National Library of Energy BETA

Sample records for arizona household graph

  1. Arizona

    Energy Information Administration (EIA) (indexed site)

    Arizona

  2. Arizona - Compare - U.S. Energy Information Administration (EIA)

    Energy Information Administration (EIA) (indexed site)

    Arizona Arizona

  3. Arizona - Rankings - U.S. Energy Information Administration (EIA)

    Energy Information Administration (EIA) (indexed site)

    Arizona Arizona

  4. Arizona - Search - U.S. Energy Information Administration (EIA)

    Energy Information Administration (EIA) (indexed site)

    Arizona Arizona

  5. Gila County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Day, Arizona Central Heights-Midland City, Arizona Claypool, Arizona Gisela, Arizona Globe, Arizona Hayden, Arizona Miami, Arizona Payson, Arizona Peridot, Arizona Pine, Arizona...

  6. Pinal County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Chuichu, Arizona Coolidge, Arizona Dudleyville, Arizona Eloy, Arizona Florence, Arizona Gold Camp, Arizona Hayden, Arizona Kearny, Arizona Mammoth, Arizona Maricopa, Arizona...

  7. Navajo County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Mesa, Arizona Shongopovi, Arizona Shonto, Arizona Show Low, Arizona Snowflake, Arizona Taylor, Arizona Whiteriver, Arizona Winslow West, Arizona Winslow, Arizona Retrieved from...

  8. Apache County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Houck, Arizona Lukachukai, Arizona Many Farms, Arizona McNary, Arizona Nazlini, Arizona Red Mesa, Arizona Rock Point, Arizona Rough Rock, Arizona Round Rock, Arizona Sawmill,...

  9. Pima County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona Flowing Wells, Arizona Green Valley, Arizona Littletown, Arizona Marana, Arizona Oro Valley, Arizona Picture Rocks, Arizona Pisinemo, Arizona Sahuarita, Arizona Santa Rosa,...

  10. Fact #565: April 6, 2009 Household Gasoline Expenditures by Income |

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

    Department of Energy 5: April 6, 2009 Household Gasoline Expenditures by Income Fact #565: April 6, 2009 Household Gasoline Expenditures by Income In the annual Consumer Expenditure Survey, household incomes are grouped into five equal parts called quintiles (each quintile is 20%). Households in the second and third quintiles consistently have a higher share of spending on gasoline each year than households in the other quintiles. Household Gasoline Expenditures by Income Quintile Bar graph

  11. Cochise County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Douglas, Arizona Huachuca City, Arizona Naco, Arizona Pirtleville, Arizona Sierra Vista Southeast, Arizona Sierra Vista, Arizona St. David, Arizona Tombstone, Arizona...

  12. Yuma County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Solar Project Places in Yuma County, Arizona Fortuna Foothills, Arizona Gadsden, Arizona San Luis, Arizona Somerton, Arizona Tacna, Arizona Wellton, Arizona Yuma, Arizona...

  13. Graph Theory

    SciTech Connect

    Sanfilippo, Antonio P.

    2005-12-27

    Graph theory is a branch of discrete combinatorial mathematics that studies the properties of graphs. The theory was pioneered by the Swiss mathematician Leonhard Euler in the 18th century, commenced its formal development during the second half of the 19th century, and has witnessed substantial growth during the last seventy years, with applications in areas as diverse as engineering, computer science, physics, sociology, chemistry and biology. Graph theory has also had a strong impact in computational linguistics by providing the foundations for the theory of features structures that has emerged as one of the most widely used frameworks for the representation of grammar formalisms.

  14. Coconino County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Sedona, Arizona Supai, Arizona Tonalea, Arizona Tuba City, Arizona Tusayan, Arizona Williams, Arizona Winslow West, Arizona Retrieved from "http:en.openei.orgw...

  15. Utilization Graphs

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

    that use data from the PDSF batch scheduler (SGE) to show the utilization of the cluster over the past 24 hours. The graphs were generated with RRDTool and are updated...

  16. 2015 Arizona Housing Forum

    Energy.gov [DOE]

    The 12th annual Arizona Housing Forum provides a platform for affordable housing professionals to network and share ideas to improve and create housing choices for Arizona. Registration is $350.

  17. ,"Arizona Natural Gas Summary"

    Energy Information Administration (EIA) (indexed site)

    Prices" "Sourcekey","N3050AZ3","N3010AZ3","N3020AZ3","N3035AZ3","N3045AZ3" "Date","Natural Gas Citygate Price in Arizona (Dollars per Thousand Cubic Feet)","Arizona Price of ...

  18. PROJECT PROFILE: Arizona State University (SEEDS2-SES) | Department of

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

    Energy (SEEDS2-SES) PROJECT PROFILE: Arizona State University (SEEDS2-SES) Project Name: Advancing Solar Innovation for Low- and Moderate-Income Households: Analysis of the Arizona Experience Funding Opportunity: Solar Energy Evolution and Diffusion Studies 2 - State Energy Strategies (SEEDS2-SES) SunShot Subprogram: Soft Costs Location: Tempe, AZ SunShot Award Amount: $729,995 Awardee Cost Share: N/A This project identifies key socioeconomic factors and social values that enable and

  19. Graham County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    B. Places in Graham County, Arizona Peridot, Arizona Pima, Arizona Safford, Arizona Swift Trail Junction, Arizona Thatcher, Arizona Retrieved from "http:en.openei.orgw...

  20. Mohave County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Creek, Arizona Mohave Valley, Arizona Mojave Ranch Estates, Arizona New Kingman-Butler, Arizona Peach Springs, Arizona Willow Valley, Arizona Retrieved from "http:...

  1. Arizona State University

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

    Arizona State University Southwestern Regional Water-Energy Nexus Event Tempe, Arizona * September 8, 2016 Exploring Regional Opportunities in the U.S. for Clean Energy Technology Innovation * Volume 2 1-2 Southwestern Regional Water-Energy Nexus Event Tempe, Arizona - September 8, 2016 Report Authors Amanda Arnold, Executive Director, Federal Research Relations, Knowledge Enterprise Development (KED) Faye Farmer, Director, Research Development, KED Karen Walker, Senior Management Research

  2. DOE - Office of Legacy Management -- Arizona

    Office of Legacy Management (LM)

    Arizona Arizona az_map Monument Valley Processing Site Tuba City Disposal

  3. ,"Arizona Natural Gas Summary"

    Energy Information Administration (EIA) (indexed site)

    ...050AZ3","N3010AZ3","N3020AZ3","N3035AZ3","NA1570SAZ3","N3045AZ3" "Date","Arizona Natural Gas Wellhead Price (Dollars per Thousand Cubic Feet)","Price of Arizona Natural Gas ...

  4. Benson, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Act Smart Grid Projects in Benson, Arizona Southwest Transmission Cooperative, Inc. Smart Grid Project Registered Energy Companies in Benson, Arizona Arizona Electric Power...

  5. Arizona Electric Power Cooperative | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona Electric Power Cooperative Jump to: navigation, search Name: Arizona Electric Power Cooperative Place: Benson, Arizona Zip: 85602 Product: AEPCO was originally founded in...

  6. Arizona Solar Center | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Center Jump to: navigation, search Logo: Arizona Solar Center Name: Arizona Solar Center Place: Mesa, Arizona Number of Employees: 1-10 Year Founded: 1999 Website:...

  7. Household magnets

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

    Household magnets Chances are very good that you have experimented with magnets. People have been fascinated with magnetism for thousands of years. As familiar to us as they may be, magnets still have some surprises for us. Here is a small collection of some of our favorite magnet experiments. What happens when we break a magnet in half? Radio Shack sells cheap ceramic magnets in several shapes. Get a ring shaped magnet and break it with pliers or a tap with a hammer. Try to put it back

  8. Methods of visualizing graphs

    DOEpatents

    Wong, Pak C.; Mackey, Patrick S.; Perrine, Kenneth A.; Foote, Harlan P.; Thomas, James J.

    2008-12-23

    Methods for visualizing a graph by automatically drawing elements of the graph as labels are disclosed. In one embodiment, the method comprises receiving node information and edge information from an input device and/or communication interface, constructing a graph layout based at least in part on that information, wherein the edges are automatically drawn as labels, and displaying the graph on a display device according to the graph layout. In some embodiments, the nodes are automatically drawn as labels instead of, or in addition to, the label-edges.

  9. Arizona/Transmission/Agency Links | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    and Fish Department Arizona State Historic Preservation Office Arizona Department of Transportation Arizona Department of Agriculture Arizona Department of Water Resources Central...

  10. mpiGraph

    Energy Science and Technology Software Center

    2007-05-22

    MpiGraph consists of an MPI application called mpiGraph written in C to measure message bandwidth and an associated crunch_mpiGraph script written in Perl to process the application output into an HTMO report. The mpiGraph application is designed to inspect the health and scalability of a high-performance interconnect while under heavy load. This is useful to detect hardware and software problems in a system, such as slow nodes, links, switches, or contention in switch routing. Itmore » is also useful to characterize how interconnect performance changes with different settings or how one interconnect type compares to another.« less

  11. Graph Generator Survey

    SciTech Connect

    Lothian, Josh; Powers, Sarah S; Sullivan, Blair D; Baker, Matthew B; Schrock, Jonathan; Poole, Stephen W

    2013-12-01

    The benchmarking effort within the Extreme Scale Systems Center at Oak Ridge National Laboratory seeks to provide High Performance Computing benchmarks and test suites of interest to the DoD sponsor. The work described in this report is a part of the effort focusing on graph generation. A previously developed benchmark, SystemBurn, allowed the emulation of dierent application behavior profiles within a single framework. To complement this effort, similar capabilities are desired for graph-centric problems. This report examines existing synthetic graph generator implementations in preparation for further study on the properties of their generated synthetic graphs.

  12. Arizona City, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    City, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.7558935, -111.6709584 Show Map Loading map... "minzoom":false,"mappingservice...

  13. MONUMENT VALLEY, ARIZONA

    Office of Legacy Management (LM)

    VALLEY, ARIZONA Sampled August 1997 DATA PACKAGE CONTENTS This data package includes the following information: Item No. Descriotion of Contents 1. Site Sampling Lead Summary 2. Data Package Assessment, which includes the following: a. Field procedures verification checklist b. Confirmation that chain-of-custody was maintained. c. Confirmation that holding time requirements were met. d. Evaluation of the adequacy of the QC sample results. Data Assessment Summary, which describes problems

  14. Graphs, matrices, and the GraphBLAS: Seven good reasons

    DOE PAGES [OSTI]

    Kepner, Jeremy; Bader, David; Buluç, Aydın; Gilbert, John; Mattson, Timothy; Meyerhenke, Henning

    2015-01-01

    The analysis of graphs has become increasingly important to a wide range of applications. Graph analysis presents a number of unique challenges in the areas of (1) software complexity, (2) data complexity, (3) security, (4) mathematical complexity, (5) theoretical analysis, (6) serial performance, and (7) parallel performance. Implementing graph algorithms using matrix-based approaches provides a number of promising solutions to these challenges. The GraphBLAS standard (istcbigdata.org/GraphBlas) is being developed to bring the potential of matrix based graph algorithms to the broadest possible audience. The GraphBLAS mathematically defines a core set of matrix-based graph operations that can be used to implementmore » a wide class of graph algorithms in a wide range of programming environments. This paper provides an introduction to the GraphBLAS and describes how the GraphBLAS can be used to address many of the challenges associated with analysis of graphs.« less

  15. Graphs, matrices, and the GraphBLAS: Seven good reasons

    SciTech Connect

    Kepner, Jeremy; Bader, David; Buluç, Aydın; Gilbert, John; Mattson, Timothy; Meyerhenke, Henning

    2015-01-01

    The analysis of graphs has become increasingly important to a wide range of applications. Graph analysis presents a number of unique challenges in the areas of (1) software complexity, (2) data complexity, (3) security, (4) mathematical complexity, (5) theoretical analysis, (6) serial performance, and (7) parallel performance. Implementing graph algorithms using matrix-based approaches provides a number of promising solutions to these challenges. The GraphBLAS standard (istcbigdata.org/GraphBlas) is being developed to bring the potential of matrix based graph algorithms to the broadest possible audience. The GraphBLAS mathematically defines a core set of matrix-based graph operations that can be used to implement a wide class of graph algorithms in a wide range of programming environments. This paper provides an introduction to the GraphBLAS and describes how the GraphBLAS can be used to address many of the challenges associated with analysis of graphs.

  16. Energy Exchange 2015: Phoenix, Arizona

    Energy.gov [DOE]

    Presentations from Energy Exchange, a two-and-a-half day training scheduled for August 11-13, 2015, at the Phoenix Convention Center in Phoenix, Arizona.

  17. Grecycle Arizona LLC | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    to: navigation, search Name: Grecycle Arizona LLC Place: Tucson, Arizona Product: Biodiesel producer out of cooking oil that operates a 1.2m liter plant in Tucson, Arizona....

  18. Phoenix, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    is a stub. You can help OpenEI by expanding it. Phoenix is a city in Maricopa County, Arizona. It falls under Arizona's 2nd congressional district and Arizona's 3rd congressional...

  19. EIA - Household Transportation report: Household Vehicles Energy...

    Energy Information Administration (EIA) (indexed site)

    logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1994 August 1997 Release Next Update: EIA has discontinued this series....

  20. Arizona/Incentives | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Incentive Incentive Type Active APS - Energy Efficiency Solutions for Business (Arizona) Utility Rebate Program Yes APS - GEOSmart Financing Program (Arizona) Utility Loan Program...

  1. Phoenix, Arizona Data Dashboard | Department of Energy

    Energy Saver

    Data Dashboard Phoenix, Arizona Data Dashboard The data dashboard for Phoenix, Arizona, a partner in the Better Buildings Neighborhood Program. Phoenix Data Dashboard (300.58 KB) ...

  2. Arizona State Land Department | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Department Jump to: navigation, search Logo: Arizona State Land Department Name: Arizona State Land Department Abbreviation: ASLD Address: 1616 W. Adams St. Place: Phoenix, AZ Zip:...

  3. Arizona State University | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    University Jump to: navigation, search Name: Arizona State University Place: Tempe, Arizona Zip: 85287 Website: asu.edu Coordinates: 33.4183159, -111.9311939 Show Map Loading...

  4. Geothermal energy in Arizona. Final report

    SciTech Connect

    Stone, C.; Witcher, J.C.

    1982-09-01

    Current knowledge and basic data on geothermal resources in Arizona are compiled. The following are covered: specific area investigations, thermal aspects of Arizona, and exploration methods. (MHR)

  5. Energy Department, Arizona Utilities Announce Transmission Infrastruct...

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

    County, Arizona, and runs southeast to the ED5 Substation in Pinal County, Arizona. ... Area Power Administration Transmission Substation Federal Agencies to Assist with Clean ...

  6. Arizona Corporation Commission | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Commission Jump to: navigation, search Name: Arizona Corporation Commission Abbreviation: ACC Service Territory: Arizona Website: www.azcc.gov EIA Form 861 Data This article is a...

  7. Arizona Solar Tech | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Tech Jump to: navigation, search Name: Arizona Solar Tech Place: Phoenix, Arizona Zip: 85040 Sector: Solar, Vehicles Product: Designs and installs solar PV systems for vehicles,...

  8. Arizona Administrative Code | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona Administrative Code Jump to: navigation, search OpenEI Reference LibraryAdd to library Legal Document- RegulationRegulation: Arizona Administrative CodeLegal Abstract This...

  9. Arizona Regions | U.S. DOE Office of Science (SC)

    Office of Science (SC)

    is designated for your school's state, county, city, or district. For more information, please visit the High School Coach page. Arizona Region High School Regional Arizona Arizona...

  10. Arizona Regions | U.S. DOE Office of Science (SC)

    Office of Science (SC)

    for your school's state, county, city, or district. For more information, please visit the Middle School Coach page. Arizona Region Middle School Regional Arizona Arizona...

  11. Sunshine Arizona Wind Energy LLC | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Sunshine Arizona Wind Energy LLC Jump to: navigation, search Name: Sunshine Arizona Wind Energy LLC Place: Flagstaff, Arizona Zip: 86001 Sector: Wind energy Product: Formed to...

  12. EA-108 Arizona Public Service Company | Department of Energy

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

    EA-108 Arizona Public Service Company Order authorizing Arizona Public Service to export electric energy to Mexico. PDF icon EA-108 Arizona Public Service.pdf More Documents & ...

  13. Arizona Solar Energy Industries Association | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona Solar Energy Industries Association Name: Arizona Solar Energy Industries Association Place: Arizona Website: www.arizonasolarindustry.org Coordinates: 34.0489281,...

  14. Yavapai County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    EV Solar Products Energy Generation Facilities in Yavapai County, Arizona Prescott Airport Solar Plant Solar Power Plant Places in Yavapai County, Arizona Ash Fork, Arizona...

  15. Arizona's 7th congressional district: Energy Resources | Open...

    OpenEI (Open Energy Information) [EERE & EIA]

    in Arizona's 7th congressional district Agenera, LLC Amereco Biofuels Corp Arizona Public Service Company APS Arizona Solar Tech EDGE Energy LLC EGreenIdeas Ecotality North...

  16. Arizona's 4th congressional district: Energy Resources | Open...

    OpenEI (Open Energy Information) [EERE & EIA]

    in Arizona's 4th congressional district Agenera, LLC Amereco Biofuels Corp Arizona Public Service Company APS Arizona Solar Tech EDGE Energy LLC EGreenIdeas Ecotality North...

  17. Arizona's 2nd congressional district: Energy Resources | Open...

    OpenEI (Open Energy Information) [EERE & EIA]

    in Arizona's 2nd congressional district Agenera, LLC Amereco Biofuels Corp Arizona Public Service Company APS Arizona Solar Tech EDGE Energy LLC EGreenIdeas Ecotality North...

  18. Northern Arizona University Wind Projects | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Northern Arizona University Wind Projects (Redirected from Northern Arizona University Wind Project) Jump to: navigation, search Northern Arizona University ARD Wind Project...

  19. Arizona Oil and Gas Commission | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Commission Jump to: navigation, search Logo: Arizona Oil and Gas Commission Name: Arizona Oil and Gas Commission Address: 416 W. Congress Street, Suite 100 Place: Arizona Zip:...

  20. Phoenix, Arizona Summary of Reported Data | Department of Energy

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

    Summary of Reported Data Phoenix, Arizona Summary of Reported Data Summary of data reported by Better Buildings Neighborhood Program partner Phoenix, Arizona. Phoenix, Arizona ...

  1. Arizona Department of Environmental Quality | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona Department of Environmental Quality Name: Arizona Department of Environmental Quality Abbreviation: ADEQ Address: 1110 West Washington Street Phoenix, Arizona 85007 Place:...

  2. Arizona Nuclear Profile - Power Plants

    Energy Information Administration (EIA) (indexed site)

    (thousand mwh)","Share of State nuclear net generation (percent)","Owner" "Palo Verde Unit 1, Unit 2, Unit 3","3,937","31,200",100.0,"Arizona Public Service Co" "1 Plant 3 ...

  3. Subdominant pseudoultrametric on graphs

    SciTech Connect

    Dovgoshei, A A; Petrov, E A

    2013-08-31

    Let (G,w) be a weighted graph. We find necessary and sufficient conditions under which the weight w:E(G)→R{sup +} can be extended to a pseudoultrametric on V(G), and establish a criterion for the uniqueness of such an extension. We demonstrate that (G,w) is a complete k-partite graph, for k≥2, if and only if for any weight that can be extended to a pseudoultrametric, among all such extensions one can find the least pseudoultrametric consistent with w. We give a structural characterization of graphs for which the subdominant pseudoultrametric is an ultrametric for any strictly positive weight that can be extended to a pseudoultrametric. Bibliography: 14 titles.

  4. Fact #614: March 15, 2010 Average Age of Household Vehicles | Department of

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

    Energy 4: March 15, 2010 Average Age of Household Vehicles Fact #614: March 15, 2010 Average Age of Household Vehicles The average age of household vehicles has increased from 6.6 years in 1977 to 9.2 years in 2009. Pickup trucks have the oldest average age in every year listed. Sport utility vehicles (SUVs), first reported in the 1995 survey, have the youngest average age. Average Vehicle Age by Vehicle Type Graph showing the average vehicle age by type (car, van, pickup, SUV, all household

  5. GraphLib

    Energy Science and Technology Software Center

    2013-02-19

    This library is used in several LLNL projects, including STAT (the Stack Trace Analysis Tool for scalable debugging) and some modules in P^nMPI (a tool MPI tool infrastructure). It can also be used standalone for creating and manipulationg graphs, but its API is primarily tuned to support these other projects

  6. Simple and Flexible Scene Graph

    Energy Science and Technology Software Center

    2007-10-01

    The system implements a flexible and extensible scene graph for the visualization and analysis of scientific information.

  7. Temporal Representation in Semantic Graphs

    SciTech Connect

    Levandoski, J J; Abdulla, G M

    2007-08-07

    A wide range of knowledge discovery and analysis applications, ranging from business to biological, make use of semantic graphs when modeling relationships and concepts. Most of the semantic graphs used in these applications are assumed to be static pieces of information, meaning temporal evolution of concepts and relationships are not taken into account. Guided by the need for more advanced semantic graph queries involving temporal concepts, this paper surveys the existing work involving temporal representations in semantic graphs.

  8. A Clustering Graph Generator

    SciTech Connect

    Winlaw, Manda; De Sterck, Hans; Sanders, Geoffrey

    2015-10-26

    In very simple terms a network can be de ned as a collection of points joined together by lines. Thus, networks can be used to represent connections between entities in a wide variety of elds including engi- neering, science, medicine, and sociology. Many large real-world networks share a surprising number of properties, leading to a strong interest in model development research and techniques for building synthetic networks have been developed, that capture these similarities and replicate real-world graphs. Modeling these real-world networks serves two purposes. First, building models that mimic the patterns and prop- erties of real networks helps to understand the implications of these patterns and helps determine which patterns are important. If we develop a generative process to synthesize real networks we can also examine which growth processes are plausible and which are not. Secondly, high-quality, large-scale network data is often not available, because of economic, legal, technological, or other obstacles [7]. Thus, there are many instances where the systems of interest cannot be represented by a single exemplar network. As one example, consider the eld of cybersecurity, where systems require testing across diverse threat scenarios and validation across diverse network structures. In these cases, where there is no single exemplar network, the systems must instead be modeled as a collection of networks in which the variation among them may be just as important as their common features. By developing processes to build synthetic models, so-called graph generators, we can build synthetic networks that capture both the essential features of a system and realistic variability. Then we can use such synthetic graphs to perform tasks such as simulations, analysis, and decision making. We can also use synthetic graphs to performance test graph analysis algorithms, including clustering algorithms and anomaly detection algorithms.

  9. Recursive Feature Extraction in Graphs

    Energy Science and Technology Software Center

    2014-08-14

    ReFeX extracts recursive topological features from graph data. The input is a graph as a csv file and the output is a csv file containing feature values for each node in the graph. The features are based on topological counts in the neighborhoods of each nodes, as well as recursive summaries of neighbors' features.

  10. Arizona Map for Commercial Buildings

    Energy Information Administration (EIA) (indexed site)

    Home > Households, Buildings & Industry > Background Information on CBECS > 1979-1999 CBECS climate zone map Corrections Corrections to 1979-1999 CBECS Climate Zone Map, February...

  11. Arizona Map for Commercial Buildings

    Energy Information Administration (EIA) (indexed site)

    Documents%20and%20SettingsLPJEMEUstyleseiasitewideF.css" rel"stylesheet" type"textcss" > Home > Households, Buildings & Industry > Background Information on CBECS > 2003...

  12. Active mines in Arizona and Arizona exploration offices

    SciTech Connect

    Not Available

    1988-01-01

    This book is a directory that lists 91 mining operations and 107 sand and gravel operations. It lists the company name, address, key personnel, mine, mill, or smelter location, and a description of the operation. A map plotting the locations of all the active mines is also available ($2). Arizona Exploration Offices is a directory that lists 68 exploration companies in Arizona, 80% of whom list gold or silver as their principal exploration target. Other exploration companies are searching for industrial minerals, uranium, beryllium, rare earths, ferroalloys, and sulfur.

  13. Flagstaff, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    a stub. You can help OpenEI by expanding it. Flagstaff is a city in Coconino County, Arizona. It falls under Arizona's 1st congressional district.12 Contents 1 Registered...

  14. Arizona Power Authority | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona Power Authority Place: Arizona Phone Number: 602-368-4265 Website: www.powerauthority.org Outage Hotline: 602-368-4265 References: EIA Form EIA-861 Final Data File for...

  15. Energy Incentive Programs, Arizona | Department of Energy

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

    Arizona Energy Incentive Programs, Arizona Updated February 2015 What public-purpose-funded energy efficiency programs are available in my state? Arizona's restructuring law provides for a systems benefits charge (SBC) to fund energy efficiency programs. The SBC is collected through a non-bypassable surcharge on electricity bills. Although some of these funds have been devoted to renewable energy programs, in 2013 Arizona utilities budgeted over $160 million to promote energy efficiency and load

  16. Arizona: Building Smart from the Start

    SciTech Connect

    2003-06-01

    A fact sheet that describes Arizona's Housing Tax Credit Program, to make sure houses were built more efficiently.

  17. Spectral fluctuations of quantum graphs

    SciTech Connect

    Pluhař, Z.; Weidenmüller, H. A.

    2014-10-15

    We prove the Bohigas-Giannoni-Schmit conjecture in its most general form for completely connected simple graphs with incommensurate bond lengths. We show that for graphs that are classically mixing (i.e., graphs for which the spectrum of the classical Perron-Frobenius operator possesses a finite gap), the generating functions for all (P,Q) correlation functions for both closed and open graphs coincide (in the limit of infinite graph size) with the corresponding expressions of random-matrix theory, both for orthogonal and for unitary symmetry.

  18. Tribal Water in Arizona Conference

    Energy.gov [DOE]

    The Law Seminars International is hosting the Tribal Water in Arizona: New Development for Indian Water Rights, Regulations, and Settlement Processes. The two-day conference will present an overview of the law governing tribal water rights and impacting the development of tribal water projects.

  19. Graph Coarsening for Path Finding in Cybersecurity Graphs

    SciTech Connect

    Hogan, Emilie A.; Johnson, John R.; Halappanavar, Mahantesh

    2013-01-01

    n the pass-the-hash attack, hackers repeatedly steal password hashes and move through a computer network with the goal of reaching a computer with high level administrative privileges. In this paper we apply graph coarsening in network graphs for the purpose of detecting hackers using this attack or assessing the risk level of the network's current state. We repeatedly take graph minors, which preserve the existence of paths in the graph, and take powers of the adjacency matrix to count the paths. This allows us to detect the existence of paths as well as find paths that have high risk of being used by adversaries.

  20. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    Air Conditioning Tables (Million U.S. Households; 24 pages, 138 kb) Contents Pages HC4-1a. Air Conditioning by Climate Zone, Million U.S. Households, 2001 2 HC4-2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 2 HC4-3a. Air Conditioning by Household Income, Million U.S. Households, 2001 2 HC4-4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 2 HC4-5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 2

  1. Quantum Graph Analysis

    SciTech Connect

    Maunz, Peter Lukas Wilhelm; Sterk, Jonathan David; Lobser, Daniel; Parekh, Ojas D.; Ryan-Anderson, Ciaran

    2016-01-01

    In recent years, advanced network analytics have become increasingly important to na- tional security with applications ranging from cyber security to detection and disruption of ter- rorist networks. While classical computing solutions have received considerable investment, the development of quantum algorithms to address problems, such as data mining of attributed relational graphs, is a largely unexplored space. Recent theoretical work has shown that quan- tum algorithms for graph analysis can be more efficient than their classical counterparts. Here, we have implemented a trapped-ion-based two-qubit quantum information proces- sor to address these goals. Building on Sandia's microfabricated silicon surface ion traps, we have designed, realized and characterized a quantum information processor using the hyperfine qubits encoded in two 171 Yb + ions. We have implemented single qubit gates using resonant microwave radiation and have employed Gate set tomography (GST) to characterize the quan- tum process. For the first time, we were able to prove that the quantum process surpasses the fault tolerance thresholds of some quantum codes by demonstrating a diamond norm distance of less than 1 . 9 x 10 [?] 4 . We used Raman transitions in order to manipulate the trapped ions' motion and realize two-qubit gates. We characterized the implemented motion sensitive and insensitive single qubit processes and achieved a maximal process infidelity of 6 . 5 x 10 [?] 5 . We implemented the two-qubit gate proposed by Molmer and Sorensen and achieved a fidelity of more than 97 . 7%.

  2. Recovery Act State Memos Arizona

    Energy.gov [DOE] (indexed site)

    Arizona For questions about DOE's Recovery Act activities, please contact the DOE Recovery Act Clearinghouse: 1-888-DOE-RCVY (888-363-7289), Monday through Friday, 9 a.m. to 7 p.m. Eastern Time https://recoveryclearinghouse.energy.gov/contactUs.htm. All numbers and projects listed as of June 1, 2010 TABLE OF CONTENTS RECOVERY ACT SNAPSHOT................................................................................... 1 FUNDING ALLOCATION

  3. Try This: Household Magnets

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

    Household Magnets Household Magnets Chances are very good that you have experimented with magnets. People have been fascinated with magnetism for thousands of years. As familiar to us as they may be, magnets still have some surprises for us. Here is a small collection of some of our favorite magnet experiments. What happens when we break a magnet in half? Radio Shack sells cheap ceramic magnets in several shapes. Get a ring shaped magnet and break it with pliers or a tap with a hammer. Try to

  4. A Collection of Features for Semantic Graphs

    SciTech Connect

    Eliassi-Rad, T; Fodor, I K; Gallagher, B

    2007-05-02

    Semantic graphs are commonly used to represent data from one or more data sources. Such graphs extend traditional graphs by imposing types on both nodes and links. This type information defines permissible links among specified nodes and can be represented as a graph commonly referred to as an ontology or schema graph. Figure 1 depicts an ontology graph for data from National Association of Securities Dealers. Each node type and link type may also have a list of attributes. To capture the increased complexity of semantic graphs, concepts derived for standard graphs have to be extended. This document explains briefly features commonly used to characterize graphs, and their extensions to semantic graphs. This document is divided into two sections. Section 2 contains the feature descriptions for static graphs. Section 3 extends the features for semantic graphs that vary over time.

  5. Graph Partitioning and Sequencing Software

    Energy Science and Technology Software Center

    1995-09-19

    Graph partitioning is a fundemental problem in many scientific contexts. CHACO2.0 is a software package designed to partition and sequence graphs. CHACO2.0 allows for recursive application of several methods for finding small edge separators in weighted graphs. These methods include inertial, spectral, Kernighan Lin and multilevel methods in addition to several simpler strategies. Each of these approaches can be used to partition the graph into two, four, or eight pieces at each level of recursion.more » In addition, the Kernighan Lin method can be used to improve partitions generated by any of the other algorithms. CHACO2.0 can also be used to address various graph sequencing problems, with applications to scientific computing, database design, gene sequencing and other problems.« less

  6. Monument Valley, Arizona, Processing Site Fact Sheet

    Office of Legacy Management (LM)

    Monument Valley, Arizona, Processing Site This fact sheet provides information about the Uranium Mill Tailings Radiation Control Act of 1978 Title I processing site at Monument Valley, Arizona. This site is managed by the U.S. Department of Energy Office of Legacy Management. Site Description and History The Monument Valley processing site is located on the Navajo Nation in northeastern Arizona, approximately 15 miles south of Mexican Hat, Utah, on the west side of Cane Valley. A uranium-ore

  7. Categorical Exclusion Determinations: Arizona | Department of Energy

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

    Arizona Categorical Exclusion Determinations: Arizona Location Categorical Exclusion Determinations issued for actions in Arizona. DOCUMENTS AVAILABLE FOR DOWNLOAD September 9, 2016 CX-100742 Categorical Exclusion Determination A Novel Platform for Algal Biomass Production Using Cellulosic Mixotrophy Award Number: DE-EE0007562 CX(s) Applied: A9, B3.6, B5.15 Bioenergy Technologies Office Date: 8/29/2016 Location(s): AZ Office(s): Golden Field Office August 26, 2016 CX-100700 Categorical Exclusion

  8. Williams, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Williams, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.2494566, -112.1910031 Show Map Loading map... "minzoom":false,"mappingser...

  9. County, Arizona RECORD OF CATEGORICAL EXCLUSION DETERMINATION

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

    electrical equipment replacementat Gila Substation in Yuma County, Arizona RECORD OF ... This work is necessary to maintain the safety and reliability of the bulk electrical ...

  10. ARIZONA RECOVERY ACT SNAPSHOT | Department of Energy

    Energy.gov [DOE] (indexed site)

    Arizona has substantial natural resources, including coal, solar, and hydroelectric resources. The American Recovery & Reinvestment Act (ARRA) is making a meaningful down payment ...

  11. Arizona Indian Gaming Association (AIGA) Expo

    Energy.gov [DOE]

    This year’s EXPO will take place November 5-7, 2014 at the Radisson Fort McDowell Resort & Casino located in Scottsdale, Arizona.

  12. Arizona Teachers Prepare Students for Green Economy

    Energy.gov [DOE]

    Students led by their building trades teacher , are wiring parts of the Raymond S. Kellis High School in Glendale, Arizona for solar power.

  13. Flagstaff, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona Wind Energy LLC References US Census Bureau Incorporated place and minor civil division population dataset (All States, all geography) US Census Bureau...

  14. Tuba City, Arizona, Disposal Site Community Information

    Office of Legacy Management (LM)

    Tuba City, Arizona, Disposal Site marker. Solar panels supply energy to operate the ... is responsible for caring for the disposal cell and cleaning up groundwater at the Tuba ...

  15. Arizona/Wind Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    source History View New Pages Recent Changes All Special Pages Semantic SearchQuerying Get Involved Help Apps Datasets Community Login | Sign Up Search Page Edit History Arizona...

  16. Arizona Department of Environmental Quality's AZPDES Website...

    OpenEI (Open Energy Information) [EERE & EIA]

    AZPDES Website Jump to: navigation, search OpenEI Reference LibraryAdd to library Web Site: Arizona Department of Environmental Quality's AZPDES Website Abstract This website...

  17. Tucson, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    in Tucson, Arizona Environmentally Protective Power Generation EPPG Ethanol Capital Management Expert Solar Systems General Plasma Inc Genesis Solar LLC GeoInnovation Global...

  18. Prescott, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    district.12 Energy Generation Facilities in Prescott, Arizona Prescott Airport Solar Plant Solar Power Plant References US Census Bureau Incorporated place and...

  19. Mesa, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Inc. ETA Engineering Renegy Holdings Inc The Arizona Center for Algae Technology and Innovation References US Census Bureau Incorporated place and minor civil division...

  20. Arizona Center for Innovation | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Innovation Jump to: navigation, search Name: Arizona Center for Innovation Place: United States Sector: Services Product: General Financial & Legal Services ( Academic Research...

  1. Burnside, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Burnside, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.7511228, -109.6245514 Show Map Loading map... "minzoom":false,"mappingser...

  2. Summit, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Summit, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.0670238, -110.9514796 Show Map Loading map... "minzoom":false,"mappingservi...

  3. Cameron, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.8758285, -111.4129207 Show Map Loading map... "minzoom":false,"mappingservice":"goo...

  4. Ganado, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Ganado, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.7114022, -109.5420492 Show Map Loading map... "minzoom":false,"mappingservi...

  5. Avondale, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Avondale, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.4355977, -112.3496021 Show Map Loading map... "minzoom":false,"mappingser...

  6. Jerome, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.7489107, -112.1137716 Show Map Loading map... "minzoom":false,"mappingservice":"goo...

  7. Northern Arizona University | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    University Jump to: navigation, search Name: Northern Arizona University Place: Flagstaff, AZ Zip: 86011 Phone Number: 928-523-0715 Website: nau.edu Coordinates: 35.1905403,...

  8. Littletown, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Littletown, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.1303561, -110.8728658 Show Map Loading map... "minzoom":false,"mappings...

  9. Peoria, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Peoria, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.5805955, -112.2373779 Show Map Loading map... "minzoom":false,"mappingservi...

  10. Springerville, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Springerville, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.1333799, -109.2859196 Show Map Loading map... "minzoom":false,"mappi...

  11. Surprise, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Surprise, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.6305938, -112.333216 Show Map Loading map... "minzoom":false,"mappingserv...

  12. Cottonwood, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.7391876, -112.0098791 Show Map Loading map... "minzoom":false,"mappingservice":"goo...

  13. Maricopa, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.0581063, -112.0476423 Show Map Loading map... "minzoom":false,"mappingservice":"goo...

  14. Kaibab, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Kaibab, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 36.896652, -112.7407596 Show Map Loading map... "minzoom":false,"mappingservic...

  15. Coolidge, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Coolidge, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.977839, -111.517624 Show Map Loading map... "minzoom":false,"mappingservi...

  16. Gadsden, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Gadsden, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.5544974, -114.7849577 Show Map Loading map... "minzoom":false,"mappingserv...

  17. Whetstone, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Whetstone, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 31.701705, -110.340746 Show Map Loading map... "minzoom":false,"mappingserv...

  18. Chinle, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Chinle, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 36.1544483, -109.5526072 Show Map Loading map... "minzoom":false,"mappingservi...

  19. Blackwater, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Blackwater, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.0311702, -111.582627 Show Map Loading map... "minzoom":false,"mappingse...

  20. Vail, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.0478583, -110.7120272 Show Map Loading map... "minzoom":false,"mappingservice":"goo...

  1. Cornville, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Cornville, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.7177989, -111.9215438 Show Map Loading map... "minzoom":false,"mappingse...

  2. Tsaile, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Tsaile, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 36.303712, -109.214705 Show Map Loading map... "minzoom":false,"mappingservice...

  3. Wilhoit, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Wilhoit, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.4258586, -112.5868398 Show Map Loading map... "minzoom":false,"mappingserv...

  4. Mountainaire, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Mountainaire, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.0852924, -111.6659925 Show Map Loading map... "minzoom":false,"mappin...

  5. Kingman, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.189443, -114.0530065 Show Map Loading map... "minzoom":false,"mappingservice":"goog...

  6. Oracle, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Oracle, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.6109054, -110.7709348 Show Map Loading map... "minzoom":false,"mappingservi...

  7. Fredonia, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 36.945542, -112.5265889 Show Map Loading map... "minzoom":false,"mappingservice":"goog...

  8. Chuichu, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Chuichu, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.752002, -111.7831837 Show Map Loading map... "minzoom":false,"mappingservi...

  9. Sahuarita, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Sahuarita, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 31.9575818, -110.955646 Show Map Loading map... "minzoom":false,"mappingser...

  10. Tortolita, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Tortolita, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.4005302, -111.0400795 Show Map Loading map... "minzoom":false,"mappingse...

  11. Sacaton, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Sacaton, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.0767225, -111.7392993 Show Map Loading map... "minzoom":false,"mappingserv...

  12. Moenkopi, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Moenkopi, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 36.1111043, -111.2223624 Show Map Loading map... "minzoom":false,"mappingser...

  13. Paulden, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Paulden, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.8855756, -112.4682271 Show Map Loading map... "minzoom":false,"mappingserv...

  14. Parks, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Parks, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.2605664, -111.9487743 Show Map Loading map... "minzoom":false,"mappingservic...

  15. Arizona Natural Gas Repressuring (Million Cubic Feet)

    Energy Information Administration (EIA) (indexed site)

    12312015 Next Release Date: 01292016 Referring Pages: Natural Gas Used for Repressuring Arizona Natural Gas Gross Withdrawals and Production Natural Gas Used for Repressuring...

  16. Tacna, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Tacna, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.6975472, -113.9535427 Show Map Loading map... "minzoom":false,"mappingservic...

  17. Houck, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Houck, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.2830803, -109.2070391 Show Map Loading map... "minzoom":false,"mappingservic...

  18. Tucson, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Tucson, Arizona: Energy Resources (Redirected from Tucson, AZ) Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.2217429, -110.926479 Show Map Loading map......

  19. Congress, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Congress, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.162526, -112.8507374 Show Map Loading map... "minzoom":false,"mappingserv...

  20. Supai, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Supai, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 36.2369265, -112.6890791 Show Map Loading map... "minzoom":false,"mappingservic...

  1. Superior, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Superior, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.293945, -111.0962305 Show Map Loading map... "minzoom":false,"mappingserv...

  2. Wellton, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Wellton, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.6728256, -114.1468821 Show Map Loading map... "minzoom":false,"mappingserv...

  3. Carefree, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Carefree, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.8222611, -111.918203 Show Map Loading map... "minzoom":false,"mappingserv...

  4. Willcox, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Willcox, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.2528519, -109.8320124 Show Map Loading map... "minzoom":false,"mappingserv...

  5. Chandler, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Chandler, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.3061605, -111.8412502 Show Map Loading map... "minzoom":false,"mappingser...

  6. Pirtleville, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Pirtleville, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 31.3570467, -109.561734 Show Map Loading map... "minzoom":false,"mappings...

  7. Dudleyville, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Dudleyville, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.914267, -110.733779 Show Map Loading map... "minzoom":false,"mappingse...

  8. Tonalea, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Tonalea, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 36.3224923, -110.9634781 Show Map Loading map... "minzoom":false,"mappingserv...

  9. Mayer, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Mayer, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.3978054, -112.2362734 Show Map Loading map... "minzoom":false,"mappingservic...

  10. Ajo, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Ajo, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.3717248, -112.8607099 Show Map Loading map... "minzoom":false,"mappingservice"...

  11. Wickenburg, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Wickenburg, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.9686412, -112.729622 Show Map Loading map... "minzoom":false,"mappingse...

  12. Glendale, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.5386523, -112.1859866 Show Map Loading map... "minzoom":false,"mappingservice":"goo...

  13. Bisbee, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Bisbee, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 31.4481547, -109.9284084 Show Map Loading map... "minzoom":false,"mappingservi...

  14. Eloy, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Eloy, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.7558962, -111.554844 Show Map Loading map... "minzoom":false,"mappingservice"...

  15. Tolleson, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Tolleson, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.4500425, -112.259321 Show Map Loading map... "minzoom":false,"mappingserv...

  16. Nazlini, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Nazlini, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.8963986, -109.4487147 Show Map Loading map... "minzoom":false,"mappingserv...

  17. Tombstone, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Tombstone, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 31.7128683, -110.0675764 Show Map Loading map... "minzoom":false,"mappingse...

  18. Sedona, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Sedona, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.8697395, -111.7609896 Show Map Loading map... "minzoom":false,"mappingservi...

  19. Sawmill, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Sawmill, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.6181083, -110.3964911 Show Map Loading map... "minzoom":false,"mappingserv...

  20. Pisinemo, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Pisinemo, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.0378487, -112.3209689 Show Map Loading map... "minzoom":false,"mappingser...

  1. Sells, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Sells, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 31.9120215, -111.881234 Show Map Loading map... "minzoom":false,"mappingservice...

  2. Hayden, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Hayden, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.0047878, -110.7853836 Show Map Loading map... "minzoom":false,"mappingservi...

  3. Kearny, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.0570085, -110.9106656 Show Map Loading map... "minzoom":false,"mappingservice":"goo...

  4. Eagar, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Eagar, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.1111581, -109.291475 Show Map Loading map... "minzoom":false,"mappingservice...

  5. Stanfield, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Stanfield, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.8825531, -111.9620805 Show Map Loading map... "minzoom":false,"mappingse...

  6. Mammoth, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Mammoth, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.722568, -110.6406547 Show Map Loading map... "minzoom":false,"mappingservi...

  7. Lukachukai, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Lukachukai, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 36.416946, -109.2287125 Show Map Loading map... "minzoom":false,"mappingse...

  8. Florence, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.0314508, -111.3873431 Show Map Loading map... "minzoom":false,"mappingservice":"goo...

  9. Lechee, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Lechee, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.0322421, -110.7529145 Show Map Loading map... "minzoom":false,"mappingservi...

  10. Guadalupe, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Guadalupe, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.3708798, -111.9629216 Show Map Loading map... "minzoom":false,"mappingse...

  11. Dennehotso, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Dennehotso, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.479167, -111.2375 Show Map Loading map... "minzoom":false,"mappingservi...

  12. Naco, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Naco, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 31.3353801, -109.9481297 Show Map Loading map... "minzoom":false,"mappingservice...

  13. Marana, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Marana, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.414432, -111.172754 Show Map Loading map... "minzoom":false,"mappingservice...

  14. Winkelman, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Winkelman, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.9875659, -110.7709387 Show Map Loading map... "minzoom":false,"mappingse...

  15. Somerton, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Somerton, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.5964404, -114.709677 Show Map Loading map... "minzoom":false,"mappingserv...

  16. Williamson, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Williamson, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.6900229, -112.5410052 Show Map Loading map... "minzoom":false,"mappings...

  17. Buckeye, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Buckeye, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.3703197, -112.5837766 Show Map Loading map... "minzoom":false,"mappingserv...

  18. Santan, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Santan, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.145476, -111.801546 Show Map Loading map... "minzoom":false,"mappingservice...

  19. Gilbert, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.3528264, -111.789027 Show Map Loading map... "minzoom":false,"mappingservice":"goog...

  20. Kaibito, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Kaibito, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 36.5972186, -111.0743114 Show Map Loading map... "minzoom":false,"mappingserv...

  1. Page, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Page, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 36.9147222, -111.4558333 Show Map Loading map... "minzoom":false,"mappingservice...

  2. Douglas, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Douglas, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 31.3445471, -109.5453447 Show Map Loading map... "minzoom":false,"mappingserv...

  3. Steamboat, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Steamboat, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.7513983, -109.8478915 Show Map Loading map... "minzoom":false,"mappingse...

  4. Phoenix, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Phoenix, Arizona: Energy Resources (Redirected from Phoenix, AZ) Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.4483771, -112.0740373 Show Map Loading map......

  5. Leupp, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Leupp, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.2980659, -111.0062528 Show Map Loading map... "minzoom":false,"mappingservic...

  6. Seligman, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Seligman, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.3255608, -112.8774057 Show Map Loading map... "minzoom":false,"mappingser...

  7. Tusayan, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Tusayan, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.9735954, -112.1265569 Show Map Loading map... "minzoom":false,"mappingserv...

  8. Goodyear, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Goodyear, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.4353199, -112.3582135 Show Map Loading map... "minzoom":false,"mappingser...

  9. Catalina, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Catalina, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.5000731, -110.9212146 Show Map Loading map... "minzoom":false,"mappingser...

  10. Yarnell, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Yarnell, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.2216927, -112.7474007 Show Map Loading map... "minzoom":false,"mappingserv...

  11. Yuma, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Yuma, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.7253248, -114.624397 Show Map Loading map... "minzoom":false,"mappingservice"...

  12. Arizona Department of Environmental Quality's Individual Permits...

    OpenEI (Open Energy Information) [EERE & EIA]

    search OpenEI Reference LibraryAdd to library Web Site: Arizona Department of Environmental Quality's Individual Permits Website Abstract This website contains information...

  13. Arizona Department of Environmental Quality's General Permits...

    OpenEI (Open Energy Information) [EERE & EIA]

    search OpenEI Reference LibraryAdd to library Web Site: Arizona Department of Environmental Quality's General Permits Website Abstract This website provides information...

  14. Arizona Department of Environmental Quality's Application Forms...

    OpenEI (Open Energy Information) [EERE & EIA]

    search OpenEI Reference LibraryAdd to library Web Site: Arizona Department of Environmental Quality's Application Forms and Guidance Website Abstract This site contains forms...

  15. BLM Arizona State Office | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona Address: One North Central Avenue, Suite 800 Place: Phoenix, AZ Zip: 85004 Phone Number: 602-417-9200 ParentHolding Organization: Bureau of Land Management...

  16. EA-106 Arizona Public Service Company | Department of Energy

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

    EA-106 Arizona Public Service Company Order authorizing Arizona Public Service Company to export electric energy to Mexico. PDF icon EA-106 Arizona Public Service (MX).pdf More ...

  17. A Solar Win for Arizona | Department of Energy

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

    A Solar Win for Arizona A Solar Win for Arizona January 9, 2013 - 5:11pm Addthis The 150 megawatt Mesquite Solar 1 installation in Maricopa County, Arizona. | Photo courtesy of Sempra Energy. The 150 megawatt Mesquite Solar 1 installation in Maricopa County, Arizona. | Photo courtesy of Sempra Energy. The 150 megawatt Mesquite Solar 1 installation in Maricopa County, Arizona. | Photo courtesy of Sempra Energy. The 150 megawatt Mesquite Solar 1 installation in Maricopa County, Arizona. | Photo

  18. The Future of Electric Vehicles and Arizona State University's MAIL

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

    Battery | Department of Energy The Future of Electric Vehicles and Arizona State University's MAIL Battery The Future of Electric Vehicles and Arizona State University's MAIL Battery August 11, 2010 - 4:26pm Addthis Cody Friesen and his team at Arizona State University | Photo Credit Arizona State University Cody Friesen and his team at Arizona State University | Photo Credit Arizona State University Andy Oare Andy Oare Former New Media Strategist, Office of Public Affairs What does this

  19. spaceheat_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  20. usage_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    Usage Indicators by South Census Region, Million U.S. Households, 2001 5 HC6-12a. Usage Indicators by West Census Region, Million U.S. Households, 2001 5 These data are from the ...

  1. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2001 2 HC2-12a. Household Characteristics by West Census Region, Million U.S. Households, 2001 2 These data are from the 2001 Residential Energy Consumption Survey ...

  2. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    Home Office Equipment by South Census Region, Million U.S. Households, 2001 1 HC7-12a. Home Office Equipment by West Census Region, Million U.S. Households, 2001 1 These data are ...

  3. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    9a. Household Characteristics by Northeast Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.5 Total .............................................................. 107.0 20.3 14.8 5.4 NE Household Size 1 Person ...................................................... 28.2 6.0 4.4 1.6 3.5 2 Persons

  4. City of Williams - AZ, Arizona (Utility Company) | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    Williams - AZ, Arizona (Utility Company) Jump to: navigation, search Name: City of Williams - AZ Place: Arizona Phone Number: 928-635-2667 or 928-635-4451 Website:...

  5. Final Report - Arizona Rooftop Solar Challenge | Department of...

    Energy.gov [DOE] (indexed site)

    Arizona Governor's Office of Energy Policy Location: Phoenix, AZ Subprogram: Soft Costs Funding Program: Rooftop Solar Challenge 1 The Arizona Rooftop Solar Challenge (ARC) is a ...

  6. EERE Success Story-Arizona: Solar Panels Replace Inefficient...

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

    Arizona: Solar Panels Replace Inefficient Fossil Fuel-Powered Energy Systems EERE Success Story-Arizona: Solar Panels Replace Inefficient Fossil Fuel-Powered Energy Systems May 1, ...

  7. Arizona Const. Art.15 - The Corporation Commission | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona Const. Art.15 - The Corporation CommissionLegal Abstract This article sets forth the Constitutional provisions governing the Arizona Corporations Commission. Published...

  8. Arizona's 3rd congressional district: Energy Resources | Open...

    OpenEI (Open Energy Information) [EERE & EIA]

    congressional district Agenera, LLC Alchemix Corporation Amereco Biofuels Corp Arizona Public Service Company APS Arizona Solar Tech EDGE Energy LLC EGreenIdeas Ecotality North...

  9. Arizona Public Service Company APS | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Public Service Company APS Jump to: navigation, search Name: Arizona Public Service Company (APS) Place: Phoenix, Arizona Zip: 85004 Product: Generates, transmits and distributes...

  10. The Arizona Center for Algae Technology and Innovation | Open...

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona Center for Algae Technology and Innovation Jump to: navigation, search Name: The Arizona Center for Algae Technology and Innovation Abbreviation: AzCATI Address: 7418 East...

  11. Northern Arizona University Wind Projects | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Wind Projects Jump to: navigation, search Northern Arizona University ARD Wind Project Northern Arizona University SHRM Wind Project Retrieved from "http:en.openei.orgw...

  12. Arizona Transmission Line Siting Committee | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Line Siting Committee Jump to: navigation, search Name: Arizona Transmission Line Siting Committee Abbreviation: TLSC Address: 1200 West Washington Street Place: Phoenix, Arizona...

  13. EIS-0474: Southline Transmission Line Project; Arizona and New...

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

    Transmission Line Project; Arizona and New Mexico EIS-0474: Southline Transmission Line Project; Arizona and New Mexico Summary The Bureau of Land Management and Western ...

  14. Household energy consumption and expenditures 1987

    SciTech Connect

    Not Available

    1990-01-22

    This report is the third in the series of reports presenting data from the 1987 Residential Energy Consumption Survey (RECS). The 1987 RECS, seventh in a series of national surveys of households and their energy suppliers, provides baseline information on household energy use in the United States. Data from the seven RECS and its companion survey, the Residential Transportation Energy Consumption Survey (RTECS), are made available to the public in published reports such as this one, and on public use data files. This report presents data for the four Census regions and nine Census divisions on the consumption of and expenditures for electricity, natural gas, fuel oil and kerosene (as a single category), and liquefied petroleum gas (LPG). Data are also presented on consumption of wood at the Census region level. The emphasis in this report is on graphic depiction of the data. Data from previous RECS surveys are provided in the graphics, which indicate the regional trends in consumption, expenditures, and uses of energy. These graphs present data for the United States and each Census division. 12 figs., 71 tabs.

  15. Efficient Graph Analytics for Genomics

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

    Design » Types of Homes » Efficient Earth-Sheltered Homes Efficient Earth-Sheltered Homes This house in Tempe, Arizona, uses earth-sheltered construction methods to help decrease cooling costs. | Photo by Pamm McFadden This house in Tempe, Arizona, uses earth-sheltered construction methods to help decrease cooling costs. | Photo by Pamm McFadden If you are looking for a home with energy-efficient features that will provide a comfortable, tranquil, weather-resistant dwelling, an earth-sheltered

  16. Bisfuel links - Arizona State University

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

    Arizona State University http://chemistry.asu.edu/" target="_blank">ASU Department of Chemistry and Biochemistry http://sustainability.asu.edu/index.php" target="_blank">ASU Global Institute of Sustainability http://asulightworks.com/" target="_blank">ASU Lightworks http://sols.asu.edu/" target="_blank">ASU School of Life Sciences http://www.biodesign.asu.edu/" target="_blank">Biodesign Institute

  17. Arizona Nuclear Profile - Power Plants

    Energy Information Administration (EIA) (indexed site)

    nuclear power plants, summer capacity and net generation, 2010" "Plant name/total reactors","Summer capacity (mw)","Net generation (thousand mwh)","Share of State nuclear net generation (percent)","Owner" "Palo Verde Unit 1, Unit 2, Unit 3","3,937","31,200",100.0,"Arizona Public Service Co" "1 Plant 3 Reactors","3,937","31,200",100.0 "Note: Totals may not equal sum of

  18. Phoenix, Arizona Data Dashboard | Department of Energy

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

    Data Dashboard Phoenix, Arizona Data Dashboard The data dashboard for Phoenix, Arizona, a partner in the Better Buildings Neighborhood Program. Phoenix Data Dashboard (300.58 KB) More Documents & Publications Austin Energy Data Dashboard Massachusetts -- SEP Data Dashboard Camden, New Jersey Data Dashboard

  19. Khovanov homology of graph-links

    SciTech Connect

    Nikonov, Igor M

    2012-08-31

    Graph-links arise as the intersection graphs of turning chord diagrams of links. Speaking informally, graph-links provide a combinatorial description of links up to mutations. Many link invariants can be reformulated in the language of graph-links. Khovanov homology, a well-known and useful knot invariant, is defined for graph-links in this paper (in the case of the ground field of characteristic two). Bibliography: 14 titles.

  20. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    3a. Household Characteristics by Household Income, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Household Size 1 Person ....................................... 28.2 9.7 --

  1. ac_household2001.pdf

    Annual Energy Outlook

    ... those households were treated as if the fuel was electricity. 3 The 2001 RECS reported ... Notes: * To obtain the RSE percentage for any table cell, multiply the corresponding ...

  2. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    or commercial trucks (See Table 1). Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 5 The 1991 RTECS count includes vehicles that were owned or used...

  3. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1991 December 1993 Release Next Update: August 1997. Based on the 1991...

  4. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    0a. Household Characteristics by Midwest Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 24.5 17.1 7.4 NE Household Size 1 Person ...................................................... 28.2 6.7 4.7 2.0 6.2 2 Persons

  5. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    1a. Household Characteristics by South Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.1 1.5 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Household Size 1 Person ...................................................... 28.2 9.9 5.0 1.8 3.1 6.3 2 Persons

  6. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2a. Household Characteristics by West Census Region, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.8 1.1 Total .............................................................. 107.0 23.3 6.7 16.6 NE Household Size 1 Person ...................................................... 28.2 5.6 1.8 3.8 5.4 2 Persons .................................................... 35.1 7.3 1.9 5.5

  7. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    4a. Household Characteristics by Type of Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Homes Two to Four Units Five or More Units 0.4 0.5 1.6 1.4 2.0 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.3 Household Size 1 Person ....................................... 28.2 15.0 3.3 7.9 1.9 5.9 2 Persons

  8. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    6a. Household Characteristics by Type of Rented Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total Rented Units ........................ 34.3 10.5 7.4 15.2 1.1 6.9 Household Size 1 Person ....................................... 12.3 2.5 2.6 7.0 0.3 10.0 2 Persons

  9. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    8a. Household Characteristics by Urban/Rural Location, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.1 Household Size 1 Person ...................................................... 28.2 14.6 5.3 4.8 3.6 6.4 2 Persons .................................................... 35.1 15.7 5.7

  10. Graph Analytics for Signature Discovery

    SciTech Connect

    Hogan, Emilie A.; Johnson, John R.; Halappanavar, Mahantesh; Lo, Chaomei

    2013-06-01

    Within large amounts of seemingly unstructured data it can be diffcult to find signatures of events. In our work we transform unstructured data into a graph representation. By doing this we expose underlying structure in the data and can take advantage of existing graph analytics capabilities, as well as develop new capabilities. Currently we focus on applications in cybersecurity and communication domains. Within cybersecurity we aim to find signatures for perpetrators using the pass-the-hash attack, and in communications we look for emails or phone calls going up or down a chain of command. In both of these areas, and in many others, the signature we look for is a path with certain temporal properties. In this paper we discuss our methodology for finding these temporal paths within large graphs.

  11. Graph modeling systems and methods

    SciTech Connect

    Neergaard, Mike

    2015-10-13

    An apparatus and a method for vulnerability and reliability modeling are provided. The method generally includes constructing a graph model of a physical network using a computer, the graph model including a plurality of terminating vertices to represent nodes in the physical network, a plurality of edges to represent transmission paths in the physical network, and a non-terminating vertex to represent a non-nodal vulnerability along a transmission path in the physical network. The method additionally includes evaluating the vulnerability and reliability of the physical network using the constructed graph model, wherein the vulnerability and reliability evaluation includes a determination of whether each terminating and non-terminating vertex represents a critical point of failure. The method can be utilized to evaluate wide variety of networks, including power grid infrastructures, communication network topologies, and fluid distribution systems.

  12. Arizona Natural Gas Repressuring (Million Cubic Feet)

    Gasoline and Diesel Fuel Update

    Repressuring (Million Cubic Feet) Arizona Natural Gas Repressuring (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 103 ...

  13. EIS-0322: Sundance Energy Project, Arizona

    Energy.gov [DOE]

    This EIS analyzes Western Area Power Administration (Western) decision to approve Sundance Energy LLC (Sundance) to interconnect a planned generator facility to Westerns transmission system in the vicinity of Coolidge, Arizona.

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

    Energy Information Administration (EIA) (indexed site)

    ,,"(202) 586-8800",,,"08292016 11:11:29 AM" "Back to Contents","Data 1: Arizona Natural Gas Gross Withdrawals and Production" "Sourcekey","N9010AZ2","N9011AZ2","N9012AZ2","NGME...

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

    Energy Information Administration (EIA) (indexed site)

    ,,"(202) 586-8800",,,"08292016 11:11:30 AM" "Back to Contents","Data 1: Arizona Natural Gas Gross Withdrawals and Production" "Sourcekey","N9010AZ2","N9011AZ2","N9012AZ2","NGME...

  16. Federal Correctional Institution - Phoenix, Arizona | Department...

    Energy Saver

    Photo of a Parabolic-Trough Solar Water-Heating System Installed at the Federal Correctional Institution Facility north of Phoenix, Arizona A parabolic-trough solar water-heating ...

  17. Northern Arizona University 2014 | Department of Energy

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

    Northern Arizona University 2014 Northern Arizona University 2014 Pictured: Torey Schreiner, Mariflor Caronan, Ian Mason, Andrew Hoffman, Jonathan Pepper, Carlos Tarango, Chris Feyen, Stephen Kuluris, Jared Parks, Nathan Croswell, Devon Martindale, Kyle Yates, Anna Manning, Kenny Saxer, Norman Khoo, Charles Burge, Melissa Head, Chris Bozworth, Gabriel O'Reilly, Lukas Loehr, Kelsey Morales, Ashley Jerome, Frank Spitznogle, Karin Wadsack, and David Willy. Photo by MIWhittakerPhotos. Pictured:

  18. Dr.L: Distributed Recursive (Graph) Layout

    Energy Science and Technology Software Center

    2007-11-19

    Dr. L provides two-dimensional visualizations of very large abstract graph structures. it can be used for data mining applications including biology, scientific literature, and social network analysis. Dr. L is a graph layout program that uses a multilevel force-directed algorithm. A graph is input and drawn using a force-directed algorithm based on simulated annealing. The resulting layout is clustered using a single link algorithm. This clustering is used to produce a coarsened graph (fewer nodes)more » which is then re-drawn. this process is repeated until a sufficiently small graph is produced. The smallest graph is drawn and then used as a basis for drawing the original graph by refining the series of coarsened graphs that were produced. The layout engine can be run in serial or in parallel.« less

  19. Household vehicles energy consumption 1994

    SciTech Connect

    1997-08-01

    Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use some 6,000 vehicles provided information to describe vehicle stock, vehicle-miles traveled, energy end-use consumption, and energy expenditures for personal vehicles. The survey results represent the characteristics of the 84.9 million households that used or had access to vehicles in 1994 nationwide. (An additional 12 million households neither owned or had access to vehicles during the survey year.) To be included in then RTECS survey, vehicles must be either owned or used by household members on a regular basis for personal transportation, or owned by a company rather than a household, but kept at home, regularly available for the use of household members. Most vehicles included in the RTECS are classified as {open_quotes}light-duty vehicles{close_quotes} (weighing less than 8,500 pounds). However, the RTECS also includes a very small number of {open_quotes}other{close_quotes} vehicles, such as motor homes and larger trucks that are available for personal use.

  20. Strategies for Collecting Household Energy Data | Department...

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

    Collecting Household Energy Data Strategies for Collecting Household Energy Data Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for ...

  1. Household Vehicles Energy Use Cover Page

    Energy Information Administration (EIA) (indexed site)

    Energy Use Cover Page Glossary Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use Cover Page Contact Us * Feedback * PrivacySecurity *...

  2. Shared Solar Projects Powering Households Throughout America...

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

    Shared Solar Projects Powering Households Throughout America Shared Solar Projects Powering Households Throughout America January 31, 2014 - 2:30pm Addthis Shared solar projects ...

  3. Next Generation Household Refrigerator | Department of Energy

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

    Next Generation Household Refrigerator Next Generation Household Refrigerator Embraco's high efficiency, oil-free linear compressor.
    Credit: Whirlpool Embraco's high ...

  4. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    9a. Air Conditioning by Northeast Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.8 Households With Electric Air-Conditioning Equipment ...................... 82.9 14.5 11.3 3.2 3.3 Air Conditioners Not Used ........................... 2.1 0.3 0.3 Q 28.3 Households Using Electric Air-Conditioning 1

  5. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    3a. Appliances by Household Income, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.5 1.4 1.1 1.0 0.8 1.6 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.2 Kitchen Appliances Cooking Appliances Oven

  6. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    0a. Air Conditioning by Midwest Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 20.5 13.6 6.8 2.2 Air Conditioners Not Used ........................... 2.1 0.3 Q Q 27.5 Households Using Electric Air-Conditioning 1

  7. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    1a. Air Conditioning by South Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 37.2 19.3 6.4 11.5 1.5 Air Conditioners Not Used ........................... 2.1 0.4 Q Q Q 28.2 Households Using Electric Air-Conditioning 1

  8. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2a. Air Conditioning by West Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.4 1.2 1.7 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 10.7 3.4 7.2 7.1 Air Conditioners Not Used ........................... 2.1 1.1 0.2 0.9 15.5 Households Using Electric Air-Conditioning 1 ........................................ 80.8 9.6 3.2

  9. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.6 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 82.9 58.7 6.5 12.4 5.3 4.9 Air Conditioners Not Used ............ 2.1 1.1 Q 0.6 Q 21.8 Households Using Electric Air-Conditioning 1

  10. SOURCE PHENOMENOLOGY EXPERIMENTS IN ARIZONA

    SciTech Connect

    Jessie L. Bonner; Brian Stump; Mark Leidig; Heather Hooper; Xiaoning Yang; Rongmao Zhou; Tae Sung Kim; William R. Walter; Aaron Velasco; Chris Hayward; Diane Baker; C. L. Edwards; Steven Harder; Travis Glenn; Cleat Zeiler; James Britton; James F. Lewkowicz

    2005-09-30

    The Arizona Source Phenomenology Experiments (SPE) have resulted in an important dataset for the nuclear monitoring community. The 19 dedicated single-fired explosions and multiple delay-fired mining explosions were recorded by one of the most densely instrumented accelerometer and seismometer arrays ever fielded, and the data have already proven useful in quantifying confinement and excitation effects for the sources. It is very interesting to note that we have observed differences in the phenomenology of these two series of explosions resulting from the differences between the relatively slow (limestone) and fast (granodiorite) media. We observed differences at the two SPE sites in the way the rock failed during the explosions, how the S-waves were generated, and the amplitude behavior as a function of confinement. Our consortium's goal is to use the synergy of the multiple datasets collected during this experiment to unravel the phenomenological differences between the two emplacement media. The data suggest that the main difference between single-fired chemical and delay-fired mining explosion seismograms at regional distances is the increased surface wave energy for the latter source type. The effect of the delay-firing is to decrease the high-frequency P-wave amplitudes while increasing the surface wave energy because of the longer source duration and spall components. The results suggest that the single-fired explosions are surrogates for nuclear explosions in higher frequency bands (e.g., 6-8 Hz Pg/Lg discriminants). We have shown that the SPE shots, together with the mining explosions, are efficient sources of S-wave energy, and our next research stage is to postulate the possible sources contributing to the shear-wave energy.

  11. Generalized graph states based on Hadamard matrices

    SciTech Connect

    Cui, Shawn X.; Yu, Nengkun; Zeng, Bei

    2015-07-15

    Graph states are widely used in quantum information theory, including entanglement theory, quantum error correction, and one-way quantum computing. Graph states have a nice structure related to a certain graph, which is given by either a stabilizer group or an encoding circuit, both can be directly given by the graph. To generalize graph states, whose stabilizer groups are abelian subgroups of the Pauli group, one approach taken is to study non-abelian stabilizers. In this work, we propose to generalize graph states based on the encoding circuit, which is completely determined by the graph and a Hadamard matrix. We study the entanglement structures of these generalized graph states and show that they are all maximally mixed locally. We also explore the relationship between the equivalence of Hadamard matrices and local equivalence of the corresponding generalized graph states. This leads to a natural generalization of the Pauli (X, Z) pairs, which characterizes the local symmetries of these generalized graph states. Our approach is also naturally generalized to construct graph quantum codes which are beyond stabilizer codes.

  12. ,"Arizona Natural Gas Gross Withdrawals from Shale Gas (Million...

    Energy Information Administration (EIA) (indexed site)

    7:59:59 AM" "Back to Contents","Data 1: Arizona Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)" "Sourcekey","NGMEPG0FGSSAZMMCF" "Date","Arizona Natural Gas ...

  13. Fort Defiance, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    OpenEI by expanding it. Fort Defiance is a census-designated place in Apache County, Arizona.1 US Recovery Act Smart Grid Projects in Fort Defiance, Arizona Navajo Tribal...

  14. San Luis, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Hide Map This article is a stub. You can help OpenEI by expanding it. San Luis is a city in Yuma County, Arizona. It falls under Arizona's 7th congressional...

  15. Casa Grande, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Hide Map This article is a stub. You can help OpenEI by expanding it. Casa Grande is a city in Pinal County, Arizona. It falls under Arizona's 1st congressional...

  16. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    16.8 17.4 18.6 18.9 1.7 2.2 0.6 1.5 Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 15 Vehicle Miles Traveled per Vehicle (Thousand) . . . . . . . . ....

  17. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    a. Household Characteristics by Climate Zone, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.0 Total ............................................... 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Household Size 1 Person ....................................... 28.2 2.5 8.1 6.5

  18. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2a. Household Characteristics by Year of Construction, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.0 1.2 1.2 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Household Size 1 Person ....................................... 28.2 2.5 4.5 5.1 4.0 3.7 8.3 7.5 2 Persons

  19. char_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    5a. Household Characteristics by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Household Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Homes Two to Four Units Five or More Units 0.3 0.4 2.0 2.9 1.3 Total Owner-Occupied Units ....... 72.7 63.2 2.1 1.8 5.7 6.7 Household Size 1 Person ....................................... 15.8 12.5 0.8 0.9 1.6 10.3 2 Persons

  20. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    3a. Air Conditioning by Household Income, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.5 1.4 1.1 1.0 0.9 1.5 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 12.3 17.4 21.5 31.7 9.6 23.4 3.9 Air Conditioners Not Used ............ 2.1 0.4 0.7 0.5 0.5 0.4 0.9 20.8

  1. Havasupai Indian Reservation, Supai Village, Arizona | Department of Energy

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

    Havasupai Indian Reservation, Supai Village, Arizona Havasupai Indian Reservation, Supai Village, Arizona Photo of Photovoltaic Energy System at Havasupai Indian Reservation Village of Supai, Arizona The Havasupai Indian Reservation village of Supai, Arizona, is located approximately 40 miles northwest of Grand Canyon Village, AZ. It is one of the most remote Native American communities in the nation. Most supplies must be either flown in by helicopter or trekked in on horseback or by mule

  2. EA-134-APS Arizona Public Service Company | Department of Energy

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

    4-APS Arizona Public Service Company EA-134-APS Arizona Public Service Company Order authorizing Arizona Public Service Company to export electric energy to Mexico. EA-134-APS Arizona Public Service Company (24.95 KB) More Documents & Publications EA-184 Morgan Stanley Capital Group Inc. EA-166 Duke Energy Trading and Marketing, L.L.C EA-181 H.Q Energy Services (U.S) Inc

  3. Arizona Recovery Act State Memo | Department of Energy

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

    Arizona Recovery Act State Memo Arizona Recovery Act State Memo Arizona has substantial natural resources, including coal, solar, and hydroelectric resources. The American Recovery & Reinvestment Act (ARRA) is making a meaningful down payment on the nation's energy and environmental future. The Recovery Act investments in Arizona reflect a broad range of clean energy projects, from energy efficiency and the smart grid to transportation, carbon capture and storage, and geothermal energy.

  4. Cover Page of Household Vehicles Energy Use: Latest Data & Trends

    Gasoline and Diesel Fuel Update

    Household Vehicles Energy Use Cover Page Cover Page of Household Vehicles Energy Use: Latest Data & Trends...

  5. Phoenix, Arizona Summary of Reported Data | Department of Energy

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

    Summary of Reported Data Phoenix, Arizona Summary of Reported Data Summary of data reported by Better Buildings Neighborhood Program partner Phoenix, Arizona. Phoenix, Arizona Summary of Reported Data (2.15 MB) More Documents & Publications Virginia -- SEP Summary of Reported Data University Park Summary of Reported Data Alabama -- SEP Summary of Reported Data

  6. Fast generation of sparse random kernel graphs

    DOE PAGES [OSTI]

    Hagberg, Aric; Lemons, Nathan; Du, Wen -Bo

    2015-09-10

    The development of kernel-based inhomogeneous random graphs has provided models that are flexible enough to capture many observed characteristics of real networks, and that are also mathematically tractable. We specify a class of inhomogeneous random graph models, called random kernel graphs, that produces sparse graphs with tunable graph properties, and we develop an efficient generation algorithm to sample random instances from this model. As real-world networks are usually large, it is essential that the run-time of generation algorithms scales better than quadratically in the number of vertices n. We show that for many practical kernels our algorithm runs in timemore » at most ο(n(logn)²). As an example, we show how to generate samples of power-law degree distribution graphs with tunable assortativity.« less

  7. Fast generation of sparse random kernel graphs

    SciTech Connect

    Hagberg, Aric; Lemons, Nathan; Du, Wen -Bo

    2015-09-10

    The development of kernel-based inhomogeneous random graphs has provided models that are flexible enough to capture many observed characteristics of real networks, and that are also mathematically tractable. We specify a class of inhomogeneous random graph models, called random kernel graphs, that produces sparse graphs with tunable graph properties, and we develop an efficient generation algorithm to sample random instances from this model. As real-world networks are usually large, it is essential that the run-time of generation algorithms scales better than quadratically in the number of vertices n. We show that for many practical kernels our algorithm runs in time at most ο(n(logn)²). As an example, we show how to generate samples of power-law degree distribution graphs with tunable assortativity.

  8. API Requirements for Dynamic Graph Prediction

    SciTech Connect

    Gallagher, B; Eliassi-Rad, T

    2006-10-13

    Given a large-scale time-evolving multi-modal and multi-relational complex network (a.k.a., a large-scale dynamic semantic graph), we want to implement algorithms that discover patterns of activities on the graph and learn predictive models of those discovered patterns. This document outlines the application programming interface (API) requirements for fast prototyping of feature extraction, learning, and prediction algorithms on large dynamic semantic graphs. Since our algorithms must operate on large-scale dynamic semantic graphs, we have chosen to use the graph API developed in the CASC Complex Networks Project. This API is supported on the back end by a semantic graph database (developed by Scott Kohn and his team). The advantages of using this API are (i) we have full-control of its development and (ii) the current API meets almost all of the requirements outlined in this document.

  9. Graph algorithms in the titan toolkit.

    SciTech Connect

    McLendon, William Clarence, III; Wylie, Brian Neil

    2009-10-01

    Graph algorithms are a key component in a wide variety of intelligence analysis activities. The Graph-Based Informatics for Non-Proliferation and Counter-Terrorism project addresses the critical need of making these graph algorithms accessible to Sandia analysts in a manner that is both intuitive and effective. Specifically we describe the design and implementation of an open source toolkit for doing graph analysis, informatics, and visualization that provides Sandia with novel analysis capability for non-proliferation and counter-terrorism.

  10. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.8 0.5 1.4 1.2 1.6 Households With Electric Air-Conditioning Equipment ........ 23.4 58.7 6.5 12.4 5.3 6.1 Air Conditioners Not Used ............ 0.9 1.1 Q 0.6 Q 23.0 Households Using Electric Air-Conditioning

  11. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.1 1.2 1.1 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 13.6 16.0 14.7 10.4 10.5 17.6 4.7 Air Conditioners Not Used ............ 2.1 Q 0.3 0.5 0.3 0.4 0.5 27.2 Households Using Electric Air-Conditioning 2

  12. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 59.5 58.7 6.5 12.4 5.3 5.2 Air Conditioners Not Used ............ 1.2 1.1 Q 0.6 Q 23.3 Households Using

  13. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    0a. Home Office Equipment by Midwest Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Households Using Office Equipment ......................................... 96.2 22.4 15.7 6.7 1.3 Personal Computers 1 ................................. 60.0

  14. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    1a. Home Office Equipment by South Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Households Using Office Equipment ......................................... 96.2 34.6 18.4 6.0 10.1 1.2 Personal Computers 1

  15. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2a. Home Office Equipment by West Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Households Using Office Equipment ......................................... 96.2 21.4 6.2 15.2 1.0 Personal Computers 1 ................................. 60.0 14.3 4.0 10.4 3.7 Number of

  16. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    9a. Home Office Equipment by Northeast Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.1 1.4 1.2 Total .............................................................. 107.0 20.3 14.8 5.4 NE Households Using Office Equipment ......................................... 96.2 17.9 12.8 5.0 1.3 Personal Computers 1 ................................. 60.0 10.9

  17. Enabling Graph Appliance for Genome Assembly

    SciTech Connect

    Singh, Rina; Graves, Jeffrey A; Lee, Sangkeun; Sukumar, Sreenivas R; Shankar, Mallikarjun

    2015-01-01

    In recent years, there has been a huge growth in the amount of genomic data available as reads generated from various genome sequencers. The number of reads generated can be huge, ranging from hundreds to billions of nucleotide, each varying in size. Assembling such large amounts of data is one of the challenging computational problems for both biomedical and data scientists. Most of the genome assemblers developed have used de Bruijn graph techniques. A de Bruijn graph represents a collection of read sequences by billions of vertices and edges, which require large amounts of memory and computational power to store and process. This is the major drawback to de Bruijn graph assembly. Massively parallel, multi-threaded, shared memory systems can be leveraged to overcome some of these issues. The objective of our research is to investigate the feasibility and scalability issues of de Bruijn graph assembly on Cray s Urika-GD system; Urika-GD is a high performance graph appliance with a large shared memory and massively multithreaded custom processor designed for executing SPARQL queries over large-scale RDF data sets. However, to the best of our knowledge, there is no research on representing a de Bruijn graph as an RDF graph or finding Eulerian paths in RDF graphs using SPARQL for potential genome discovery. In this paper, we address the issues involved in representing a de Bruin graphs as RDF graphs and propose an iterative querying approach for finding Eulerian paths in large RDF graphs. We evaluate the performance of our implementation on real world ebola genome datasets and illustrate how genome assembly can be accomplished with Urika-GD using iterative SPARQL queries.

  18. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... 29.1 5.3 22.7 3.8 1 Below 150 percent of poverty line or 60 percent of median State income

  19. ac_household2001.pdf

    Annual Energy Outlook

    RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With ... RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Pays for Electricity ...

  20. char_household2001.pdf

    Annual Energy Outlook

    RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Total ... RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Household Owns or ...

  1. Useful Graphs and Charts - Ion Beams - Radiation Effects Facility...

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

    Times 15 MeVu LET vs Range Graph 25 MeVu LET vs Range Graph 40 Mevu LET vs Range Graph Radiation Effects Facility Cyclotron Institute Texas A&M University MS 3366 ...

  2. Graph Mining Meets the Semantic Web

    SciTech Connect

    Lee, Sangkeun; Sukumar, Sreenivas R; Lim, Seung-Hwan

    2015-01-01

    The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today, data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. We address that need through implementation of three popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, and PageRank). We implement these algorithms as SPARQL queries, wrapped within Python scripts. We evaluate the performance of our implementation on 6 real world data sets and show graph mining algorithms (that have a linear-algebra formulation) can indeed be unleashed on data represented as RDF graphs using the SPARQL query interface.

  3. GraphReduce: Processing Large-Scale Graphs on Accelerator-Based Systems

    SciTech Connect

    Sengupta, Dipanjan; Song, Shuaiwen; Agarwal, Kapil; Schwan, Karsten

    2015-11-15

    Recent work on real-world graph analytics has sought to leverage the massive amount of parallelism offered by GPU devices, but challenges remain due to the inherent irregularity of graph algorithms and limitations in GPU-resident memory for storing large graphs. We present GraphReduce, a highly efficient and scalable GPU-based framework that operates on graphs that exceed the device’s internal memory capacity. GraphReduce adopts a combination of edge- and vertex-centric implementations of the Gather-Apply-Scatter programming model and operates on multiple asynchronous GPU streams to fully exploit the high degrees of parallelism in GPUs with efficient graph data movement between the host and device.

  4. GraphReduce: Large-Scale Graph Analytics on Accelerator-Based HPC Systems

    SciTech Connect

    Sengupta, Dipanjan; Agarwal, Kapil; Song, Shuaiwen; Schwan, Karsten

    2015-09-30

    Recent work on real-world graph analytics has sought to leverage the massive amount of parallelism offered by GPU devices, but challenges remain due to the inherent irregularity of graph algorithms and limitations in GPU-resident memory for storing large graphs. We present GraphReduce, a highly efficient and scalable GPU-based framework that operates on graphs that exceed the device’s internal memory capacity. GraphReduce adopts a combination of both edge- and vertex-centric implementations of the Gather-Apply-Scatter programming model and operates on multiple asynchronous GPU streams to fully exploit the high degrees of parallelism in GPUs with efficient graph data movement between the host and the device.

  5. UNIVERSITY OF ARIZONA HIGH ENERGY PHYSICS PROGRAM

    SciTech Connect

    Rutherfoord, John P.; Johns, Kenneth A.; Shupe, Michael A.; Cheu, Elliott C.; Varnes, Erich W.; Dienes, Keith; Su, Shufang; Toussaint, William Doug; Sarcevic, Ina

    2013-07-29

    The High Energy Physics Group at the University of Arizona has conducted forefront research in elementary particle physics. Our theorists have developed new ideas in lattice QCD, SUSY phenomenology, string theory phenomenology, extra spatial dimensions, dark matter, and neutrino astrophysics. The experimentalists produced significant physics results on the ATLAS experiment at CERN's Large Hadron Collider and on the D0 experiment at the Fermilab Tevatron. In addition, the experimentalists were leaders in detector development and construction, and on service roles in these experiments.

  6. University of Arizona Compressed Air Energy Storage

    SciTech Connect

    Simmons, Joseph; Muralidharan, Krishna

    2012-12-31

    Boiled down to its essentials, the grant’s purpose was to develop and demonstrate the viability of compressed air energy storage (CAES) for use in renewable energy development. While everyone agrees that energy storage is the key component to enable widespread adoption of renewable energy sources, the development of a viable scalable technology has been missing. The Department of Energy has focused on expanded battery research and improved forecasting, and the utilities have deployed renewable energy resources only to the extent of satisfying Renewable Portfolio Standards. The lack of dispatchability of solar and wind-based electricity generation has drastically increased the cost of operation with these components. It is now clear that energy storage coupled with accurate solar and wind forecasting make up the only combination that can succeed in dispatchable renewable energy resources. Conventional batteries scale linearly in size, so the price becomes a barrier for large systems. Flow batteries scale sub-linearly and promise to be useful if their performance can be shown to provide sufficient support for solar and wind-base electricity generation resources. Compressed air energy storage provides the most desirable answer in terms of scalability and performance in all areas except efficiency. With the support of the DOE, Tucson Electric Power and Science Foundation Arizona, the Arizona Research Institute for Solar Energy (AzRISE) at the University of Arizona has had the opportunity to investigate CAES as a potential energy storage resource.

  7. Massive graph visualization : LDRD final report.

    SciTech Connect

    Wylie, Brian Neil; Moreland, Kenneth D.

    2007-10-01

    Graphs are a vital way of organizing data with complex correlations. A good visualization of a graph can fundamentally change human understanding of the data. Consequently, there is a rich body of work on graph visualization. Although there are many techniques that are effective on small to medium sized graphs (tens of thousands of nodes), there is a void in the research for visualizing massive graphs containing millions of nodes. Sandia is one of the few entities in the world that has the means and motivation to handle data on such a massive scale. For example, homeland security generates graphs from prolific media sources such as television, telephone, and the Internet. The purpose of this project is to provide the groundwork for visualizing such massive graphs. The research provides for two major feature gaps: a parallel, interactive visualization framework and scalable algorithms to make the framework usable to a practical application. Both the frameworks and algorithms are designed to run on distributed parallel computers, which are already available at Sandia. Some features are integrated into the ThreatView{trademark} application and future work will integrate further parallel algorithms.

  8. EIS-0441: Mohave County Wind Farm Project, Mohave County, Arizona...

    Office of Environmental Management (EM)

    as a cooperating agency, evaluated the environmental impacts of a proposed wind energy project on public lands in Mohave County, Arizona. Power generated by this project...

  9. Sierra Vista, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Vista, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 31.5545394, -110.3036912 Show Map Loading map... "minzoom":false,"mappingservic...

  10. Sierra Vista Southeast, Arizona: Energy Resources | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    Vista Southeast, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 31.460592, -110.217428 Show Map Loading map... "minzoom":false,"mappi...

  11. Prescott Valley, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Page Edit with form History Prescott Valley, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.6100243, -112.315721 Show Map Loading...

  12. St. David, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    David, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 31.9042517, -110.2142399 Show Map Loading map... "minzoom":false,"mappingservic...

  13. Arizona - Natural Gas 2015 Million Cu. Feet Percent...

    Gasoline and Diesel Fuel Update

    4 Arizona - Natural Gas 2015 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: ...

  14. Arizona Electric Pwr Coop Inc | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Facebook: https:www.facebook.compagesArizonas-GT-Cooperatives347352335037?refts Outage Hotline: (520) 586-3631 References: EIA Form EIA-861 Final Data File for 2010...

  15. Arizona State Land Department Applications and Permits Website...

    OpenEI (Open Energy Information) [EERE & EIA]

    to: navigation, search OpenEI Reference LibraryAdd to library Web Site: Arizona State Land Department Applications and Permits Website Abstract This website contains supplemental...

  16. PP-106 Arizona Public Service Company | Department of Energy

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

    Presidential permit authorizing Arizona Public Service Company to construct, operate, and maintain electric transmission facilities at the U.S-Mexico border. PDF icon PP-106 ...

  17. PP-107 Arizona Public Service Company | Department of Energy

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

    Presidential permit authorizing Arizona Public Service Company to construct, operate, and maintain electric transmission facilities at the U.S-Mexico border. PDF icon PP-107 ...

  18. PP-108 Arizona Public Service Company | Department of Energy

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

    Presidential Permit authorizing APSC to construct, operate and maintain electric transmission facitilites at the U.S. - Mexico Border. PDF icon PP-108 Arizona Public Service ...

  19. Peach Springs, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Springs, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.5291589, -113.425491 Show Map Loading map... "minzoom":false,"mappingservi...

  20. Arizona State Historic Preservation Office | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Historic Preservation Office Jump to: navigation, search Name: Arizona State Historic Preservation Office Abbreviation: SHPO Address: 1300 West Washington Street Place: Phoenix,...

  1. Arizona State University TUV Rheinland JV | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    University TUV Rheinland JV Jump to: navigation, search Name: Arizona State University & TUV Rheinland JV Sector: Solar Product: Solar JV formed for technology testing and...

  2. Ash Fork, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Ash Fork, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.2250114, -112.4840675 Show Map Loading map... "minzoom":false,"mappingser...

  3. La Paz County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Paz County, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.0061091, -113.9536466 Show Map Loading map... "minzoom":false,"mappings...

  4. Flowing Wells, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Wells, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.2939638, -111.0098178 Show Map Loading map... "minzoom":false,"mappingservic...

  5. Green Valley, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 31.8542511, -110.9937019 Show Map Loading map... "minzoom":false,"mappingservice":"goo...

  6. EIS-0474: Southline Transmission Line Project; Arizona and New...

    Energy.gov [DOE] (indexed site)

    consist of a new 225-mile transmission line between existing substations at Afton, New Mexico, and Apache, Arizona, and improvements to approximately 130 miles of existing...

  7. Arizona's 1st congressional district: Energy Resources | Open...

    OpenEI (Open Energy Information) [EERE & EIA]

    System Solar Power Plant Retrieved from "http:en.openei.orgwindex.php?titleArizona%27s1stcongressionaldistrict&oldid175300" Feedback Contact needs updating Image needs...

  8. RAPID/BulkTransmission/Arizona | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    the Regional Entity responsible for coordinating and promoting Bulk Electric System reliability in the Western Interconnection, including Arizona. WECC also provides an...

  9. Ajo Improvement Co (Arizona) EIA Revenue and Sales - April 2008...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ajo Improvement Co (Arizona) EIA Revenue and Sales - April 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ajo Improvement Co for April...

  10. Ajo Improvement Co (Arizona) EIA Revenue and Sales - October...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ajo Improvement Co (Arizona) EIA Revenue and Sales - October 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ajo Improvement Co for October...

  11. Camp Verde, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Verde, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.5636358, -111.8543178 Show Map Loading map... "minzoom":false,"mappingservic...

  12. Rio Verde, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Verde, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.7225429, -111.6756942 Show Map Loading map... "minzoom":false,"mappingservic...

  13. Tanque Verde, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Tanque Verde, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.2517422, -110.7373056 Show Map Loading map... "minzoom":false,"mappin...

  14. Cottonwood-Verde Village, Arizona: Energy Resources | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    Cottonwood-Verde Village, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.6949847, -111.9820582 Show Map Loading map......

  15. Arizona Online Environmental Review Tool | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Online Environmental Review ToolInfo GraphicMapChart Abstract The Arizona Game and Fish Department's Heritage Data Management System (HDMS) and Project Evaluation Program...

  16. Phoenix Convention Center * Phoenix, Arizona Playing the Entire...

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

    Phoenix, Arizona Playing the Entire Value Chain for Energy Storage Session 6: Innovation Energy Storage for Federal Installations Scott Sklar The Stella Group, LTD August 12, 2015 ...

  17. New Kingman-Butler, Arizona: Energy Resources | Open Energy Informatio...

    OpenEI (Open Energy Information) [EERE & EIA]

    Kingman-Butler, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.2593696, -114.0190671 Show Map Loading map... "minzoom":false,"mapp...

  18. Dewey-Humboldt, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Dewey-Humboldt, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.53, -112.2422222 Show Map Loading map... "minzoom":false,"mappingse...

  19. Oro Valley, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Oro Valley, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.3909071, -110.966488 Show Map Loading map... "minzoom":false,"mappingse...

  20. Geothermal-Exploration In Arizona | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    In Arizona Authors C. Stone and W. R. Hahman Published Journal Transactions-American Geophysical Union, 1978 DOI Not Provided Check for DOI availability: http:...

  1. Analysis of MSE Cores Tuba City, Arizona, Site | Department of...

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

    More Documents & Publications Analysis of Contaminant Rebound in Ground Water in Extraction Wells at the Tuba City, Arizona, Site Diffusion Multilayer Sampling of Ground Water in ...

  2. Fort Defiance, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Act Smart Grid Projects in Fort Defiance, Arizona Navajo Tribal Utility Association Smart Grid Project References US Census Bureau 2005 Place to 2006 CBSA Retrieved from...

  3. Sun City, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Sun City, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.5975393, -112.2718239 Show Map Loading map... "minzoom":false,"mappingser...

  4. Big Park, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Park, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.780297, -111.7626535 Show Map Loading map... "minzoom":false,"mappingservice"...

  5. Munds Park, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Munds Park, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.945574, -111.6401551 Show Map Loading map... "minzoom":false,"mappingse...

  6. Litchfield Park, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Park, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.4933743, -112.3579364 Show Map Loading map... "minzoom":false,"mappingservice...

  7. Arizona's 5th congressional district: Energy Resources | Open...

    OpenEI (Open Energy Information) [EERE & EIA]

    Registered Energy Companies in Arizona's 5th congressional district AFV Solutions Inc AZ Biodiesel Advanced Energy Systems Inc AESI also Advanced Energy Inc AeroElektra...

  8. Arizona's 6th congressional district: Energy Resources | Open...

    OpenEI (Open Energy Information) [EERE & EIA]

    ETA Engineering Renegy Holdings Inc The Arizona Center for Algae Technology and Innovation WindPower Innovations Inc Retrieved from "http:en.openei.orgw...

  9. Desert Hills, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Desert Hills, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.5538996, -114.3724569 Show Map Loading map... "minzoom":false,"mappin...

  10. St. Johns, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Johns, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.5058698, -109.3609327 Show Map Loading map... "minzoom":false,"mappingservic...

  11. Greenlee County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Greenlee County, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.2405598, -109.2831531 Show Map Loading map... "minzoom":false,"map...

  12. South Tucson, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Tucson, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.199521, -110.968425 Show Map Loading map... "minzoom":false,"mappingservice...

  13. Winslow West, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    West, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.0322421, -110.7529145 Show Map Loading map... "minzoom":false,"mappingservice...

  14. Chino Valley, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Valley, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.7575227, -112.4537809 Show Map Loading map... "minzoom":false,"mappingservi...

  15. Arizona Natural Gas Vented and Flared (Million Cubic Feet)

    Gasoline and Diesel Fuel Update

    Date: 12312015 Next Release Date: 01292016 Referring Pages: Natural Gas Vented and Flared Arizona Natural Gas Gross Withdrawals and Production Natural Gas Vented and Flared...

  16. Apache Junction, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Junction, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.4150485, -111.5495777 Show Map Loading map... "minzoom":false,"mappingser...

  17. Queen Creek, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Creek, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.2486638, -111.6342993 Show Map Loading map... "minzoom":false,"mappingservic...

  18. McNary, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    McNary, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.0736564, -109.8570472 Show Map Loading map... "minzoom":false,"mappingservi...

  19. Bitter Springs, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Bitter Springs, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 36.6285991, -111.6543255 Show Map Loading map... "minzoom":false,"mapp...

  20. Bullhead City, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Bullhead City, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 35.1477774, -114.5682983 Show Map Loading map... "minzoom":false,"mappi...

  1. Mohave Valley, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Valley, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.9330585, -114.5888533 Show Map Loading map... "minzoom":false,"mappingservi...

  2. Paradise Valley, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Valley, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.5311541, -111.9426452 Show Map Loading map... "minzoom":false,"mappingservi...

  3. Drexel Heights, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Drexel Heights, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.1411888, -111.028427 Show Map Loading map... "minzoom":false,"mappi...

  4. Colorado City, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    City, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 36.9902621, -112.9757702 Show Map Loading map... "minzoom":false,"mappingservice...

  5. Huachuca City, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Huachuca City, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 31.6278703, -110.3339678 Show Map Loading map... "minzoom":false,"mappi...

  6. Cordes Lakes, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Lakes, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 34.3078074, -112.1034912 Show Map Loading map... "minzoom":false,"mappingservic...

  7. Gila Bend, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Gila Bend, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 32.9478236, -112.7168305 Show Map Loading map... "minzoom":false,"mappingse...

  8. Enabling Graph Mining in RDF Triplestores using SPARQL for Holistic In-situ Graph Analysis

    DOE PAGES [OSTI]

    Lee, Sangkeun; Sukumar, Sreenivas R; Hong, Seokyong; Lim, Seung-Hwan

    2016-01-01

    The graph analysis is now considered as a promising technique to discover useful knowledge in data with a new perspective. We envi- sion that there are two dimensions of graph analysis: OnLine Graph Analytic Processing (OLGAP) and Graph Mining (GM) where each respectively focuses on subgraph pattern matching and automatic knowledge discovery in graph. Moreover, as these two dimensions aim to complementarily solve complex problems, holistic in-situ graph analysis which covers both OLGAP and GM in a single system is critical for minimizing the burdens of operating multiple graph systems and transferring intermediate result-sets between those systems. Nevertheless, most existingmore » graph analysis systems are only capable of one dimension of graph analysis. In this work, we take an approach to enabling GM capabilities (e.g., PageRank, connected-component analysis, node eccentricity, etc.) in RDF triplestores, which are originally developed to store RDF datasets and provide OLGAP capability. More specifically, to achieve our goal, we implemented six representative graph mining algorithms using SPARQL. The approach allows a wide range of available RDF data sets directly applicable for holistic graph analysis within a system. For validation of our approach, we evaluate performance of our implementations with nine real-world datasets and three different computing environments - a laptop computer, an Amazon EC2 instance, and a shared-memory Cray XMT2 URIKA-GD graph-processing appliance. The experimen- tal results show that our implementation can provide promising and scalable performance for real world graph analysis in all tested environments. The developed software is publicly available in an open-source project that we initiated.« less

  9. Enabling Graph Mining in RDF Triplestores using SPARQL for Holistic In-situ Graph Analysis

    SciTech Connect

    Lee, Sangkeun; Sukumar, Sreenivas R; Hong, Seokyong; Lim, Seung-Hwan

    2016-01-01

    The graph analysis is now considered as a promising technique to discover useful knowledge in data with a new perspective. We envi- sion that there are two dimensions of graph analysis: OnLine Graph Analytic Processing (OLGAP) and Graph Mining (GM) where each respectively focuses on subgraph pattern matching and automatic knowledge discovery in graph. Moreover, as these two dimensions aim to complementarily solve complex problems, holistic in-situ graph analysis which covers both OLGAP and GM in a single system is critical for minimizing the burdens of operating multiple graph systems and transferring intermediate result-sets between those systems. Nevertheless, most existing graph analysis systems are only capable of one dimension of graph analysis. In this work, we take an approach to enabling GM capabilities (e.g., PageRank, connected-component analysis, node eccentricity, etc.) in RDF triplestores, which are originally developed to store RDF datasets and provide OLGAP capability. More specifically, to achieve our goal, we implemented six representative graph mining algorithms using SPARQL. The approach allows a wide range of available RDF data sets directly applicable for holistic graph analysis within a system. For validation of our approach, we evaluate performance of our implementations with nine real-world datasets and three different computing environments - a laptop computer, an Amazon EC2 instance, and a shared-memory Cray XMT2 URIKA-GD graph-processing appliance. The experimen- tal results show that our implementation can provide promising and scalable performance for real world graph analysis in all tested environments. The developed software is publicly available in an open-source project that we initiated.

  10. homeoffice_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.4 1.1 1.1 1.2 1.2 1.0 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Households Using Office Equipment .......................... 96.2 14.9 16.7 17.0 12.2 13.0 22.4 4.4 Personal Computers 2

  11. ac_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    a. Air Conditioning by Climate Zone, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 2.1 1.0 0.9 1.5 1.0 Total Households With Air-Conditioning ........................... 82.9 5.4 20.9 20.2 14.2 22.1 8.1 Air Conditioners Not Used ............ 2.1 Q 0.4 0.3 0.8 0.4 23.2

  12. The MultiThreaded Graph Library (MTGL)

    Energy Science and Technology Software Center

    2008-07-17

    The MultiThreaded Graph Library (MTGL) is a set of header files that implement graph algorithm in such a way that they can run on massively multithreaded architectures. It is based upon the Boost Graph Library, but doesn’t use Boost since the latter doesn’t run well on these architectures.

  13. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2a. Appliances by West Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 22.1 6.6 15.5 1.1 1

  14. Microsoft Word - DOE-ID-13-047 Arizona State EC B3-6.doc

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

    7 SECTION A. Project Title: Radiation Hardened Electronics Destined for Severe Nuclear Reactor Environments - Arizona State University SECTION B. Project Description Arizona State ...

  15. Microsoft Word - DOE-ID-13-056 Arizona State EC B3-6.doc

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

    Testing and Multiscale Simulation for Creep Fatigue Damage Analysis of Alloy 617 - Arizona State University SECTION B. Project Description Arizona State University proposes to...

  16. Bipartite graph partitioning and data clustering

    SciTech Connect

    Zha, Hongyuan; He, Xiaofeng; Ding, Chris; Gu, Ming; Simon, Horst D.

    2001-05-07

    Many data types arising from data mining applications can be modeled as bipartite graphs, examples include terms and documents in a text corpus, customers and purchasing items in market basket analysis and reviewers and movies in a movie recommender system. In this paper, the authors propose a new data clustering method based on partitioning the underlying biopartite graph. The partition is constructed by minimizing a normalized sum of edge weights between unmatched pairs of vertices of the bipartite graph. They show that an approximate solution to the minimization problem can be obtained by computing a partial singular value decomposition (SVD) of the associated edge weight matrix of the bipartite graph. They point out the connection of their clustering algorithm to correspondence analysis used in multivariate analysis. They also briefly discuss the issue of assigning data objects to multiple clusters. In the experimental results, they apply their clustering algorithm to the problem of document clustering to illustrate its effectiveness and efficiency.

  17. Visualization Graph | OpenEI Community

    OpenEI (Open Energy Information) [EERE & EIA]

    8 August, 2012 - 12:37 New Gapminder Visualizations Added EIA Energy data Gapminder OECD OpenEI SEDS Visualization Graph OpenEI now features some cool new Gapminder...

  18. Fault-tolerant dynamic task graph scheduling

    SciTech Connect

    Kurt, Mehmet C.; Krishnamoorthy, Sriram; Agrawal, Kunal; Agrawal, Gagan

    2014-11-16

    In this paper, we present an approach to fault tolerant execution of dynamic task graphs scheduled using work stealing. In particular, we focus on selective and localized recovery of tasks in the presence of soft faults. We elicit from the user the basic task graph structure in terms of successor and predecessor relationships. The work stealing-based algorithm to schedule such a task graph is augmented to enable recovery when the data and meta-data associated with a task get corrupted. We use this redundancy, and the knowledge of the task graph structure, to selectively recover from faults with low space and time overheads. We show that the fault tolerant design retains the essential properties of the underlying work stealing-based task scheduling algorithm, and that the fault tolerant execution is asymptotically optimal when task re-execution is taken into account. Experimental evaluation demonstrates the low cost of recovery under various fault scenarios.

  19. Bayati Kim Saberi random graph sampler

    Energy Science and Technology Software Center

    2012-06-05

    This software package implements the algorithm from a paper by Bayati, Kim, and Saberi (first reference below) to generate a uniformly random sample of a graph with a prescribed degree distribution.

  20. Accelerating semantic graph databases on commodity clusters

    SciTech Connect

    Morari, Alessandro; Castellana, Vito G.; Haglin, David J.; Feo, John T.; Weaver, Jesse R.; Tumeo, Antonino; Villa, Oreste

    2013-10-06

    We are developing a full software system for accelerating semantic graph databases on commodity cluster that scales to hundreds of nodes while maintaining constant query throughput. Our framework comprises a SPARQL to C++ compiler, a library of parallel graph methods and a custom multithreaded runtime layer, which provides a Partitioned Global Address Space (PGAS) programming model with fork/join parallelism and automatic load balancing over a commodity clusters. We present preliminary results for the compiler and for the runtime.

  1. Arizona Renewable Electric Power Industry Statistics

    Energy Information Administration (EIA) (indexed site)

    Arizona Primary Renewable Energy Capacity Source Hydro Conventional Primary Renewable Energy Generation Source Hydro Conventional Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 26,392 100.0 Total Net Summer Renewable Capacity 2,901 11.0 Geothermal - - Hydro Conventional 2,720 10.3 Solar 20 0.1 Wind 128 0.5 Wood/Wood Waste 29 0.1 MSW/Landfill Gas 4 * Other Biomass - - Generation (thousand megawatthours) Total Electricity Net Generation 111,751 100.0 Total

  2. Arizona Renewable Electric Power Industry Statistics

    Energy Information Administration (EIA) (indexed site)

    Arizona" "Primary Renewable Energy Capacity Source","Hydro Conventional" "Primary Renewable Energy Generation Source","Hydro Conventional" "Capacity (megawatts)","Value","Percent of State Total" "Total Net Summer Electricity Capacity",26392,100 "Total Net Summer Renewable Capacity",2901,11 " Geothermal","-","-" " Hydro Conventional",2720,10.3 "

  3. Storage opportunities in Arizona bedded evaporites

    SciTech Connect

    Neal, J.T.; Rauzi, S.L.

    1996-10-01

    Arizona is endowed with incredibly diverse natural beauty, and has also been blessed with at least seven discrete deposits of bedded salt. These deposits are dispersed around the state and cover some 2, 500 square miles; they currently contain 14 LPG storage caverns, with preliminary plans for more in the future. The areal extent and thickness of the deposits creates the opportunity for greatly expanded storage of LPG, natural gas, and compressed air energy storage (CAES). The location of salt deposits near Tucson and Phoenix may make CAES an attractive prospect in the future. The diversity of both locations and evaporate characteristics allows for much tailoring of individual operations to meet specific requirements.

  4. Graph representation of protein free energy landscape

    SciTech Connect

    Li, Minghai; Duan, Mojie; Fan, Jue; Huo, Shuanghong; Han, Li

    2013-11-14

    The thermodynamics and kinetics of protein folding and protein conformational changes are governed by the underlying free energy landscape. However, the multidimensional nature of the free energy landscape makes it difficult to describe. We propose to use a weighted-graph approach to depict the free energy landscape with the nodes on the graph representing the conformational states and the edge weights reflecting the free energy barriers between the states. Our graph is constructed from a molecular dynamics trajectory and does not involve projecting the multi-dimensional free energy landscape onto a low-dimensional space defined by a few order parameters. The calculation of free energy barriers was based on transition-path theory using the MSMBuilder2 package. We compare our graph with the widely used transition disconnectivity graph (TRDG) which is constructed from the same trajectory and show that our approach gives more accurate description of the free energy landscape than the TRDG approach even though the latter can be organized into a simple tree representation. The weighted-graph is a general approach and can be used on any complex system.

  5. Arizona State Historic Preservation Programmatic Agreement | Department of

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

    Energy Arizona State Historic Preservation Programmatic Agreement Arizona State Historic Preservation Programmatic Agreement Fully executed programmatic agreement between DOE, State Energy Office and State Historic Preservation Office. state_historic_preservation_programmatic_agreement_az.pdf (492.93 KB) More Documents & Publications Delaware State Historic Preservation Programmatic Agreement Florida State Historic Preservation Programmatic Agreement Louisiana

  6. Continuous-time quantum walks on star graphs

    SciTech Connect

    Salimi, S.

    2009-06-15

    In this paper, we investigate continuous-time quantum walk on star graphs. It is shown that quantum central limit theorem for a continuous-time quantum walk on star graphs for N-fold star power graph, which are invariant under the quantum component of adjacency matrix, converges to continuous-time quantum walk on K{sub 2} graphs (complete graph with two vertices) and the probability of observing walk tends to the uniform distribution.

  7. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    0a. Appliances by Midwest Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.5 Total .............................................................. 107.0 24.5 17.1 7.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 23.8 16.6 7.2 NE 1

  8. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    1a. Appliances by South Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.1 1.4 1.5 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 36.2 19.4 6.4 10.3 1.5 1

  9. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    4a. Appliances by Type of Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.5 1.7 1.6 1.9 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 69.1 9.4 16.7 6.6 4.3 1

  10. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    5a. Appliances by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.3 0.4 2.1 3.1 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Kitchen Appliances Cooking Appliances Oven ...........................................

  11. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    6a. Appliances by Type of Rented Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total ............................................... 34.3 10.5 7.4 15.2 1.1 6.9 Kitchen Appliances Cooking Appliances Oven ........................................... 33.4 10.1 7.3 14.9 1.1

  12. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    8a. Appliances by Urban/Rural Location, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.9 1.4 1.2 1.3 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.1 Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 47.5 17.5 19.9 16.8 4.2 1

  13. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    9a. Appliances by Northeast Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.3 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 19.6 14.5 5.2 1.1 1

  14. spaceheat_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2a. Space Heating by West Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.6 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Heat Home .................................................... 106.0 22.6 6.7 15.9 NE Do Not Heat Home ....................................... 1.0 0.7 Q 0.7 10.6 No Heating Equipment

  15. spaceheat_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    5a. Space Heating by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.4 1.9 3.0 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Heat Home ..................................... 72.4 63.0 2.0 1.7 5.7 6.7 Do Not Heat Home

  16. spaceheat_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    6a. Space Heating by Type of Rented Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total ............................................... 34.3 10.5 7.4 15.2 1.1 6.9 Heat Home ..................................... 33.7 10.4 7.4 14.8 1.1 6.9 Do Not Heat Home

  17. Strategies for Collecting Household Energy Data

    Energy.gov [DOE]

    Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for Collecting Household Energy Data, Call Slides and Discussion Summary, July 19, 2012.

  18. Household energy consumption and expenditures, 1990

    SciTech Connect

    Not Available

    1993-03-02

    This report, Household Energy Consumption and Expenditures 1990, is based upon data from the 1990 Residential Energy Consumption Survey (RECS). Focusing on energy end-use consumption and expenditures of households, the 1990 RECS is the eighth in a series conducted since 1978 by the Energy Information Administration (EIA). Over 5,000 households were surveyed, providing information on their housing units, housing characteristics, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information provided represents the characteristics and energy consumption of 94 million households nationwide.

  19. Plant-Wide Energy Efficiency Assessment at the Arizona Portland Cement Plant in Rillito, Arizona

    SciTech Connect

    Stephen J. Coppinger, P.E.; Bruce Colburn, Ph.D., P.E., CEM

    2007-05-17

    A Department of Energy Plant-wide Assessment was undertaken by Arizona Portland Cement (APC) beginning in May 2005. The assessment was performed at APC’s cement production facility in Rillito, Arizona. The assessment included a compressed air evaluation along with a detailed process audit of plant operations and equipment. The purpose of this Energy Survey was to identify a series of energy cost savings opportunities at the Plant, and provide preliminary cost and savings estimates for the work. The assessment was successful in identifying projects that could provide annual savings of over $2.7 million at an estimated capital cost of $4.3 million. If implemented, these projects could amount to a savings of over 4.9 million kWh/yr and 384,420 MMBtu/year.

  20. Dynamic graph system for a semantic database

    DOEpatents

    Mizell, David

    2015-01-27

    A method and system in a computer system for dynamically providing a graphical representation of a data store of entries via a matrix interface is disclosed. A dynamic graph system provides a matrix interface that exposes to an application program a graphical representation of data stored in a data store such as a semantic database storing triples. To the application program, the matrix interface represents the graph as a sparse adjacency matrix that is stored in compressed form. Each entry of the data store is considered to represent a link between nodes of the graph. Each entry has a first field and a second field identifying the nodes connected by the link and a third field with a value for the link that connects the identified nodes. The first, second, and third fields represent the rows, column, and elements of the adjacency matrix.

  1. Dynamic graph system for a semantic database

    DOEpatents

    Mizell, David

    2016-04-12

    A method and system in a computer system for dynamically providing a graphical representation of a data store of entries via a matrix interface is disclosed. A dynamic graph system provides a matrix interface that exposes to an application program a graphical representation of data stored in a data store such as a semantic database storing triples. To the application program, the matrix interface represents the graph as a sparse adjacency matrix that is stored in compressed form. Each entry of the data store is considered to represent a link between nodes of the graph. Each entry has a first field and a second field identifying the nodes connected by the link and a third field with a value for the link that connects the identified nodes. The first, second, and third fields represent the rows, column, and elements of the adjacency matrix.

  2. Department of Energy Offers Support for Arizona Solar Project | Department

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

    of Energy Arizona Solar Project Department of Energy Offers Support for Arizona Solar Project January 20, 2011 - 12:00am Addthis Washington D.C. --- U.S. Energy Secretary Steven Chu today announced the offer of a conditional commitment to Agua Caliente Solar, LLC for a loan guarantee of up to $967 million. The loan guarantee will support the construction of a 290-megawatt photovoltaic solar generating facility located in Yuma County, Arizona that will use thin film solar panels from First

  3. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    a. Appliances by Climate Zone, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.1 Total .................................................. 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Kitchen Appliances Cooking Appliances Oven

  4. appl_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2a. Appliances by Year of Construction, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.5 1.2 1.1 1.2 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 14.3 17.2 17.8 12.9 13.7 25.9 4.2 1

  5. spaceheat_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    2a. Space Heating by Year of Construction, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.5 1.5 1.1 1.1 1.1 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.3 Heat Home ..................................... 106.0 15.4 18.2 18.6 13.6 13.9 26.4 4.3 Do Not Heat Home ........................

  6. spaceheat_household2001.pdf

    Energy Information Administration (EIA) (indexed site)

    4a. Space Heating by Type of Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.7 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.4 Heat Home ..................................... 106.0 73.4 9.4 16.4 6.8 4.5 Do Not Heat Home ........................ 1.0 0.3 Q 0.6 Q 19.0 No

  7. Corona de Tucson, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Hide Map This article is a stub. You can help OpenEI by expanding it. Corona de Tucson is a census-designated place in Pima County, Arizona.1 References US...

  8. DOI Approves Three Renewable Energy Projects in Arizona and Nevada...

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

    The 100-megawatt Quartzsite Solar Energy Project, located on 1,600 acres of BLM-managed lands in La Paz County, Arizona, will use concentrating solar power (CSP) "power tower" ...

  9. Town of Wickenburg, Arizona (Utility Company) | Open Energy Informatio...

    OpenEI (Open Energy Information) [EERE & EIA]

    Name: Town of Wickenburg Place: Arizona Phone Number: (928) 684-5451 x1520 Website: www.ci.wickenburg.az.us694Ut Outage Hotline: 928-684-5411 References: EIA Form EIA-861 Final...

  10. Valencia West, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Hide Map This article is a stub. You can help OpenEI by expanding it. Valencia West is a census-designated place in Pima County, Arizona.1 References US...

  11. Garkane Energy Coop, Inc (Arizona) | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Garkane Energy Coop, Inc Place: Arizona Phone Number: Kanab Office: (888)644-5026 -- Loa Office (800) 747-5403 -- Hatch Office(888)735-4288 -- Hildale Office(435) 874-2810 Website:...

  12. Arizona Natural Gas Vented and Flared (Million Cubic Feet)

    Gasoline and Diesel Fuel Update

    Vented and Flared (Million Cubic Feet) Arizona Natural Gas Vented and Flared (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 ...

  13. 2,"Four Corners","Coal","Arizona Public Service Co",1540

    Energy Information Administration (EIA) (indexed site)

    Mexico" ,"Plant","Primary energy source","Operating company","Net summer capacity (MW)" 1,"San Juan","Coal","Public Service Co of NM",1684 2,"Four Corners","Coal","Arizona Public ...

  14. EECBG Success Story: Energy Upgrades to Save Small Arizona Town...

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

    of Oro Valley Energy Upgrades to Save Small Arizona Town Big Money Workers demonstrate the nitrogen tank used to inflate tires in St. Peters, MO. | Courtesy of the City of St. ...

  15. Arizona Natural Gas Input Supplemental Fuels (Million Cubic Feet...

    Energy Information Administration (EIA) (indexed site)

    Input Supplemental Fuels (Million Cubic Feet) Arizona Natural Gas Input Supplemental Fuels (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  16. Spring Valley, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Hide Map This article is a stub. You can help OpenEI by expanding it. Spring Valley is a census-designated place in Yavapai County, Arizona.1 References US...

  17. Red Mesa, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Hide Map This article is a stub. You can help OpenEI by expanding it. Red Mesa is a census-designated place in Apache County, Arizona.1 References US...

  18. DOI Approves Three Renewable Energy Projects in Arizona and Nevada

    Energy.gov [DOE]

    The U.S. Department of the Interior (DOI) on June 3 announced the approval of three major renewable energy projects in Arizona and Nevada that are expected to deliver up to 520 megawatts to the electricity grid.

  19. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and Sales - April 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin Electric...

  20. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and Sales - November 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin...

  1. Ajo Improvement Co (Arizona) EIA Revenue and Sales - June 2008...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ajo Improvement Co (Arizona) EIA Revenue and Sales - June 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ajo Improvement Co for June 2008....

  2. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and Sales - May 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin Electric...

  3. Ajo Improvement Co (Arizona) EIA Revenue and Sales - July 2008...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ajo Improvement Co (Arizona) EIA Revenue and Sales - July 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ajo Improvement Co for July 2008....

  4. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and Sales - February 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin...

  5. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and Sales - June 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin Electric...

  6. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and Sales - February 2009 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin...

  7. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and Sales - January 2009 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin...

  8. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and Sales - March 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin Electric...

  9. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and Sales - October 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin...

  10. Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and...

    OpenEI (Open Energy Information) [EERE & EIA]

    Ak-Chin Electric Utility Authority (Arizona) EIA Revenue and Sales - January 2008 Jump to: navigation, search EIA Monthly Electric Utility Sales and Revenue Data for Ak-Chin...

  11. Santa Cruz County, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Hide Map This article is a stub. You can help OpenEI by expanding it. Santa Cruz County is a county in Arizona. Its FIPS County Code is 023. It is classified as...

  12. Santa Rosa, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Hide Map This article is a stub. You can help OpenEI by expanding it. Santa Rosa is a census-designated place in Pima County, Arizona.1 References US Census...

  13. Arizona Right-of-Way Instruction Sheet | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Right-of-Way Instruction Sheet Jump to: navigation, search OpenEI Reference LibraryAdd to library PermittingRegulatory Guidance - Instructions: Arizona Right-of-Way Instruction...

  14. Gold Camp, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Hide Map This article is a stub. You can help OpenEI by expanding it. Gold Camp is a census-designated place in Pinal County, Arizona.1 References US Census...

  15. Arizona Natural Gas Lease Fuel Consumption (Million Cubic Feet...

    Annual Energy Outlook

    Fuel Consumption (Million Cubic Feet) Arizona Natural Gas Lease Fuel Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

  16. Arizona Natural Gas Total Consumption (Million Cubic Feet)

    Annual Energy Outlook

    Total Consumption (Million Cubic Feet) Arizona Natural Gas Total Consumption (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9...

  17. Arizona Natural Gas Exports (No Intransit Deliveries) (Million...

    Annual Energy Outlook

    Exports (No Intransit Deliveries) (Million Cubic Feet) Arizona Natural Gas Exports (No Intransit Deliveries) (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

  18. Arizona Natural Gas % of Total Residential Deliveries (Percent...

    Annual Energy Outlook

    % of Total Residential Deliveries (Percent) Arizona Natural Gas % of Total Residential Deliveries (Percent) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  19. Arizona Price of Natural Gas Sold to Commercial Consumers (Dollars...

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

    Sold to Commercial Consumers (Dollars per Thousand Cubic Feet) Arizona Price of Natural Gas Sold to Commercial Consumers (Dollars per Thousand Cubic Feet) Year Jan Feb Mar Apr May...

  20. ,"Arizona Dry Natural Gas Production (Million Cubic Feet)"

    Energy Information Administration (EIA) (indexed site)

    ,,"(202) 586-8800",,,"01042016 7:36:54 AM" "Back to Contents","Data 1: Arizona Dry Natural Gas Production (Million Cubic Feet)" "Sourcekey","NA1160SAZ2"...

  1. DOE - Office of Legacy Management -- University of Arizona Southwest...

    Office of Legacy Management (LM)

    of the University of Arizona under FUSRAP; October 13, 1987 AZ.01-4 - DOE Letter; Bauer to Liverman; Past Operations and a Survey by Messrs, Jascewsky, and Smith; February 7, 1978

  2. EIS-0427: Grapevine Canyon Wind Project, Coconino County, Arizona

    Energy.gov [DOE]

    This EIS evaluates the environmental impacts of a proposed wind energy generation project in Coconino County, Arizona, on privately owned ranch lands and trust lands administered by the Arizona State Land Department. The proposed project includes a new transmission tie-line that would cross lands administered by Coconino National Forest and interconnect with DOE’s Western Area Power Administration’s existing Glen Canyon-Pinnacle Peak transmission lines.

  3. DOE-University of Arizona Faculty Development Project. Final report

    SciTech Connect

    Fillerup, Joseph M.

    1980-09-08

    The DOE-University of Arizona Faculty Development Project on Energy successfully completed a faculty development program. There were three phases of the program consisting of: a three week energy workshop for teachers, participation and cooperation with Students for Safe Energy in presentation of an Alternative Energy Festival at the University of Arizona, and workshops for teachers conducted at Flowing Wells School District. Each of these is described. Attendees are listed and a director's evaluation of the workshop is given.

  4. Communication Graph Generator for Parallel Programs

    Energy Science and Technology Software Center

    2014-04-08

    Graphator is a collection of relatively simple sequential programs that generate communication graphs/matrices for commonly occurring patterns in parallel programs. Currently, there is support for five communication patterns: two-dimensional 4-point stencil, four-dimensional 8-point stencil, all-to-alls over sub-communicators, random near-neighbor communication, and near-neighbor communication.

  5. GraphPrints: Towards a Graph Analytic Method for Network Anomaly Detection

    SciTech Connect

    Harshaw, Chris R; Bridges, Robert A; Iannacone, Michael D; Reed, Joel W; Goodall, John R

    2016-01-01

    This paper introduces a novel graph-analytic approach for detecting anomalies in network flow data called \\textit{GraphPrints}. Building on foundational network-mining techniques, our method represents time slices of traffic as a graph, then counts graphlets\\textemdash small induced subgraphs that describe local topology. By performing outlier detection on the sequence of graphlet counts, anomalous intervals of traffic are identified, and furthermore, individual IPs experiencing abnormal behavior are singled-out. Initial testing of GraphPrints is performed on real network data with an implanted anomaly. Evaluation shows false positive rates bounded by 2.84\\% at the time-interval level, and 0.05\\% at the IP-level with 100\\% true positive rates at both.

  6. ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS

    SciTech Connect

    Kramer, Klaas Jan; Homan, Greg; Brown, Rich; Worrell, Ernst; Masanet, Eric

    2009-04-15

    The term ?household carbon footprint? refers to the total annual carbon emissions associated with household consumption of energy, goods, and services. In this project, Lawrence Berkeley National Laboratory developed a carbon footprint modeling framework that characterizes the key underlying technologies and processes that contribute to household carbon footprints in California and the United States. The approach breaks down the carbon footprint by 35 different household fuel end uses and 32 different supply chain fuel end uses. This level of end use detail allows energy and policy analysts to better understand the underlying technologies and processes contributing to the carbon footprint of California households. The modeling framework was applied to estimate the annual home energy and supply chain carbon footprints of a prototypical California household. A preliminary assessment of parameter uncertainty associated with key model input data was also conducted. To illustrate the policy-relevance of this modeling framework, a case study was conducted that analyzed the achievable carbon footprint reductions associated with the adoption of energy efficient household and supply chain technologies.

  7. Loan Programs for Low- and Moderate-Income Households | Department...

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

    Programs for Low- and Moderate-Income Households Loan Programs for Low- and Moderate-Income Households Better Buildings Residential Network Multifamily and Low-Income Housing Peer ...

  8. Energy Information Administration/Household Vehicles Energy Consumptio...

    Energy Information Administration (EIA) (indexed site)

    , Energy Information AdministrationHousehold Vehicles Energy Consumption 1994 ix Household Vehicles Energy Consumption 1994 presents statistics about energy-related...

  9. Kingston Creek Hydro Project Powers 100 Households | Department...

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

    Kingston Creek Hydro Project Powers 100 Households Kingston Creek Hydro Project Powers 100 Households August 21, 2013 - 12:00am Addthis Nevada-based contracting firm Nevada ...

  10. Household Response To Dynamic Pricing Of Electricity: A Survey...

    OpenEI (Open Energy Information) [EERE & EIA]

    Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Household Response To Dynamic...

  11. Microsoft Word - Household Energy Use CA

    Energy Information Administration (EIA) (indexed site)

    0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household  California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site

  12. Geothermal development plan: northern Arizona counties

    SciTech Connect

    White, D.H.; Goldstone, L.A.

    1982-08-01

    The Northern Counties Area Development Plan evaluated the regional market potential for utilizing geothermal energy. This study identified five potential geothermal resource areas, four of which have low temperature (<90{sup 0}C, 194{sup 0}F) potential and one possible igneous system. The average population growth rate in the Northern Counties is expected to be five percent per year over the next 40 years, with Mohave and Yavapai Counties growing the fastest. Rapid growth is anticipated in all major employment sectors, including trade, service, manufacturing, mining and utilities. A regional energy use analysis is included, containing information on current energy use patterns for all user classes. Water supplies are expected to be adequate for expected growth generally, though Yavapai and Gila Counties will experience water deficiencies. A preliminary district heating analysis is included for the towns of Alpine and Springerville. Both communities are believed located on geothermal resource sites. The study also contains a section identifying potential geothermal resource users in northern Arizona.

  13. Active mines in Arizona - 1993. Directory 40

    SciTech Connect

    Phillips, K.A.; Niemuth, N.J.; Bain, D.R.

    1992-01-01

    A directory of the active mines in Arizona is presented. The directory was compiled in November, 1992 from field visits and information received by the Department's technical staff. For the purpose of this directory, an active mine is defined as a mine in continuous operation, either in production or under full-time development for production. Custom milling operations that are active or available on a full-time basis are also included in the directory. It is acknowledged that there are additional mines not listed that are in an exploration, evaluation, or part-time development phase. There are others where production is on an intermittent basis that are not listed. The report is dependent on the cooperation of government agencies, private industry, and individuals who voluntarily provide information on their projects and activities. The directory is arranged alphabetically by company name. Each listing includes corporate addresses, mine name and location, operation description, and key personnel. The listing for the sand and gravel operations include name, address, and phone number.

  14. Modular Environment for Graph Research and Analysis with a Persistent

    Energy Science and Technology Software Center

    2009-11-18

    The MEGRAPHS software package provides a front-end to graphs and vectors residing on special-purpose computing resources. It allows these data objects to be instantiated, destroyed, and manipulated. A variety of primitives needed for typical graph analyses are provided. An example program illustrating how MEGRAPHS can be used to implement a PageRank computation is included in the distribution.The MEGRAPHS software package is targeted towards developers of graph algorithms. Programmers using MEGRAPHS would write graph analysis programsmore » in terms of high-level graph and vector operations. These computations are transparently executed on the Cray XMT compute nodes.« less

  15. StreamWorks - A system for Dynamic Graph Search

    SciTech Connect

    Choudhury, Sutanay; Holder, Larry; Chin, George; Ray, Abhik; Beus, Sherman J.; Feo, John T.

    2013-06-11

    Acting on time-critical events by processing ever growing social media, news or cyber data streams is a major technical challenge. Many of these data sources can be modeled as multi-relational graphs. Mining and searching for subgraph patterns in a continuous setting requires an efficient approach to incremental graph search. The goal of our work is to enable real-time search capabilities for graph databases. This demonstration will present a dynamic graph query system that leverages the structural and semantic characteristics of the underlying multi-relational graph.

  16. Household energy consumption and expenditures 1993

    SciTech Connect

    1995-10-05

    This presents information about household end-use consumption of energy and expenditures for that energy. These data were collected in the 1993 Residential Energy Consumption Survey; more than 7,000 households were surveyed for information on their housing units, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information represents all households nationwide (97 million). Key findings: National residential energy consumption was 10.0 quadrillion Btu in 1993, a 9% increase over 1990. Weather has a significant effect on energy consumption. Consumption of electricity for appliances is increasing. Houses that use electricity for space heating have lower overall energy expenditures than households that heat with other fuels. RECS collected data for the 4 most populous states: CA, FL, NY, TX.

  17. Graph processing platforms at scale: practices and experiences

    SciTech Connect

    Lim, Seung-Hwan; Lee, Sangkeun; Brown, Tyler C; Sukumar, Sreenivas R; Ganesh, Gautam

    2015-01-01

    Graph analysis unveils hidden associations of data in many phenomena and artifacts, such as road network, social networks, genomic information, and scientific collaboration. Unfortunately, a wide diversity in the characteristics of graphs and graph operations make it challenging to find a right combination of tools and implementation of algorithms to discover desired knowledge from the target data set. This study presents an extensive empirical study of three representative graph processing platforms: Pegasus, GraphX, and Urika. Each system represents a combination of options in data model, processing paradigm, and infrastructure. We benchmarked each platform using three popular graph operations, degree distribution, connected components, and PageRank over a variety of real-world graphs. Our experiments show that each graph processing platform shows different strength, depending the type of graph operations. While Urika performs the best in non-iterative operations like degree distribution, GraphX outputforms iterative operations like connected components and PageRank. In addition, we discuss challenges to optimize the performance of each platform over large scale real world graphs.

  18. Knowledge Representation Issues in Semantic Graphs for Relationship Detection

    SciTech Connect

    Barthelemy, M; Chow, E; Eliassi-Rad, T

    2005-02-02

    An important task for Homeland Security is the prediction of threat vulnerabilities, such as through the detection of relationships between seemingly disjoint entities. A structure used for this task is a ''semantic graph'', also known as a ''relational data graph'' or an ''attributed relational graph''. These graphs encode relationships as typed links between a pair of typed nodes. Indeed, semantic graphs are very similar to semantic networks used in AI. The node and link types are related through an ontology graph (also known as a schema). Furthermore, each node has a set of attributes associated with it (e.g., ''age'' may be an attribute of a node of type ''person''). Unfortunately, the selection of types and attributes for both nodes and links depends on human expertise and is somewhat subjective and even arbitrary. This subjectiveness introduces biases into any algorithm that operates on semantic graphs. Here, we raise some knowledge representation issues for semantic graphs and provide some possible solutions using recently developed ideas in the field of complex networks. In particular, we use the concept of transitivity to evaluate the relevance of individual links in the semantic graph for detecting relationships. We also propose new statistical measures for semantic graphs and illustrate these semantic measures on graphs constructed from movies and terrorism data.

  19. Frequent Subgraph Discovery in Large Attributed Streaming Graphs

    SciTech Connect

    Ray, Abhik; Holder, Larry; Choudhury, Sutanay

    2014-08-13

    The problem of finding frequent subgraphs in large dynamic graphs has so far only consid- ered a dynamic graph as being represented by a series of static snapshots taken at various points in time. This representation of a dynamic graph does not lend itself well to real time processing of real world graphs like social networks or internet traffic which consist of a stream of nodes and edges. In this paper we propose an algorithm that discovers the frequent subgraphs present in a graph represented by a stream of labeled nodes and edges. Our algorithm is efficient and consists of tunable parameters that can be tuned by the user to get interesting patterns from various kinds of graph data. In our model updates to the graph arrive in the form of batches which contain new nodes and edges. Our algorithm con- tinuously reports the frequent subgraphs that are estimated to be found in the entire graph as each batch arrives. We evaluate our system using 5 large dynamic graph datasets: the Hetrec 2011 challenge data, Twitter, DBLP and two synthetic. We evaluate our approach against two popular large graph miners, i.e., SUBDUE and GERM. Our experimental re- sults show that we can find the same frequent subgraphs as a non-incremental approach applied to snapshot graphs, and in less time.

  20. Solar energy system performance evaluation: seasonal report for Elcam Tempe Arizona State University, Tempe, Arizona

    SciTech Connect

    Not Available

    1980-05-01

    The analysis used is based on instrumented system data monitored and collected for at least one full season of operation. The objective of the analysis is to report the long-term field performance of the installed system and to make technical contributions to the definition of techniques and requirements for solar energy system design. The solar system, Elcam-Tempe, was designed to supply commercial domestic hot water heating systems that utilize two, four by eight foot flat plate collectors to heat water in a fifty-two gallon preheat tank or a fifty-two gallon domestic hot water (DHW) tank. The DHW tank provides hot water to the Agriculture Department residence at Arizona State University. The system uses an automatic cascade control system to control three independent actuators, the coolant circulation pump, the cascade valve, and the electric heating element. The system provides freeze protection by automatically circulating hot water from the hot water tank through the collectors when the collector outlet temperature is below a specified value. The building is a single story residence located at the agriculture experiment farm of the Arizona State University. The Elcam-Tempe Solar Energy System has four modes of operation.

  1. Implementing Graph Pattern Queries on a Relational Database

    SciTech Connect

    Kaplan, I L; Abdulla, G M; Brugger, S T; Kohn, S R

    2007-12-26

    When a graph database is implemented on top of a relational database, queries in the graph query language are translated into relational SQL queries. Graph pattern queries are an important feature of a graph query language. Translating graph pattern queries into single SQL statements results in very poor query performance. By taking into account the pattern query structure and generating multiple SQL statements, pattern query performance can be dramatically improved. The performance problems encountered with the single SQL statements generated for pattern queries reflects a problem in the SQL query planner and optimizer. Addressing this problem would allow relational databases to better support semantic graph databases. Relational database systems that provide good support for graph databases may also be more flexible platforms for data warehouses.

  2. Jargon and Graph Modularity on Twitter

    SciTech Connect

    Dowling, Chase P.; Corley, Courtney D.; Farber, Robert M.; Reynolds, William

    2013-09-01

    The language of conversation is just as dependent upon word choice as it is on who is taking part. Twitter provides an excellent test-bed in which to conduct experiments not only on language usage but on who is using what language with whom. To this end, we combine large scale graph analytical techniques with known socio-linguistic methods. In this article we leverage both expert curated vocabularies and naive mathematical graph analyses to determine if network behavior on Twitter corroborates with the current understanding of language usage. The results reported indicate that, based on networks constructed from user to user communication and communities identified using the Clauset- Newman greedy modularity algorithm we find that more prolific users of these curated vocabularies are concentrated in distinct network communities.

  3. Oil and gas exploration and development in Arizona

    SciTech Connect

    Nations, D.; Doss, A.K.; Ubarra, R.

    1984-07-01

    Recent oil and gas exploration activity has been widespread throughout Arizona. Development drilling has continued in the Dineh-bi-keyah and Teec-nos-Pos fields in the northeastern corner, and exploratory drilling continues to test potential Paleozoic reservoirs elsewhere on the plateau. Several shallow wells north of the Grand Canyon encountered shows and limited recoveries of oil from Permian and Triassic rocks. The greatest activity has occurred along the Overthrust trend from northwestern to southeastern Arizona. Several million acres were leased and eight exploratory wells drilled along this trend. None were discoveries, but the presence of a Laramide thrust fault in the vicinity of Tombstone was established. The other tests have neither proved nor disproved the concept of the Overthrust belt in southern Arizona. Recent discoveries in the nonmarine Tertiary and marine Paleozoic of southern Nevada have stimulated interest in the oil potential of similar rocks and structures in the Basin and Range province of Arizona, which are coincident with the Overthrust trend. Reported gas discoveries by Pemex in Miocene marine sediments of the Gulf of California have stimulated leasing in the Yuma area, where one uncompleted well is reported to be a potential producer. The Pedregosa basin of extreme southeastern Arizona remains an area of great interest to explorationists because of the presence of a 25,000-ft (7600-m) sequence of Paleozoic marine sediments similar to those of the Permian basin, and Cretaceous marine rocks, including coral-rudist reefs, similar to those that produce in Texas and Mexico.

  4. Integrated solid waste management of Scottsdale, Arizona

    SciTech Connect

    1995-11-01

    The subject document reports the results of an in-depth investigation of the fiscal year 1992 cost of the city of Scottsdale, Arizona, integrated municipal solid waste management (IMSWM) system, the energy consumed to operate the system, and the environmental performance requirements for each of the system`s waste-processing and disposal facilities. The document reports actual data from records kept by participants. Every effort was made to minimize the use of assumptions, and no attempt is made to interpret the data reported. Analytical approaches are documented so that interested analysts may per-form manipulation or further analysis of the data. As such, the report is a reference document for municipal solid waste (MSW) management professionals who are interested in the actual costs and energy consumption, for a 1-year period, of an operating IMSWM system. The report is organized into two main parts. The first part is the executive summary and case study portion of the report. The executive summary provides a basic description of the study area and selected economic and energy information. Within the case study are detailed descriptions of each component operating during the study period; the quantities of solid waste collected, processed, and marketed within the study boundaries; the cost of MSW in Scottsdale; an energy usage analysis; a review of federal, state, and local environmental requirement compliance; a reference section; and a glossary of terms. The second part of the report focuses on a more detailed discourse on the above topics. In addition, the methodology used to determine the economic costs and energy consumption of the system components is found in the second portion of this report. The methodology created for this project will be helpful for those professionals who wish to break out the costs of their own integrated systems.

  5. SWTC v. Arizona Corp. Comn, 142 P3d 1240 (2006) | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    SWTC v. Arizona Corp. Comn, 142 P3d 1240 (2006) Jump to: navigation, search OpenEI Reference LibraryAdd to library Legal CaseHearing: SWTC v. Arizona Corp. Comn, 142 P3d 1240...

  6. Apache County, Arizona ASHRAE 169-2006 Climate Zone | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    Apache County, Arizona ASHRAE 169-2006 Climate Zone Jump to: navigation, search County Climate Zone Place Apache County, Arizona ASHRAE Standard ASHRAE 169-2006 Climate Zone Number...

  7. Independent Confirmatory Survey Report for the University of Arizona Nuclear Reactor Laboratory, Tucson, Arizona

    SciTech Connect

    Nick A. Altic

    2011-11-11

    The University of Arizona (University) research reactor is a TRIGA swimming pool type reactor designed by General Atomics and constructed at the University in 1958. The reactor first went into operation in December of 1958 under U.S. Nuclear Regulatory Commission (NRC) license R-52 until final shut down on May 18, 2010. Initial site characterization activities were conducted in February 2009 during ongoing reactor operations to assess the radiological status of the Nuclear Reactor Laboratory (NRL) excluding the reactor tank, associated components, and operating systems. Additional post-shutdown characterization activities were performed to complete characterization activities as well as verify assumptions made in the Decommissioning Plan (DP) that were based on a separate activation analysis (ESI 2009 and WMG 2009). Final status survey (FSS) activities began shortly after the issuance of the FSS plan in May 2011. The contractor completed measurement and sampling activities during the week of August 29, 2011.

  8. In Arizona, Helping Communities Realize the Promise of Solar Power |

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

    Department of Energy In Arizona, Helping Communities Realize the Promise of Solar Power In Arizona, Helping Communities Realize the Promise of Solar Power May 15, 2012 - 3:07pm Addthis 1 of 4 Image: Darrylee Cohen 2 of 4 Image: Darrylee Cohen 3 of 4 Image: Darrylee Cohen 4 of 4 Image: Darrylee Cohen Greg Stanton Greg Stanton Mayor, City of Phoenix What are the key facts? The City of Phoenix launched Solar Phoenix 2, the largest city-sponsored residential solar program. Solar Phoenix 2 puts

  9. Arizona Natural Gas Number of Oil Wells (Number of Elements)

    Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Arizona Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 1 1 1 0 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Arizona Natural Gas Summary

  10. August 2015 Groundwater and Surface Water Sampling at the Tuba City, Arizona, Disposal Site

    Office of Legacy Management (LM)

    5 Groundwater and Surface Water Sampling at the Tuba City, Arizona, Disposal Site November 2015 LMS/TUB/S00815 This page intentionally left blank U.S. Department of Energy DVP-August 2015, Tuba City, Arizona, Disposal Site November 2015 RIN 15087262 Page i Contents Sampling Event Summary ...............................................................................................................1 Tuba City, Arizona, Disposal Site, Sample Location Map

  11. December 2015 Groundwater and Surface Water Sampling at the Monument Valley, Arizona, Processing Site

    Office of Legacy Management (LM)

    and Surface Water Sampling at the Monument Valley, Arizona, Processing Site March 2016 LMS/MON/S01215 This page intentionally left blank U.S. Department of Energy DVP-December 2015, Monument Valley, Arizona March 2016 RIN 15117527 Page i Contents Sampling Event Summary ...............................................................................................................1 Monument Valley, Arizona, Disposal Site Sample Location Map ..................................................5 Data

  12. A Graph Search Heuristic for Shortest Distance Paths

    SciTech Connect

    Chow, E

    2005-03-24

    This paper presents a heuristic for guiding A* search for finding the shortest distance path between two vertices in a connected, undirected, and explicitly stored graph. The heuristic requires a small amount of data to be stored at each vertex. The heuristic has application to quickly detecting relationships between two vertices in a large information or knowledge network. We compare the performance of this heuristic with breadth-first search on graphs with various topological properties. The results show that one or more orders of magnitude improvement in the number of vertices expanded is possible for large graphs, including Poisson random graphs.

  13. Sequoia supercomputer tops Graph 500 | National Nuclear Security...

    National Nuclear Security Administration (NNSA)

    Lawrence Livermore National Laboratory scientists' search for new ways to solve large complex national security problems led to the top ranking on Graph 500 and new techniques for ...

  14. Mining Graphs for Understanding Time-Varying Volumetric Data...

    Office of Scientific and Technical Information (OSTI)

    SciTech Connect Search Results Journal Article: Mining Graphs for Understanding ... DOE Contract Number: AC02-06CH11357 Resource Type: Journal Article Resource Relation: ...

  15. Two linear time, low overhead algorithms for graph layout

    Energy Science and Technology Software Center

    2008-01-10

    The software comprises two algorithms designed to perform a 2D layout of a graph structure in time linear with respect to the vertices and edges in the graph, whereas most other layout algorithms have a running time that is quadratic with respect to the number of vertices or greater. Although these layout algorithms run in a fraction of the time as their competitors, they provide competitive results when applied to most real-world graphs. These algorithmsmore » also have a low constant running time and small memory footprint, making them useful for small to large graphs.« less

  16. Energy Department, Arizona Utilities Announce Transmission Infrastructure Project Energization

    Energy.gov [DOE]

    Today, the Department of Energy’s Western Area Power Administration (Western) and a group of Arizona utilities celebrated the energizing of a new transmission infrastructure project that will serve the state’s growing electrical energy needs, attract renewable energy development to the area, and strengthen the transmission system in the Southwestern United States.

  17. EA-1989: Cliffrose Solar Energy Interconnection Project, Mohave County, Arizona

    Energy.gov [DOE]

    DOE’s Western Area Power Administration (Western) is preparing an EA that will assess the potential environmental impacts of interconnecting the proposed Cliffrose Solar Energy Project in Mohave County, Arizona, to Western’s transmission system at the existing Griffith Substation. Additional information is available at http://www.wapa.gov/dsw/environment/CliffroseSolarEnergyProject.html.

  18. EIS-0417: South Mountain Freeway (Loop 202); Phoenix, Arizona

    Energy.gov [DOE]

    Federal Highway Administration and Arizona Department of Transportation, with Western Area Power Administration as a cooperating agency, prepared an EIS that analyzes the potential environmental impacts of the proposed South Mountain Freeway (Loop 202) project in the Greater Metropolitan Phoenix Area.

  19. EIS-0297: Griffith Energy Project, Mohave County, Arizona

    Energy.gov [DOE]

    Western Area Power Administration (Western) intends to prepare an environmental impact statement (EIS) regarding the proposal by Griffith Energy (GE), LLC, to construct an electric generating facility on private property and to interconnect this facility with Western’s system in the vicinity of Kingman, Arizona.

  20. EIS-0441: Mohave County Wind Farm Project, Mohave County, Arizona

    Energy.gov [DOE]

    This EIS, prepared by the Bureau of Land Management with DOE’s Western Area Power Administration as a cooperating agency, evaluated the environmental impacts of a proposed wind energy project on public lands in Mohave County, Arizona. Power generated by this project would tie to the electrical power grid through an interconnection to one of Western’s transmission lines.

  1. International energy indicators. [Statistical tables and graphs

    SciTech Connect

    Bauer, E.K.

    1980-05-01

    International statistical tables and graphs are given for the following: (1) Iran - Crude Oil Capacity, Production and Shut-in, June 1974-April 1980; (2) Saudi Arabia - Crude Oil Capacity, Production, and Shut-in, March 1974-Apr 1980; (3) OPEC (Ex-Iran and Saudi Arabia) - Capacity, Production and Shut-in, June 1974-March 1980; (4) Non-OPEC Free World and US Production of Crude Oil, January 1973-February 1980; (5) Oil Stocks - Free World, US, Japan, and Europe (Landed, 1973-1st Quarter, 1980); (6) Petroleum Consumption by Industrial Countries, January 1973-December 1979; (7) USSR Crude Oil Production and Exports, January 1974-April 1980; and (8) Free World and US Nuclear Generation Capacity, January 1973-March 1980. Similar statistical tables and graphs included for the United States include: (1) Imports of Crude Oil and Products, January 1973-April 1980; (2) Landed Cost of Saudi Oil in Current and 1974 Dollars, April 1974-January 1980; (3) US Trade in Coal, January 1973-March 1980; (4) Summary of US Merchandise Trade, 1976-March 1980; and (5) US Energy/GNP Ratio, 1947 to 1979.

  2. Scaling Semantic Graph Databases in Size and Performance

    SciTech Connect

    Morari, Alessandro; Castellana, Vito G.; Villa, Oreste; Tumeo, Antonino; Weaver, Jesse R.; Haglin, David J.; Choudhury, Sutanay; Feo, John T.

    2014-08-06

    In this paper we present SGEM, a full software system for accelerating large-scale semantic graph databases on commodity clusters. Unlike current approaches, SGEM addresses semantic graph databases by only employing graph methods at all the levels of the stack. On one hand, this allows exploiting the space efficiency of graph data structures and the inherent parallelism of graph algorithms. These features adapt well to the increasing system memory and core counts of modern commodity clusters. On the other hand, however, these systems are optimized for regular computation and batched data transfers, while graph methods usually are irregular and generate fine-grained data accesses with poor spatial and temporal locality. Our framework comprises a SPARQL to data parallel C compiler, a library of parallel graph methods and a custom, multithreaded runtime system. We introduce our stack, motivate its advantages with respect to other solutions and show how we solved the challenges posed by irregular behaviors. We present the result of our software stack on the Berlin SPARQL benchmarks with datasets up to 10 billion triples (a triple corresponds to a graph edge), demonstrating scaling in dataset size and in performance as more nodes are added to the cluster.

  3. Competition Helps Kids Learn About Energy and Save Their Households...

    Energy Saver

    Competition Helps Kids Learn About Energy and Save Their Households Some Money Competition Helps Kids Learn About Energy and Save Their Households Some Money May 21, 2013 - 2:40pm ...

  4. Query optimization for graph analytics on linked data using SPARQL

    SciTech Connect

    Hong, Seokyong; Lee, Sangkeun; Lim, Seung -Hwan; Sukumar, Sreenivas R.; Vatsavai, Ranga Raju

    2015-07-01

    Triplestores that support query languages such as SPARQL are emerging as the preferred and scalable solution to represent data and meta-data as massive heterogeneous graphs using Semantic Web standards. With increasing adoption, the desire to conduct graph-theoretic mining and exploratory analysis has also increased. Addressing that desire, this paper presents a solution that is the marriage of Graph Theory and the Semantic Web. We present software that can analyze Linked Data using graph operations such as counting triangles, finding eccentricity, testing connectedness, and computing PageRank directly on triple stores via the SPARQL interface. We describe the process of optimizing performance of the SPARQL-based implementation of such popular graph algorithms by reducing the space-overhead, simplifying iterative complexity and removing redundant computations by understanding query plans. Our optimized approach shows significant performance gains on triplestores hosted on stand-alone workstations as well as hardware-optimized scalable supercomputers such as the Cray XMT.

  5. EAGLE: 'EAGLE'Is an' Algorithmic Graph Library for Exploration

    SciTech Connect

    2015-01-16

    The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. Today there is no tools to conduct "graph mining" on RDF standard data sets. We address that need through implementation of popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, degree distribution, diversity degree, PageRank, etc.). We implement these algorithms as SPARQL queries, wrapped within Python scripts and call our software tool as EAGLE. In RDF style, EAGLE stands for "EAGLE 'Is an' algorithmic graph library for exploration. EAGLE is like 'MATLAB' for 'Linked Data.'

  6. An Experiment on Graph Analysis Methodologies for Scenarios

    SciTech Connect

    Brothers, Alan J.; Whitney, Paul D.; Wolf, Katherine E.; Kuchar, Olga A.; Chin, George

    2005-09-30

    Visual graph representations are increasingly used to represent, display, and explore scenarios and the structure of organizations. The graph representations of scenarios are readily understood, and commercial software is available to create and manage these representations. The purpose of the research presented in this paper is to explore whether these graph representations support quantitative assessments of the underlying scenarios. The underlying structure of the scenarios is the information that is being targeted in the experiment and the extent to which the scenarios are similar in content. An experiment was designed that incorporated both the contents of the scenarios and analysts’ graph representations of the scenarios. The scenarios’ content was represented graphically by analysts, and both the structure and the semantics of the graph representation were attempted to be used to understand the content. The structure information was not found to be discriminating for the content of the scenarios in this experiment; but, the semantic information was discriminating.

  7. Determinants of Household Use of Selected Energy Star Appliances - Energy

    Gasoline and Diesel Fuel Update

    Information Administration Determinants of Household Use of Selected Energy Star Appliances Release date: May 25, 2016 Introduction According to the 2009 Residential Energy Consumption Survey (RECS), household appliances1accounted for 35% of U.S. household energy consumption, up from 24% in 1993. Thus, improvements in the energy performance of residential appliances as well as increases in the use of more efficient appliances can be effective in reducing household energy consumption and

  8. Graph facilitates tracking water and gas influx

    SciTech Connect

    Gruy, H.J. )

    1990-03-26

    Graphing the vertical distribution of reservoir volume is an easy method for estimating the acre-ft remaining to be exploited in reservoirs with water or gas encroachment. To evaluate reservoir performance and estimate oil and gas reserves in water-drive reservoirs or oil reservoirs with a gas cap, it is necessary to determine the magnitude of the movement of oil-water and gas-oil contact surfaces. In reviewing reserve estimates and reservoir studies done by others, the authors have found that very few reservoir engineers or geologists have an easy method for tracking the movement of these surfaces and estimating the volumes of oil displaced water encroachment, gas cap expansion, or the volumes of oil lost by wetting the gas cap. The following method evolved from the author's studies of the East Texas field starting in 1942, and it took this form in the early 1950s.

  9. The effects of indoor pollution on Arizona children

    SciTech Connect

    Dodge, R.

    1982-05-01

    The respiratory health of a large group of Arizona school children who have been exposed to indoor pollutants-tobacco smoke and home cooking fumes-is reported. A significant relationship was found between parental smoking and symptoms of cough, wheeze, and sputum production. Also, children in homes where gas cooking fuel was used had higher rates of cough than children in homes where electricity was used. No differences in pulmonary function or yearly lung growth rates occurred among subjects grouped by exposure to tobacco smoke or cooking fuel. Thus, parental smoking and home cooking fuel affected cross-sectional respiratory symptom rates in a large group of Arizona school children. Study of pulmonary function, however, revealed no lung function or lung growth effects during 4 yr of study.

  10. Household Energy Consumption Segmentation Using Hourly Data

    SciTech Connect

    Kwac, J; Flora, J; Rajagopal, R

    2014-01-01

    The increasing US deployment of residential advanced metering infrastructure (AMI) has made hourly energy consumption data widely available. Using CA smart meter data, we investigate a household electricity segmentation methodology that uses an encoding system with a pre-processed load shape dictionary. Structured approaches using features derived from the encoded data drive five sample program and policy relevant energy lifestyle segmentation strategies. We also ensure that the methodologies developed scale to large data sets.

  11. Household energy consumption and expenditures, 1987

    SciTech Connect

    Not Available

    1989-10-10

    Household Energy Consumption and Expenditures 1987, Part 1: National Data is the second publication in a series from the 1987 Residential Energy Consumption Survey (RECS). It is prepared by the Energy End Use Division (EEUD) of the Office of Energy Markets and End Use (EMEU), Energy Information Administration (EIA). The EIA collects and publishes comprehensive data on energy consumption in occupied housing units in the residential sector through the RECS. 15 figs., 50 tabs.

  12. Student research in criticality safety at the University of Arizona

    SciTech Connect

    Hetrick, D.L.

    1997-06-01

    A very brief progress report on four University of Arizona student projects is given. Improvements were made in simulations of power pulses in aqueous solutions, including the TWODANT model. TWODANT calculations were performed to investigate the effect of assembly shape on the expansion coefficient of reactivity for solutions. Preliminary calculations were made of critical heights for the Los Alamos SHEBA assembly. Calculations to support French experiments to measure temperature coefficients of dilute plutonium solutions confirmed feasibility.

  13. PROJECT PROFILE: Arizona State University 3 (PVRD) | Department of Energy

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

    3 (PVRD) PROJECT PROFILE: Arizona State University 3 (PVRD) Project Name: Pushing the Limits of Silicon Heterojunction Solar Cells: Demonstration of 26% Efficiency and Improving Electrical Yield Funding Opportunity: PVRD SunShot Subprogram: Photovoltaics Location: Tempe, AZ SunShot Award Amount: $837,044 Awardee Cost Share: $92,991 Project Investigator: Stuart Bowden This project examines the manufacturability of n-type industrial silicon heterojunction cells and develops methods to improve

  14. PROJECT PROFILE: Arizona State University 4 (PVRD) | Department of Energy

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

    4 (PVRD) PROJECT PROFILE: Arizona State University 4 (PVRD) Project Name: Plant and Module Designs for Uniform and Reduced Operating Temperature Funding Opportunity: PVRD SunShot Subprogram: Photovoltaics Location: Tempe, AZ SunShot Award Amount: $899,316 Awardee Cost Share: $100,000 Project Investigator: Govindasamy Tamizhmani This project intends to identify and evaluate thermally conductive and radiative but electrically insulating backsheets, which can be used by the photovoltaic (PV) module

  15. EA-2023: Crossman Peak Communications Facility; Mohave County, Arizona

    Office of Energy Efficiency and Renewable Energy (EERE)

    Western Area Power Administration is preparing an EA that assesses the potential environmental impacts of a proposed new microwave communication facility to be located adjacent to a privately-owned one near Crossman Peak, east of Lake Havasu City in Mohave County, Arizona. The proposal would consist of a microwave communication facility, an access road, and an approximately 8-mile electrical service distribution line across private land and land administered by the Bureau of Land Management.

  16. Composing Data Parallel Code for a SPARQL Graph Engine

    SciTech Connect

    Castellana, Vito G.; Tumeo, Antonino; Villa, Oreste; Haglin, David J.; Feo, John

    2013-09-08

    Big data analytics process large amount of data to extract knowledge from them. Semantic databases are big data applications that adopt the Resource Description Framework (RDF) to structure metadata through a graph-based representation. The graph based representation provides several benefits, such as the possibility to perform in memory processing with large amounts of parallelism. SPARQL is a language used to perform queries on RDF-structured data through graph matching. In this paper we present a tool that automatically translates SPARQL queries to parallel graph crawling and graph matching operations. The tool also supports complex SPARQL constructs, which requires more than basic graph matching for their implementation. The tool generates parallel code annotated with OpenMP pragmas for x86 Shared-memory Multiprocessors (SMPs). With respect to commercial database systems such as Virtuoso, our approach reduces memory occupation due to join operations and provides higher performance. We show the scaling of the automatically generated graph-matching code on a 48-core SMP.

  17. Determinants of Household Use of Selected Energy Star Appliances

    Gasoline and Diesel Fuel Update

    Restructuring by State Map. State: 51 items, 51 with data. Alabama is 0. Value is in the Not Active range, Alabama Deregulation: NO Retail Choice: NO Click for more information (State Restructuring Activities: None since 10/2000), Detail for AL. Arkansas is 9. Value is in the Suspended range, Arkansas Deregulation: SUSPENDED Retail Choice: NO Click for more information (State Restructuring Activities: None since 03/2003), Detail for AR. Arizona is 9. Value is in the Suspended range, Arizona

  18. Household and environmental characteristics related to household energy-consumption change: A human ecological approach

    SciTech Connect

    Guerin, D.A.

    1988-01-01

    This study focused on the family household as an organism and on its interaction with the three environments of the human ecosystem (natural, behavioral, and constructed) as these influence energy consumption and energy-consumption change. A secondary statistical analysis of data from the US Department of Energy Residential Energy Consumption Surveys (RECS) was completed. The 1980 and 1983 RECS were used as the data base. Longitudinal data, including household, environmental, and energy-consumption measures, were available for over 800 households. The households were selected from a national sample of owner-occupied housing units surveyed in both years. Results showed a significant( p = <.05) relationship between the dependent-variable energy-consumption change and the predictor variables heating degree days, addition of insulation, addition of a wood-burning stove, year the housing unit was built, and weighted number of appliances. A significant (p = <.05) relationship was found between the criterion variable energy-consumption change and the discriminating variables of age of the head of the household, cooling degree days, heating degree days, year the housing unit was built, and number of stories in the housing unit.

  19. Impacts of High Penetration of PV with Energy Storage at Flagstaff Arizona

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

    | Department of Energy Impacts of High Penetration of PV with Energy Storage at Flagstaff Arizona Impacts of High Penetration of PV with Energy Storage at Flagstaff Arizona aps-logo.gif --This project is inactive -- The project team, led by Arizona Public Service, will evaluate the impacts of high penetrations of distributed PV and energy storage on a dedicated feeder to identify the technical and operational modifications that could be deployed in future feeder designs. APPROACH Models

  20. Vegetation Cover Analysis of Hazardous Waste Sites in Utah and Arizona

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

    Using Hyperspectral Remote Sensing | Department of Energy Vegetation Cover Analysis of Hazardous Waste Sites in Utah and Arizona Using Hyperspectral Remote Sensing Vegetation Cover Analysis of Hazardous Waste Sites in Utah and Arizona Using Hyperspectral Remote Sensing January 17, 2012 Jungho Im, John R. Jensen, Ryan R. Jensen, John Gladden, Jody Waugh and Mike Serrato Vegetation Cover Analysis of Hazardous Waste Sites in Utah and Arizona Using Hyperspectral Remote Sensing (3.07 MB) More

  1. PP-107-1 Arizona Public Service Company | Department of Energy

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

    Presidential permit authorizing Arizona Public Service Company to construct, operate, and maintain electric transmission facilities at the U.S-Mexico border. PDF icon PP-107-1 ...

  2. Top-of-the-World, Arizona: Energy Resources | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Top-of-the-World, Arizona: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 33.3494997, -110.9926154 Show Map Loading map......

  3. Could Gila Bend, Arizona, Become the Solar Capital of the World?

    Energy.gov [DOE]

    Serving approximately 9,000 homes with clean renewable energy, the Paloma and Cotton Center solar plants highlight the rapidly rising solar corridor in Gila Bend, Arizona.

  4. Arizona Regional High Science Bowl | U.S. DOE Office of Science...

    Office of Science (SC)

    Arizona Regional High Science Bowl National Science Bowl (NSB) NSB Home About Regional Competitions Rules, Forms, and Resources High School Regionals Middle School Regionals ...

  5. Must all charting and graphing code be written in javascript...

    OpenEI (Open Energy Information) [EERE & EIA]

    Must all charting and graphing code be written in javascript? Home > Groups > Databus In the documentation chapter entitled Developing charts using 3rd party api, we are told that...

  6. Parallel Algorithms for Graph Optimization using Tree Decompositions

    SciTech Connect

    Sullivan, Blair D; Weerapurage, Dinesh P; Groer, Christopher S

    2012-06-01

    Although many $\\cal{NP}$-hard graph optimization problems can be solved in polynomial time on graphs of bounded tree-width, the adoption of these techniques into mainstream scientific computation has been limited due to the high memory requirements of the necessary dynamic programming tables and excessive runtimes of sequential implementations. This work addresses both challenges by proposing a set of new parallel algorithms for all steps of a tree decomposition-based approach to solve the maximum weighted independent set problem. A hybrid OpenMP/MPI implementation includes a highly scalable parallel dynamic programming algorithm leveraging the MADNESS task-based runtime, and computational results demonstrate scaling. This work enables a significant expansion of the scale of graphs on which exact solutions to maximum weighted independent set can be obtained, and forms a framework for solving additional graph optimization problems with similar techniques.

  7. EAGLE: 'EAGLE'Is an' Algorithmic Graph Library for Exploration

    Energy Science and Technology Software Center

    2015-01-16

    The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. Today there is no tools to conduct "graphmore » mining" on RDF standard data sets. We address that need through implementation of popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, degree distribution, diversity degree, PageRank, etc.). We implement these algorithms as SPARQL queries, wrapped within Python scripts and call our software tool as EAGLE. In RDF style, EAGLE stands for "EAGLE 'Is an' algorithmic graph library for exploration. EAGLE is like 'MATLAB' for 'Linked Data.'« less

  8. Data Sources For Emerging Technologies Program MYPP Target Graphs

    Office of Energy Efficiency and Renewable Energy (EERE)

    The BTO Emerging Technologies Accomplishments and Outcomes – 2015 page contains graphs on Multi-Year Program Plan R&D targets for certain technologies. This page contains information on data...

  9. Highly Asynchronous VisitOr Queue Graph Toolkit

    Energy Science and Technology Software Center

    2012-10-01

    HAVOQGT is a C++ framework that can be used to create highly parallel graph traversal algorithms. The framework stores the graph and algorithmic data structures on external memory that is typically mapped to high performance locally attached NAND FLASH arrays. The framework supports a vertex-centered visitor programming model. The frameworkd has been used to implement breadth first search, connected components, and single source shortest path.

  10. TIFF Image Writer patch for OpenSceneGraph

    Energy Science and Technology Software Center

    2012-01-05

    This software consists of code modifications to the open-source OpenSceneGraph software package to enable the creation of TlFF images containing 16 bit unsigned data. They also allow the user to disable compression and set the DPI tags in the resulting TIFF Images. Some image analysis programs require uncompressed, 16 bit unsigned input data. These code modifications allow programs based on OpenSceneGraph to write out such images, improving connectivity between applications.

  11. The peculiar phase structure of random graph bisection

    SciTech Connect

    Percus, Allon G; Istrate, Gabriel; Goncalves, Bruno T; Sumi, Robert Z

    2008-01-01

    The mincut graph bisection problem involves partitioning the n vertices of a graph into disjoint subsets, each containing exactly n/2 vertices, while minimizing the number of 'cut' edges with an endpoint in each subset. When considered over sparse random graphs, the phase structure of the graph bisection problem displays certain familiar properties, but also some surprises. It is known that when the mean degree is below the critical value of 2 log 2, the cutsize is zero with high probability. We study how the minimum cutsize increases with mean degree above this critical threshold, finding a new analytical upper bound that improves considerably upon previous bounds. Combined with recent results on expander graphs, our bound suggests the unusual scenario that random graph bisection is replica symmetric up to and beyond the critical threshold, with a replica symmetry breaking transition possibly taking place above the threshold. An intriguing algorithmic consequence is that although the problem is NP-hard, we can find near-optimal cutsizes (whose ratio to the optimal value approaches 1 asymptotically) in polynomial time for typical instances near the phase transition.

  12. Appliance Commitment for Household Load Scheduling

    SciTech Connect

    Du, Pengwei; Lu, Ning

    2011-06-30

    This paper presents a novel appliance commitment algorithm that schedules thermostatically-controlled household loads based on price and consumption forecasts considering users comfort settings to meet an optimization objective such as minimum payment or maximum comfort. The formulation of an appliance commitment problem was described in the paper using an electrical water heater load as an example. The thermal dynamics of heating and coasting of the water heater load was modeled by physical models; random hot water consumption was modeled with statistical methods. The models were used to predict the appliance operation over the scheduling time horizon. User comfort was transformed to a set of linear constraints. Then, a novel linear, sequential, optimization process was used to solve the appliance commitment problem. The simulation results demonstrate that the algorithm is fast, robust, and flexible. The algorithm can be used in home/building energy-management systems to help household owners or building managers to automatically create optimal load operation schedules based on different cost and comfort settings and compare cost/benefits among schedules.

  13. National Uranium Resource Evaluation: Kingman Quadrangle, Arizona, Nevada, and California

    SciTech Connect

    Luning, R.H.; Penley, H.M.; Johnson, C.L.; Dotterrer, F.E.

    1982-09-01

    Literature research, surface geologic investigations, and rock sampling were conducted for the Kingman Quadrangle, Arizona, Nevada, and California, to identify geologic environments and delineate areas favorable for uranium deposits. Favorability criteria developed during the National Uranium Resource Evaluation program were used. The studies were augmented by aerial radiometric and hydrogeochemical and stream-sediment surveys. No environments favorable for uranium deposits of at least 100 tons U/sub 3/O/sub 8/ were found. Unfavorable environments include all sedimentary, igneous, and metamorphic rocks of Precambrian to Laramide age; Tertiary volcanic sequences; and Quaternary caliche. Unevaluated environments include the Bird Spring Formation and the intermontane valleys.

  14. PROJECT PROFILE: Arizona State University 2 (PVRD) | Department of Energy

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

    2 (PVRD) PROJECT PROFILE: Arizona State University 2 (PVRD) Project Name: Monolithic Silicon Module Manufacturing at Under $0.40 per Watt Funding Opportunity: PVRD SunShot Subprogram: Photovoltaics Location: Tempe, AZ SunShot Award Amount: $800,000 Awardee Cost Share: $88,886 Project Investigator: Zachary Holman This project aims to lower the cost of photovoltaic (PV) electricity generation in fewer than five years to $0.04 per kilowatt hour through the development of a PV module that is based

  15. Arizona Natural Gas Number of Industrial Consumers (Number of Elements)

    Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Arizona Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 358 344 354 1990's 526 532 532 526 519 530 534 480 514 555 2000's 526 504 488 450 414 425 439 395 383 390 2010's 368 371 379 383 386 400 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release

  16. Arizona Quantity of Production Associated with Reported Wellhead Value

    Energy Information Administration (EIA) (indexed site)

    (Million Cubic Feet) Quantity of Production Associated with Reported Wellhead Value (Million Cubic Feet) Arizona Quantity of Production Associated with Reported Wellhead Value (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 26 10 0 0 0 0 1,360 1990's 2,125 1,225 730 548 691 500 405 401 411 439 2000's 332 266 243 426 306 211 588 634 503 695 2010's 165 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  17. Arizona Total Electric Power Industry Net Generation, by Energy Source

    Energy Information Administration (EIA) (indexed site)

    Arizona" "Energy Source",2006,2007,2008,2009,2010 "Fossil",73385,79794,82715,74509,73386 " Coal",40443,41275,43840,39707,43644 " Petroleum",73,49,52,63,66 " Natural Gas",32869,38469,38822,34739,29676 " Other Gases","-","-","-","-","-" "Nuclear",24012,26782,29250,30662,31200 "Renewables",6846,6639,7400,6630,6941 "Pumped Storage",149,125,95,169,209

  18. Barriers to household investment in residential energy conservation: preliminary assessment

    SciTech Connect

    Hoffman, W.L.

    1982-12-01

    A general assessment of the range of barriers which impede household investments in weatherization and other energy efficiency improvements for their homes is provided. The relationship of similar factors to households' interest in receiving a free energy audits examined. Rates of return that underly household investments in major conservation improvements are assessed. A special analysis of household knowledge of economically attractive investments is provided that compares high payback improvements specified by the energy audit with the list of needed or desirable conservation improvements identified by respondents. (LEW)

  19. Loan Programs for Low- and Moderate-Income Households

    Energy.gov [DOE]

    Better Buildings Residential Network Multifamily and Low-Income Housing Peer Exchange Call Series: Loan Programs for Low- and Moderate-Income Households, March 13, 2014.

  20. Delivering Energy Efficiency to Middle Income Single Family Households

    SciTech Connect

    none,

    2011-12-01

    Provides state and local policymakers with information on successful approaches to the design and implementation of residential efficiency programs for households ineligible for low-income programs.