Sample records for transportation total automated

  1. Automated Transportation Management System (ATMS) | Department...

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

    of Energy's (DOE's) Automated Transportation Management System is an integrated web-based logistics management system allowing users to manage inbound and outbound freight...

  2. Automating journey fare calculation for transport for London

    E-Print Network [OSTI]

    Maciejewski, Joshua J. (Joshua John)

    2008-01-01T23:59:59.000Z

    This thesis develops a method to automate journey fare calculation for Transport for London. Today, fares for every possible origin-destination station pair within the London Underground are prepared manually based on the ...

  3. Automated Vehicle Policy Work Automated vehicles are a subject of great interest, both in transportation and society in general.

    E-Print Network [OSTI]

    Automated Vehicle Policy Work Automated vehicles are a subject of great interest, both researchers are currently exploring automation's effects on the transportation system, determining preparation in the estimations of how automation will affect both congestion and safety. Both of these issues are critical

  4. Automated transportation management system (ATMS) software project management plan (SPMP)

    SciTech Connect (OSTI)

    Weidert, R.S., Westinghouse Hanford

    1996-05-20T23:59:59.000Z

    The Automated Transportation Management System (ATMS) Software Project Management plan (SPMP) is the lead planning document governing the life cycle of the ATMS and its integration into the Transportation Information Network (TIN). This SPMP defines the project tasks, deliverables, and high level schedules involved in developing the client/server ATMS software.

  5. Automated Transportation Logistics and Analysis System (ATLAS)

    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 FutureComments from TarasaName4ServicesTribalWorkplaceAutomated

  6. Transport Research Arena Europe 2010, Brussels Towards Highly Automated Driving

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    of HAVEit is to develop and investigate vehicle automation beyond ADAS systems, especially highly automated automated vehicles In 2010, two lines of research and development exist in the domain of ground vehicle automation: Either the automation is driving the vehicle fully automated without a human driver

  7. Vision-based Control of a Smart Wheelchair for the Automated Transport and Retrieval System (ATRS)

    E-Print Network [OSTI]

    Spletzer, John R.

    for autonomously docking a wheelchair onto a vehicle lift platform. This is a principle component of the AutomatedVision-based Control of a Smart Wheelchair for the Automated Transport and Retrieval System (ATRS disabilities. The ATRS employs robotics, automation, and machine vision technologies, and can be integrated

  8. automated transportation management: Topics by E-print Network

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

    OverviewManaged Lanes OverviewManaged Lanes OverviewManaged Lanes Overview 2012 Road Vehicle Automation Workshop2012 Road Vehicle Automation Workshop Engineering Websites...

  9. Automated Transportation Management System (ATMS) Software Project Management Plan (SPMP). Revision 2

    SciTech Connect (OSTI)

    Weidert, R.S.

    1995-05-26T23:59:59.000Z

    As a cabinet level federal agency with a diverse range of missions and an infrastructure spanning the United States, the US Department of Energy (DOE) has extensive freight transportation requirements. Performance and management of this freight activity is a critical function. DOE`s Transportation Management Division (TMD) has an agency-wide responsibility for overseeing transportation activities. Actual transportation operations are handled by government or contractor staff at the field locations. These staff have evolved a diverse range of techniques and procedures for performing transportation functions. In addition to minimizing the economic impact of transportation on programs, facility transportation staff must be concerned with the increasingly complex task of complying with complex shipment safety regulations. Maintaining the department`s safety record for shipping hazardous and radioactive materials is a primary goal. Use of automation to aid transportation functions is not widespread within DOE, though TMD has a number of software systems designed to gather and analyze data pertaining to field transportation activities. These systems are not integrated. Historically, most field facilities have accomplished transportation-related tasks manually or with minimal computer assistance. At best, information and decision support systems available to transportation staffs within the facilities are fragmented. In deciding where to allocate resources for automation, facility managers have not tended to give the needs of transportation departments a high priority. This diversity causes TMD significant difficulty in collecting data for use in managing department-wide transportation activities.

  10. Functional requirements for the Automated Transportation Management System: TTP number: RL 439002

    SciTech Connect (OSTI)

    Portsmouth, J.H. [Westinghouse Hanford Co., Richland, WA (United States)

    1992-12-31T23:59:59.000Z

    This requirements analysis, documents Department of Energy (DOE) transportation management procedures for the purpose of providing a clear and mutual understanding between users and designers of the proposed Automated Transportation Management System (ATMS). It is imperative that one understand precisely how DOE currently performs traffic management tasks; only then can an integrated system be proposed that successfully satisfies the major requirements of transportation managers and other system users. Accordingly, this report describes the current workings of DOE transportation organizations and then proposes a new system which represents a synthesis of procedures (both current and desired) which forms the basis for further systems development activities.

  11. US Department of Energy automated transportation management system

    SciTech Connect (OSTI)

    Thomas, T.M. [Dept. of Energy, Germantown, MD (United States); Frost, D.M.; Lopez, C.A. [MELE Associates, Rockville, MD (United States)] [and others

    1996-12-31T23:59:59.000Z

    The US Department of Energy (DOE) has approximately 80 facilities throughout the United States that specialize in either scientific research, engineering, technology, production, and/or waste management activities. These facilities can best be described as Government Owned, Contractor Operated (GOCO) sites, and vary in size from very small laboratories to large industrial plant type facilities. Each of these GOCO`s have varying needs for transportation of materials into and/or out of their facility. Therefore, Traffic Management operations will differ from site to site due to size and the internal or site specific mission. The DOE Transportation Management Division (TMD) has the corporate responsibility to provide a well managed transportation management program for the safe, efficient, and economical transportation of all DOE-owned materials. To achieve this mission, TMD provides oversight, and when necessary, resources to assist in ensuring regulatory compliance in the packaging and shipment of DOE-owned materials. A large part of TMD`s responsibility is to develop, administer, and provide policies and guidance concerning department-wide transportation and packaging operations. This responsibility includes overall Transportation Management policies and programs for the packaging and movement of all DOE materials, including radioactive materials, other hazardous materials/substances, and hazardous wastes. TMD formulates policies and guidance that assist the DOE Field Elements and GOCO`s in meeting TMD`s goal for safe, efficient and economical transportation. Considering there are at least 80 shipping and receiving sites, the challenge encountered by TMD has been the difficulty in managing such a diverse transportation community.

  12. Efficient, automated Monte Carlo methods for radiation transport

    SciTech Connect (OSTI)

    Kong Rong; Ambrose, Martin [Claremont Graduate University, 150 E. 10th Street, Claremont, CA 91711 (United States); Spanier, Jerome [Claremont Graduate University, 150 E. 10th Street, Claremont, CA 91711 (United States); Beckman Laser Institute and Medical Clinic, University of California, 1002 Health Science Road E., Irvine, CA 92612 (United States)], E-mail: jspanier@uci.edu

    2008-11-20T23:59:59.000Z

    Monte Carlo simulations provide an indispensible model for solving radiative transport problems, but their slow convergence inhibits their use as an everyday computational tool. In this paper, we present two new ideas for accelerating the convergence of Monte Carlo algorithms based upon an efficient algorithm that couples simulations of forward and adjoint transport equations. Forward random walks are first processed in stages, each using a fixed sample size, and information from stage k is used to alter the sampling and weighting procedure in stage k+1. This produces rapid geometric convergence and accounts for dramatic gains in the efficiency of the forward computation. In case still greater accuracy is required in the forward solution, information from an adjoint simulation can be added to extend the geometric learning of the forward solution. The resulting new approach should find widespread use when fast, accurate simulations of the transport equation are needed.

  13. Modeling the Energy Use of a Connected and Automated Transportation System (Poster)

    SciTech Connect (OSTI)

    Gonder, J.; Brown, A.

    2014-07-01T23:59:59.000Z

    Early research points to large potential impacts of connected and automated vehicles (CAVs) on transportation energy use - dramatic savings, increased use, or anything in between. Due to a lack of suitable data and integrated modeling tools to explore these complex future systems, analyses to date have relied on simple combinations of isolated effects. This poster proposes a framework for modeling the potential energy implications from increasing penetration of CAV technologies and for assessing technology and policy options to steer them toward favorable energy outcomes. Current CAV modeling challenges include estimating behavior change, understanding potential vehicle-to-vehicle interactions, and assessing traffic flow and vehicle use under different automation scenarios. To bridge these gaps and develop a picture of potential future automated systems, NREL is integrating existing modeling capabilities with additional tools and data inputs to create a more fully integrated CAV assessment toolkit.

  14. (en transport pblic) Temps total del trajecte: 123 minuts

    E-Print Network [OSTI]

    Oro, Daniel

    addicionals (CO2): 13,96 Kg Emissions addicionals (SO2): 0,009 Kg Durada: 123 min. Cost mitjà del viatge2 : 1,52 Emissions addicionals (CO2): 0 kg Emissions addicionals (SO2): 0 kg Transport públicTransport privat.392'96 Emissions addicionals (CO2): 4.914,07 Kg Emissions addicionals (SO2): 3,02 Kg Temps acumulat: 30,07 dies

  15. (en transport pblic) Temps total del trajecte: 40 minuts

    E-Print Network [OSTI]

    Oro, Daniel

    addicionals (CO2): 3,78 Kg Emissions addicionals (SO2): 0,002 Kg Durada: 40 min. Cost mitjà del viatge2 : 1,90 Emissions addicionals (CO2): 0 kg Emissions addicionals (SO2): 0 kg Transport públicTransport privat.188,35 Emissions addicionals (CO2): 1.329,32 Kg Emissions addicionals (SO2): 0,82 Kg Temps acumulat: 9,78 dies

  16. Table 20. Total Delivered Transportation Energy Consumption, Projected vs. Actual

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

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

  17. A new formula for the total longshore sediment transport rate Atilla Bayram a,, Magnus Larson b

    E-Print Network [OSTI]

    US Army Corps of Engineers

    A new formula for the total longshore sediment transport rate Atilla Bayram a,, Magnus Larson b April 2007 Available online 7 June 2007 Abstract A new predictive formula for the total longshore employed to evaluate the predictive capability of the new formula. The main parameter of the formula (a

  18. Poynting's theorem and luminal total energy transport in passive dielectric media S. Glasgow,1

    E-Print Network [OSTI]

    Hart, Gus

    Poynting's theorem and luminal total energy transport in passive dielectric media S. Glasgow,1 M to a virtual, ``instantaneous'' field spectrum, 2 that a causal, passive medium supports only a luminal front velocity, 3 that the spatial ``center-of-mass'' motion of the total dynamical energy is also always luminal

  19. Total Recall: System Support for Automated Availability Management Ranjita Bhagwan, Kiran Tati, Yu-Chung Cheng, Stefan Savage, and Geoffrey M. Voelker

    E-Print Network [OSTI]

    Savage, Stefan

    Total Recall: System Support for Automated Availability Management Ranjita Bhagwan, Kiran Tati, Yu of California, San Diego Abstract Availability is a storage system property that is both highly desired and yet and with only a cursory understanding of how the config- uration will impact overall performance or availability

  20. Test Automation Test Automation

    E-Print Network [OSTI]

    Mousavi, Mohammad

    Test Automation Test Automation Mohammad Mousavi Eindhoven University of Technology, The Netherlands Software Testing 2013 Mousavi: Test Automation #12;Test Automation Outline Test Automation Mousavi: Test Automation #12;Test Automation Why? Challenges of Manual Testing Test-case design: Choosing inputs

  1. A Cooperative Personal Automated Transport System A CityMobil Demonstration in Rocquencourt

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    the problem of the autonomous navigation and coordination of multiple driverless vehicles for the transport advanced concepts for efficient urban transportation capable of reducing energy consumption, optimizing during the period of 3 months service. This demonstration showed how autonomous road vehicles can

  2. 40 IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 1, NO. 1, MARCH 2000 Designing Human-Centered Automation: Tradeoffs

    E-Print Network [OSTI]

    Goodrich, Michael A.

    -centered automation in advanced vehicle systems, the decision method identifies performance valuations and compares--Advanced vehicle systems, decision making, human-centered automation, human factors, satisficing. I. INTRODUCTION Human-Centered Automation: Tradeoffs in Collision Avoidance System Design Michael A. Goodrich, Member

  3. Framework for a flexible, real-time controller for automated material transport systems

    E-Print Network [OSTI]

    Edlabadkar, Abhay

    1995-01-01T23:59:59.000Z

    The Manager Module. 5. 5. 1 Configuration 1. . 5. 5. 2 Configurations 2 2k 3. 5. 5. 3 Configuratron 4. . 5. 5. 4 Error Handling and Recovery Routines. . . . . . 5. 6 The Dispatcher Module. . 5. 6. 1 Configurations I 2k 4 5. 6. 2 Configurations 2 & 3... for the manager module. MTC control structure. 25 28 43 61 16 17 19 20 Material transport system layout . Intermediate decision ports . . Intermediate MTS network representation. . Graph representation of the MTS. . . Basic flowchart for the MTC...

  4. "Table 20. Total Delivered Transportation Energy Consumption, Projected vs. Actual"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells,1 U.S. Department of Energygasoline4 Space Heating8Total

  5. Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response

    E-Print Network [OSTI]

    Kiliccote, Sila

    2011-01-01T23:59:59.000Z

    andindustrialfacilities. Thelong?termvisionistoembedthe automationIndustrial/Agricultural/WaterEnd?UseEnergyEfficiency RenewableEnergyTechnologies Transportation TheAutomation

  6. Feasible Path Synthesis for Automated Guided Vehicles

    E-Print Network [OSTI]

    Vuik, Kees

    Feasible Path Synthesis for Automated Guided Vehicles Reijer Idema 2005 TU Delft FROG Navigation for Automated Guided Vehicles Author: Reijer Idema Supervisors: prof.dr.ir. P. Wesseling (TU Delft) dr.ir. Kees is a manufacturer of Automated Guided Vehicles. They have developed a multitude of vehicles that transport products

  7. Transportation

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

    Transportation Home Agenda Awards Exhibitors Lodging Posters Registration Transportation Workshops Contact Us User Meeting Archives Users' Executive Committee Getting to Berkeley...

  8. Transportation

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

    Transportation Print Home Agenda Awards Exhibitors Lodging Posters Registration Transportation Workshops Contact Us User Meeting Archives Users' Executive Committee Getting to...

  9. Test Automation Ant JUnit Test Automation

    E-Print Network [OSTI]

    Mousavi, Mohammad

    Test Automation Ant JUnit Test Automation Mohammad Mousavi Eindhoven University of Technology, The Netherlands Software Testing 2012 Mousavi: Test Automation #12;Test Automation Ant JUnit Outline Test Automation Ant JUnit Mousavi: Test Automation #12;Test Automation Ant JUnit Why? Challenges of Manual Testing

  10. Transportation

    E-Print Network [OSTI]

    Vinson, Steve

    2013-01-01T23:59:59.000Z

    Transportation in ancient Egypt entailed the use of boats2007 Land transport in Roman Egypt: A study of economics andDieter 1991 Building in Egypt: Pharaonic stone masonry. New

  11. Automated Transportation Management System (ATMS)

    Office of Environmental Management (EM)

    s lading, fre * W * C S * A * H * E * * O 0 mated T artment of Ene tation Manage ated web-base lowing users freight shipm arly developm E Inspector G t opportunitie al...

  12. Coordinating Automated Vehicles via Communication

    E-Print Network [OSTI]

    Bana, Soheila Vahdati

    2001-01-01T23:59:59.000Z

    1.1 Vehicle Automation . . . . . . . . . . . 1.1.1 Controlareas of technology in vehicle automation and communicationChapter 1 Introduction Vehicle Automation Automation is an

  13. Intermodal passenger flows on London's public transport network : automated inference of full passenger journeys using fare-transaction and vehicle-location data

    E-Print Network [OSTI]

    Gordon, Jason B. (Jason Benjamin)

    2012-01-01T23:59:59.000Z

    Urban public transport providers have historically planned and managed their networks and services with limited knowledge of their customers' travel patterns. While ticket gates and bus fareboxes yield counts of passenger ...

  14. Revolutionizing Our Roadways The Challenges and Benefits of Making Automated Vehicles a Reality

    E-Print Network [OSTI]

    Revolutionizing Our Roadways The Challenges and Benefits of Making Automated Vehicles a Reality #12 of Making Automated Vehicles a Reality by Jason Wagner Associate Transportation Researcher Texas A Station, Texas 77843-3135 #12;iv | REVOLUTIONIZING OUR ROADWAYS #12;v Contents 1.0 Automated Vehicles

  15. A Real-Time Navigation Architecture for Automated Vehicles in Urban Environments

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    A Real-Time Navigation Architecture for Automated Vehicles in Urban Environments Gang Chen presents a novel navigation architec- ture for automated car-like vehicles in urban environments. Motion with fully automated driving capabilities. A fleet of such vehicles would form a managed transportation

  16. Design, Simulation, and Analysis of Substation Automation Networks

    E-Print Network [OSTI]

    Kembanur Natarajan, Elangovan

    2012-07-16T23:59:59.000Z

    on the Substation Automation Systems (SAS). Substations are nodes in the smart grid infrastructure that help the in transportation of power by connecting the transmission and distribution lines. The SAS applications are con figured to operate with minimal human...

  17. Transportation Decision Support Systems Oak Ridge National Laboratory

    E-Print Network [OSTI]

    Transportation Decision Support Systems Oak Ridge National Laboratory managed by UT-Battelle, LLC Passenger Flows Supply Chain Efficiency Transportation: Energy Environment Safety Security Vehicle and implementation of automated transportation decision support models for the scheduling and routing of cargo

  18. Multiplex automated genome engineering

    DOE Patents [OSTI]

    Church, George M; Wang, Harris H; Isaacs, Farren J

    2013-10-29T23:59:59.000Z

    The present invention relates to automated methods of introducing multiple nucleic acid sequences into one or more target cells.

  19. Charmaine Toy Automation Engineer,

    E-Print Network [OSTI]

    Horowitz, Roberto

    @me.berkeley.edu Nonstationary Velocity Profiles for Emergency Vehicles on Automated Highways This paper explores the notion and usefulness of nonstationary velocity profiles for high priority emergency vehicle transit on automatedCharmaine Toy Automation Engineer, DiCon Fiberoptics, Inc., Richmond, CA 94804 e-mail: charm

  20. Sensors and Automated Analyzers for Radionuclides

    SciTech Connect (OSTI)

    Grate, Jay W.; Egorov, Oleg B.

    2003-03-27T23:59:59.000Z

    The production of nuclear weapons materials has generated large quantities of nuclear waste and significant environmental contamination. We have developed new, rapid, automated methods for determination of radionuclides using sequential injection methodologies to automate extraction chromatographic separations, with on-line flow-through scintillation counting for real time detection. This work has progressed in two main areas: radionuclide sensors for water monitoring and automated radiochemical analyzers for monitoring nuclear waste processing operations. Radionuclide sensors have been developed that collect and concentrate radionuclides in preconcentrating minicolumns with dual functionality: chemical selectivity for radionuclide capture and scintillation for signal output. These sensors can detect pertechnetate to below regulatory levels and have been engineered into a prototype for field testing. A fully automated process monitor has been developed for total technetium in nuclear waste streams. This instrument performs sample acidification, speciation adjustment, separation and detection in fifteen minutes or less.

  1. Joint Genome Institute's Automation Approach and History

    E-Print Network [OSTI]

    Roberts, Simon

    2006-01-01T23:59:59.000Z

    Joint Genome Institutes Automation Approach and Historythroughput environment; automation does not necessarilyissues Islands of Automation modular instruments with

  2. An Automation System for Optimizing a Supply Chain Network Design under the Influence of Demand Uncertainty

    E-Print Network [OSTI]

    Polany, Rany

    2012-01-01T23:59:59.000Z

    Automation . . . . . . . . . . . . . . . . . . . . . . iii 3Automation . . . . . . . . . . . . . . . . . . . . . . 5Dashboard/Cockpit Automation . . . . . . . . . . . . .

  3. Architectures of Test Automation 1 High Volume Test AutomationHigh Volume Test Automation

    E-Print Network [OSTI]

    Architectures of Test Automation 1 High Volume Test AutomationHigh Volume Test Automation Cem Kaner Institute of Technology October 2003 #12;Architectures of Test Automation 2 Acknowledgements developed a course on test automation architecture, and in the Los Altos Workshops on Software Testing

  4. Copyright (c) Cem Kaner, Automated Testing. 1 Software Test Automation:Software Test Automation

    E-Print Network [OSTI]

    Copyright (c) Cem Kaner, Automated Testing. 1 Software Test Automation:Software Test Automation: A RealA Real--World ProblemWorld Problem Cem Kaner, Ph.D., J.D. #12;Copyright (c) Cem Kaner, Automated Testing. 2 This TalkThis Talk The most widely used class of automated testing tools leads senior software

  5. High Volume Test Automation 1 High Volume Test AutomationHigh Volume Test Automation

    E-Print Network [OSTI]

    High Volume Test Automation 1 High Volume Test AutomationHigh Volume Test Automation Keynote Automation 2 AcknowledgementsAcknowledgements · Many of the ideas in this presentation were initially jointly developed with Doug Hoffman,as we developed a course on test automation architecture, and in the Los Altos

  6. A Verified Hybrid Controller For Automated Vehicles

    E-Print Network [OSTI]

    Lygeros, J.; Godbole, D. N.; Sastry, S.

    1997-01-01T23:59:59.000Z

    con- trollers for vehicle automation," in American ControlTomizuka, Vehicle lateral control for highway automation,"

  7. Convection automated logic oven control

    SciTech Connect (OSTI)

    Boyer, M.A.; Eke, K.I. [Apollo U.S.A. Inc., Orlando, FL (United States)] [Apollo U.S.A. Inc., Orlando, FL (United States)

    1998-03-01T23:59:59.000Z

    For the past few years, there has been a greater push to bring more automation to the cooling process. There have been attempts at automated cooking using a wide range of sensors and procedures, but with limited success. The authors have the answer to the automated cooking process; this patented technology is called Convection AutoLogic (CAL). The beauty of the technology is that it requires no extra hardware for the existing oven system. They use the existing temperature probe, whether it is an RTD, thermocouple, or thermistor. This means that the manufacturer does not have to be burdened with extra costs associated with automated cooking in comparison to standard ovens. The only change to the oven is the program in the central processing unit (CPU) on the board. As for its operation, when the user places the food into the oven, he or she is required to select a category (e.g., beef, poultry, or casseroles) and then simply press the start button. The CAL program then begins its cooking program. It first looks at the ambient oven temperature to see if it is a cold, warm, or hot start. CAL stores this data and then begins to look at the food`s thermal footprint. After CAL has properly detected this thermal footprint, it can calculate the time and temperature at which the food needs to be cooked. CAL then sets up these factors for the cooking stage of the program and, when the food has finished cooking, the oven is turned off automatically. The total time for this entire process is the same as the standard cooking time the user would normally set. The CAL program can also compensate for varying line voltages and detect when the oven door is opened. With all of these varying factors being monitored, CAL can produce a perfectly cooked item with minimal user input.

  8. TOTAL M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total Spring 2010

    E-Print Network [OSTI]

    Hayes, Jane E.

    202 51 *total new freshmen 684: 636 Lexington campus, 48 Paducah campus MS Total 216 12 5 17 2 0 2 40 248 247 648 45 210 14 *total new freshmen 647: 595 Lexington campus, 52 Paducah campus MS Total 192 14

  9. Cognitive Engineering Automation and Human

    E-Print Network [OSTI]

    Parasuraman, Raja

    · Home automation · Robotics · Unmanned vehicles (UAVs and UGVs) · Drug design/Molecular geneticsCognitive Engineering PSYC 530 Automation and Human Performance Raja Parasuraman #12;Overview Automation-Related Accidents Levels and Stages of Automation Information Acquisition and Analysis Decision

  10. RF test bench automation Description

    E-Print Network [OSTI]

    Dobigeon, Nicolas

    RF test bench automation Description: Callisto would like to implement automated RF test bench. Three RF test benches have to be studied and automated: LNA noise temperature test bench LNA gain phase of the test benches and an implementation of the automation phase. Tasks: Noise temperature

  11. State Residential Commercial Industrial Transportation Total

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home 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 ErrorsSeptemberState Nuclear Profiles

  12. Development of Building Automation and Control Systems

    E-Print Network [OSTI]

    Yang, Yang; Zhu, Qi; Maasoumy, Mehdi; Sangiovanni-Vincentelli, Alberto

    2012-01-01T23:59:59.000Z

    A design flow for building automation and control systems,Development of Building Automation and Control Systems Yangdesign of the build- ing automation system (including the

  13. Demonstration of Automated Heavy-Duty Vehicles

    E-Print Network [OSTI]

    2006-01-01T23:59:59.000Z

    a future in which vehicle automation technologies are ableto support the heavy vehicle automation including PrecisionCommittee on Vehicle-Highway Automation, and the attendees

  14. Development of Building Automation and Control Systems

    E-Print Network [OSTI]

    Yang, Yang; Zhu, Qi; Maasoumy, Mehdi; Sangiovanni-Vincentelli, Alberto

    2012-01-01T23:59:59.000Z

    design flow for building automation systems that focuses onflow for building automation and control systems, in Proc.Development of Building Automation and Control Systems Yang

  15. Automated Lattice Perturbation Theory

    SciTech Connect (OSTI)

    Monahan, Christopher

    2014-11-01T23:59:59.000Z

    I review recent developments in automated lattice perturbation theory. Starting with an overview of lattice perturbation theory, I focus on the three automation packages currently "on the market": HiPPy/HPsrc, Pastor and PhySyCAl. I highlight some recent applications of these methods, particularly in B physics. In the final section I briefly discuss the related, but distinct, approach of numerical stochastic perturbation theory.

  16. Automated pavement crack detection

    E-Print Network [OSTI]

    Rao, Ashok Madhava

    1991-01-01T23:59:59.000Z

    : Electrical Engineering AUTOMATED PAVEMENT CRACK DETECTION A Thesis by ASHOK MADHAVA RAO Approved as to style and content by . c Norman C. Grisw d (Chair of Committ ) Nasser Kehtarnavaz (Member) g, J~, Karan Watson Robert L. Lytt (Member) Jo W.... Howze (Head of Department) December 1991 111 ABSTRACT Automated Pavement Crack Detection. (December 1991) Ashok Madhava, Rao, B. E. , Mysore University Chair of Advisory Committee: Norman. C. Griswold Due to load, environmental and structural...

  17. General approach to automation of FLASH subsystems

    E-Print Network [OSTI]

    General approach to automation of FLASH subsystems Boguslaw Kosda #12;Agenda Motivation Nature of automation software for high energy experiments. Ultimate role of the automation software: Maximization of lasers availability. Automation of routine activities as startup, shutdown ... Continuous monitoring

  18. alteraciones del transporte: Topics by E-print Network

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

    total del trajecte: 40 minuts Comparaci transport pblic,90 Emissions addicionals (CO2): 0 kg Emissions addicionals (SO2): 0 kg Transport pblicTransport privat Despesa...

  19. Automated distribution scheme speeds service restoration

    SciTech Connect (OSTI)

    Atwell, E. [Lakeland Electric and Water, FL (United States)] [Lakeland Electric and Water, FL (United States); Gamvrelis, T. [Harris Canada, Inc., Calgary, Alberta (Canada). Control Div.] [Harris Canada, Inc., Calgary, Alberta (Canada). Control Div.; Kearns, D. [S and C Electric Co., Chicago, IL (United States)] [S and C Electric Co., Chicago, IL (United States); Landman, R. [H and L Instruments, North Hampton, NH (United States)] [H and L Instruments, North Hampton, NH (United States)

    1996-01-01T23:59:59.000Z

    This article describes an automated distribution scheme that met Lakeland Electric requirements for an automated scheme that would restore power to a major customer in less than 60 seconds. In January 1993, Lakeland Electric and Water (LEW) took on the design and construction of a new 12.47-kV automated distribution system for the Publix Supermarket Industrial complex. The industrial complex in Lakeland, Florida, totals 2 million square feet and houses a dairy processing plant, bakery, produce plant, deli plant, data processing facility for Publix`s entire retail network, purchasing department, as well as several maintenance facilities. The retail chain is LEW`s largest customer with a peak demand of 15.5 MW and a load factor of 81%. Publix`s rapid expansion plan has placed a great deal of pressure on this facility to perform at peak level with no interruptions of product flow. The task at hand was to provide Publix with a state-of-the-art, automated, distribution system built to withstand the inherent weather-related situations in central Florida, lightning and hurricanes.

  20. Automated gas chromatography

    DOE Patents [OSTI]

    Mowry, Curtis D. (Albuquerque, NM); Blair, Dianna S. (Albuquerque, NM); Rodacy, Philip J. (Albuquerque, NM); Reber, Stephen D. (Corrales, NM)

    1999-01-01T23:59:59.000Z

    An apparatus and process for the continuous, near real-time monitoring of low-level concentrations of organic compounds in a liquid, and, more particularly, a water stream. A small liquid volume of flow from a liquid process stream containing organic compounds is diverted by an automated process to a heated vaporization capillary where the liquid volume is vaporized to a gas that flows to an automated gas chromatograph separation column to chromatographically separate the organic compounds. Organic compounds are detected and the information transmitted to a control system for use in process control. Concentrations of organic compounds less than one part per million are detected in less than one minute.

  1. Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response

    E-Print Network [OSTI]

    Kiliccote, Sila

    2011-01-01T23:59:59.000Z

    ProtocolforBuildingAutomationandControl Networks. ProtocolforBuildingAutomationandControl Networks,DemandResponseAutomationServer DemandResponseResearch

  2. Office Automation Document Preparation

    E-Print Network [OSTI]

    North Carolina at Chapel Hill, University of

    .2 Distinctions 1.3 Facilities 1.3.1 Document Preparation 1.3.2 Records Management 1.3.3 Communication 1 organizations contemplating the installation of document-preparation systems. * Administrative managersOffice Automation and Document Preparation for the v' University of North Carolina at Chapel Hill

  3. Automated Microbial Genome Annotation

    SciTech Connect (OSTI)

    Land, Miriam [DOE Joint Genome Institute at Oak Ridge National Laboratory

    2009-05-29T23:59:59.000Z

    Miriam Land of the DOE Joint Genome Institute at Oak Ridge National Laboratory gives a talk on the current state and future challenges of moving toward automated microbial genome annotation at the "Sequencing, Finishing, Analysis in the Future" meeting in Santa Fe, NM

  4. automated serum chemistry: Topics by E-print Network

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

    Summary: Test Automation Test Automation Mohammad Mousavi Eindhoven University of Technology, The Netherlands Software Testing 2013 Mousavi: Test Automation 12;Test Automation...

  5. Automated gas chromatography

    DOE Patents [OSTI]

    Mowry, C.D.; Blair, D.S.; Rodacy, P.J.; Reber, S.D.

    1999-07-13T23:59:59.000Z

    An apparatus and process for the continuous, near real-time monitoring of low-level concentrations of organic compounds in a liquid, and, more particularly, a water stream. A small liquid volume of flow from a liquid process stream containing organic compounds is diverted by an automated process to a heated vaporization capillary where the liquid volume is vaporized to a gas that flows to an automated gas chromatograph separation column to chromatographically separate the organic compounds. Organic compounds are detected and the information transmitted to a control system for use in process control. Concentrations of organic compounds less than one part per million are detected in less than one minute. 7 figs.

  6. Theorie des langages Automates `a pile

    E-Print Network [OSTI]

    Bonzon, Elise

    Th´eorie des langages Automates `a pile Elise Bonzon http://web.mi.parisdescartes.fr/ bonzon/ elise.bonzon@parisdescartes.fr 1 / 62 Th´eorie des langages #12;Automates `a pile Automates `a pile Introduction Rappels sur les piles Automates `a pile : d´efinition Automates `a pile : configurations Les crit`eres d

  7. Methodology for Prototyping Increased Levels of Automation

    E-Print Network [OSTI]

    Valasek, John

    of automation than previous NASA vehicles, due to program requirements for automation, including Automated Ren into a human space flight vehicle, NASA has created the Function-specific Level of Autonomy and Automation Tool levels of automation than previous NASA vehicles. A key technology to the success of the CEV

  8. Automated Job Hazards Analysis

    Broader source: Energy.gov [DOE]

    AJHA Program - The Automated Job Hazard Analysis (AJHA) computer program is part of an enhanced work planning process employed at the Department of Energy's Hanford worksite. The AJHA system is routinely used to performed evaluations for medium and high risk work, and in the development of corrective maintenance work packages at the site. The tool is designed to ensure that workers are fully involved in identifying the hazards, requirements, and controls associated with tasks.

  9. Automated Demand Response Opportunities in Wastewater Treatment Facilities

    SciTech Connect (OSTI)

    Thompson, Lisa; Song, Katherine; Lekov, Alex; McKane, Aimee

    2008-11-19T23:59:59.000Z

    Wastewater treatment is an energy intensive process which, together with water treatment, comprises about three percent of U.S. annual energy use. Yet, since wastewater treatment facilities are often peripheral to major electricity-using industries, they are frequently an overlooked area for automated demand response opportunities. Demand response is a set of actions taken to reduce electric loads when contingencies, such as emergencies or congestion, occur that threaten supply-demand balance, and/or market conditions occur that raise electric supply costs. Demand response programs are designed to improve the reliability of the electric grid and to lower the use of electricity during peak times to reduce the total system costs. Open automated demand response is a set of continuous, open communication signals and systems provided over the Internet to allow facilities to automate their demand response activities without the need for manual actions. Automated demand response strategies can be implemented as an enhanced use of upgraded equipment and facility control strategies installed as energy efficiency measures. Conversely, installation of controls to support automated demand response may result in improved energy efficiency through real-time access to operational data. This paper argues that the implementation of energy efficiency opportunities in wastewater treatment facilities creates a base for achieving successful demand reductions. This paper characterizes energy use and the state of demand response readiness in wastewater treatment facilities and outlines automated demand response opportunities.

  10. Design and Construction of an Automated Community Bicycle Loan/

    E-Print Network [OSTI]

    Goadrich, Mark

    $20 Box $50 Solar Power Panels $50 CPU $200 Total Per Unit $432 #12;Conclusion and Future Lessons design and construct an automated community bike share system in-house in a cost efficient manner? Accessible and easy to use Maintain security Cost effective Allow monitoring of information #12

  11. Automation of Painted Slate Inspection

    E-Print Network [OSTI]

    Whelan, Paul F.

    Automation of Painted Slate Inspection BY Tim Carew (B.Eng.) carewt@eeng.dcu.ie Submitted...........................................................................................................18 2.1 Prior research on inspection of slates

  12. Valliappa Lakshmanan Automating the Analysis of

    E-Print Network [OSTI]

    Lakshmanan, Valliappa

    Geospatial Images January 5, 2012 Springer #12;Contents 1 Automated Analysis of Spatial Grids: MotivationValliappa Lakshmanan Automating the Analysis of Spatial Grids A Practitioner's Guide to Data Mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.5 Challenges in Automated Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1

  13. automation: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  14. Installation and Commissioning Automated Demand Response Systems

    SciTech Connect (OSTI)

    Global Energy Partners; Pacific Gas and Electric Company; Kiliccote, Sila; Kiliccote, Sila; Piette, Mary Ann; Wikler, Greg; Prijyanonda, Joe; Chiu, Albert

    2008-04-21T23:59:59.000Z

    Demand Response (DR) can be defined as actions taken to reduce electric loads when contingencies, such as emergencies and congestion, occur that threaten supply-demand balance, or market conditions raise supply costs. California utilities have offered price and reliability DR based programs to customers to help reduce electric peak demand. The lack of knowledge about the DR programs and how to develop and implement DR control strategies is a barrier to participation in DR programs, as is the lack of automation of DR systems. Most DR activities are manual and require people to first receive notifications, and then act on the information to execute DR strategies. Levels of automation in DR can be defined as follows. Manual Demand Response involves a labor-intensive approach such as manually turning off or changing comfort set points at each equipment switch or controller. Semi-Automated Demand Response involves a pre-programmed demand response strategy initiated by a person via centralized control system. Fully-Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. The receipt of the external signal initiates pre-programmed demand response strategies. We refer to this as Auto-DR (Piette et. al. 2005). Auto-DR for commercial and industrial facilities can be defined as fully automated DR initiated by a signal from a utility or other appropriate entity and that provides fully-automated connectivity to customer end-use control strategies. One important concept in Auto-DR is that a homeowner or facility manager should be able to 'opt out' or 'override' a DR event if the event comes at time when the reduction in end-use services is not desirable. Therefore, Auto-DR is not handing over total control of the equipment or the facility to the utility but simply allowing the utility to pass on grid related information which then triggers facility defined and programmed strategies if convenient to the facility. From 2003 through 2006 Lawrence Berkeley National Laboratory (LBNL) and the Demand Response Research Center (DRRC) developed and tested a series of demand response automation communications technologies known as Automated Demand Response (Auto-DR). In 2007, LBNL worked with three investor-owned utilities to commercialize and implement Auto-DR programs in their territories. This paper summarizes the history of technology development for Auto-DR, and describes the DR technologies and control strategies utilized at many of the facilities. It outlines early experience in commercializing Auto-DR systems within PG&E DR programs, including the steps to configure the automation technology. The paper also describes the DR sheds derived using three different baseline methodologies. Emphasis is given to the lessons learned from installation and commissioning of Auto-DR systems, with a detailed description of the technical coordination roles and responsibilities, and costs.

  15. Automated cassette-to-cassette substrate handling system

    DOE Patents [OSTI]

    Kraus, Joseph Arthur; Boyer, Jeremy James; Mack, Joseph; DeChellis, Michael; Koo, Michael

    2014-03-18T23:59:59.000Z

    An automated cassette-to-cassette substrate handling system includes a cassette storage module for storing a plurality of substrates in cassettes before and after processing. A substrate carrier storage module stores a plurality of substrate carriers. A substrate carrier loading/unloading module loads substrates from the cassette storage module onto the plurality of substrate carriers and unloads substrates from the plurality of substrate carriers to the cassette storage module. A transport mechanism transports the plurality of substrates between the cassette storage module and the plurality of substrate carriers and transports the plurality of substrate carriers between the substrate carrier loading/unloading module and a processing chamber. A vision system recognizes recesses in the plurality of substrate carriers corresponding to empty substrate positions in the substrate carrier. A processor receives data from the vision system and instructs the transport mechanism to transport substrates to positions on the substrate carrier in response to the received data.

  16. Installation and Commissioning Automated Demand Response Systems

    E-Print Network [OSTI]

    Kiliccote, Sila; Global Energy Partners; Pacific Gas and Electric Company

    2008-01-01T23:59:59.000Z

    their partnership in demand response automation research andand Techniques for Demand Response. LBNL Report 59975. Mayof Fully Automated Demand Response in Large Facilities.

  17. Home Network Technologies and Automating Demand Response

    E-Print Network [OSTI]

    McParland, Charles

    2010-01-01T23:59:59.000Z

    and Automating Demand Response Charles McParland, Lawrenceand Automating Demand Response Charles McParland, LBNLCommercial and Residential Demand Response Overview of the

  18. Installation and Commissioning Automated Demand Response Systems

    E-Print Network [OSTI]

    Kiliccote, Sila; Global Energy Partners; Pacific Gas and Electric Company

    2008-01-01T23:59:59.000Z

    al: Installation and Commissioning Automated Demand ResponseConference on Building Commissioning: April 22 24, 2008al: Installation and Commissioning Automated Demand Response

  19. Integration of automation design information using XML technologies

    E-Print Network [OSTI]

    Integration of automation design information using XML technologies Master of Science Thesis Mika Degree Program Institute of Automation and Control Viinikkala, Mika: Integration of automation design Software Ltd., Metso Automation, and TEKES Department of Automation June 2002 Keywords: System integration

  20. Participation through Automation: Fully Automated Critical PeakPricing in Commercial Buildings

    SciTech Connect (OSTI)

    Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Kiliccote,Sila; Linkugel, Eric

    2006-06-20T23:59:59.000Z

    California electric utilities have been exploring the use of dynamic critical peak prices (CPP) and other demand response programs to help reduce peaks in customer electric loads. CPP is a tariff design to promote demand response. Levels of automation in DR can be defined as follows: Manual Demand Response involves a potentially labor-intensive approach such as manually turning off or changing comfort set points at each equipment switch or controller. Semi-Automated Demand Response involves a pre-programmed demand response strategy initiated by a person via centralized control system. Fully Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. The receipt of the external signal initiates pre-programmed demand response strategies. They refer to this as Auto-DR. This paper describes the development, testing, and results from automated CPP (Auto-CPP) as part of a utility project in California. The paper presents the project description and test methodology. This is followed by a discussion of Auto-DR strategies used in the field test buildings. They present a sample Auto-CPP load shape case study, and a selection of the Auto-CPP response data from September 29, 2005. If all twelve sites reached their maximum saving simultaneously, a total of approximately 2 MW of DR is available from these twelve sites that represent about two million ft{sup 2}. The average DR was about half that value, at about 1 MW. These savings translate to about 0.5 to 1.0 W/ft{sup 2} of demand reduction. They are continuing field demonstrations and economic evaluations to pursue increasing penetrations of automated DR that has demonstrated ability to provide a valuable DR resource for California.

  1. Automated fiber pigtailing machine

    DOE Patents [OSTI]

    Strand, O.T.; Lowry, M.E.

    1999-01-05T23:59:59.000Z

    The Automated Fiber Pigtailing Machine (AFPM) aligns and attaches optical fibers to optoelectronic (OE) devices such as laser diodes, photodiodes, and waveguide devices without operator intervention. The so-called pigtailing process is completed with sub-micron accuracies in less than 3 minutes. The AFPM operates unattended for one hour, is modular in design and is compatible with a mass production manufacturing environment. This machine can be used to build components which are used in military aircraft navigation systems, computer systems, communications systems and in the construction of diagnostics and experimental systems. 26 figs.

  2. Methods for Multisweep Automation

    SciTech Connect (OSTI)

    SHEPHERD,JASON F.; MITCHELL,SCOTT A.; KNUPP,PATRICK; WHITE,DAVID R.

    2000-09-14T23:59:59.000Z

    Sweeping has become the workhorse algorithm for creating conforming hexahedral meshes of complex models. This paper describes progress on the automatic, robust generation of MultiSwept meshes in CUBIT. MultiSweeping extends the class of volumes that may be swept to include those with multiple source and multiple target surfaces. While not yet perfect, CUBIT's MultiSweeping has recently become more reliable, and been extended to assemblies of volumes. Sweep Forging automates the process of making a volume (multi) sweepable: Sweep Verification takes the given source and target surfaces, and automatically classifies curve and vertex types so that sweep layers are well formed and progress from sources to targets.

  3. Automated fiber pigtailing machine

    DOE Patents [OSTI]

    Strand, Oliver T. (Castro Valley, CA); Lowry, Mark E. (Castro Valley, CA)

    1999-01-01T23:59:59.000Z

    The Automated Fiber Pigtailing Machine (AFPM) aligns and attaches optical fibers to optoelectonic (OE) devices such as laser diodes, photodiodes, and waveguide devices without operator intervention. The so-called pigtailing process is completed with sub-micron accuracies in less than 3 minutes. The AFPM operates unattended for one hour, is modular in design and is compatible with a mass production manufacturing environment. This machine can be used to build components which are used in military aircraft navigation systems, computer systems, communications systems and in the construction of diagnostics and experimental systems.

  4. Towards Automated Service Composition using Policy Ontology in Building Automation System

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Towards Automated Service Composition using Policy Ontology in Building Automation System Son N.crespi}@it-sudparis.eu Abstract--Automated service composition is critical for suc- cessfully implementing Building Automation-service composition; semantic web; policy; ontol- ogy; building automation system; I. INTRODUCTION In building

  5. L3 Informatique Automates et langages formels 4 mars 2009 TD 5 : Automates `a pile

    E-Print Network [OSTI]

    Schmitz, Sylvain

    L3 Informatique Automates et langages formels 4 mars 2009 TD 5 : Automates `a pile Exercice 1 (Exemples d'automates `a pile). Donner un automate `a pile A = Q, , Z, T, q0, z0, F pour chacun des trois pile. Montrer que l'on peut construire un automate `a pile A ´equivalent avec une relation de

  6. ABV-A Low Speed Automation Project to Study the Technical Feasibility of Fully Automated Driving

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    on vehicle automation since many years. From 1987 to 1995 the European Commission funded the 800 million concepts of vehicles designed as fully automated vehicles [1]. Beyond its fully automation ability Automated Highway System Consortium (NAHSC) that demonstrated about 20 automated vehicles in Demo'97 on I-15

  7. Communication in automation, including networking and wireless

    E-Print Network [OSTI]

    Antsaklis, Panos

    Communication in automation, including networking and wireless Nicholas Kottenstette and Panos J and networking in automation is given. Digital communication fundamentals are reviewed and networked control are presented. 1 Introduction 1.1 Why communication is necessary in automated systems Automated systems use

  8. automated on-line separation-preconcentration: Topics by E-print...

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

    Automation 12;Test Automation Outline Test Automation Mousavi: Test Automation 12;Test Automation Why? Challenges of Manual Testing Test-case design: Choosing inputs Mousavi,...

  9. automated on-line solvent: Topics by E-print Network

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

    Automation 12;Test Automation Outline Test Automation Mousavi: Test Automation 12;Test Automation Why? Challenges of Manual Testing Test-case design: Choosing inputs Mousavi,...

  10. Robust automated knowledge capture.

    SciTech Connect (OSTI)

    Stevens-Adams, Susan Marie; Abbott, Robert G.; Forsythe, James Chris; Trumbo, Michael Christopher Stefan; Haass, Michael Joseph; Hendrickson, Stacey M. Langfitt

    2011-10-01T23:59:59.000Z

    This report summarizes research conducted through the Sandia National Laboratories Robust Automated Knowledge Capture Laboratory Directed Research and Development project. The objective of this project was to advance scientific understanding of the influence of individual cognitive attributes on decision making. The project has developed a quantitative model known as RumRunner that has proven effective in predicting the propensity of an individual to shift strategies on the basis of task and experience related parameters. Three separate studies are described which have validated the basic RumRunner model. This work provides a basis for better understanding human decision making in high consequent national security applications, and in particular, the individual characteristics that underlie adaptive thinking.

  11. Participation through Automation: Fully Automated Critical Peak Pricing in Commercial Buildings

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Kiliccote, Sila; Linkugel, Eric

    2006-01-01T23:59:59.000Z

    Figure 2. Demand Response Automation Server and BuildingII system to notify the Automation Server of an up comingoccurs day-ahead). 2. The Automation Server posts two pieces

  12. Automation of Termination: Abstracting CCG through MWG Automation of Termination: Abstracting Calling

    E-Print Network [OSTI]

    Ayala-Rincn, Mauricio

    Automation of Termination: Abstracting CCG through MWG Automation of Termination: Abstracting of Termination: Abstracting CCG through MWG Motivation Termination analysis is a fundamental topic in computer science. While classical results state the undecidability of various termination problems, automated

  13. Home Network Technologies and Automating Demand Response

    SciTech Connect (OSTI)

    McParland, Charles

    2009-12-01T23:59:59.000Z

    Over the past several years, interest in large-scale control of peak energy demand and total consumption has increased. While motivated by a number of factors, this interest has primarily been spurred on the demand side by the increasing cost of energy and, on the supply side by the limited ability of utilities to build sufficient electricity generation capacity to meet unrestrained future demand. To address peak electricity use Demand Response (DR) systems are being proposed to motivate reductions in electricity use through the use of price incentives. DR systems are also be design to shift or curtail energy demand at critical times when the generation, transmission, and distribution systems (i.e. the 'grid') are threatened with instabilities. To be effectively deployed on a large-scale, these proposed DR systems need to be automated. Automation will require robust and efficient data communications infrastructures across geographically dispersed markets. The present availability of widespread Internet connectivity and inexpensive, reliable computing hardware combined with the growing confidence in the capabilities of distributed, application-level communications protocols suggests that now is the time for designing and deploying practical systems. Centralized computer systems that are capable of providing continuous signals to automate customers reduction of power demand, are known as Demand Response Automation Servers (DRAS). The deployment of prototype DRAS systems has already begun - with most initial deployments targeting large commercial and industrial (C & I) customers. An examination of the current overall energy consumption by economic sector shows that the C & I market is responsible for roughly half of all energy consumption in the US. On a per customer basis, large C & I customers clearly have the most to offer - and to gain - by participating in DR programs to reduce peak demand. And, by concentrating on a small number of relatively sophisticated energy consumers, it has been possible to improve the DR 'state of the art' with a manageable commitment of technical resources on both the utility and consumer side. Although numerous C & I DR applications of a DRAS infrastructure are still in either prototype or early production phases, these early attempts at automating DR have been notably successful for both utilities and C & I customers. Several factors have strongly contributed to this success and will be discussed below. These successes have motivated utilities and regulators to look closely at how DR programs can be expanded to encompass the remaining (roughly) half of the state's energy load - the light commercial and, in numerical terms, the more important residential customer market. This survey examines technical issues facing the implementation of automated DR in the residential environment. In particular, we will look at the potential role of home automation networks in implementing wide-scale DR systems that communicate directly to individual residences.

  14. Aspects of automation mode confusion

    E-Print Network [OSTI]

    Wheeler, Paul H. (Paul Harrison)

    2007-01-01T23:59:59.000Z

    Complex systems such as commercial aircraft are difficult for operators to manage. Designers, intending to simplify the interface between the operator and the system, have introduced automation to assist the operator. In ...

  15. A Survey of Automated Deduction

    E-Print Network [OSTI]

    Bundy, Alan

    We survey research in the automation of deductive inference, from its beginnings in the early history of computing to the present day. We identify and describe the major areas of research interest and their applications. ...

  16. Automated Assembly Using Feature Localization

    E-Print Network [OSTI]

    Gordon, Steven Jeffrey

    1986-12-01T23:59:59.000Z

    Automated assembly of mechanical devices is studies by researching methods of operating assembly equipment in a variable manner; that is, systems which may be configured to perform many different assembly operations ...

  17. Facilities Automation and Energy Management

    E-Print Network [OSTI]

    Jen, D. P.

    1983-01-01T23:59:59.000Z

    Computerized facilities automation and energy management systems can be used to maintain high levels of facilities operations efficiencies. The monitoring capabilities provides the current equipment and process status, and the analysis...

  18. Role of Standard Demand Response Signals for Advanced Automated Aggregation

    E-Print Network [OSTI]

    Kiliccote, Sila

    2013-01-01T23:59:59.000Z

    for the Open Automated Demand Response (OpenADR) StandardsControl for Automated Demand Response, Grid Interop, 2009. [C. McParland, Open Automated Demand Response Communications

  19. Scenarios for Consuming Standardized Automated Demand Response Signals

    E-Print Network [OSTI]

    Koch, Ed

    2009-01-01T23:59:59.000Z

    of Fully Automated Demand Response in Large Facilities.Fully Automated Demand Response Tests in Large Facilities.Interoperable Automated Demand Response Infrastructure.

  20. Open Automated Demand Response for Small Commerical Buildings

    E-Print Network [OSTI]

    Dudley, June Han

    2009-01-01T23:59:59.000Z

    ofFullyAutomatedDemand ResponseinLargeFacilities. FullyAutomatedDemandResponseTestsinLargeFacilities. OpenAutomated DemandResponseCommunicationStandards:

  1. automation simulation system: Topics by E-print Network

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

    and the future expectations and challenges in process automation and power system automation. Anannya Mukherjee 9 Emergency Vehicle Maneuvers and Control Laws for Automated...

  2. Program Assistant (Office Automation)

    Broader source: Energy.gov [DOE]

    The Office of Science is the single largest supporter of basic research in the physical sciences in the United States, providing more than 40 percent of total funding for this vital area of...

  3. European Union Energy Performance of Building Directive and the Impact of Building Automation on Energy Efficiency

    E-Print Network [OSTI]

    Wirth, U.

    2008-01-01T23:59:59.000Z

    Gubelstrasse 22 CH-6301 Zug 00 41 41/ 7 24 55 60 wirth.ulrich@siemens.com European Union Energy Performance of Buildings Directive and The impact of Building Automation on Energy Efficiency Buildings account for 40 percent of global energy... building automation and control and technical building management based on the same may provide a demonstrable contribution to EU savings goals of 20 percent by 2020. The goal of European Directive 2002/91/EC on the total energy efficiency of buildings...

  4. Total Light Management

    Broader source: Energy.gov [DOE]

    Presentation covers total light management, and is given at the Spring 2010 Federal Utility Partnership Working Group (FUPWG) meeting in Providence, Rhode Island.

  5. Total Space Heat-

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

    Commercial Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration...

  6. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings...

  7. Author manuscript, published in "International Conference on Information Fusion (2013)" An Ontology-based Model to Determine the Automation Level of an Automated Vehicle for Co-Driving

    E-Print Network [OSTI]

    Evangeline Pollard; Fawzi Nashashibi

    2013-01-01T23:59:59.000Z

    AbstractFull autonomy of ground vehicles is a major goal of the ITS (Intelligent Transportation Systems) community. However, reaching such highest autonomy level in all situations (weather, traffic,...) may seem difficult in practice, despite recent results regarding driverless cars (e.g., Google Cars). In addition, an automated vehicle should also self-assess its own perception abilities, and not only perceive its environment. In this paper, we propose an intermediate approach towards full automation, by defining a spectrum of automation layers, from fully manual (the car is driven by a driver) to fully automated (the car is driven by a computer), based on an ontological model for representing knowledge. We also propose a second ontology for situation assessment (what does the automated car perceive?), including the sensors/actuators state, environmental conditions and drivers state. Finally, we also define inference rules to link the situation assessment ontology to the automation level one. Both ontological models have been built and first results are presented. I.

  8. Automation in image cytometry : continuous HCS and kinetic image cytometry

    E-Print Network [OSTI]

    Charlot, David J.

    2012-01-01T23:59:59.000Z

    OF CALIFORNIA, SAN DIEGO Automation in Image Cytometry:xiv Abstract of Dissertation Automation in Image Cytometry:

  9. Automated Demand Response Opportunities in Wastewater Treatment Facilities

    E-Print Network [OSTI]

    Thompson, Lisa

    2008-01-01T23:59:59.000Z

    Interoperable Automated Demand Response Infrastructure,study of automated demand response in wastewater treatmentopportunities for demand response control strategies in

  10. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    Linking Continuous Energy Management and Open AutomatedKeywords: Continuous Energy Management, Automated Demandlinking continuous energy management and continuous

  11. 2013 Faculty Publications A Cloud-Based Framework for Automating MODFLOW Simulations for Aquifer Management

    E-Print Network [OSTI]

    Olsen Jr., Dan R.

    2013 Faculty Publications A Cloud-Based Framework for Automating MODFLOW Simulations for Aquifer Performance-Based Liquefaction Triggering Models for the SPT. Seismological Society of America 2013 Annual. A Simplified Uniform Hazard Liquefaction Analysis Procedure for Bridges. Transportation Research Record. Kevin

  12. Disciplined agility for process control & automation

    E-Print Network [OSTI]

    Tibazarwa, Augustine

    2009-01-01T23:59:59.000Z

    Process automation vendors must consider agility as a basis to gain a competitive edge in innovation. Process Automation systems can impact the operating cost of manufacturing equipment, the safe control of large quantities ...

  13. Technical University of Denmark rsted DTU Automation

    E-Print Network [OSTI]

    Technical University of Denmark ?rsted · DTU Automation Project: SICAM - SIngle Conversion stage based SICAM using an LC-network Petar Ljusev, MSc., Ph.D. student, ?rsted · DTU Automation e-mail: pl

  14. The Automation Of Proof By Mathematical Induction

    E-Print Network [OSTI]

    Bundy, Alan

    This paper is a chapter of the Handbook of Automated Reasoning edited by Voronkov and Robinson. It describes techniques for automated reasoning in theories containing rules of mathematical induction. Firstly, inductive reasoning is defined and its...

  15. Technical University of Denmark rsted DTU Automation

    E-Print Network [OSTI]

    Technical University of Denmark ?rsted · DTU Automation Project: SICAM - SIngle Conversion stage, ?rsted · DTU Automation e-mail: pl@oersted.dtu.dk Abstract In this report an isolated PWM DC-AC SICAM

  16. INTRODUCTION Sophisticated automation is becoming ubiq-

    E-Print Network [OSTI]

    Lee, John D.

    INTRODUCTION Sophisticated automation is becoming ubiq- uitous, appearing in work environments as di- verse as aviation, maritime operations, process control, motor vehicle operation, and informa- tion retrieval. Automation is technology that actively selects data, transforms information, makes

  17. TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 1 Automated Guiding Task of a Flexible Micropart

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 1 Automated Guiding Task of a Flexible Micropart Lutz, Member, IEEE Abstract--This paper studies automated tasks based on hybrid force/position control of automated guiding task are presented. Note to Practitioners -- This article's motivation is the need of very

  18. An Ontology-based Model to Determine the Automation Level of an Automated Vehicle for

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    An Ontology-based Model to Determine the Automation Level of an Automated Vehicle for Co). In addition, an automated vehicle should also self-assess its own perception abilities, and not only perceive this idea, cybercars were designed as fully automated vehicles [3], thought since its inception as a new

  19. Automated Immobilized Metal Affinity Chromatography System for...

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

    Immobilized Metal Affinity Chromatography System for Enrichment of Escherichia coli Phosphoproteome. Automated Immobilized Metal Affinity Chromatography System for Enrichment of...

  20. SUSTAINABLE TRANSPORTATION ENERGY PATHWAYS A Research Summary for Decision Makers

    E-Print Network [OSTI]

    California at Davis, University of

    the total CO2 -equivalent GHG emissions from the entire transportation sector on a full fuel-cycle basis

  1. Local Transportation

    E-Print Network [OSTI]

    Local Transportation. Transportation from the Airport to Hotel. There are two types of taxi companies that operate at the airport: special and regular taxis (

  2. Greening Transportation

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

    Transportation Goal 2: Greening Transportation LANL supports and encourages employees to reduce their personal greenhouse gas emissions by offering various commuting and work...

  3. Total Synthesis of (?)-Himandrine

    E-Print Network [OSTI]

    Movassaghi, Mohammad

    We describe the first total synthesis of (?)-himandrine, a member of the class II galbulimima alkaloids. Noteworthy features of this chemistry include a diastereoselective Diels?Alder reaction in the rapid synthesis of the ...

  4. INTEGRATING AUTOMATION DESIGN INFORMATION WITH XML

    E-Print Network [OSTI]

    INTEGRATING AUTOMATION DESIGN INFORMATION WITH XML Mika Viinikkala, Seppo Kuikka Institute of Automation and Control, Tampere University of Technology, P.O. Box 692, 33101 Tampere, Finland Email: mika.viinikkala@tut.fi, seppo.kuikka@tut.fi Keywords: Systems integration, XML, automation design Abstract: This paper presents

  5. Comparison lamps automation CTIO 60 inches Echelle

    E-Print Network [OSTI]

    Tokovinin, Andrei A.

    Comparison lamps automation CTIO 60 inches Echelle ECH60S5.1 La Serena, December 09, 2009 #12)...............................................................................12 CTIO 60 inches Echelle / Comparison lamps automation, ECH60S5.1 2 #12;Introduction The present document is just a brief summary of the work done automating the 60 inches echelle comparison lamps

  6. TAMPERE UNIVERSITY OF TECHNOLOGY DEPARTMENT OF AUTOMATION

    E-Print Network [OSTI]

    TAMPERE UNIVERSITY OF TECHNOLOGY DEPARTMENT OF AUTOMATION An Intelligent Web Service for Operation 2004 Examiner: Prof. Seppo Kuikka #12;2 Abstract TAMPERE UNIVERSITY OF TECHNOLOGY Automation Degree Program Institute of Automation and Control Jaakkola, Veli-Pekka: An Intelligent Web Service for Operation

  7. Comparison lamps automation CTIO 60 inches CHIRON

    E-Print Network [OSTI]

    Tokovinin, Andrei A.

    Comparison lamps automation CTIO 60 inches CHIRON CHI60HF5.2 La Serena, March 16, 2011 #12;Table)...............................................................................12 CTIO 60 inches Chiron / Comparison lamps automation, CHI60HF5.2 2 #12;Introduction The present document is just a brief summary of the work done automating the 60 inches chiron comparison lamps

  8. Prparation l'agrgation Automates pile

    E-Print Network [OSTI]

    Schmitz, Sylvain

    Préparation à l'agrégation Automates à pile Exercice 1 (Exemples de langages reconnus par automate à pile) Montrer que les langages suivants sont reconnus par automate à pile : 1. Le langage de Dyck. 2. {an bp | 0 pile) 1. Montrer que

  9. Automated Purge Valve Joseph Edward Farrell, III.

    E-Print Network [OSTI]

    Wood, Stephen L.

    Automated Purge Valve by Joseph Edward Farrell, III. Bachelor of Science Marine Engineering the undersigned committee hereby approve the attached thesis Automated Purge Valve by Joseph Edward Farrell, III.D. Department Head Department of Marine and Environmental Systems #12;iii Abstract Title: Automated Purge Valve

  10. AUTOMATED CRITICAL PEAK PRICING FIELD TESTS

    E-Print Network [OSTI]

    ) for development of the DR Automation Server System This project could not have been completed without extensive: Greg Watson and Mark Lott C&C Building Automation: Mark Johnson and John Fiegel Chabot Space AUTOMATED CRITICAL PEAK PRICING FIELD TESTS: 2006 PROGRAM DESCRIPTION AND RESULTS

  11. Automated packing systems: Review of industrial implementations.

    E-Print Network [OSTI]

    Whelan, Paul F.

    Automated packing systems: Review of industrial implementations. Paul F. Whelan School in these applications. An outline of one such industrial application, the automated placement of shape templates Mathematics University of Wales Cardiff, Wales. ABSTRACT The problems involved in the automated packing

  12. Chamber transport

    SciTech Connect (OSTI)

    OLSON,CRAIG L.

    2000-05-17T23:59:59.000Z

    Heavy ion beam transport through the containment chamber plays a crucial role in all heavy ion fusion (HIF) scenarios. Here, several parameters are used to characterize the operating space for HIF beams; transport modes are assessed in relation to evolving target/accelerator requirements; results of recent relevant experiments and simulations of HIF transport are summarized; and relevant instabilities are reviewed. All transport options still exist, including (1) vacuum ballistic transport, (2) neutralized ballistic transport, and (3) channel-like transport. Presently, the European HIF program favors vacuum ballistic transport, while the US HIF program favors neutralized ballistic transport with channel-like transport as an alternate approach. Further transport research is needed to clearly guide selection of the most attractive, integrated HIF system.

  13. EBS Radionuclide Transport Abstraction

    SciTech Connect (OSTI)

    J. Prouty

    2006-07-14T23:59:59.000Z

    The purpose of this report is to develop and analyze the engineered barrier system (EBS) radionuclide transport abstraction model, consistent with Level I and Level II model validation, as identified in Technical Work Plan for: Near-Field Environment and Transport: Engineered Barrier System: Radionuclide Transport Abstraction Model Report Integration (BSC 2005 [DIRS 173617]). The EBS radionuclide transport abstraction (or EBS RT Abstraction) is the conceptual model used in the total system performance assessment (TSPA) to determine the rate of radionuclide releases from the EBS to the unsaturated zone (UZ). The EBS RT Abstraction conceptual model consists of two main components: a flow model and a transport model. Both models are developed mathematically from first principles in order to show explicitly what assumptions, simplifications, and approximations are incorporated into the models used in the TSPA. The flow model defines the pathways for water flow in the EBS and specifies how the flow rate is computed in each pathway. Input to this model includes the seepage flux into a drift. The seepage flux is potentially split by the drip shield, with some (or all) of the flux being diverted by the drip shield and some passing through breaches in the drip shield that might result from corrosion or seismic damage. The flux through drip shield breaches is potentially split by the waste package, with some (or all) of the flux being diverted by the waste package and some passing through waste package breaches that might result from corrosion or seismic damage. Neither the drip shield nor the waste package survives an igneous intrusion, so the flux splitting submodel is not used in the igneous scenario class. The flow model is validated in an independent model validation technical review. The drip shield and waste package flux splitting algorithms are developed and validated using experimental data. The transport model considers advective transport and diffusive transport from a breached waste package. Advective transport occurs when radionuclides that are dissolved or sorbed onto colloids (or both) are carried from the waste package by the portion of the seepage flux that passes through waste package breaches. Diffusive transport occurs as a result of a gradient in radionuclide concentration and may take place while advective transport is also occurring, as well as when no advective transport is occurring. Diffusive transport is addressed in detail because it is the sole means of transport when there is no flow through a waste package, which may dominate during the regulatory compliance period in the nominal and seismic scenarios. The advective transport rate, when it occurs, is generally greater than the diffusive transport rate. Colloid-facilitated advective and diffusive transport is also modeled and is presented in detail in Appendix B of this report.

  14. Total Energy Monitor

    SciTech Connect (OSTI)

    Friedrich, S

    2008-08-11T23:59:59.000Z

    The total energy monitor (TE) is a thermal sensor that determines the total energy of each FEL pulse based on the temperature rise induced in a silicon wafer upon absorption of the FEL. The TE provides a destructive measurement of the FEL pulse energy in real-time on a pulse-by-pulse basis. As a thermal detector, the TE is expected to suffer least from ultra-fast non-linear effects and to be easy to calibrate. It will therefore primarily be used to cross-calibrate other detectors such as the Gas Detector or the Direct Imager during LCLS commissioning. This document describes the design of the TE and summarizes the considerations and calculations that have led to it. This document summarizes the physics behind the operation of the Total Energy Monitor at LCLS and derives associated engineering specifications.

  15. Automated Transportation Logistics and Analysis System (ATLAS) | Department

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33Frequently20,000 RussianBy:WhetherNovember 13, 2009 Management(UpdatedInsulated Cladding Systems

  16. Automated Transportation Logistics and Analysis System (ATLAS) | Department

    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 FutureComments from TarasaName4ServicesTribalWorkplaceAutomatedof Energy

  17. Total Precipitable Water

    SciTech Connect (OSTI)

    None

    2012-01-01T23:59:59.000Z

    The simulation was performed on 64K cores of Intrepid, running at 0.25 simulated-years-per-day and taking 25 million core-hours. This is the first simulation using both the CAM5 physics and the highly scalable spectral element dynamical core. The animation of Total Precipitable Water clearly shows hurricanes developing in the Atlantic and Pacific.

  18. Specimen coordinate automated measuring machine/fiducial automated measuring machine

    DOE Patents [OSTI]

    Hedglen, Robert E. (Bethel Park, PA); Jacket, Howard S. (Pittsburgh, PA); Schwartz, Allan I. (Turtle Creek, PA)

    1991-01-01T23:59:59.000Z

    The Specimen coordinate Automated Measuring Machine (SCAMM) and the Fiducial Automated Measuring Machine (FAMM) is a computer controlled metrology system capable of measuring length, width, and thickness, and of locating fiducial marks. SCAMM and FAMM have many similarities in their designs, and they can be converted from one to the other without taking them out of the hot cell. Both have means for: supporting a plurality of samples and a standard; controlling the movement of the samples in the +/- X and Y directions; determining the coordinates of the sample; compensating for temperature effects; and verifying the accuracy of the measurements and repeating as necessary. SCAMM and FAMM are designed to be used in hot cells.

  19. "Utility Characteristics",,,,,,"Number AMR- Automated Meter Reading",,,,,"Number AMI- Advanced Metering Infrastructure",,,,,"Non AMR/AMI Meters",,,,,"Total Numbers of Meters",,,,,"Energy Served - AMI (MWh)"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home 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,1Stocksa. AppliancesTotal"1" "Shell1.

  20. "Utility Characteristics",,,,,,"Number AMR- Automated Meter Reading",,,,,"Number AMI- Advanced Metering Infrastructure",,,,,"Non AMR/AMI Meters1",,,,,"Total Numbers of Meters",,,,,"Energy Served - AMI (MWh)"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home 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,1Stocksa. AppliancesTotal"1"

  1. Automated nutrient analyses in seawater

    SciTech Connect (OSTI)

    Whitledge, T.E.; Malloy, S.C.; Patton, C.J.; Wirick, C.D.

    1981-02-01T23:59:59.000Z

    This manual was assembled for use as a guide for analyzing the nutrient content of seawater samples collected in the marine coastal zone of the Northeast United States and the Bering Sea. Some modifications (changes in dilution or sample pump tube sizes) may be necessary to achieve optimum measurements in very pronounced oligotrophic, eutrophic or brackish areas. Information is presented under the following section headings: theory and mechanics of automated analysis; continuous flow system description; operation of autoanalyzer system; cookbook of current nutrient methods; automated analyzer and data analysis software; computer interfacing and hardware modifications; and trouble shooting. The three appendixes are entitled: references and additional reading; manifold components and chemicals; and software listings. (JGB)

  2. Automated Demand Response and Commissioning

    SciTech Connect (OSTI)

    Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

    2005-04-01T23:59:59.000Z

    This paper describes the results from the second season of research to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve the electric grid reliability and manage electricity costs. Fully-Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. We refer to this as Auto-DR. The evaluation of the control and communications must be properly configured and pass through a set of test stages: Readiness, Approval, Price Client/Price Server Communication, Internet Gateway/Internet Relay Communication, Control of Equipment, and DR Shed Effectiveness. New commissioning tests are needed for such systems to improve connecting demand responsive building systems to the electric grid demand response systems.

  3. Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response

    E-Print Network [OSTI]

    Kiliccote, Sila

    2011-01-01T23:59:59.000Z

    program,demand responseaggregator,demandresponse viiWITH AN AGGREGATOR USING OPEN AUTOMATED DEMAND RESPONSE ThisWithanAggregatorUsingOpenAutomatedDemandResponseis

  4. The effects of level of automation and adaptive automation on human performance, situation awareness and workload in a

    E-Print Network [OSTI]

    Kaber, David B.

    The effects of level of automation and adaptive automation on human performance, situation., 4731 East Forest Peak, Marietta, GA 30066, USA Keywords: Level of automation (LOA); adaptive automation of automation (LOAs) for maintaining operator involvement in complex systems control and facilitating situation

  5. TotalView Training

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengthening a solidSynthesisAppliances » Top InnovativeTopoisomeraseTotalView

  6. Comparative analyses of spent nuclear fuel transport modal options: Transport options under existing site constraints

    SciTech Connect (OSTI)

    Brentlinger, L.A.; Hofmann, P.L.; Peterson, R.W.

    1989-08-01T23:59:59.000Z

    The movement of nuclear waste can be accomplished by various transport modal options involving different types of vehicles, transport casks, transport routes, and intermediate intermodal transfer facilities. A series of systems studies are required to evaluate modal/intermodal spent fuel transportation options in a consistent fashion. This report provides total life-cycle cost and life-cycle dose estimates for a series of transport modal options under existing site constraints. 14 refs., 7 figs., 28 tabs.

  7. Thorie des Langages -TD 7 AUTOMATES PILE

    E-Print Network [OSTI]

    Bonzon, Elise

    Théorie des Langages - TD 7 AUTOMATES ? PILE Exercice 1 - Donnez deux automates à pile (acceptation par pile vide ; par état final) qui reconnaissent chacun des langages suivants : 1. L1 = {anbm|n,m 0 l'automate à pile suivant reconnaissant le langage L par état final : 0 1 3 2 a, Z0/AZ0 , A/ a, A

  8. Automated micro-tracking planar solar concentrators

    E-Print Network [OSTI]

    Hallas, Justin Matthew

    2011-01-01T23:59:59.000Z

    E. Ford, Reactive self-tracking solar concentration: designFord, Reactive self- tracking solar concentration: designAutomated Micro-Tracking Planar Solar Concentrators by

  9. Automated Continuous Commissioning of Commercial Buildings

    E-Print Network [OSTI]

    Bailey, Trevor

    2013-01-01T23:59:59.000Z

    Conference on Building Commissioning. San Francisco, CA. 17.Commercial Buildings Commissioning, LBNL- 56637, Nov. 2004.Automated Continuous Commissioning Tool GUI Screenshots from

  10. LANL to certify automated influenza surveillance system

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

    will design the automated high-throughput extraction and screening system for a prototype Global Bio Lab-a compact, modular laboratory that can reliably process thousands of...

  11. Safety Analysis Of Automated Highway Systems

    E-Print Network [OSTI]

    Leveson, Nancy G.

    1997-01-01T23:59:59.000Z

    Lee. Towards an automated fmea assis- tant. In Applicationsmodes and effects analysis (FMEA) is employed to determineof multiple failures. ) FMEA was developed Potential Part

  12. Honeywell Demonstrates Automated Demand Response Benefits for...

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

    Honeywell's Smart Grid Investment Grant (SGIG) project demonstrates utility-scale performance of a hardwaresoftware platform for automated demand response (ADR). This project...

  13. Architectures of Test Automation Copyright Cem Kaner, 2000. All rights reserved. 1 Architectures of Test Automation

    E-Print Network [OSTI]

    Architectures of Test Automation Copyright © Cem Kaner, 2000. All rights reserved. 1 Architectures of Test Automation Copyright © August, 2000 Cem Kaner, kaner@kaner.com Acknowledgement Many of the ideas in this presentation were jointly developed with Doug Hoffman, in a course that we taught together on test automation

  14. REMOTE LABORATORIES IN AUTOMATION: AIP-PRIMECA RAO ARI PLATFORM Remote Laboratories in Automation

    E-Print Network [OSTI]

    Paris-Sud XI, Universit de

    for thorough trainings in industrial We thank our sponsors : Schneider Electric which provided the automationREMOTE LABORATORIES IN AUTOMATION: AIP-PRIMECA RAO ARI PLATFORM Remote Laboratories in Automation of resources and competencies about industrial topics for many universities in Rhne-Alpes french Region. Due

  15. automated breast mass: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  16. automated basic driving: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  17. automated plate assay: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  18. automated endothelial keratoplasty: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  19. automated speed enforcement: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  20. automation study aids: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  1. automated fiber pigtailing: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  2. automated chemiluminescence immunoassays: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  3. automated quantitative nuclear: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  4. automated blood culture: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  5. automated potentiometric titrations: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  6. automating eccs switchover: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  7. automated sampling assessment: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  8. automated mounter enabling: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  9. automated personal dosimetry: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  10. automated checkin: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  11. automated elution time: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  12. automated enzyme immunoassays: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  13. automated edman degradation: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  14. automated air sampling: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  15. automated liquid handler: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  16. automated cytogenetic biodosimetry: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  17. automated endothelial keratoplastydsaek: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  18. automating breast radiation: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  19. automated liquid handlers: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  20. automated sample preparation: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  1. automated sample mounting: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  2. automated immunoradiometric assay: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  3. automated urine microscopy: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  4. automating collateral evolutions: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  5. automated affymetrix expression: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  6. automated pulmonary fissure: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  7. automated container terminal: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  8. automated peritoneal dialysis: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  9. automated gas tonometric: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  10. automated blood sampling: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  11. ammos automated molecular: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  12. automated steel cleanliness: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  13. automated nucleophilic 18ffluorination: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  14. automated pressure-controlled discography: Topics by E-print...

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  15. automated clearance: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  16. automated radiometric technic: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  17. automated sample transfer: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  18. automated procalcitonin assay: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  19. automated hot embossing: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  20. automated dose dispensing: Topics by E-print Network

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

    Websites Summary: of a partial automation since they act on the control part of the vehicle. This increasing automationABV- A Low Speed Automation Project to Study the...

  1. Reference Model for Control and Automation Systems in Electrical...

    Office of Environmental Management (EM)

    Model for Control and Automation Systems in Electrical Power (October 2005) Reference Model for Control and Automation Systems in Electrical Power (October 2005) Modern...

  2. ISA Approves Standard for Wireless Automation in Process Control...

    Energy Savers [EERE]

    ISA Approves Standard for Wireless Automation in Process Control Applications ISA Approves Standard for Wireless Automation in Process Control Applications On September 9, the...

  3. V-132: IBM Tivoli System Automation Application Manager Multiple...

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

    IBM has acknowledged multiple vulnerabilities in IBM Tivoli System Automation Application Manager PLATFORM: The vulnerabilities are reported in IBM Tivoli System Automation...

  4. Small- and Medium-Size Building Automation and Control System...

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

    Small- and Medium-Size Building Automation and Control System Needs: Scoping Study Small- and Medium-Size Building Automation and Control System Needs: Scoping Study Emerging...

  5. Open Automated Demand Response Communications Specification (Version 1.0)

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    and Techniques for Demand Response. May 2007. LBNL-59975.tofacilitateautomating demandresponseactionsattheInteroperable Automated Demand Response Infrastructure,

  6. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01T23:59:59.000Z

    Goodin. 2009. Open Automated Demand Response Communicationsin Demand Response for Wholesale Ancillary Services. InOpen Automated Demand Response Demonstration Project. LBNL-

  7. SciTech Connect: Multiplex automated genome engineering

    Office of Scientific and Technical Information (OSTI)

    Multiplex automated genome engineering Citation Details In-Document Search Title: Multiplex automated genome engineering You are accessing a document from the Department of...

  8. automated guideway transit: Topics by E-print Network

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

    Automated Data Collection Systems, such as Automated Fare Collection (AFC) and Automatic Vehicle Location (AVL), provides ... Schil, Mickal (Mickal Ren Jerme) 2012-01-01...

  9. automated file management: Topics by E-print Network

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

    OverviewManaged Lanes OverviewManaged Lanes OverviewManaged Lanes Overview 2012 Road Vehicle Automation Workshop2012 Road Vehicle Automation Workshop Engineering Websites...

  10. automated toll collection: Topics by E-print Network

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

    Automated Data Collection Systems, such as Automated Fare Collection (AFC) and Automatic Vehicle Location (AVL), provides ... Schil, Mickal (Mickal Ren Jerme) 2012-01-01...

  11. automated concise extraction: Topics by E-print Network

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

    of Computer Science, Bar-Ilan University, Ramat-Gan 52900, Israel 4 Center for Automation Research, University of Maryland Plaza, Antonio J. 5 Automated Pointcut Extraction...

  12. automated rna extraction: Topics by E-print Network

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

    of Computer Science, Bar-Ilan University, Ramat-Gan 52900, Israel 4 Center for Automation Research, University of Maryland Plaza, Antonio J. 5 Automated Pointcut Extraction...

  13. automated relation extraction: Topics by E-print Network

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

    of Computer Science, Bar-Ilan University, Ramat-Gan 52900, Israel 4 Center for Automation Research, University of Maryland Plaza, Antonio J. 6 Automated Pointcut Extraction...

  14. automated ammunition logistics: Topics by E-print Network

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

    major industrial accident. The origin times and number of explosions were key 3 Test Automation Test Automation Computer Technologies and Information Sciences Websites Summary:...

  15. Inventors in Action: Composites and Automation | GE Global Research

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

    Composite Materials and Automation Inventors in Action: Composite Materials and Automation As our composite materials evolve, our manufacturing processes do too. A new class of...

  16. An automated tool for three types of saturated hydraulic conductivity...

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

    automated tool for three types of saturated hydraulic conductivity laboratory measurements. An automated tool for three types of saturated hydraulic conductivity laboratory...

  17. automated analysis tool: Topics by E-print Network

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

    and Information Sciences Websites Summary: automating tools or an open source DBMS whose lack of automated tools might increase the operational cost their benefits. We...

  18. automated words stability: Topics by E-print Network

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

    Coach that Listens: Automated Detection Mostow, Jack 38 Model-driven Automated Software FMEA Neal Snooke, PhD, Aberystwyth University Computer Technologies and Information Sciences...

  19. automated visual fields: Topics by E-print Network

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

    Approach to Sensor Selection- prehensive automated Failure Modes and Effects Analysis (FMEA) using qualitative model based reasoning au- tonomous aircraft. Automated failure mode...

  20. automated motif analysis: Topics by E-print Network

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

    Approach to Sensor Selection- prehensive automated Failure Modes and Effects Analysis (FMEA) using qualitative model based reasoning au- tonomous aircraft. Automated failure mode...

  1. analysis automation caa: Topics by E-print Network

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

    Approach to Sensor Selection- prehensive automated Failure Modes and Effects Analysis (FMEA) using qualitative model based reasoning au- tonomous aircraft. Automated failure mode...

  2. analysis automated perimetry: Topics by E-print Network

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

    Approach to Sensor Selection- prehensive automated Failure Modes and Effects Analysis (FMEA) using qualitative model based reasoning au- tonomous aircraft. Automated failure mode...

  3. automated risk analysis: Topics by E-print Network

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

    Approach to Sensor Selection- prehensive automated Failure Modes and Effects Analysis (FMEA) using qualitative model based reasoning au- tonomous aircraft. Automated failure mode...

  4. automated visual inspection: Topics by E-print Network

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

    Approach to Sensor Selection- prehensive automated Failure Modes and Effects Analysis (FMEA) using qualitative model based reasoning au- tonomous aircraft. Automated failure...

  5. automated quantitative analysis: Topics by E-print Network

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

    Approach to Sensor Selection- prehensive automated Failure Modes and Effects Analysis (FMEA) using qualitative model based reasoning au- tonomous aircraft. Automated failure...

  6. Open Automated Demand Response Communications Specification (Version 1.0)

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    Keywords:demandresponse,buildings,electricityuse,Interface AutomatedDemandResponse BuildingAutomationofdemandresponsein commercialbuildings. Onekey

  7. Open Automated Demand Response for Small Commerical Buildings

    E-Print Network [OSTI]

    Dudley, June Han

    2009-01-01T23:59:59.000Z

    Demand ResponseforSmallCommercialBuildings. CEC?500?automateddemandresponse Forsmallcommercialbuildings,AUTOMATED DEMAND RESPONSE FOR SMALL COMMERCIAL BUILDINGS

  8. Simulation And Visualization Of Automated Guided Vehicle Systems In A Real Production Environment

    E-Print Network [OSTI]

    Axel Hoff; Holger Vogelsang; Uwe Brinkschulte; Oliver Hammerschmidt

    1997-01-01T23:59:59.000Z

    Low-cost Automated Guided Vehicle Systems (AGVS) play an increasing role for the automation of production plants. For complex installations, a simulation of the transport system should be performed during the planning phase in order to check for possible problems and to optimize parameters. During operation of complex AGVS a visualization of the whole system is desirable in order to allow a continuous monitoring. Since most of the relevant tasks have to be performed for simulation and visualization as well, we constructed an integrated tool which is able to deal with both jobs. As an example for operation of the simulation tool, results are presented for the calculation of the number of vehicles for optimal performance of an AGVS given a layout and a transport matrix. OVERVIEW As mentioned above, low-cost Automated Guided Vehicle Systems (AGVS) play an increasing role for the automation of production plants since they can be used as a flexible assembly line (Muller 1993). In recent yea...

  9. 44 IEEE ROBOTICS & AUTOMATION MAGAZINE SEPTEMBER 2011 1070-9932/11/$26.002011 IEEE A Hybrid Control Approach

    E-Print Network [OSTI]

    Del Vecchio, Domitilla

    44 · IEEE ROBOTICS & AUTOMATION MAGAZINE · SEPTEMBER 2011 1070-9932/11/$26.00ª2011 IEEE A Hybrid Control Approach I ntelligent transportation systems (ITS) for in-vehicle cooperative active safety, and ultimately take control of the vehicle to prevent an otherwise certain collision. Several initiatives

  10. Automating An Industrial Power Plant

    E-Print Network [OSTI]

    Williams, D. R.; McCowen, R. R.

    1987-01-01T23:59:59.000Z

    and electricity requirements of the Component Works as well as all of the heat and a portion of the electricity needed by the adjacent John Deere Foundry. This paper describes the automation of an eXisting industrial power plant and tells how the project...AUTlliATING AN INDUSTRIAL POWER PLANT DAVID R. WILLIAMS, P.E. Energy Coordi?nator John Deere Component Works Waterloo, Iowa ABSTRACT The need for an upgrade of boiler and turbine controls in the 15 MW coal-fired cogeneration plant...

  11. Automated mass spectrometer grows up

    SciTech Connect (OSTI)

    McInteer, B.B.; Montoya, J.G.; Stark, E.E.

    1984-01-01T23:59:59.000Z

    In 1980 we reported the development of an automated mass spectrometer for large scale batches of samples enriched in nitrogen-15 as ammonium salts. Since that time significant technical progress has been made in the instrument. Perhaps more significantly, administrative and institutional changes have permitted the entire effort to be transferred to the private sector from its original base at the Los Alamos National Laboratory. This has ensured the continuance of a needed service to the international scientific community as revealed by a development project at a national laboratory, and is an excellent example of beneficial technology transfer to private industry.

  12. Chapter VIII Automated Overlay of Infrared

    E-Print Network [OSTI]

    Hopgood, Adrian

    166 Chapter VIII Automated Overlay of Infrared and Visual Medical Images G. Schaefer Aston written permission of IGI Global is prohibited. AbstrAct Medical infrared imaging captures the temperature a useful diagnostic visualisation for the clinician. #12;167 Automated Overlay of Infrared and Visual

  13. Technical University of Denmark rsted DTU Automation

    E-Print Network [OSTI]

    Technical University of Denmark ?rsted · DTU Automation Project: SICAM - SIngle Conversion stage;Isolated PDM and PWM DC-AC SICAMs Petar Ljusev, MSc., Ph.D. student, ?rsted · DTU Automation e-mail: pl

  14. Demand Response and Open Automated Demand Response

    E-Print Network [OSTI]

    LBNL-3047E Demand Response and Open Automated Demand Response Opportunities for Data Centers G described in this report was coordinated by the Demand Response Research Center and funded by the California. Demand Response and Open Automated Demand Response Opportunities for Data Centers. California Energy

  15. Trust Calibration for Automated Decision Aids

    E-Print Network [OSTI]

    McShea, Daniel W.

    March 2010 Trust Calibration for Automated Decision Aids Project Leads Maranda McBride, PhD, North in a system is poorly calibrated. "Calibration" is a term used to describe the process by which automated such as homeland security. Therefore, it is imperative that DMs' trust be calibrated so that they effectively use

  16. D Riso-R-429 Automated Uranium

    E-Print Network [OSTI]

    -induced delayed-neutron coun- ting is applied preferably in large geochemical exploration pro- grammes. UraniumCM i D Riso-R-429 Automated Uranium Analysis by Delayed-Neutron Counting H. Kunzendorf, L. Lvborg AUTOMATED URANIUM ANALYSIS BY DELAYED-NEUTRON COUNTING H. Kunzendorf, L. Lvborg and E.M. Christiansen

  17. Automated Eye-Movement Protocol Analysis

    E-Print Network [OSTI]

    Salvucci, Dario D.

    Automated Eye-Movement Protocol Analysis Dario D. Salvucci and John R. Anderson Carnegie Mellon analysis of eye-movement protocols. Although eye movements have be- come increasingly popular as a tool an ap- proach to automating eye-movement protocol analysis by means of tracing--re- lating observed eye

  18. PeopleSoft HR ECR Automation Process

    E-Print Network [OSTI]

    Huang, Jianyu

    PeopleSoft HR ECR Automation Process Short Term Disability with Pay May 2011 #12;Processing a Short Term Disability with Pay ECR Search Page To process a Short Term Disability using the automated ECR. 2. Enter the Effective Date of the Short Term Disability. This is the Effective Date

  19. Workload State Classification With Automation During Simulated

    E-Print Network [OSTI]

    Kaber, David B.

    Workload State Classification With Automation During Simulated Air Traffic Control David B. Kaber and Carlene M. Perry Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State to dynamically apply automation to information pro- cessing functions in aviation systems. This research examined

  20. Automated ConstraintBased Nucleotide Sequence Selection

    E-Print Network [OSTI]

    Gifford, David K.

    Automated Constraint­Based Nucleotide Sequence Selection for DNA Computation Alexander J. Hartemink computational melting temper­ ature primitive to search a ``nucleotide space'' for sequences satisfying a pre that offer the promise of an efficient method for selecting optimal nucleotide sequences in an automated

  1. Automated Constraint-Based Nucleotide Sequence Selection

    E-Print Network [OSTI]

    Gifford, David K.

    Automated Constraint-Based Nucleotide Sequence Selection for DNA Computation Alexander J. Hartemink computational melting temperature primitive to search a "nucleotide space" for sequences satisfying a pre that offer the promise of an efficient method for selecting optimal nucleotide sequences in an automated

  2. Computational Transportation

    E-Print Network [OSTI]

    Illinois at Chicago, University of

    ), in-vehicle computers, and computers in the transportation infrastructure are integrated ride- sharing, real-time multi-modal routing and navigation, to autonomous/assisted driving

  3. myCopter Enabling Technologies for Personal Aerial Transportation Systems

    E-Print Network [OSTI]

    towards a Personal Aerial Transportation System, in which vehicles would also have vertical space into account the required operational infrastructure, instead of starting with the design of a vehicle. By investigating human-machine interfaces and training, automation technologies, and socio-economic impact, the my

  4. Open Automated Demand Response for Small Commerical Buildings

    SciTech Connect (OSTI)

    Dudley, June Han; Piette, Mary Ann; Koch, Ed; Hennage, Dan

    2009-05-01T23:59:59.000Z

    This report characterizes small commercial buildings by market segments, systems and end-uses; develops a framework for identifying demand response (DR) enabling technologies and communication means; and reports on the design and development of a low-cost OpenADR enabling technology that delivers demand reductions as a percentage of the total predicted building peak electric demand. The results show that small offices, restaurants and retail buildings are the major contributors making up over one third of the small commercial peak demand. The majority of the small commercial buildings in California are located in southern inland areas and the central valley. Single-zone packaged units with manual and programmable thermostat controls make up the majority of heating ventilation and air conditioning (HVAC) systems for small commercial buildings with less than 200 kW peak electric demand. Fluorescent tubes with magnetic ballast and manual controls dominate this customer group's lighting systems. There are various ways, each with its pros and cons for a particular application, to communicate with these systems and three methods to enable automated DR in small commercial buildings using the Open Automated Demand Response (or OpenADR) communications infrastructure. Development of DR strategies must consider building characteristics, such as weather sensitivity and load variability, as well as system design (i.e. under-sizing, under-lighting, over-sizing, etc). Finally, field tests show that requesting demand reductions as a percentage of the total building predicted peak electric demand is feasible using the OpenADR infrastructure.

  5. EBS Radionuclide Transport Abstraction

    SciTech Connect (OSTI)

    J.D. Schreiber

    2005-08-25T23:59:59.000Z

    The purpose of this report is to develop and analyze the engineered barrier system (EBS) radionuclide transport abstraction model, consistent with Level I and Level II model validation, as identified in ''Technical Work Plan for: Near-Field Environment and Transport: Engineered Barrier System: Radionuclide Transport Abstraction Model Report Integration'' (BSC 2005 [DIRS 173617]). The EBS radionuclide transport abstraction (or EBS RT Abstraction) is the conceptual model used in the total system performance assessment for the license application (TSPA-LA) to determine the rate of radionuclide releases from the EBS to the unsaturated zone (UZ). The EBS RT Abstraction conceptual model consists of two main components: a flow model and a transport model. Both models are developed mathematically from first principles in order to show explicitly what assumptions, simplifications, and approximations are incorporated into the models used in the TSPA-LA. The flow model defines the pathways for water flow in the EBS and specifies how the flow rate is computed in each pathway. Input to this model includes the seepage flux into a drift. The seepage flux is potentially split by the drip shield, with some (or all) of the flux being diverted by the drip shield and some passing through breaches in the drip shield that might result from corrosion or seismic damage. The flux through drip shield breaches is potentially split by the waste package, with some (or all) of the flux being diverted by the waste package and some passing through waste package breaches that might result from corrosion or seismic damage. Neither the drip shield nor the waste package survives an igneous intrusion, so the flux splitting submodel is not used in the igneous scenario class. The flow model is validated in an independent model validation technical review. The drip shield and waste package flux splitting algorithms are developed and validated using experimental data. The transport model considers advective transport and diffusive transport from a breached waste package. Advective transport occurs when radionuclides that are dissolved or sorbed onto colloids (or both) are carried from the waste package by the portion of the seepage flux that passes through waste package breaches. Diffusive transport occurs as a result of a gradient in radionuclide concentration and may take place while advective transport is also occurring, as well as when no advective transport is occurring. Diffusive transport is addressed in detail because it is the sole means of transport when there is no flow through a waste package, which may dominate during the regulatory compliance period in the nominal and seismic scenarios. The advective transport rate, when it occurs, is generally greater than the diffusive transport rate. Colloid-facilitated advective and diffusive transport is also modeled and is presented in detail in Appendix B of this report.

  6. Transportation Market Distortions

    E-Print Network [OSTI]

    Litman, Todd

    2006-01-01T23:59:59.000Z

    of Highways, Volpe National Transportation Systems Center (Evaluating Criticism of Transportation Costing, VictoriaFrom Here: Evaluating Transportation Diversity, Victoria

  7. Longshore sediment transport rate calculated incorporating wave orbital velocity fluctuations

    E-Print Network [OSTI]

    Smith, Ernest Ray

    2006-10-30T23:59:59.000Z

    Laboratory experiments were performed to study and improve longshore sediment transport rate predictions. Measured total longshore transport in the laboratory was approximately three times greater for plunging breakers than spilling breakers. Three...

  8. Transportation Center Seminar........ Elaine Croft McKenzie

    E-Print Network [OSTI]

    Bustamante, Fabin E.

    Transportation Center Seminar........ Elaine Croft McKenzie PhD Candidate, Civil & Environmental Engineering; Transportation Center Dissertation Year Fellow Northwestern University "A Framework be valued in light of their total environmental and economic footprint over the planning horizon. Currently

  9. AUTOMATING GROUNDWATER SAMPLING AT HANFORD

    SciTech Connect (OSTI)

    CONNELL CW; HILDEBRAND RD; CONLEY SF; CUNNINGHAM DE

    2009-01-16T23:59:59.000Z

    Until this past October, Fluor Hanford managed Hanford's integrated groundwater program for the U.S. Department of Energy (DOE). With the new contract awards at the Site, however, the CH2M HILL Plateau Remediation Company (CHPRC) has assumed responsibility for the groundwater-monitoring programs at the 586-square-mile reservation in southeastern Washington State. These programs are regulated by the Resource Conservation and Recovery Act (RCRA) and the Comprehensive Environmental Response Compensation and Liability Act (CERCLA). The purpose of monitoring is to track existing groundwater contamination from past practices, as well as other potential contamination that might originate from RCRA treatment, storage, and disposal (TSD) facilities. An integral part of the groundwater-monitoring program involves taking samples of the groundwater and measuring the water levels in wells scattered across the site. More than 1,200 wells are sampled each year. Historically, field personnel or 'samplers' have been issued pre-printed forms that have information about the well(s) for a particular sampling evolution. This information is taken from the Hanford Well Information System (HWIS) and the Hanford Environmental Information System (HEIS)--official electronic databases. The samplers used these hardcopy forms to document the groundwater samples and well water-levels. After recording the entries in the field, the samplers turned the forms in at the end of the day and the collected information was posted onto a spreadsheet that was then printed and included in a log book. The log book was then used to make manual entries of the new information into the software application(s) for the HEIS and HWIS databases. This is a pilot project for automating this tedious process by providing an electronic tool for automating water-level measurements and groundwater field-sampling activities. The automation will eliminate the manual forms and associated data entry, improve the accuracy of the information recorded, and enhance the efficiency and sampling capacity of field personnel. The goal of the effort is to eliminate 100 percent of the manual input to the database(s) and replace the management of paperwork by the field and clerical personnel with an almost entirely electronic process. These activities will include the following: scheduling the activities of the field teams, electronically recording water-level measurements, electronically logging and filing Groundwater Sampling Reports (GSR), and transferring field forms into the site-wide Integrated Document Management System (IDMS).

  10. Human-Automation Interaction By Thomas B. Sheridan & Raja Parasuraman

    E-Print Network [OSTI]

    Parasuraman, Raja

    89 CHAPTER 2 Human-Automation Interaction By Thomas B. Sheridan & Raja Parasuraman Automation does with automation in complex and typically large-scale systems, including aircraft and air traffic control, nuclear-free task for either the system designer or the human operator/automation supervisor, especially as computer

  11. A SIP-based Home Automation Platform: an Experimental Study

    E-Print Network [OSTI]

    Boyer, Edmond

    A SIP-based Home Automation Platform: an Experimental Study Benjamin Bertran, Charles Consel INRIA automation applications that consist of heterogeneous, distributed entities. We describe how SIP fulfills the requirements of home automation; we present the resulting architecture of a home automation system; and, we

  12. Fueling Robot Automates Hydrogen Hose Reliability Testing (Fact Sheet)

    SciTech Connect (OSTI)

    Harrison, K.

    2014-01-01T23:59:59.000Z

    Automated robot mimics fueling action to test hydrogen hoses for durability in real-world conditions.

  13. Automated Fresnel lens tester system

    SciTech Connect (OSTI)

    Phipps, G.S.

    1981-07-01T23:59:59.000Z

    An automated data collection system controlled by a desktop computer has been developed for testing Fresnel concentrators (lenses) intended for solar energy applications. The system maps the two-dimensional irradiance pattern (image) formed in a plane parallel to the lens, whereas the lens and detector assembly track the sun. A point detector silicon diode (0.5-mm-dia active area) measures the irradiance at each point of an operator-defined rectilinear grid of data positions. Comparison with a second detector measuring solar insolation levels results in solar concentration ratios over the image plane. Summation of image plane energies allows calculation of lens efficiencies for various solar cell sizes. Various graphical plots of concentration ratio data help to visualize energy distribution patterns.

  14. Automation of BESSY scanning tables

    E-Print Network [OSTI]

    Hanton, J

    1981-01-01T23:59:59.000Z

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

  15. MUJERES TOTAL BIOLOGIA 16 27

    E-Print Network [OSTI]

    Autonoma de Madrid, Universidad

    , PLASTICA Y VISUAL 2 2 EDUCACION FISICA, DEPORTE Y MOTRICIDAD HUMANA 1 1 6 11 TOTAL CIENCIAS N DE TESIS

  16. MUJERES ( * ) TOTAL BIOLOGA 16 22

    E-Print Network [OSTI]

    Autonoma de Madrid, Universidad

    , DEPORTE Y MOTRICIDAD HUMANA 0 4 TOTAL FORMACIN DE PROFESORADO Y EDUCACIN 0 6 ANATOMA PATOLGICA 2 5

  17. Low Speed Automation, a French Initiative

    E-Print Network [OSTI]

    Sbastien Glaser; Maurice Cour; Lydie Nouveliere; Alain Lambert; Fawzi Nashashibi; Jean-christophe Popieul; Benjamin Mourllion

    MIPS, 2 rue des frres Lumire,68093 Mulhouse-FRANCE Nowadays, vehicle safety is constantly increasing thanks to the improvement of vehicle passive and active safety. However, on a daily usage of the car, traffic jams remains a problem. With limited space for road infrastructure, automation of the driving task on specific situation seems to be a possible solution. The French project ABV, which stands for low speed automation, tries to demonstrate the feasibility of the concept and to prove the benefits. In this article, we describe the scientific background of the project and expected outputs. "Keywords: vehicle automation, shared control, environment sensing, data fusion;" 1.

  18. The Total RNA Story Introduction

    E-Print Network [OSTI]

    Goldman, Steven A.

    The Total RNA Story Introduction Assessing RNA sample quality as a routine part of the gene about RNA sample quality. Data from a high quality total RNA preparation Although a wide variety RNA data interpretation and identify features from total RNA electropherograms that reveal information

  19. Modeling Total Solar Irradiance Variations Using Automated Classification Software on Mount Wilson Data

    E-Print Network [OSTI]

    Ulrich, R. K.; Parker, D.; Bertello, L.; Boyden, J.

    2010-01-01T23:59:59.000Z

    S. , Joukoff, A. : 2004, Solar Phys. 224, 209. Djafer, D. ,a, S. , Egidi, A. : 2008, Solar Phys. 247, 225. Fazel, Z. ,Bernasconi, P.N. : 2008, Solar Phys. 248, 1. Foukal, P. ,

  20. Participation through Automation: Fully Automated Critical Peak Pricing in Commercial Buildings

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Kiliccote, Sila; Linkugel, Eric

    2006-01-01T23:59:59.000Z

    Figure 2. Demand Response Automation Server and BuildingDemand Response Control Strategies in Commercial Buildings,X X Example of Demand Response from an Office Building This

  1. electrifyingthefuture transportation

    E-Print Network [OSTI]

    Birmingham, University of

    electrifyingthefuture transportation The UK Government's carbon reduction strategy vehicles and the new Birmingham Science City Energy Systems Integration Laboratory (ESIL) will further enhance this work. The laboratory - unique within the UK and world leading - brings together cutting edge

  2. Automation, Energy Conservation and Common Sense

    E-Print Network [OSTI]

    Hester, D.

    1981-01-01T23:59:59.000Z

    and contains 5 million square feet of administration office and research laboratory space. An Engineering study to investigate an automated computer controlled energy management system has been completed. The study objectives were to identify system parameters...

  3. Improved Usability of Aviation Automation Through Direct

    E-Print Network [OSTI]

    Kaber, David B.

    Improved Usability of Aviation Automation Through Direct Manipulation and Graphical User Interface Design David B. Kaber and Jennifer M. Riley Department of Industrial Engineering North Carolina State University Kheng-Wooi Tan Department of Industrial Engineering Mississippi State University Problems

  4. Towards Automated System Synthesis Using SCIDUCTION

    E-Print Network [OSTI]

    Jha, Susmit Kumar

    2011-01-01T23:59:59.000Z

    120] SRI Intl. Yices: An SMT solver. [121] Mark Stephenson,and use fully automated SMT solvers [13] for deduction.in literature. Brahma[46] uses SMT solving technology to

  5. Stochastic versus Robust Optimization for a Transportation Problem

    E-Print Network [OSTI]

    2015-03-05T23:59:59.000Z

    minimize the total cost, given by the sum of the transportation costs and buying cost .... variables and the newly available data and report the respective costs.

  6. Explorations of Space-Charge Limits in Parallel-Plate Diodes and Associated Techniques for Automation

    E-Print Network [OSTI]

    Ragan-Kelley, Benjamin

    2013-01-01T23:59:59.000Z

    and Associated Techniques for Automation by Benjamin Ragan-and Associated Techniques for Automation Copyright 2013 byand Associated Techniques for Automation by Benjamin Ragan-

  7. Demonstration of Datacenter Automation Software and Hardware (DASH) at the California Franchise Tax Board

    E-Print Network [OSTI]

    Bell, Geoffrey C.

    2010-01-01T23:59:59.000Z

    of Datacenter Automation Software and Hardware (DASH) at theof Datacenter Automation Software and Hardware (DASH) at theprotocol for building automation and control networks. It is

  8. E-Print Network 3.0 - automated high performance Sample Search...

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

    Towards Highly Automated Driving: Intermediate... of HAVEit is to develop and investigate vehicle automation beyond ADAS systems, especially highly automated... driving, where the...

  9. E-Print Network 3.0 - automated signal processing Sample Search...

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

    Towards Highly Automated Driving: Intermediate... of HAVEit is to develop and investigate vehicle automation beyond ADAS systems, especially highly automated... driving, where the...

  10. E-Print Network 3.0 - automated synthesis module Sample Search...

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

    Towards Highly Automated Driving: Intermediate... of HAVEit is to develop and investigate vehicle automation beyond ADAS systems, especially highly automated... driving, where the...

  11. Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01T23:59:59.000Z

    for Automated Demand Response in Commercial Buildings. In2010. Open Automated Demand Response Dynamic Pricing2009. Open Automated Demand Response Communications

  12. An Interface Between Continuous And Discrete-event Controllers For Vehicle Automation

    E-Print Network [OSTI]

    Lygeros, John; Godbole, Datta N.

    1994-01-01T23:59:59.000Z

    Event Controllers for Vehicle Automation John Lygeros DattaEvent Controllers for Vehicle Automation John Lygeros andTomizuka, Vehicle lateral control for highway automation,"

  13. Automated Critical Peak Pricing Field Tests: 2006 Pilot Program Description and Results

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila

    2007-01-01T23:59:59.000Z

    andindustrialfacilities),furtherdevelopingtheDRAutomationofindustrialprocesscontrolsystemsfor automation. of industrialprocesscontrol systemsforautomation.

  14. Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01T23:59:59.000Z

    for Automated Demand Response in Commercial Buildings. InAutomated Demand Response for Small Commercial Buildings. in automated demand response programs with building control

  15. NAVIGATION SOFTWARE OF AUTOMATED GUIDED VEHICLE

    E-Print Network [OSTI]

    Magdalena Dobrza?ska; Pawe? Dobrza?ski

    Abstract: In the article it has been presented the structure of the control system and measurement data processing of an automated guided vehicle. The basic navigation technique odometry, which is applied in the automated guided vehicle, has been described, as well as connected with it errors of position tracing. Next the navigation software was shown which enables to design the trajectory of the vehicle movement as well as the registration and reading of the measurement data from the measurement sensors.

  16. A Mobile Automated Tomographic Gamma Scanning System - 13231

    SciTech Connect (OSTI)

    Kirkpatrick, J.M.; LeBlanc, P.J.; Nakazawa, D.; Petroka, D.L.; Kane Smith, S.; Venkataraman, R.; Villani, M. [Canberra Industries, Inc. 800 Research Parkway, Meriden CT 06450 (United States)] [Canberra Industries, Inc. 800 Research Parkway, Meriden CT 06450 (United States)

    2013-07-01T23:59:59.000Z

    Canberra Industries have recently designed and built a new automated Tomographic Gamma Scanning (TGS) system for mobile deployment. The TGS technique combines high-resolution gamma spectroscopy with low spatial resolution 3-dimensional image reconstruction to provide increased accuracy over traditional approaches for the assay of non-uniform source distributions in low-to medium-density, non-heterogeneous matrices. Originally pioneered by R. Estep at Los Alamos National Laboratory (LANL), the TGS method has been further developed and commercialized by Canberra Industries in recent years. The present system advances the state of the art on several fronts: it is designed to be housed in a standard cargo transport container for ease of transport, allowing waste characterization at multiple facilities under the purview of a single operator. Conveyor feed, drum rotator, and detector and collimator positioning mechanisms operated by programmable logic control (PLC) allow automated batch mode operation. The variable geometry settings can accommodate a wide range of waste packaging, including but not limited to standard 220 liter drums, 380 liter overpack drums, and smaller 20 liter cans. A 20 mCi Eu-152 transmission source provides attenuation corrections for drum matrices up to 1 g/cm{sup 3} in TGS mode; the system can be operated in Segmented Gamma Scanning (SGS) mode to measure higher density drums. To support TGS assays at higher densities, the source shield is sufficient to house an alternate Co-60 transmission source of higher activity, up to 250 mCi. An automated shutter and attenuator assembly is provided for operating the system with a dual intensity transmission source. The system's 1500 kg capacity rotator turntable can handle heavy containers such as concrete lined 380 liter overpack drums. Finally, data acquisition utilizes Canberra's Broad Energy Germanium (BEGE) detector and Lynx MCA, with 32 k channels, providing better than 0.1 keV/channel resolution to support both isotopic analysis with the MGA/MGAU software and a wide 3 MeV dynamic range. The calibration and verification of the system is discussed, and quantitative results are presented for a variety of drum types and matrices. (authors)

  17. Modeling the impact of complexity on transportation

    E-Print Network [OSTI]

    Fernandez, Jose A. (Jose Antonio Fernandez Chavira)

    2012-01-01T23:59:59.000Z

    This thesis aimed to understand the drivers of total transportation costs during supply chain complexity events, in particular new product launches, in a fast moving consumer goods company in the United States. The research ...

  18. Total..........................................................

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

    Q 0.4 3 or More Units... 5.4 0.3 Q Q Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  19. Total..........................................................

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

    ... 1.9 1.1 Q Q 0.3 Q Do Not Use Central Air-Conditioning... 45.2 24.6 3.6 5.0 8.8 3.2 Use a Programmable...

  20. Total..........................................................

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

    Q 0.6 3 or More Units... 5.4 3.8 2.9 0.4 Q N 0.2 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  1. Total..........................................................

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

    1.3 Q 3 or More Units... 5.4 1.6 0.8 Q 0.3 0.3 Q Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  2. Total..........................................................

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

    3 or More Units... 5.4 2.4 1.4 0.7 0.9 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  3. Total..........................................................

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

    3 or More Units... 5.4 2.3 1.7 0.6 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  4. Total..........................................................

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

    8.6 Have Equipment But Do Not Use it... 1.9 Q Q Q Q 0.6 0.4 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System......

  5. Total..........................................................

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

    3 or More Units... 5.4 2.1 0.9 0.2 1.0 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  6. Total..........................................................

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

    30.3 Have Equipment But Do Not Use it... 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Type of Air-Conditioning Equipment 1, 2 Central System......

  7. Total..........................................................

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

    0.3 3 or More Units... 5.4 0.7 0.5 Q Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  8. Total..........................................................

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

    3 or More Units... 5.4 2.3 0.7 2.1 0.3 Central Air-Conditioning Usage Air-Conditioned Floorspace (Square Feet)...

  9. Total..........................................................

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

    111.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer... 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer......

  10. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer......

  11. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    Personal Computers Do Not Use a Personal Computer... 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer... 75.6...

  12. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer... 35.5 8.1 5.6 2.5 Use a Personal Computer......

  13. Total..........................................................

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

    4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer... 35.5 6.4 2.2 4.2 Use a Personal Computer......

  14. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    ..... 111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer......

  15. Total..........................................................

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

    25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer... 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer......

  16. Total..........................................................

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

    1.3 0.8 0.5 Once a Day... 19.2 4.6 3.0 1.6 Between Once a Day and Once a Week... 32.0 8.9 6.3 2.6 Once a...

  17. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    AppliancesTools.... 56.2 11.6 3.3 8.2 Other Appliances Used Auto BlockEngineBattery Heater... 0.8 0.2 Q 0.1 Hot Tub or Spa......

  18. Total..........................................................

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

    Tools... 56.2 20.5 10.8 3.6 6.1 Other Appliances Used Auto BlockEngineBattery Heater... 0.8 N N N N Hot Tub or Spa......

  19. Total..........................................................

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

    Tools... 56.2 27.2 10.6 9.3 9.2 Other Appliances Used Auto BlockEngineBattery Heater... 0.8 Q Q Q 0.4 Hot Tub or Spa......

  20. Total..........................................................

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

    AppliancesTools.... 56.2 12.2 9.4 2.8 Other Appliances Used Auto BlockEngineBattery Heater... 0.8 Q Q Q Hot Tub or Spa......

  1. Total..........................................................

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

    1.3 3.8 Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line Eligible for Federal Assistance 1 40,000 to 59,999 60,000 to 79,999 80,000...

  2. Total..............................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6 2,720

  3. Total................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6 2,720..

  4. Total........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6 2,720..

  5. Total..........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6

  6. Total...........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6Q Table

  7. Total...........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6Q TableQ

  8. Total...........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6Q

  9. Total...........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1 86.6Q26.7

  10. Total............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1

  11. Total............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.1

  12. Total.............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.7 28.8 20.6

  13. Total..............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.7 28.8

  14. Total..............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.7 28.8,171

  15. Total...............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.7

  16. Total...............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.7 21.7

  17. Total...............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.7

  18. Total...............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.747.1

  19. Total...............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.747.1Do

  20. Total................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline. 111.126.70.747.1Do

  1. Total.................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.

  2. Total.................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4 12.5 12.5

  3. Total.................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4 12.5

  4. Total..................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4 12.578.1

  5. Total..................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4

  6. Total..................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4. 111.1 14.7

  7. Total...................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4. 111.1

  8. Total...................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4. 111.115.2

  9. Total...................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7 7.4.

  10. Total...................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.7

  11. Total...................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,033 1,618

  12. Total....................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,033 1,61814.7

  13. Total.......................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,033

  14. Total.......................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.6 17.7

  15. Total.......................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.6 17.74.2

  16. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.6

  17. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.615.1 5.5

  18. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.615.1

  19. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II: AnPipeline.14.72,0335.615.10.7

  20. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:

  1. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not Have

  2. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not Have7.1

  3. Total.........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not

  4. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not25.6 40.7

  5. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not25.6

  6. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do Not25.65.6

  7. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do

  8. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2 7.6 16.6

  9. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2 7.6

  10. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2 7.67.1

  11. Total...........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2 7.67.10.6

  12. Total...........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.2

  13. Total...........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.24.2 7.6

  14. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.24.2

  15. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1 Do4.24.2Cooking

  16. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1

  17. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do Not Have

  18. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do Not HaveDo

  19. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do Not HaveDoDo

  20. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do Not

  1. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo Not

  2. Total..............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo Not

  3. Total..............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo Not20.6

  4. Total..............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo

  5. Total..............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo7.1 19.0

  6. Total.................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo7.1

  7. Total.................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo7.1...

  8. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do

  9. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1DoCooking

  10. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1DoCooking25.6

  11. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1DoCooking25.65.6

  12. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0

  13. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.04.2 7.6 16.6 Personal

  14. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.04.2 7.6 16.6 Personal

  15. Total.........................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.04.2 7.6 16.6

  16. Total

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear JanYear Jan Feb Mar Apr May(MillionFeet)July 23,

  17. Total

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear JanYear Jan Feb Mar Apr May(MillionFeet)July 23,Product:

  18. Total..............................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720 1,970

  19. Total................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720

  20. Total........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720 111.1

  1. Total..........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720

  2. Total...........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720Q Table

  3. Total...........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720Q

  4. Total...........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720Q14.7

  5. Total...........................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6

  6. Total............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1

  7. Total............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1

  8. Total.............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.8 20.6

  9. Total..............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.8 20.6,171

  10. Total..............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.8

  11. Total...............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.820.6 25.6

  12. Total...............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.820.6

  13. Total...............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.820.626.7

  14. Total...............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7

  15. Total...............................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1 19.0 22.7

  16. Total................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1 19.0 22.7

  17. Total.................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1 19.0

  18. Total.................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1 19.014.7

  19. Total.................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1

  20. Total..................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.178.1 64.1

  1. Total..................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.178.1

  2. Total..................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.178.1.

  3. Total...................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770

  4. Total...................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.2 3.3 1.9

  5. Total...................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.2 3.3

  6. Total...................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.2 3.3Type

  7. Total...................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.2

  8. Total....................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.214.7 7.4

  9. Total.......................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.214.7

  10. Total.......................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.214.75.6

  11. Total.......................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0

  12. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.6 40.7

  13. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.6

  14. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.65.6 17.7

  15. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.65.6

  16. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.65.64.2

  17. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8

  18. Total........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.0 22.7

  19. Total.........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.0

  20. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.025.6

  1. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.025.6.

  2. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.025.6.5.6

  3. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1

  4. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2 7.6 16.6

  5. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2 7.6

  6. Total..........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2 7.67.1

  7. Total...........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2 7.67.10.6

  8. Total...........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2

  9. Total...........................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.24.2 7.6

  10. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.24.2 7.6Do

  11. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.24.2

  12. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.24.2Cooking

  13. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2

  14. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not Have Cooling

  15. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not Have

  16. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo Not

  17. Total.............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo NotDo

  18. Total..............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo

  19. Total..............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo0.7

  20. Total..............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo0.7

  1. Total..............................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo0.77.1

  2. Total.................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not

  3. Total.................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1 7.0 8.0

  4. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1 7.0

  5. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1 7.05.6

  6. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1

  7. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1Personal

  8. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1Personal4.2

  9. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do

  10. Total....................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do 111.1 47.1 19.0

  11. Total.........................................................................................

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do 111.1 47.1

  12. Underground coal mining is an industry well suited for robotic automation. Human operators are severely hampered in

    E-Print Network [OSTI]

    Stentz, Tony

    Abstract Underground coal mining is an industry well suited for robotic automation. Human operators approach meets the requirements for cutting straight entries and mining the proper amount of coal per cycle. Introduction The mining of soft materials, such as coal, is a large industry. Worldwide, a total of 435 million

  13. Automating Pen and InkAutomating Pen and Ink Landscape RenderingsLandscape Renderings

    E-Print Network [OSTI]

    Mower, James E.

    Automating Pen and InkAutomating Pen and Ink Landscape RenderingsLandscape Renderings Jim Mower geology They employThey employ Large scale viewsLarge scale views Pen and ink renderingsPen and ink renderings #12;ArminArmin LobeckLobeck LobeckLobeck wrote a wonderful book onwrote a wonderful book on block

  14. MASS: An automated accountability system

    SciTech Connect (OSTI)

    Erkkila, B.H.; Kelso, F.

    1994-08-01T23:59:59.000Z

    All Department of Energy contractors who manage accountable quantities of nuclear materials are required to implement an accountability system that tracks, and records the activities associated with those materials. At Los Alamos, the automated accountability system allows data entry on computer terminals and data base updating as soon as the entry is made. It is also able to generate all required reports in a timely Fashion. Over the last several years, the hardware and software have been upgraded to provide the users with all the capability needed to manage a large variety of operations with a wide variety of nuclear materials. Enhancements to the system are implemented as the needs of the users are identified. The system has grown with the expanded needs of the user; and has survived several years of changing operations and activity. The user community served by this system includes processing, materials control and accountability, and nuclear material management personnel. In addition to serving the local users, the accountability system supports the national data base (NMMSS). This paper contains a discussion of several details of the system design and operation. After several years of successful operation, this system provides an operating example of how computer systems can be used to manage a very dynamic data management problem.

  15. Automated diagnostics scoping study. Final report

    SciTech Connect (OSTI)

    Quadrel, R.W.; Lash, T.A.

    1994-06-01T23:59:59.000Z

    The objective of the Automated Diagnostics Scoping Study was to investigate the needs for diagnostics in building operation and to examine some of the current technologies in automated diagnostics that can address these needs. The study was conducted in two parts. In the needs analysis, the authors interviewed facility managers and engineers at five building sites. In the technology survey, they collected published information on automated diagnostic technologies in commercial and military applications as well as on technologies currently under research. The following describe key areas that the authors identify for the research, development, and deployment of automated diagnostic technologies: tools and techniques to aid diagnosis during building commissioning, especially those that address issues arising from integrating building systems and diagnosing multiple simultaneous faults; technologies to aid diagnosis for systems and components that are unmonitored or unalarmed; automated capabilities to assist cause-and-effect exploration during diagnosis; inexpensive, reliable sensors, especially those that expand the current range of sensory input; technologies that aid predictive diagnosis through trend analysis; integration of simulation and optimization tools with building automation systems to optimize control strategies and energy performance; integration of diagnostic, control, and preventive maintenance technologies. By relating existing technologies to perceived and actual needs, the authors reached some conclusions about the opportunities for automated diagnostics in building operation. Some of a building operator`s needs can be satisfied by off-the-shelf hardware and software. Other needs are not so easily satisfied, suggesting directions for future research. Their conclusions and suggestions are offered in the final section of this study.

  16. Automated reaction mechanism generation : data collaboration, Heteroatom implementation, and model validation

    E-Print Network [OSTI]

    Harper, Michael Richard, Jr

    2011-01-01T23:59:59.000Z

    Nearly two-thirds of the United States' transportation fuels are derived from non-renewable fossil fuels. This demand of fossil fuels requires the United States to import ~ 60% of its total fuel consumption. Relying so ...

  17. Automation cueing modulates cerebral blood flow and vigilance in a simulated air traffic control task

    E-Print Network [OSTI]

    Parasuraman, Raja

    Automation cueing modulates cerebral blood flow and vigilance in a simulated air traffic control: Automation; vigilance; cerebral blood flow; mental workload; attentional resources. Automation cueing operator, depending on automation reliability. To assess these effects, transcranial Doppler sonography

  18. Appendix III to OMB Circular No. A-130 -Security of Federal Automated Information Resources

    E-Print Network [OSTI]

    Appendix III to OMB Circular No. A-130 - Security of Federal Automated Information Resources A automated information security programs; assigns Federal agency responsibilities for the security of automated information; and links agency automated information security programs and agency management

  19. Method and apparatus for routing data in an inter-nodal communications lattice of a massively parallel computer system by routing through transporter nodes

    DOE Patents [OSTI]

    Archer, Charles Jens (Rochester, MN); Musselman, Roy Glenn (Rochester, MN); Peters, Amanda (Rochester, MN); Pinnow, Kurt Walter (Rochester, MN); Swartz, Brent Allen (Chippewa Falls, WI); Wallenfelt, Brian Paul (Eden Prairie, MN)

    2010-11-16T23:59:59.000Z

    A massively parallel computer system contains an inter-nodal communications network of node-to-node links. An automated routing strategy routes packets through one or more intermediate nodes of the network to reach a destination. Some packets are constrained to be routed through respective designated transporter nodes, the automated routing strategy determining a path from a respective source node to a respective transporter node, and from a respective transporter node to a respective destination node. Preferably, the source node chooses a routing policy from among multiple possible choices, and that policy is followed by all intermediate nodes. The use of transporter nodes allows greater flexibility in routing.

  20. E-Print Network 3.0 - automated network analysis Sample Search...

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

    automation, which resulted in better performance. Conclusion: In decentralized unmanned vehicle networks... , decentralized network, automation ... Source: Cummings, Mary "Missy"...

  1. Transportation and its Infrastructure

    E-Print Network [OSTI]

    2007-01-01T23:59:59.000Z

    40 pp. IEA, 2004c: Biofuels for Transport: An Internationalthe ACT Map scenario, transport biofuels production reachesestimates that biofuels share of transport fuel could

  2. Department of Mechanical Engineering Spring 2011 Nanoparticle Reactor Automation

    E-Print Network [OSTI]

    Demirel, Melik C.

    PENNSTATE Department of Mechanical Engineering Spring 2011 Nanoparticle Reactor Automation Overview would be fully automated and able to run overnight. The team was also asked to keep the solutions from

  3. Analysis of Open Automated Demand Response Deployments in California

    E-Print Network [OSTI]

    LBNL-6560E Analysis of Open Automated Demand Response Deployments in California and Guidelines The work described in this report was coordinated by the Demand Response Research. #12; #12;Abstract This report reviews the Open Automated Demand Response

  4. The value of accurate automated data collection to manufacturing

    E-Print Network [OSTI]

    Perez, Alfonso Alexander

    2014-01-01T23:59:59.000Z

    The purpose of this thesis is to demonstrate the value of implementing a novel, accurate automated data collection system and to describe a practical method for doing so. This thesis addresses the value of accurate automated ...

  5. Automated Demand Response Strategies and Commissioning Commercial Building Controls

    E-Print Network [OSTI]

    Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Linkugel, Eric

    2006-01-01T23:59:59.000Z

    4 9 . Piette et at Automated Demand Response Strategies andDynamic Controls for Demand Response in New and ExistingFully Automated Demand Response Tests in Large Facilities"

  6. Decision support systems for automated terminal area air traffic control

    E-Print Network [OSTI]

    Pararas, John Demetrios

    1982-01-01T23:59:59.000Z

    This work studies the automation of the terminal area Air Traffic Management and Control (ATM/C) system. The ATM/C decision-making process is analyzed and broken down into a number of "automation functions". Each of these ...

  7. automated materials discrimination: Topics by E-print Network

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

    automated materials discrimination First Page Previous Page 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 1 Automated...

  8. automated magnetometry based: Topics by E-print Network

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

    Behera, R; Poornima,; Dasgupta, K 2014-01-01 47 An Ontology-based Model to Determine the Automation Level of an Automated Vehicle for Physics Websites Summary: towards full...

  9. automated nmr determination: Topics by E-print Network

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

    pre-existing XPLOR program Clore, G. Marius 29 An Ontology-based Model to Determine the Automation Level of an Automated Vehicle for Physics Websites Summary: towards full...

  10. automated electrolytic enrichment: Topics by E-print Network

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

    11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 1 Test Automation Test Automation Computer Technologies and Information Sciences Websites Summary:...

  11. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    building electric load management concepts and faster scale dynamic DR using open automation systems.systems are being designed to be compatible with existing open building automationbuilding controls, weather sensitivity and occupancy patterns. Automation - Historically many energy management systems

  12. NEW INDUSTRIAL AUTOMATION LABORATORY & COURSES ECET TECHONOLOGY PROGRAM ADVANCEMENT

    E-Print Network [OSTI]

    Allen, Gale

    Paper #16 NEW INDUSTRIAL AUTOMATION LABORATORY & COURSES ECET TECHONOLOGY PROGRAM ADVANCEMENT Gale, Engineering and Technology. A new industrial automation laboratory was recently assembled and seven stations Minnesota state funding, industry contributions, and curriculum planning efforts resulted in a significant

  13. automated computational tool: Topics by E-print Network

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

    1731022.1731030 2011-01-01 8 Automated Tool Handling for the Trauma Pod Surgical Robot Engineering Websites Summary: Work Automated tool changers have been used in CNC...

  14. Automated Continuous Commissioning of Commercial Buildings

    E-Print Network [OSTI]

    Bailey, Trevor

    2013-01-01T23:59:59.000Z

    electricity consumption ..the total building electricity consumption between measured87 Figure 49 Total electricity consumption end use breakdown

  15. Automated imaging system for single molecules

    DOE Patents [OSTI]

    Schwartz, David Charles; Runnheim, Rodney; Forrest, Daniel

    2012-09-18T23:59:59.000Z

    There is provided a high throughput automated single molecule image collection and processing system that requires minimal initial user input. The unique features embodied in the present disclosure allow automated collection and initial processing of optical images of single molecules and their assemblies. Correct focus may be automatically maintained while images are collected. Uneven illumination in fluorescence microscopy is accounted for, and an overall robust imaging operation is provided yielding individual images prepared for further processing in external systems. Embodiments described herein are useful in studies of any macromolecules such as DNA, RNA, peptides and proteins. The automated image collection and processing system and method of same may be implemented and deployed over a computer network, and may be ergonomically optimized to facilitate user interaction.

  16. Saturated Zone Colloid Transport

    SciTech Connect (OSTI)

    H. S. Viswanathan

    2004-10-07T23:59:59.000Z

    This scientific analysis provides retardation factors for colloids transporting in the saturated zone (SZ) and the unsaturated zone (UZ). These retardation factors represent the reversible chemical and physical filtration of colloids in the SZ. The value of the colloid retardation factor, R{sub col} is dependent on several factors, such as colloid size, colloid type, and geochemical conditions (e.g., pH, Eh, and ionic strength). These factors are folded into the distributions of R{sub col} that have been developed from field and experimental data collected under varying geochemical conditions with different colloid types and sizes. Attachment rate constants, k{sub att}, and detachment rate constants, k{sub det}, of colloids to the fracture surface have been measured for the fractured volcanics, and separate R{sub col} uncertainty distributions have been developed for attachment and detachment to clastic material and mineral grains in the alluvium. Radionuclides such as plutonium and americium sorb mostly (90 to 99 percent) irreversibly to colloids (BSC 2004 [DIRS 170025], Section 6.3.3.2). The colloid retardation factors developed in this analysis are needed to simulate the transport of radionuclides that are irreversibly sorbed onto colloids; this transport is discussed in the model report ''Site-Scale Saturated Zone Transport'' (BSC 2004 [DIRS 170036]). Although it is not exclusive to any particular radionuclide release scenario, this scientific analysis especially addresses those scenarios pertaining to evidence from waste-degradation experiments, which indicate that plutonium and americium may be irreversibly attached to colloids for the time scales of interest. A section of this report will also discuss the validity of using microspheres as analogs to colloids in some of the lab and field experiments used to obtain the colloid retardation factors. In addition, a small fraction of colloids travels with the groundwater without any significant retardation. Radionuclides irreversibly sorbed onto this fraction of colloids also transport without retardation. The transport times for these radionuclides will be the same as those for nonsorbing radionuclides. The fraction of nonretarding colloids developed in this analysis report is used in the abstraction of SZ and UZ transport models in support of the total system performance assessment (TSPA) for the license application (LA). This analysis report uses input from two Yucca Mountain Project (YMP) analysis reports. This analysis uses the assumption from ''Waste Form and In-Drift Colloids-Associated Radionuclide Concentrations: Abstraction and Summary'' that plutonium and americium are irreversibly sorbed to colloids generated by the waste degradation processes (BSC 2004 [DIRS 170025]). In addition, interpretations from RELAP analyses from ''Saturated Zone In-Situ Testing'' (BSC 2004 [DIRS 170010]) are used to develop the retardation factor distributions in this analysis.

  17. automated software engineering: Topics by E-print Network

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

    Genomic Engineering (SAGE) Enabled by Electrowetting-on-Dielectric Digital Microfluidics Materials Science Websites Summary: Software Automated Genomic Engineering (SAGE)...

  18. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    Report 2009. Open Automated Demand Response Communicationsand Techniques for Demand Response. California Energyand S. Kiliccote. Estimating Demand Response Load Impacts:

  19. automated production line: Topics by E-print Network

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

    of web services 3 12;Cloud Resource Orchestration - Automated orchestration Cloud resource orchestration constraint optimization problems 4 Provider operational Plotkin,...

  20. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01T23:59:59.000Z

    January 2008. Biography Mary Ann Piette is a Staff ScientistAutomated Demand Response Mary Ann Piette, Sila Kiliccote,

  1. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01T23:59:59.000Z

    gateway device or building automation system. DR automationautomation of DR systems. Most DR activities are manual and require building

  2. Automated Surface Observing System: Standby Power Options

    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 FutureComments from TarasaName4ServicesTribalWorkplaceAutomated SteelAutomated

  3. Improving Home Automation by Discovering Regularly Occurring Device Usage Patterns

    E-Print Network [OSTI]

    Cook, Diane J.

    Improving Home Automation by Discovering Regularly Occurring Device Usage Patterns Edwin O in an environment can be mined to discover significant patterns, which an intelligent agent could use to automate of two prediction algorithms, thus demonstrating multiple uses for a home automation system. Finally, we

  4. The Automation of Sound Reasoning and Successful Proof Finding

    E-Print Network [OSTI]

    Fitelson, Branden

    709 44 The Automation of Sound Reasoning and Successful Proof Finding LARRY WOS AND BRANDEN scientist naturally envisioned the automation of sound rea- soning ­ reasoning in which conclusions, and find proofs. But can such logical reasoning be fully automated? Can a single computer program

  5. Modular and Generic Control Software System for Scalable Automation

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Modular and Generic Control Software System for Scalable Automation Christian Brecher, Martin.freundt@ipt.fraunhofer.de Abstract. The development of automated production systems is subdivided in two mayor tasks. One production with a high rate of changes, this is why fully automated solutions don't pay off and manual

  6. Trust Model for Security Automation Data 1.0 (TMSAD)

    E-Print Network [OSTI]

    Trust Model for Security Automation Data 1.0 (TMSAD) HaroldBooth AdamHalbardier NIST Interagency Report 7802 #12;NIST Interagency Report 7802 Trust Model for Security Automation Data 1.0 (TMSAD) Harold FOR SECURITY AUTOMATION DATA 1.0 (TMSAD) iii Reports on Computer Systems Technology The Information Technology

  7. TEMPORAL PERFORMANCE EVALUATION OF CONTROL ARCHITECTURE IN AUTOMATION

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    TEMPORAL PERFORMANCE EVALUATION OF CONTROL ARCHITECTURE IN AUTOMATION SYSTEMS Pascal Meunier, Bruno, France pascal.meunier@lurpa.ens-cachan.fr (Pascal Meunier) Abstract The performances of automation performances of networked automation system and which guides the engineer throughout the control architecture

  8. Designing Automation to Reduce Operator Errors Nancy G. Leveson

    E-Print Network [OSTI]

    Leveson, Nancy

    Designing Automation to Reduce Operator Errors Nancy G. Leveson Computer Science and Engineering University of Washington Everett Palmer NASA Ames Research Center Introduction Advanced automation has been of mode­related problems [SW95]. After studying accidents and incidents in the new, highly automated

  9. Density Functional Theory-Based Database Development and CALPHAD Automation

    E-Print Network [OSTI]

    Chen, Long-Qing

    Density Functional Theory-Based Database Development and CALPHAD Automation YI WANG,1,2 SHUNLI, the integration of first-principles calculations, CALPHAD modeling, and the automation of phase diagram, and the automated calculation of a phase diagram for the Al- Mg system. INTRODUCTION In thermodynamics, a phase

  10. http://jla.sagepub.com/ Journal of Laboratory Automation

    E-Print Network [OSTI]

    Demirel, Melik C.

    http://jla.sagepub.com/ Journal of Laboratory Automation http://jla.sagepub.com/content/early/2012 2012Journal of Laboratory Automation Timothy J. Bunning and Tony Jun Huang Yan Jun Liu, Mengqian Lu://www.sagepublications.com On behalf of: Society for Laboratory Automation and Screening can be found at:Journal of Laboratory

  11. IT/Automation Cost Reduction in Intel's Manufacturing Environment

    E-Print Network [OSTI]

    IT/Automation Cost Reduction in Intel's Manufacturing Environment Brian Subirana subirana@mit.edu MIT Center for Coordination Science WP #222 July 2003 #12;IT/Automation Cost Reduction in Intel maintaining existing service levels. "We want you to reduce automation costs by 50% while maintaining equal

  12. INTRODUCTION Recent research on human-automation inter-

    E-Print Network [OSTI]

    Kaber, David B.

    INTRODUCTION Recent research on human-automation inter- action theory (Endsley & Kaber, 1999 decisions about what complex system functions to automate, and to what extent, in advance of implementation and as part of the systems de- sign process. This work has relevance to adap- tive automation. Adaptive

  13. Scope and Description Laboratory Robotics and Automation seeks to

    E-Print Network [OSTI]

    Kostic, Milivoje M.

    #12;Scope and Description Laboratory Robotics and Automation seeks to communicate developments and information about the automation of the laboratory. Application areas generally include analytical peripherals, and other robotics developments that may have an impact on laboratory automation. In the area

  14. System Performances under Automation Degradation E. Hollnagel3

    E-Print Network [OSTI]

    Boyer, Edmond

    System Performances under Automation Degradation (SPAD) E. Hollnagel3 , C. Martinie1 , P. Palanque1 of the project objectives augmented by some early findings. Abstract - Increased automation is one of the main changes foreseen by SESAR in ATM. This will pose new challenges including possible automation degradation

  15. EMBEDDED SW DESIGN SPACE EXPLORATION AND AUTOMATION USING

    E-Print Network [OSTI]

    Wagner, Flávio Rech

    EMBEDDED SW DESIGN SPACE EXPLORATION AND AUTOMATION USING UML-BASED TOOLS FLÁVIO R. WAGNER, carro}@inf.ufrgs.br Abstract: This tutorial discusses design space exploration and software automation based on an UML front-end. First, we review software automation tools targeted at the embedded systems

  16. Vehicle Following Control Design for Automated Highway Systems

    E-Print Network [OSTI]

    Ioannou, Petros

    Vehicle Following Control Design for Automated Highway Systems H. Raza and P. Ioannou A, utomatic vehicle following isan important feature of a fully rpartially automated highwaysystem (AHS is todesign and test avehicle control system in order toachieve full vehicle automation in the longitudinal

  17. A Loop Material Flow System Design for Automated Guided Vehicles

    E-Print Network [OSTI]

    Dessouky, Maged

    A Loop Material Flow System Design for Automated Guided Vehicles Ardavan Asef-Vaziri 1 Maged load automated guided vehicles. The model simultaneously determines both the design are attributed to material handling (Tompkins et al., 1996). Automated guided vehicles (AGVs) are among

  18. TOWARD AUTOMATED DESIGN OF INDUSTRIAL-STRENGTH ANALOG CIRCUITS

    E-Print Network [OSTI]

    Fernandez, Thomas

    Chapter 8 TOWARD AUTOMATED DESIGN OF INDUSTRIAL-STRENGTH ANALOG CIRCUITS BY MEANS OF GENETIC be extended to deliver industrial-strength automated design of analog circuits, but two countervailing factors been previously established that genetic programming can be used as an automated invention machine

  19. Automated FMEA based diagnostic symptom generation. Neal Snooke1,

    E-Print Network [OSTI]

    Snooke, Neal

    Automated FMEA based diagnostic symptom generation. Neal Snooke1, , Chris Price Department the model based simulation used to produce an automated Failure Modes and Effect Analysis (FMEA to automate the production of a FMEA report, and the paper also considers the relationship between FMEA

  20. Coal Transportation Issues (released in AEO2007)

    Reports and Publications (EIA)

    2007-01-01T23:59:59.000Z

    Most of the coal delivered to U.S. consumers is transported by railroads, which accounted for 64% of total domestic coal shipments in 2004. Trucks transported approximately 12% of the coal consumed in the United States in 2004, mainly in short hauls from mines in the East to nearby coal-fired electricity and industrial plants. A number of minemouth power plants in the West also use trucks to haul coal from adjacent mining operations. Other significant modes of coal transportation in 2004 included conveyor belt and slurry pipeline (12%) and water transport on inland waterways, the Great Lakes, and tidewater areas (9%).