for Sustainability Lab, Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628CE Delft (Netherlands); Huisman, Jaco [Institute for Sustainability and Peace, United Nations University, Hermann-Ehler-Str. 10, 53113 Bonn (Germany); Design for Sustainability Lab, Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628CE Delft (Netherlands); Stevels, Ab [Design for Sustainability Lab, Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628CE Delft (Netherlands); Baldé, Cornelis Peter [Institute for Sustainability and Peace, United Nations University, Hermann-Ehler-Str. 10, 53113 Bonn (Germany); Statistics Netherlands, Henri Faasdreef 312, 2492 JP Den Haag (Netherlands)

    2013-11-15T23:59:59.000Z

    Highlights: • A multivariate Input–Output Analysis method for e-waste estimates is proposed. • Applying multivariate analysis to consolidate data can enhance e-waste estimates. • We examine the influence of model selection and data quality on e-waste estimates. • Datasets of all e-waste related variables in a Dutch case study have been provided. • Accurate modeling of time-variant lifespan distributions is critical for estimate. - Abstract: Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lack of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate Input–Output Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e-waste estimation studies.

  5. Energy Department Launches Alternative Fueling Station Locator...

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

    Energy Department Launches Alternative Fueling Station Locator App Energy Department Launches Alternative Fueling Station Locator App November 7, 2013 - 11:16am Addthis As part of...

  6. Asymptotic analysis of an optimal location problem

    E-Print Network [OSTI]

    2003-05-13T23:59:59.000Z

    Asymptotic analysis of an optimal location problem. One considers the problem of optimal location of masses(say production centers) in order to approximate a ...

  7. Spatial Interference Mitigation for Multiple Input Multiple Output Ad Hoc Networks: MISO Gains

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Spatial Interference Mitigation for Multiple Input Multiple Output Ad Hoc Networks: MISO Gains beamforming for a multiple input single output (MISO) ad hoc network to increase the density of successful

  8. Design of a 3.3 V analog video line driver with controlled output impedance

    E-Print Network [OSTI]

    Ramachandran, Narayan Prasad

    2004-09-30T23:59:59.000Z

    impedance of the line. The main requirements for design are high output swing, high linearity, matched impedance to the line and power efficiency. These requirements are addressed by a class AB amplifier whose output impedance can be controlled through...

  9. Predicting the Power Output of Distributed Renewable Energy Resources within a Broad Geographical Region

    E-Print Network [OSTI]

    Chalkiadakis, Georgios

    Predicting the Power Output of Distributed Renewable Energy Resources within a Broad Geographical potentially dis- tributed renewable energy resources (su years, estimating the power output of in- herently intermittent and potentially distributed renewable

  10. Regulatory Reform to Promote Clean Energy: The Potential of Output-Based Emissions Standards

    SciTech Connect (OSTI)

    Cox, Matthew [Georgia Institute of Technology] [Georgia Institute of Technology; Brown, Dr. Marilyn Ann [Georgia Institute of Technology] [Georgia Institute of Technology; Jackson, Roderick K [ORNL] [ORNL

    2011-01-01T23:59:59.000Z

    Barriers to industrial energy-efficient technologies hinder their use. A number of EPA analyses and industrial experts have found that the utilization of input-based emissions standards (measured in parts-per-million or pounds/MMBtu) in the Clean Air Act creates a regulatory barrier to the installation and deployment of technologies that emit fewer criteria pollutants and use energy more efficiently. Changing emission management strategies to an output-based emissions standard (measured in tons of pollutant emitted) is a way to ameliorate some of these barriers. Combined heat and power (CHP) is one of the key technologies that would see increased industrial application if the emissions standards were modified. Many states have made this change since the EPA first approved it in 2000, although direction from the Federal government could speed implementation modifications. To analyze the national impact of accelerated state adoption of output-based standards on CHP technologies, this paper uses detailed National Energy Modeling System (NEMS) and spreadsheet analysis illustrating two phased-in adoption scenarios for output-based emissions standards in the industrial sector. Benefit/cost metrics are calculated from a private and public perspective, and also a social perspective that considers the criteria and carbon air pollution emissions. These scenarios are compared to the reference case of AEO 2010 and are quite favorable, with a social benefit-cost ratio of 16.0 for a five-year phase-in scenario. In addition, the appropriateness of the Federal role, applicability, technology readiness, and administrative feasibility are discussed.

  11. Soft-Input Soft-Output King Decoder for Coded MIMO Wireless Communications

    E-Print Network [OSTI]

    Soft-Input Soft-Output King Decoder for Coded MIMO Wireless Communications Giuseppe PAPA, Domenico,{domenico.ciuonzo,gianmarco.romano,pierluigi.salvorossi}@unina2.it Abstract--This paper presents a Soft-Input Soft-Output (SISO) version of the King Decoder (KD for Multiple-Input Multiple-Output (MIMO) communication systems. More specifically, four versions of the KD

  12. The electrical and lumen output characteristics of an RF lamp

    SciTech Connect (OSTI)

    Alexandrovich, B.M.; Godyak, V.A.; Piejak, R.B. [Osram Sylvania Inc., Beverly, MA (United States)

    1996-12-31T23:59:59.000Z

    Low pressure rf discharges have been studied for over a century. Their first practical application for lighting was proposed by Tesla in 1891. Since then hundreds of patents have been published attempting to implement rf lighting. However, progress in understanding rf discharge phenomena (mostly driven by plasma processing needs) and dramatic improvement in the performance/cost ratio of rf power sources have recently opened the door for development of rf light sources. Today commercial inductively coupled electrodeless lamps are offered by Matsuhita, Philips and GE. In this work the authors present measurements of the electrical characteristics and lumen output from a 2.65 MHz driven inductively coupled light source. Measurements were made on a spherical lamp of 3.125 inch diameter with a re-entrant cavity that houses a cylindrical ferrite core around which is wrapped the primary coil.

  13. Output Performance and Payback Analysis of a Residential Photovoltaic System in Colorado: Preprint

    SciTech Connect (OSTI)

    Johnston, S.

    2012-06-01T23:59:59.000Z

    Cost of installation and ownership of a 9.66-kilowatt (kW) residential photovoltaic system is described, and the performance of this system over the past 3 years is shown. The system is located in Colorado at 40 degrees latitude and consists of arrays on two structures. Two arrays are installed on a detached garage, and these are each composed of 18 Kyocera 130-W modules strung in series facing south at an angle of 40 degrees above horizontal. Each 18-panel array feeds into a Xantrex/Schneider Electric 2.8-kW inverter. The other two arrays are installed on the house and face south at an angle of 30 degrees. One of these arrays has twelve 205-W Kyocera panels in series, and the other is made up of twelve 210-Kyocera panels. Each of these arrays feeds into Xantrex/Schneider Electric 3.3-kW inverters. Although there are various shading issues from trees and utility poles and lines, the overall output resembles that which is expected from PVWatts, a solar estimate program. The array cost, which was offset by rebates from the utility company and federal tax credits, was $1.17 per watt. Considering measured system performance, the estimated payback time of the system is 9 years.

  14. Updated Eastern Interconnect Wind Power Output and Forecasts for ERGIS: July 2012

    SciTech Connect (OSTI)

    Pennock, K.

    2012-10-01T23:59:59.000Z

    AWS Truepower, LLC (AWST) was retained by the National Renewable Energy Laboratory (NREL) to update wind resource, plant output, and wind power forecasts originally produced by the Eastern Wind Integration and Transmission Study (EWITS). The new data set was to incorporate AWST's updated 200-m wind speed map, additional tall towers that were not included in the original study, and new turbine power curves. Additionally, a primary objective of this new study was to employ new data synthesis techniques developed for the PJM Renewable Integration Study (PRIS) to eliminate diurnal discontinuities resulting from the assimilation of observations into mesoscale model runs. The updated data set covers the same geographic area, 10-minute time resolution, and 2004?2006 study period for the same onshore and offshore (Great Lakes and Atlantic coast) sites as the original EWITS data set.

  15. Reference values for total blood volume and cardiac output in humans

    SciTech Connect (OSTI)

    Williams, L.R. [Indiana Univ., South Bend, IN (United States). Division of Liberal Arts and Sciences] [Indiana Univ., South Bend, IN (United States). Division of Liberal Arts and Sciences

    1994-09-01T23:59:59.000Z

    Much research has been devoted to measurement of total blood volume (TBV) and cardiac output (CO) in humans but not enough effort has been devoted to collection and reduction of results for the purpose of deriving typical or {open_quotes}reference{close_quotes} values. Identification of normal values for TBV and CO is needed not only for clinical evaluations but also for the development of biokinetic models for ultra-short-lived radionuclides used in nuclear medicine (Leggett and Williams 1989). The purpose of this report is to offer reference values for TBV and CO, along with estimates of the associated uncertainties that arise from intra- and inter-subject variation, errors in measurement techniques, and other sources. Reference values are derived for basal supine CO and TBV in reference adult humans, and differences associated with age, sex, body size, body position, exercise, and other circumstances are discussed.

  16. Fail safe controllable output improved version of the Electromechanical battery

    DOE Patents [OSTI]

    Post, Richard F. (Walnut Creek, CA)

    1999-01-01T23:59:59.000Z

    Mechanical means are provided to control the voltages induced in the windings of a generator/motor. In one embodiment, a lever is used to withdraw or insert the entire stator windings from the cavity where the rotating field exists. In another embodiment, voltage control and/or switching off of the output is achievable with a variable-coupling generator/motor. A stator is made up of two concentric layers of windings, with a larger number of turns on the inner layer of windings than the outer layer of windings. The windings are to be connected in series electrically, that is, their voltages add vectorially. The mechanical arrangement is such that one or both of the windings can be rotated with respect to the other winding about their common central axis. Another improved design for the stator assembly of electromechanical batteries provides knife switch contacts that are in electrical contact with the stator windings. The operation of this embodiment depends on the fact that an abnormally large torque will be exerted on the stator structure during any short-circuit condition.

  17. Fail safe controllable output improved version of the electromechanical battery

    DOE Patents [OSTI]

    Post, R.F.

    1999-01-19T23:59:59.000Z

    Mechanical means are provided to control the voltages induced in the windings of a generator/motor. In one embodiment, a lever is used to withdraw or insert the entire stator windings from the cavity where the rotating field exists. In another embodiment, voltage control and/or switching off of the output is achievable with a variable-coupling generator/motor. A stator is made up of two concentric layers of windings, with a larger number of turns on the inner layer of windings than the outer layer of windings. The windings are to be connected in series electrically, that is, their voltages add vectorially. The mechanical arrangement is such that one or both of the windings can be rotated with respect to the other winding about their common central axis. Another improved design for the stator assembly of electromechanical batteries provides knife switch contacts that are in electrical contact with the stator windings. The operation of this embodiment depends on the fact that an abnormally large torque will be exerted on the stator structure during any short-circuit condition. 4 figs.

  18. Analysis of the AirTouch automatic vehicle location system's ability to locate moving vehicles 

    E-Print Network [OSTI]

    Henry, Tracy Lynn

    1995-01-01T23:59:59.000Z

    Automatic vehicle location systems are becoming more prevalent in diverse transportation applications. Their ability to locate vehicles can assist in locating emergency and public transit vehicles for better real-time dispatching as well...

  19. Analysis of the AirTouch automatic vehicle location system's ability to locate moving vehicles

    E-Print Network [OSTI]

    Henry, Tracy Lynn

    1995-01-01T23:59:59.000Z

    Automatic vehicle location systems are becoming more prevalent in diverse transportation applications. Their ability to locate vehicles can assist in locating emergency and public transit vehicles for better real-time dispatching as well...

  20. Data error detection and device controller failure detection in an input/output system

    SciTech Connect (OSTI)

    Katzman, J.A.; Bartlett, J.F.; Bixler, R.M.; Davidow, W.H.; Despotakis, J.A.; Graziano, P.J.; Green, M.D.; Greig, D.A.; Hayashi, S.J.; Mackie, D.R.

    1987-06-09T23:59:59.000Z

    This patent describes an input/output system for a multiprocessor system of the kind in which separate processor modules are interconnected for parallel processing, each of the processor modules having a central processing unit and a memory, at least some of the processor modules having an input/output channel, the input/output system comprising, at least one device controller for controlling the transfer of data between multiple different ones of the processor modules and a peripheral device.

  1. INTRODUCTION The power output of insect flight muscles is proportional to muscle

    E-Print Network [OSTI]

    Nieh, James

    #12;2239 INTRODUCTION The power output of insect flight muscles is proportional to muscle polaris) to forage in suboptimal thermal conditions (Heinrich, 1993). Recently, bumble bee (Bombus

  2. Fault-Tolerant Resynthesis with Dual-Output LUTs Ju-Yueh Lee1

    E-Print Network [OSTI]

    He, Lei

    utilization rate in real designs motivates us to utilize non-occupied SRAM bits of dual-output LUTs for fault

  3. Final Report - From Measurements to Models: Cross-Comparison of Measured and Simulated Behavioral States of the Atmosphere

    SciTech Connect (OSTI)

    Del Genio, Anthony D; Hoffman, Forrest M; Hargrove, Jr, William W

    2007-10-22T23:59:59.000Z

    The ARM sites and the ARM Mobile Facility (AMF) were constructed to make measurements of the atmosphere and radiation system in order to quantify deficiencies in the simulation of clouds within models and to make improvements in those models. While the measurement infrastructure of ARM is well-developed and a model parameterization testbed capability has been established, additional effort is needed to develop statistical techniques which permit the comparison of simulation output from atmospheric models with actual measurements. Our project establishes a new methodology for objectively comparing ARM measurements to the outputs of leading global climate models and reanalysis data. The quantitative basis for this comparison is provided by a statistical procedure which establishes an exhaustive set of mutually-exclusive, recurring states of the atmosphere from sets of multivariate atmospheric and cloud conditions, and then classifies multivariate measurements or simulation outputs into those states. Whether measurements and models classify the atmosphere into the same states at specific locations through time provides an unequivocal comparison result. Times and locations in both geographic and state space of model-measurement agreement and disagreement will suggest directions for the collection of additional measurements at existing sites, provide insight into the global representativeness of the current ARM sites (suggesting locations and times for use of the AMF), and provide a basis for improvement of models. Two different analyses were conducted: One, using the Parallel Climate Model, focused on an IPCC climate change scenario and clusters that characterize long-term changes in the hydrologic cycle. The other, using the GISS Model E GCM and the ARM Active Remotely Sensed Cloud Layers product, explored current climate cloud regimes in the Tropical West Pacific.

  4. COMMUNICATION Does the Location of a Mutation Determine the Ability

    E-Print Network [OSTI]

    Regan, Lynne

    COMMUNICATION Does the Location of a Mutation Determine the Ability to Form Amyloid Fibrils? Marina by a domain swapping mechanism. Domain swapping is a specific means by which oligomeric proteins are formed that the mutations in our model system facilitate domain swapping as the pathway to amyloid for- mation (Figure 1(b

  5. Structural Location of Disease-associated Single-nucleotide Polymorphisms

    E-Print Network [OSTI]

    Pervouchine, Dmitri D.

    Structural Location of Disease-associated Single-nucleotide Polymorphisms Nathan O. Stitziel1 , Yan-synonymous single-nucleotide polymorphism (nsSNP) of genes introduces amino acid changes to proteins, and plays reserved Keywords: single-nucleotide polymorphism; alpha shape; hidden Markov model; surface pockets

  6. VEHICLE USE RECORD M/Y DEPARTMENT VEHICLE LOCATION

    E-Print Network [OSTI]

    Watson, Craig A.

    VEHICLE USE RECORD M/Y DEPARTMENT VEHICLE LOCATION Date Origin/Destination Purpose Time Out Time) Accuracy of Information (b) Valid Driver's License VEHICLE # TAG # VEHICLE MAKE, MODEL, AND YEAR NOTE: Vehicle logs must be maintained for audit purposes. It is important that all of the required information

  7. HSPICE and WaveView Tutorial Hspice is used for circuit simulation and WaveView is used to view output waveforms.

    E-Print Network [OSTI]

    Mahmoodi, Hamid

    NNano-E Hs Electron Sc San Fr S spice Q Mich Hamid nics & C chool of rancisco San Fra Spr Quick By be downloaded from the following website: http://ptm.asu.edu/ Click on the latest models and download 16nm PTM "hspice job aborted". In that case, please open the output file (inv.out) and search for error to see

  8. Output correction factors for nine small field detectors in 6 MV radiation therapy photon beams: A PENELOPE Monte Carlo study

    SciTech Connect (OSTI)

    Benmakhlouf, Hamza, E-mail: hamza.benmakhlouf@karolinska.se [Department of Medical Physics, Karolinska University Hospital, SE-171 76 Stockholm, Sweden, and Department of Physics, Medical Radiation Physics, Stockholm University and Karolinska Institute, SE-171 76 Stockholm (Sweden)] [Department of Medical Physics, Karolinska University Hospital, SE-171 76 Stockholm, Sweden, and Department of Physics, Medical Radiation Physics, Stockholm University and Karolinska Institute, SE-171 76 Stockholm (Sweden); Sempau, Josep [Institut de Tècniques Energètiques, Universitat Politècnica de Catalunya, Diagonal 647, E-08028, Barcelona (Spain)] [Institut de Tècniques Energètiques, Universitat Politècnica de Catalunya, Diagonal 647, E-08028, Barcelona (Spain); Andreo, Pedro [Department of Physics, Medical Radiation Physics, Stockholm University and Karolinska Institute, SE-171 76 Stockholm (Sweden)] [Department of Physics, Medical Radiation Physics, Stockholm University and Karolinska Institute, SE-171 76 Stockholm (Sweden)

    2014-04-15T23:59:59.000Z

    Purpose: To determine detector-specific output correction factors,k{sub Q} {sub c{sub l{sub i{sub n}}}} {sub ,Q} {sub m{sub s{sub r}}} {sup f{sub {sup {sub c}{sub l}{sub i}{sub n}{sub {sup ,f{sub {sup {sub m}{sub s}{sub r}{sub ,}}}}}}}} in 6 MV small photon beams for air and liquid ionization chambers, silicon diodes, and diamond detectors from two manufacturers. Methods: Field output factors, defined according to the international formalism published byAlfonso et al. [Med. Phys. 35, 5179–5186 (2008)], relate the dosimetry of small photon beams to that of the machine-specific reference field; they include a correction to measured ratios of detector readings, conventionally used as output factors in broad beams. Output correction factors were calculated with the PENELOPE Monte Carlo (MC) system with a statistical uncertainty (type-A) of 0.15% or lower. The geometries of the detectors were coded using blueprints provided by the manufacturers, and phase-space files for field sizes between 0.5 × 0.5 cm{sup 2} and 10 × 10 cm{sup 2} from a Varian Clinac iX 6 MV linac used as sources. The output correction factors were determined scoring the absorbed dose within a detector and to a small water volume in the absence of the detector, both at a depth of 10 cm, for each small field and for the reference beam of 10 × 10 cm{sup 2}. Results: The Monte Carlo calculated output correction factors for the liquid ionization chamber and the diamond detector were within about ±1% of unity even for the smallest field sizes. Corrections were found to be significant for small air ionization chambers due to their cavity dimensions, as expected. The correction factors for silicon diodes varied with the detector type (shielded or unshielded), confirming the findings by other authors; different corrections for the detectors from the two manufacturers were obtained. The differences in the calculated factors for the various detectors were analyzed thoroughly and whenever possible the results were compared to published data, often calculated for different accelerators and using the EGSnrc MC system. The differences were used to estimate a type-B uncertainty for the correction factors. Together with the type-A uncertainty from the Monte Carlo calculations, an estimation of the combined standard uncertainty was made, assigned to the mean correction factors from various estimates. Conclusions: The present work provides a consistent and specific set of data for the output correction factors of a broad set of detectors in a Varian Clinac iX 6 MV accelerator and contributes to improving the understanding of the physics of small photon beams. The correction factors cannot in general be neglected for any detector and, as expected, their magnitude increases with decreasing field size. Due to the reduced number of clinical accelerator types currently available, it is suggested that detector output correction factors be given specifically for linac models and field sizes, rather than for a beam quality specifier that necessarily varies with the accelerator type and field size due to the different electron spot dimensions and photon collimation systems used by each accelerator model.

  9. ARM: ARSCL: multiple outputs from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Coulter, Richard; Widener, Kevin; Bharadwaj, Nitin; Johnson, Karen; Martin, Timothy

    ARSCL: multiple outputs from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

  10. The effect of imbalance distribution and measurement locations on critical speeds in a turboprop engine rotor

    E-Print Network [OSTI]

    Marin, Manuel

    1996-01-01T23:59:59.000Z

    . This study examines the influence of imbalance distribution and vibration measurement location on critical speeds for a model turboprop engine rotor. Imbalance response measurements are presented for a full scale model mounted in rolling bearings with squeeze...

  11. Locational-based Coupling of Electricity Markets: Benefits from Coordinating Unit Commitment and Balancing Markets

    E-Print Network [OSTI]

    van der Weijde, Adriaan Hendrik; Hobbs, Benjamin F.

    We formulate a series of stochastic models for committing and dispatching electric generators subject to transmission limits. The models are used to estimate the benefits of electricity locational marginal pricing (LMP) that arise from better...

  12. Estimating Solar PV Output Using Modern Space/Time Geostatistics (Presentation)

    SciTech Connect (OSTI)

    Lee, S. J.; George, R.; Bush, B.

    2009-04-29T23:59:59.000Z

    This presentation describes a project that uses mapping techniques to predict solar output at subhourly resolution at any spatial point, develop a methodology that is applicable to natural resources in general, and demonstrate capability of geostatistical techniques to predict the output of a potential solar plant.

  13. Experimental Results on Multiple-Input Single-Output (MISO) Time Reversal for UWB

    E-Print Network [OSTI]

    Qiu, Robert Caiming

    Experimental Results on Multiple-Input Single-Output (MISO) Time Reversal for UWB Systems with multiple-input single- output (MISO) antennas over ultra-wideband (UWB) channels. In particular, temporal and spatial focusing as well as array gain are studied based on a (4 × 1) MISO scheme in an office environment

  14. Mechanism of low-frequency fluctuations of the output power of gas-discharge lasers

    SciTech Connect (OSTI)

    Melekhin, G.V.; Stepanov, V.A.; Chirkin, M.V.

    1984-08-01T23:59:59.000Z

    Fluctuations of the output power of gas-discharge lasers arising on account of the random character of the processes of ionization and electron-impact excitation of atomic levels are described. Low-frequency fluctuations of the output power of a cataphoretic He--Cd laser are examined as an example.

  15. Optimizing the Output of a Human-Powered Energy Harvesting System with Miniaturization and Integrated Control

    E-Print Network [OSTI]

    Potkonjak, Miodrag

    1 Optimizing the Output of a Human-Powered Energy Harvesting System with Miniaturization mechanical energy from human foot-strikes and explore its configuration and control towards optimized energy output. Dielectric Elastomers (DEs) are high-energy density, soft, rubber-like material

  16. Non-Additivity of Minimum Output p-$\\mathbf{R\\acute{e}nyi}$ Entropy

    E-Print Network [OSTI]

    Nengkun Yu; Mingsheng Ying

    2012-12-24T23:59:59.000Z

    Hastings disproved additivity conjecture for minimum output entropy by using random unitary channels. In this note, we employ his approach to show that minimum output $p-$R\\'{e}nyi entropy is non-additive for $p\\in(0,p_0)\\cup(1-p_0,1)$ where $p_0\\approx 0.2855$.

  17. Generating Isolated Outputs in a Multilevel Modular Capacitor Clamped DC-DC Converter

    E-Print Network [OSTI]

    Tolbert, Leon M.

    balance between the fuel cell and any energy storage inside the vehicle, and provides continuous power) for Hybrid Electric and Fuel Cell Vehicles Faisal H. Khan1 , Leon M. Tolbert2 1 Electric Power Research transformers to generate isolated ac outputs. These isolated outputs can be rectified and filtered to obtain

  18. Selection of Output Function in Nonlinear Feedback Linearizing Excitation Control for Power Systems

    E-Print Network [OSTI]

    Pota, Himanshu Roy

    Selection of Output Function in Nonlinear Feedback Linearizing Excitation Control for Power Systems for power systems. Depending on the relative degree of the system which depends on the output function Power systems are large, complex, and highly nonlinear interconnected dynamic systems. The power demand

  19. Fine-grained Photovoltaic Output Prediction using a Bayesian Ensemble Prithwish Chakraborty1,2

    E-Print Network [OSTI]

    Ramakrishnan, Naren

    generation is increasingly reliant on renewable power sources, e.g., solar (pho- tovoltaic or PV) and wind Increasingly, local and distributed power generation e.g., through solar (photovoltaic or PV), wind, fuel cells and intermittent in their energy output, which makes integration with the power grid challenging. PV output

  20. Helicopter magnetic survey conducted to locate wells

    SciTech Connect (OSTI)

    Veloski, G.A.; Hammack, R.W.; Stamp, V. (Rocky Mountain Oilfield Testing Center); Hall, R. (Rocky Mountain Oilfield Testing Center); Colina, K. (Rocky Mountain Oilfield Testing Center)

    2008-07-01T23:59:59.000Z

    A helicopter magnetic survey was conducted in August 2007 over 15.6 sq mi at the Naval Petroleum Reserve No. 3’s (NPR-3) Teapot Dome Field near Casper, Wyoming. The survey’s purpose was to accurately locate wells drilled there during more than 90 years of continuous oilfield operation. The survey was conducted at low altitude and with closely spaced flight lines to improve the detection of wells with weak magnetic response and to increase the resolution of closely spaced wells. The survey was in preparation for a planned CO2 flood for EOR, which requires a complete well inventory with accurate locations for all existing wells. The magnetic survey was intended to locate wells missing from the well database and to provide accurate locations for all wells. The ability of the helicopter magnetic survey to accurately locate wells was accomplished by comparing airborne well picks with well locations from an intense ground search of a small test area.

  1. Location theory and the location of industry along an interstate highway

    E-Print Network [OSTI]

    Miller, James Patterson

    1965-01-01T23:59:59.000Z

    to determine the significance of these locational factors among plants with different characteristics that have located in certain localities should provide pertinent information with both practical and theoretical implications. Since 1956, approximately 64... Summary of Plant Location Theory Cost Fac'tots . . . . . . . . . . . . . ~ The Importance of 'the Demand Factor Greenhut's General Theory of Plant Location and the Intangible Factor Location Factors as Revealed by Empirical Study Greenhut's Case...

  2. Method for leveling the power output of an electromechanical battery as a function of speed

    DOE Patents [OSTI]

    Post, Richard F. (Walnut Creek, CA)

    1999-01-01T23:59:59.000Z

    The invention is a method of leveling the power output of an electromechanical battery during its discharge, while at the same time maximizing its power output into a given load. The method employs the concept of series resonance, employing a capacitor the parameters of which are chosen optimally to achieve the desired near-flatness of power output over any chosen charged-discharged speed ratio. Capacitors are inserted in series with each phase of the windings to introduce capacitative reactances that act to compensate the inductive reactance of these windings. This compensating effect both increases the power that can be drawn from the generator before inductive voltage drops in the windings become dominant and acts to flatten the power output over a chosen speed range. The values of the capacitors are chosen so as to optimally flatten the output of the generator over the chosen speed range.

  3. Method for leveling the power output of an electromechanical battery as a function of speed

    DOE Patents [OSTI]

    Post, R.F.

    1999-03-16T23:59:59.000Z

    The invention is a method of leveling the power output of an electromechanical battery during its discharge, while at the same time maximizing its power output into a given load. The method employs the concept of series resonance, employing a capacitor the parameters of which are chosen optimally to achieve the desired near-flatness of power output over any chosen charged-discharged speed ratio. Capacitors are inserted in series with each phase of the windings to introduce capacitative reactances that act to compensate the inductive reactance of these windings. This compensating effect both increases the power that can be drawn from the generator before inductive voltage drops in the windings become dominant and acts to flatten the power output over a chosen speed range. The values of the capacitors are chosen so as to optimally flatten the output of the generator over the chosen speed range. 3 figs.

  4. Regenerator Location Problem in Flexible Optical Networks

    E-Print Network [OSTI]

    BARIS YILDIZ

    2014-11-22T23:59:59.000Z

    Nov 22, 2014 ... Abstract: In this study we introduce the regenerator location problem in flexible optical networks (RLP-FON). With a given traffic demand, ...

  5. Fault Locating, Prediction and Protection (FLPPS)

    SciTech Connect (OSTI)

    Yinger, Robert, J.; Venkata, S., S.; Centeno, Virgilio

    2010-09-30T23:59:59.000Z

    One of the main objectives of this DOE-sponsored project was to reduce customer outage time. Fault location, prediction, and protection are the most important aspects of fault management for the reduction of outage time. In the past most of the research and development on power system faults in these areas has focused on transmission systems, and it is not until recently with deregulation and competition that research on power system faults has begun to focus on the unique aspects of distribution systems. This project was planned with three Phases, approximately one year per phase. The first phase of the project involved an assessment of the state-of-the-art in fault location, prediction, and detection as well as the design, lab testing, and field installation of the advanced protection system on the SCE Circuit of the Future located north of San Bernardino, CA. The new feeder automation scheme, with vacuum fault interrupters, will limit the number of customers affected by the fault. Depending on the fault location, the substation breaker might not even trip. Through the use of fast communications (fiber) the fault locations can be determined and the proper fault interrupting switches opened automatically. With knowledge of circuit loadings at the time of the fault, ties to other circuits can be closed automatically to restore all customers except the faulted section. This new automation scheme limits outage time and increases reliability for customers. The second phase of the project involved the selection, modeling, testing and installation of a fault current limiter on the Circuit of the Future. While this project did not pay for the installation and testing of the fault current limiter, it did perform the evaluation of the fault current limiter and its impacts on the protection system of the Circuit of the Future. After investigation of several fault current limiters, the Zenergy superconducting, saturable core fault current limiter was selected for installation. Because of some testing problems with the Zenergy fault current limiter, installation was delayed until early 2009 with it being put into operation on March 6, 2009. A malfunction of the FCL controller caused the DC power supply to the superconducting magnet to be turned off. This inserted the FCL impedance into the circuit while it was in normal operation causing a voltage resonance condition. While these voltages never reached a point where damage would occur on customer equipment, steps were taken to insure this would not happen again. The FCL was reenergized with load on December 18, 2009. A fault was experienced on the circuit with the FCL in operation on January 14, 2010. The FCL operated properly and reduced the fault current by about 8%, what was expected from tests and modeling. As of the end of the project, the FCL was still in operation on the circuit. The third phase of the project involved the exploration of several advanced protection ideas that might be at a state where they could be applied to the Circuit of the Future and elsewhere in the SCE electrical system. Based on the work done as part of the literature review and survey, as well as a number of internal meetings with engineering staff at SCE, a number of ideas were compiled. These ideas were then evaluated for applicability and ability to be applied on the Circuit of the Future in the time remaining for the project. Some of these basic ideas were implemented on the circuit including measurement of power quality before and after the FCL. It was also decided that we would take what was learned as part of the Circuit of the Future work and extend it to the next generation circuit protection for SCE. Also at this time, SCE put in a proposal to the DOE for the Irvine Smart Grid Demonstration using ARRA funding. SCE was successful in obtaining funding for this proposal, so it was felt that exploration of new protection schemes for this Irvine Smart Grid Demonstration would be a good use of the project resources. With this in mind, a protection system that uses fault interrupting switches, hi

  6. RECYCLING PROGRAM TYPE LOCATION ALLOWED NOT ALLOWED

    E-Print Network [OSTI]

    Miami, University of

    RECYCLING PROGRAM TYPE LOCATION ALLOWED NOT ALLOWED Batteries, toner, ink cartridges & cell phones and recycling is an important part of that effort. Below is a guide to on-campus recycling at RSMAS: Visit http://www.rsmas.miami.edu/msgso/ for map of recycling bin locations. NOTE: This is not an exhaustive list. If unauthorized items are found

  7. Optimized Fault Location Final Project Report

    E-Print Network [OSTI]

    Engineering Research Center Optimized Fault Location Concurrent Technologies Corporation Final Project Report by the Concurrent Technologies Corporation (CTC) and the Power Systems Engineering Research Center (PSERC). NeitherOptimized Fault Location Final Project Report Power Systems Engineering Research Center A National

  8. Location Privacy and the Personal Distributed Environment

    E-Print Network [OSTI]

    Atkinson, Robert C

    Location Privacy and the Personal Distributed Environment Robert C Atkinson, Swee Keow Goo, James-- The Personal Distributed Environment is a new concept being developed within the Mobile VCE Core 3 research, wherever their location: ubiquitous access. Devices are co-ordinated by Device Management Entities (DMEs

  9. Finding the quantum thermoelectric with maximal efficiency and minimal entropy production at given power output

    E-Print Network [OSTI]

    Robert S. Whitney

    2015-03-16T23:59:59.000Z

    We investigate the nonlinear scattering theory for quantum systems with strong Seebeck and Peltier effects, and consider their use as heat-engines and refrigerators with finite power outputs. This article gives detailed derivations of the results summarized in Phys. Rev. Lett. 112, 130601 (2014). It shows how to use the scattering theory to find (i) the quantum thermoelectric with maximum possible power output, and (ii) the quantum thermoelectric with maximum efficiency at given power output. The latter corresponds to a minimal entropy production at that power output. These quantities are of quantum origin since they depend on system size over electronic wavelength, and so have no analogue in classical thermodynamics. The maximal efficiency coincides with Carnot efficiency at zero power output, but decreases with increasing power output. This gives a fundamental lower bound on entropy production, which means that reversibility (in the thermodynamic sense) is impossible for finite power output. The suppression of efficiency by (nonlinear) phonon and photon effects is addressed in detail; when these effects are strong, maximum efficiency coincides with maximum power. Finally, we show in particular limits (typically without magnetic fields) that relaxation within the quantum system does not allow the system to exceed the bounds derived for relaxation-free systems, however, a general proof of this remains elusive.

  10. Numerical simulations of output pulse extraction from a high-power microwave compressor with a plasma switch

    SciTech Connect (OSTI)

    Shlapakovski, Anatoli; Beilin, Leonid; Bliokh, Yuri; Donskoy, Moshe; Krasik, Yakov E. [Physics Department, Technion, Haifa 32000 (Israel); Hadas, Yoav [Department of Applied Physics, Rafael, PO Box 2250, Haifa 31021 (Israel); Schamiloglu, Edl [Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico 87131 (United States)

    2014-05-07T23:59:59.000Z

    Numerical simulations of the process of electromagnetic energy release from a high-power microwave pulse compressor comprising a gas-filled cavity and interference switch were carried out. A microwave plasma discharge in a rectangular waveguide H-plane tee was modeled with the use of the fully electromagnetic particle-in-cell code MAGIC. The gas ionization, plasma evolution, and interaction with RF fields accumulated within the compressor were simulated using different approaches provided by the MAGIC code: particle-in-cell approach accounting for electron-neutral collisions, gas conductivity model based on the concept of mobility, and hybrid modeling. The dependences of the microwave output pulse peak power and waveform on parameters that can be controlled in experiments, such as an external ionization rate, RF field amplitude, and background gas pressure, were investigated.

  11. The Construction of Locative Situations: Locative Media and the Situationist International, Recuperation or Redux?

    E-Print Network [OSTI]

    McGarrigle, Conor

    2009-01-01T23:59:59.000Z

    closely aligned to the SI's construction of situations. ThisG (1957) Report on the Construction of Situations and on theThe Construction of Locative Situations: Locative Media and

  12. SFSU Building Coordinators List College or Administrative Unit Location(s)

    E-Print Network [OSTI]

    SFSU Building Coordinators List College or Administrative Unit Location(s) Building Coordinator81193 cathym@sfsu.edu GYM 102B Student Services Building SSB Mirel Tikkanen x53566 mtikkane@sfsu.edu SSB

  13. Optimization of the output and efficiency of a high power cascaded arc hydrogen plasma source

    SciTech Connect (OSTI)

    Vijvers, W. A. J.; Gils, C. A. J. van; Goedheer, W. J.; Meiden, H. J. van der; Veremiyenko, V. P.; Westerhout, J.; Lopes Cardozo, N. J.; Rooij, G. J. van [FOM-Institute for Plasma Physics Rijnhuizen, Association EURATOM-FOM, Trilateral Euregio Cluster, P.O. Box 1207, 3430 BE Nieuwegein (Netherlands); Schram, D. C. [Department of Applied Physics, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands)

    2008-09-15T23:59:59.000Z

    The operation of a cascaded arc hydrogen plasma source was experimentally investigated to provide an empirical basis for the scaling of this source to higher plasma fluxes and efficiencies. The flux and efficiency were determined as a function of the input power, discharge channel diameter, and hydrogen gas flow rate. Measurements of the pressure in the arc channel show that the flow is well described by Poiseuille flow and that the effective heavy particle temperature is approximately 0.8 eV. Interpretation of the measured I-V data in terms of a one-parameter model shows that the plasma production is proportional to the input power, to the square root of the hydrogen flow rate, and is independent of the channel diameter. The observed scaling shows that the dominant power loss mechanism inside the arc channel is one that scales with the effective volume of the plasma in the discharge channel. Measurements on the plasma output with Thomson scattering confirm the linear dependence of the plasma production on the input power. Extrapolation of these results shows that (without a magnetic field) an improvement in the plasma production by a factor of 10 over where it was in van Rooij et al. [Appl. Phys. Lett. 90, 121501 (2007)] should be possible.

  14. Design of Dual-Output Alternators With Switched-Mode Rectification

    E-Print Network [OSTI]

    Hassan, Gimba

    The push to introduce dual-voltage (42 V/14 V) automotive electrical systems necessitates power generation solutions capable of supplying power to multiple outputs. A number of approaches for implementing dual-voltage ...

  15. Limitation of the output power of cw electric-discharge CO{sub 2} lasers

    SciTech Connect (OSTI)

    Nevdakh, Vladimir V [B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk (Belarus)

    1999-04-30T23:59:59.000Z

    The output power of a sealed-off tunable cw CO{sub 2} laser was optimised. The dependences of the small-signal gain for the 10P(20) line and of the output powers for different transmittances of the cavity on the discharge current were determined. The distributed loss coefficient and the saturation parameter were measured. The saturation parameter increased continuously with increase in the discharge current, leading to a mismatch between the output power and gain maxima. It was established that the principal factor limiting the output power of cw electric-discharge CO{sub 2} lasers is not an increase in the temperature of the active medium but the dissociation of CO{sub 2} molecules. When the latter is minimised in order to achieve the maximum laser power, low gas temperatures are not required. (lasers)

  16. Output dominance as a predictor of humor content in verbal productions

    E-Print Network [OSTI]

    Hull, Rachel Gayle

    2000-01-01T23:59:59.000Z

    -dominance-ordered feature lists generated for each of the concepts. It was hypothesized that juxtapositions judged funny would rely more often on properties with significantly different output dominance scores per concept, while those judged not funny would involve fewer...

  17. Examining the Variability of Wind Power Output in the Regulation Time Frame: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Shedd, S.; Florita, A.

    2012-08-01T23:59:59.000Z

    This work examines the distribution of changes in wind power for different time scales in the regulation time frame as well as the correlation of changes in power output for individual wind turbines in a wind plant.

  18. Motor output in a bimanual continuation-tapping task is independent of visual cues 

    E-Print Network [OSTI]

    Miller, Louisa

    2009-07-03T23:59:59.000Z

    Presented are two studies examining the role of vision on motor output in the continuation-tapping paradigm (Stevens, 1886). The role of vision is measured by comparisons of motor performance under three visual feedback conditions: freeview...

  19. Multilevel Cascade H-bridge Inverter DC Voltage Estimation Through Output Voltage Sensing

    E-Print Network [OSTI]

    Tolbert, Leon M.

    system as the inverter power supply may vary. For example, interface of solar panels or fuel cell. The output voltage is then processed by a DSP unit that uses the signals that command the switches

  20. Primate Motor Cortex: Individual and Ensemble Neuron-Muscle Output Relationships

    E-Print Network [OSTI]

    Griffin, Darcy Michelle

    2008-07-30T23:59:59.000Z

    The specific aims of this study were to: 1) investigate the encoding of forelimb muscle activity timing and magnitude by corticomotoneuronal (CM) cells, 2) test the stability of primary motor cortex (M1) output to forelimb ...

  1. Augmentation of Power Output of Axisymmetric Ducted Wind Turbines by Porous Trailing Edge Disks

    E-Print Network [OSTI]

    widnall, sheila

    2014-06-30T23:59:59.000Z

    This paper presents analytical and experimental results that demonstrated that the power output from a ducted wind turbine can be dramatically increased by the addition of a trailing edge device such as a porous disk. In ...

  2. Input-Output as a Method of Evaluahon of the Economic Impact of Water Resources Development

    E-Print Network [OSTI]

    Canion, R. L.; Trock, W. L.

    In this report the results of a study of the use of input-output analysis to evaluate the economic impact of water resources development are presented. Blackburn Crossing reservoir on the Upper Neches river was the subject development...

  3. Code design for multiple-input multiple-output broadcast channels

    E-Print Network [OSTI]

    Uppal, Momin Ayub

    2009-06-02T23:59:59.000Z

    Recent information theoretical results indicate that dirty-paper coding (DPC) achieves the entire capacity region of the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). This thesis presents practical code designs for Gaussian...

  4. Concatenated codes for the multiple-input multiple-output quasi-static fading channel

    E-Print Network [OSTI]

    Gulati, Vivek

    2005-02-17T23:59:59.000Z

    CONCATENATED CODES FOR THE MULTIPLE-INPUT MULTIPLE-OUTPUT QUASI-STATIC FADING CHANNEL A Dissertation by VIVEK GULATI Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree... of DOCTOR OF PHILOSOPHY December 2004 Major Subject: Electrical Engineering CONCATENATED CODES FOR THE MULTIPLE-INPUT MULTIPLE-OUTPUT QUASI-STATIC FADING CHANNEL A Dissertation by VIVEK GULATI Submitted to Texas A&M University in partial fulfillment...

  5. Exploring the circadian outputs and function of HPT-1 in Neurospora crassa

    E-Print Network [OSTI]

    Vickery, Justin Wayde

    2013-09-28T23:59:59.000Z

    EXPLORING THE CIRCADIAN OUTPUTS AND FUNCTIONS OF HTP-1 IN NEUROSPORA CRASSA An Undergraduate Research Scholars Thesis by JUSTIN WAYDE VICKERY Submitted to Honors and Undergraduate Research Texas A&M University in partial fulfillment... ......................................................................................................................... 25 1 ABSTRACT Exploring the circadian outputs and functions of HPT-1 in N. crassa. (May 2014) Justin Wayde Vickery Department of Biology Texas A&M University Research Advisor: Dr. Deborah Bell-Pedersen Department of Biology...

  6. Water Power Calculator Temperature and Analog Input/Output Module Ambient Temperature Testing

    SciTech Connect (OSTI)

    Mark D. McKay

    2011-02-01T23:59:59.000Z

    Water Power Calculator Temperature and Analog input/output Module Ambient Temperature Testing A series of three ambient temperature tests were conducted for the Water Power Calculator development using the INL Calibration Laboratory’s Tenney Environmental Chamber. The ambient temperature test results demonstrate that the Moore Industries Temperature Input Modules, Analog Input Module and Analog Output Module, ambient temperature response meet or exceed the manufactures specifications

  7. THE PLANAR HUB LOCATION PROBLEM: A PROBABILISTIC ...

    E-Print Network [OSTI]

    2012-11-21T23:59:59.000Z

    Nov 5, 2012 ... Aykin and Brown, [4]. ...... [8] J.F. Campbell, Integer programming formulations of discrete hub location problems, European J. of O.R.. 72(1994) ...

  8. Developing a theory of nightclub location choice

    E-Print Network [OSTI]

    Crim, Stephen J. (Stephen Johnson)

    2008-01-01T23:59:59.000Z

    This work is an investigation of the factors that influence where nightclubs locate within a city. Nightclubs, like other social spaces, provide important social and economic benefits in the urban environment. As amenities, ...

  9. Techniques for Mobile Location Estimation in UMTS 

    E-Print Network [OSTI]

    Thomas, Nicholas J

    The subject area of this thesis is the locating of mobile users using the future 3rd generation spread spectrum communication system UMTS. The motivation behind this work is twofold: firstly the United States Federal ...

  10. Finite Elements in Analysis and Design 43 (2007) 397410 www.elsevier.com/locate/finel

    E-Print Network [OSTI]

    Ghosh, Somnath

    2007-01-01T23:59:59.000Z

    Finite Elements in Analysis and Design 43 (2007) 397­410 www.elsevier.com/locate/finel Modeling introduces an extended Voronoi cell finite element model (X-VCFEM) for modeling the initiation: The extended Voronoi cell finite element method (X-VCFEM); Cohesive zone models; Interfacial debonding; Matrix

  11. Driver expectancy in locating automotive controls 

    E-Print Network [OSTI]

    Francis, Dawn Suzette

    1990-01-01T23:59:59.000Z

    DRIVER EXPECTANCY IN LOCATING AUTOMOTIVE CONTROLS A Thesis by DAWN SUZETTE FRANCIS Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May 1990... Major Subject: Industrial Engineering DRIVER EXPECTANCY IN LOCATING AUTOMOTIVE CONTROLS A Thesis by DAWN SUZETTE FRANCIS Approved as to style and content by: R. Dale Huchi son (Chair of Committee) Rodger . . ppa (Member) Waymon L ohnston (M er...

  12. Optimization of the LCLS X-ray FEL output performance in the presence of strong undulator wakefields

    E-Print Network [OSTI]

    Reiche, S; Emma, P; Fawley, W M; Huang, Z; Nuhn, H D; Stupakov, G V

    2005-01-01T23:59:59.000Z

    Optimization of the LCLS X-ray FEL output performance in the presence of strong undulator wakefields

  13. Output Harmonic Termination Techniques for AlGaN/GaN HEMT Power Amplifiers Using Active Integrated Antenna Approach

    E-Print Network [OSTI]

    Itoh, Tatsuo

    Output Harmonic Termination Techniques for AlGaN/GaN HEMT Power Amplifiers Using Active Integrated 1200, Los Angeles, CA 90045 Abstract -- In this paper, effects of output harmonic terminations on PAE termination, we observe a substantial increase in PAE and output power. Further, we demonstrate the high

  14. U.S. Motor Vehicle Output and Other GDP, 1968-2007 Danilo J. Santini, Ph. D.

    E-Print Network [OSTI]

    Kemner, Ken

    U.S. Motor Vehicle Output and Other GDP, 1968-2007 Danilo J. Santini, Ph. D. Senior Economist, and perform publicly and display publicly, by or on behalf of the Government. 1 #12;U.S. Motor Vehicle Output of motor vehicle output" on the rest of the economy over the period 1968-2007. We statistically assess

  15. Modelling Dynamic Constraints in Electricity Markets and the Costs of Uncertain Wind Output

    E-Print Network [OSTI]

    Musgens, Felix; Neuhoff, Karsten

    2006-03-14T23:59:59.000Z

    generation to analyse the effects of uncertainty. We find that the costs of balancing wind power were relatively low in the Ger- man system in 2003. They could be reduced even further when a better forecast becomes available, either by implementing a later... . This was to be expected, as start-up and shut-down decisions are the key variables used to balance wind power’s volatility. On the other hand, we find that the increase in generation costs is marginal. This is also plausible as average wind generation is held constant...

  16. Scaling analyses of forcings and outputs of a simplified Last1 Millennium climate model2

    E-Print Network [OSTI]

    Lovejoy, Shaun

    with the Detrended Fluctuation Analysis method as 34 well as the effect of certain data pretreatments. 35 This suggests that at centennial and longer scales, new slow climate

  17. Artificial neural networks for input-output dynamic modeling of nonlinear processes

    E-Print Network [OSTI]

    Sarimveis, Haralambos

    1992-01-01T23:59:59.000Z

    netivork approach. ]v ACKNOWLEDGEMENTS I woukl lil&e t(& thank Dr. Michael;Mike&laou, ehairn)an of nry gra(h(ate eonuuittee, for &onc e&ving my p&&&jest and giving the assists(&r( nestle(l to n&ake it possible. His guidauce anal support, will always 1...&e appr&'cist('d I also v ish to thank D(s A. Ted watson au&1 Alexander G. Parlos for their valuable eouuuents ou u&y rcseareh anal fo( ac&viz&g on n)v &omm&ttee. Tha?ks to nry frie&r&ls here at Texas Ahi&I, wh(& we&e instrmuental iu the eon...

  18. Dissemination of Climate Model Output to the Public and Commercial Sector

    SciTech Connect (OSTI)

    Robert Stockwell, PhD

    2010-09-23T23:59:59.000Z

    Climate is defined by the Glossary of Meteorology as the mean of atmospheric variables over a period of time ranging from as short as a few months to multiple years and longer. Although the term climate is often used to refer to long-term weather statistics, the broader definition of climate is the time evolution of a system consisting of the atmosphere, hydrosphere, lithosphere, and biosphere. Physical, chemical, and biological processes are involved in interactions among the components of the climate system. Vegetation, soil moisture, and glaciers are part of the climate system in addition to the usually considered temperature and precipitation (Pielke, 2008). Climate change refers to any systematic change in the long-term statistics of climate elements (such as temperature, pressure, or winds) sustained over several decades or longer. Climate change can be initiated by external forces, such as cyclical variations in the Earth's solar orbit that are thought to have caused glacial and interglacial periods within the last 2 million years (Milankovitch, 1941). However, a linear response to astronomical forcing does not explain many other observed glacial and interglacial cycles (Petit et al., 1999). It is now understood that climate is influenced by the interaction of solar radiation with atmospheric greenhouse gasses (e.g., carbon dioxide, chlorofluorocarbons, methane, nitrous oxide, etc.), aerosols (airborne particles), and Earth's surface. A significant aspect of climate are the interannual cycles, such as the El Nino La Nina cycle which profoundly affects the weather in North America but is outside the scope of weather forecasts. Some of the most significant advances in understanding climate change have evolved from the recognition of the influence of ocean circulations upon the atmosphere (IPCC, 2007). Human activity can affect the climate system through increasing concentrations of atmospheric greenhouse gases, air pollution, increasing concentrations of aerosol, and land alteration. A particular concern is that atmospheric levels of CO{sub 2} may be rising faster than at any time in Earth's history, except possibly following rare events like impacts from large extraterrestrial objects (AMS, 2007). Atmospheric CO{sub 2} concentrations have increased since the mid-1700s through fossil fuel burning and changes in land use, with more than 80% of this increase occurring since 1900. The increased levels of CO{sub 2} will remain in the atmosphere for hundreds to thousands of years. The complexity of the climate system makes it difficult to predict specific aspects of human-induced climate change, such as exactly how and where changes will occur, and their magnitude. The Intergovernmental Panel for Climate Change (IPCC) was established by World Meteorological Organization (WMO) and the United Nations in 1988. The IPCC was tasked with assessing the scientific, technical and socioeconomic information needed to understand the risk of human-induced climate change, its observed and projected impacts, and options for adaptation and mitigation. The IPCC concluded in its Fourth Assessment Report (AR4) that warming of the climate system is unequivocal, and that most of the observed increase in globally averaged temperatures since the mid-20th century is very likely due to the observed increased in anthropogenic greenhouse gas concentrations (IPCC, 2007).

  19. Locating PHEV exchange stations in V2G

    SciTech Connect (OSTI)

    Pan, Feng [Los Alamos National Laboratory; Bent, Russell [Los Alamos National Laboratory; Berscheid, Alan [Los Alamos National Laboratory; Izraelevitz, David [Los Alamos National Laboratory

    2010-01-01T23:59:59.000Z

    Plug-in hybrid electric vehicle (PREV) is an environment friendly modem transportation method and has been rapidly penetrate the transportation system. Renewable energy is another contributor to clean power but the associated intermittence increases the uncertainty in power generation. As a foreseen benefit of a vchicle-to-grid (V2G) system, PREV supporting infrastructures like battery exchange stations can provide battery service to PREV customers as well as being plugged into a power grid as energy sources and stabilizer. The locations of exchange stations are important for these two objectives under constraints from both ,transportation system and power grid. To model this location problem and to understand and analyze the benefit of a V2G system, we develop a two-stage stochastic program to optimally locate the stations prior to the realizations of battery demands, loads, and generation capacity of renewable power sources. Based on this model, we use two data sets to construct the V2G systems and test the benefit and the performance of these systems.

  20. Reconstructing Spatial Distributions from Anonymized Locations

    SciTech Connect (OSTI)

    Horey, James L [ORNL] [ORNL; Forrest, Stephanie [University of New Mexico, Albuquerque] [University of New Mexico, Albuquerque; Groat, Michael [University of New Mexico, Albuquerque] [University of New Mexico, Albuquerque

    2012-01-01T23:59:59.000Z

    Devices such as mobile phones, tablets, and sensors are often equipped with GPS that accurately report a person's location. Combined with wireless communication, these devices enable a wide range of new social tools and applications. These same qualities, however, leave location-aware applications vulnerable to privacy violations. This paper introduces the Negative Quad Tree, a privacy protection method for location aware applications. The method is broadly applicable to applications that use spatial density information, such as social applications that measure the popularity of social venues. The method employs a simple anonymization algorithm running on mobile devices, and a more complex reconstruction algorithm on a central server. This strategy is well suited to low-powered mobile devices. The paper analyzes the accuracy of the reconstruction method in a variety of simulated and real-world settings and demonstrates that the method is accurate enough to be used in many real-world scenarios.

  1. Location theory and the location of industry along an interstate highway 

    E-Print Network [OSTI]

    Miller, James Patterson

    1965-01-01T23:59:59.000Z

    a greater gamble. This sect. ion has been devoted to s review of the fundamental factors underlying all plant location ss recognised in location theory. The next section will review some recent. empirical attempts to determine the actual... for this thesis was possible through the assistance provided )ointly by the Texas Highway Department and the Bureau of Public Roads. i. v TABLE OF CONTENTS Chapter Page INTRODUCTION Purpose Plan of Study REVIEW OF PLANT LOCATION CONCEPTS Introduction...

  2. A combined compensation method for the output voltage of an insulated core transformer power supply

    SciTech Connect (OSTI)

    Yang, L.; Yang, J., E-mail: jyang@mail.hust.edu.cn; Liu, K. F.; Qin, B.; Chen, D. Z. [State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China)

    2014-06-15T23:59:59.000Z

    An insulated core transformer (ICT) power supply is an ideal high-voltage generator for irradiation accelerators with energy lower than 3 MeV. However, there is a significant problem that the structure of the segmented cores leads to an increase in the leakage flux and voltage differences between rectifier disks. A high level of consistency in the output of the disks helps to achieve a compact structure by improving the utilization of both the rectifier components and the insulation distances, and consequently increase the output voltage of the power supply. The output voltages of the disks which are far away from the primary coils need to be improved to reduce their inhomogeneity. In this study, by investigating and comparing the existing compensation methods, a new combined compensation method is proposed, which increases the turns on the secondary coils and employs parallel capacitors to improve the consistency of the disks, while covering the entire operating range of the power supply. This method turns out to be both feasible and effective during the development of an ICT power supply. The non-uniformity of the output voltages of the disks is less than 3.5% from no-load to full-load, and the power supply reaches an output specification of 350 kV/60 mA.

  3. Utility Locating in the DOE Environment

    SciTech Connect (OSTI)

    Clark Scott; Gail Heath

    2006-04-01T23:59:59.000Z

    Some advances have been made in utility locating in recent years and standards have been recently published to try and categorize the level of information known about the utility in the subsurface. At the same time some characterization about the level of effort or technology in the geophysicist approach to utility locating may be generalized. The DOE environment poses some added difficulties and this presentation covers these issues, costs and the technical approach that has been developed at the INEEL to prevent utility hits and how it fits into the generalized classification of effort.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total2.

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total2.3.

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1. Total2.3..

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3. Revenue

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.7.

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.7.8.

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2. For9,250NetThousand1.3.6.7.8.9.

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry -

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry -2.

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry -2.3.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power Industry

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA. Net

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA.

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA.A.

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power IndustryA.A.B.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric Power

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. Net

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA. Net

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA. NetB.

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA. NetB.A.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6. Net

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6. Net7.

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9. Net

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9.

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9.1.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB. NetA.6.9.1.2.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5. Net

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5. Net6.

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8. Net

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8.0.

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4. Net5.8.0.1.

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3. Useful

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3. Useful4.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3. Useful4..

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.4.

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.4.5.

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric PowerB.4.3.B.3.4.5.6.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. Electric

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer Capacity

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9. Total

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.1.

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.1.2.

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net Summer9.1.2.3.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. Net

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B. Coal:

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.D.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.D.E.

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA. Coal:B.D.E.F.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B. Petroleum

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B. PetroleumC.

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E. Petroleum

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.C.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.C.D.

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB. NetA.B.E.A.B.C.D.E.

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural Gas:

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural Gas:B.

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural Gas:B.C.

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. Natural

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE. Natural

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D. Wood

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.F.

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.F.A.

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A. NaturalE.D.F.A.B.

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. Landfill Gas:

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. Landfill Gas:E.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. Landfill

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. LandfillA.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. LandfillA.B.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D. LandfillA.B.C.

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E. Biogenic

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E. BiogenicF.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E. BiogenicF.D.

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other Waste

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other0.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other0.1.

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F. Other0.1.2.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1. Stocks

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1. Stocks2

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4..

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4..3.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1. ElectricB.A.D.E.F.4.1.4..3.4.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost, and

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost, and7

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost,

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost,9.

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average Cost,9.0.

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.4.

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.4.5.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts, Average2.3.4.5.6.

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost of

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost0.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average Cost0.1.

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.4.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.4.5.

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8. Average3.4.5.1.

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity and

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity and4.

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity.

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity.2.

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3. Quantity.2.3.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5. Demand-Side

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7. Energy

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7. Energy8.

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7. Energy8.9.

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1. Sulfur

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1. Sulfur2.

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1.4.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghurajiConventionalMississippi"site.1 Relative Standard Errors forA2.1.6. Receipts,8.3.5.7.1.4.5. Unit

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997Million

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997MillionMajor U.S.

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997MillionMajor U.S.

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald L.1997MillionMajor

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,Ronald

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverable Coal Reserves

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverable Coal

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverable

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April 25,RonaldRecoverableRecoverable

  10. SAS Output

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

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

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number of Employees at

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number of Employees

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number of

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3. Coal

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3. Coal4.

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6. U.S.

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6.

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6.8.

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number ofCoal2.3.6.8.9.

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average Sales

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average Sales1.

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average3.

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average3.4.

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0. Average3.4.Coal

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.Coal Production

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.Coal

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.CoalCoal

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average Number0.CoalCoalMajor

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1Stocks Nov-14 Dec-14Table 4.April19. Average

  16. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3. Revenue

  17. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.

  18. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.5.

  19. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.5.A.

  20. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.5.A.B.

  1. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Energy I I' a eviequestionnairesMillion U.S.A. NetA.4.0.3.5.A.B.A.

  2. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  3. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  4. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  5. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  6. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  7. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  8. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

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

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835 2.812Average

  10. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835

  11. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average Price

  12. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average

  13. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average Steam

  14. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835Average

  15. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, 2014835AverageU.S.

  16. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9,

  17. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. Coal

  18. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. CoalAverage

  19. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. CoalAverageCoal

  20. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S.

  1. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S. Coke

  2. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.

  3. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.2. Coal

  4. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.2. CoalU.S.

  5. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.2.

  6. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S. U.S.2.Quantity

  7. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S.

  8. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S.Average Price of

  9. SAS Output

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:DeploymentSiteInformation4propanepropane9, U.S.Average Price of

  10. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropanepropane780 2.835 2.8124.

  11. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropanepropane780 2.835 2.8124..

  12. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropanepropane780 2.835 2.8124..1.

  13. SAS Output

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade Year-0E (2001) -heating oil pricepropanepropane780 2.835 2.8124..1.2.

  14. Combining Channel Output Feedback and CSI Feedback for MIMO Wireless Systems

    E-Print Network [OSTI]

    Agrawal, Mayur; Balakrishnan, Venkataramanan

    2010-01-01T23:59:59.000Z

    The use of channel output feedback to improve the reliability of fading channels has received scant attention in the literature. In most work on feedback for fading channels, only channel state information (CSI) feedback has been exploited for coding at the transmitter. In this work, the design of a coding scheme for multiple-input multiple-output (MIMO) fading systems with channel output and channel state feedback at the transmitter is considered. Under the assumption of additive white Gaussian noise and an independent and identically distributed fading process, a simple linear coding strategy that achieves any rate up to capacity is proposed. The framework assumes perfect CSI at the transmitter and receiver. This simple linear processing scheme can provide a doubly exponential probability of error decay with blocklength for all rates less than capacity. Remarkably, this encoding scheme actually consists of two separate encoding blocks: one that adapts to the current CSI and one that adapts to the previous c...

  15. Locating and tracking assets using RFID

    E-Print Network [OSTI]

    Kim, Gak Gyu

    2009-05-15T23:59:59.000Z

    . . . . . . . . . . . . . . . . . . . . . . . . 10 C. Different Technologies for Asset Tracking / Locating . . . . 10 1. Hand-held Reader . . . . . . . . . . . . . . . . . . . . 11 2. Fixed Reader Installed in Area . . . . . . . . . . . . . 11 3. Fixed Reader Installed at Chokepoint... . . . . . . . . . . . 34 a. CaseofInstallingtheFixedReaderintheMost Probable Area . . . . . . . . . . . . . . . . . . . . 35 b. Case of Installing the Fixed Reader in the Far- thest Area . . . . . . . . . . . . . . . . . . . . . . 36 3. Extension of Experiments...

  16. Recycling Bin Guide Locations and prices

    E-Print Network [OSTI]

    Kirschner, Denise

    Recycling Bin Guide Locations and prices Metal Bins Deskside Bins with Side Saddle Rubbermaid Bins.58 for auxiliaries. And Non-Public Areas Public Offices Non-Public Recyclables Recyclables RecyclablesTrash Trash Trash #12;New Recycling Bin Guidelines Frequently Asked Questions (as of December 2008) · Why

  17. Ontology-based Disambiguation of Spatiotemporal Locations

    E-Print Network [OSTI]

    Hyvönen, Eero

    , in the semantic portal MuseumFinland3 [7] a location parton- omy4 was used for annotating museum artifacts. #12;A problem when creating a semantic cultural heritage portal is that places, both modernFinland originate from regions that no longer exist and/or are not part of Finland but of Russia with new names

  18. Exact Location : Date of Accident : AM PM

    E-Print Network [OSTI]

    Swaddle, John

    SSN Cell Phone Home Phone Work Phone Exact Location : Date of Accident : AM PM Date accident treatment provided? Yes No Where Was time lost from work? Yes No If yes, how long? Could this accident have the following information as soon as it relates to your work related accident/injury/illness within 72 hours

  19. Modeling and Solving Location Routing and Scheduling Problems

    E-Print Network [OSTI]

    2008-10-13T23:59:59.000Z

    Oct 13, 2008 ... ... a standard approach for solving large-scale integer programming .... The algorithm fans out from the source node, repeatedly examining the.

  20. Earthquake locations and seismic velocity models for Southern California

    E-Print Network [OSTI]

    Lin, Guoqing

    2007-01-01T23:59:59.000Z

    systems using a conjugate gradient method. We constrain thesuch as the conjugate gradient method are effective ineven when the conjugate gradient method is used to solve the