Powered by Deep Web Technologies
Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

CSV File Documentation: Consumption  

Gasoline and Diesel Fuel Update (EIA)

Consumption Consumption The State Energy Data System (SEDS) comma-separated value (CSV) files contain consumption estimates shown in the tables located on the SEDS website. There are four files that contain estimates for all states and years. Consumption in Physical Units contains the consumption estimates in physical units for all states; Consumption in Btu contains the consumption estimates in billion British thermal units (Btu) for all states. There are two data files for thermal conversion factors: the CSV file contains all of the conversion factors used to convert data between physical units and Btu for all states and the United States, and the Excel file shows the state-level conversion factors for coal and natural gas in six Excel spreadsheets. Zip files are also available for the large data files. In addition, there is a CSV file for each state, named

2

SEDS CSV File Documentation: Price and Expenditure  

Gasoline and Diesel Fuel Update (EIA)

Prices and Expenditures Prices and Expenditures The State Energy Data System (SEDS) comma-separated value (CSV) files contain the price and expenditure estimates shown in the tables located on the SEDS website. There are three files that contain estimates for all states and years. Prices contains the price estimates for all states and Expenditures contains the expenditure estimates for all states. The third file, Adjusted Consumption for Expenditure Calculations contains adjusted consumption estimates used in calculating expenditures (see Appendix E below). Zip files are also available for the large data files. In addition, there is a CSV file for each state, named with the two-letter U.S. Postal Code listed in Appendix A, as well as a file for the United States.

3

OMBDOEFAIR2005.xls | Department of Energy  

Office of Environmental Management (EM)

OMBDOEFAIR2005.xls&0; OMBDOEFAIR2005.xls&0; More Documents & Publications 2003 DOE IGCA Inventory Data for web.xls&0; 3REV2004DOEFAIR.xls&0; N:My Documentsporfin.pdf...

4

FFATA sub reporting data model_draft_100715.xls | Department...  

Energy Savers [EERE]

FFATA sub reporting data modeldraft100715.xls FFATA sub reporting data modeldraft100715.xls FFATA sub reporting data modeldraft100715.xls More Documents & Publications...

5

How do I display the Map of Wind Farms csv coordinates in ArcMap software?  

Open Energy Info (EERE)

display the Map of Wind Farms csv coordinates in ArcMap software? display the Map of Wind Farms csv coordinates in ArcMap software? Home > Groups > Geospatial I downloaded the Map of Wind Farms data as a .csv from http://en.openei.org/wiki/Map_of_Wind_Farms/Data. The downloaded data contains the latitude and longitude values in a single column. ArcMap requires separate fields for lat/long. Also, there is a strange character at the end of the coordinate values, °. It looks like this might be due to using the degree symbol? Will this cause an issue when attempting to import the downloaded data into ESRI ArcMap software? Thanks for any guidance you can provide! Submitted by Scourer on 10 September, 2013 - 09:40 1 answer Points: 1 Hi- Yes, you are correct with determining why the ° characters appear in the CSV. This is an artifact of transforming the coordinates to values for the

6

3REV2004DOEFAIR.xls | Department of Energy  

Office of Environmental Management (EM)

3REV2004DOEFAIR.xls&0; 3REV2004DOEFAIR.xls&0; More Documents & Publications N:My Documentsporfin.pdf&0; OMBDOEFAIR2005.xls&0; 2003 DOE IGCA Inventory Data for web...

7

How do I display the Map of Wind Farms csv coordinates in ArcMap software?  

Open Energy Info (EERE)

How do I display the Map of Wind Farms csv coordinates in ArcMap software? How do I display the Map of Wind Farms csv coordinates in ArcMap software? Home > Groups > Geospatial I downloaded the Map of Wind Farms data as a .csv from http://en.openei.org/wiki/Map_of_Wind_Farms/Data. The downloaded data contains the latitude and longitude values in a single column. ArcMap requires separate fields for lat/long. Also, there is a strange character at the end of the coordinate values, °. It looks like this might be due to using the degree symbol? Will this cause an issue when attempting to import the downloaded data into ESRI ArcMap software? Thanks for any guidance you can provide! Submitted by Scourer on 10 September, 2013 - 09:40 1 answer Points: 1 Hi- Yes, you are correct with determining why the ° characters appear in the

8

owip_jobs_calculator_v11-0.xls | Department of Energy  

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

owipjobscalculatorv11-0.xls owipjobscalculatorv11-0.xls owipjobscalculatorv11-0.xls More Documents & Publications bbanxxxxxxxpmcprogressreport2y12qx.xlsx Job...

9

2011 Cost Symposium Agenda 4-28-11 web draft.xls | Department...  

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

2011 Cost Symposium Agenda 4-28-11 web draft.xls 2011 Cost Symposium Agenda 4-28-11 web draft.xls 2011 Cost Symposium Agenda 4-28-11 web draft.xls More Documents & Publications...

10

2003 DOE IGCA Inventory Data for web.xls | Department of Energy  

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

3 DOE IGCA Inventory Data for web.xls&0; 2003 DOE IGCA Inventory Data for web.xls&0; 2003 DOE IGCA Inventory Data for web.xls&0; More Documents & Publications...

11

FINAL Combined SGIG Selections - By State for Press -5.xls |...  

Office of Environmental Management (EM)

- By State for Press -5.xls More Documents & Publications Recovery Act Selections for Smart Grid Invesment Grant Awards- By Category Updated July 2010 FINAL Combined SGIG...

12

Graph Algorithms Tours in Graphs  

E-Print Network [OSTI]

terminates only at y. Graph Algorithms 14 #12;Combining the Main and the Secondary Cycles Let C = (x a secondary cycle C starting with y. - Combine the cycles C and C into C. Return the cycle C. Graph AlgorithGraph Algorithms Tours in Graphs Graph Algorithms #12;Special Paths and Cycles in Graphs Euler Path

Bar-Noy, Amotz

13

Oil and Gas Recovery Data from the Riser Insertion Tub - XLS...  

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

XLS Oil and Gas Recovery Data from the Riser Insertion Tub - XLS Oil and Gas Recovery Data from the Riser Insertion Tube from May 17 until the Riser Insertion Tube was disconnected...

14

TOTAL ARRA Homes Weatherized thru Q2 2010 8.19.10.xls | Department...  

Energy Savers [EERE]

TOTAL ARRA Homes Weatherized thru Q2 2010 8.19.10.xls TOTAL ARRA Homes Weatherized thru Q2 2010 8.19.10.xls TOTAL ARRA Homes Weatherized thru Q2 2010 8.19.10.xls More Documents &...

15

Copy of FINAL SG Demo Project List 11 13 09-External.xls | Department...  

Office of Environmental Management (EM)

Copy of FINAL SG Demo Project List 11 13 09-External.xls More Documents & Publications Smart Grid Regional and Energy Storage Demonstration Projects: Awards Energy Storage...

16

Graph Algorithms Special Sets in Graphs  

E-Print Network [OSTI]

{u e}. Graph Algorithms 8 #12;Example: A Vertex Cover Set Graph Algorithms 9 #12;Example: A Minimum Size Vertex Cover Set Graph Algorithms 10 #12;A Clique A set of vertices for which all possible edges * * * * * Graph Algorithms 20 #12;Independent Sets and Vertex Cover Sets Observation: I is an independent set

Bar-Noy, Amotz

17

Annual Energy Review - Energy Information Administration  

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

Annual Energy Review Annual Energy Review Superseded -- see MER for key annual tables Annual Energy Review archives for data year: 2011 2010 2009 2008 all archives Go EIA has expanded the Monthly Energy Review (MER) to include annual data as far back as 1949 for those data tables that are found in both the Annual Energy Review (AER) and the MER . During this transition, EIA will not publish the 2012 edition of the AER. In the list of tables below, grayed-out table numbers now go to MER tables that contain 1949-2012 (and later) data series. New interactive tables and graphs have also been added and are currently on EIA's Beta site. Data categories + EXPAND ALL Energy Overview 1.0 Total Energy Flow, GRAPH 1.1 Primary Energy Overview, 1949- PDF XLS CSV INTERACTIVE 1.2 Primary Energy Production by Source, 1949- PDF XLS CSV INTERACTIVE

18

Graph Algorithms Edge Coloring  

E-Print Network [OSTI]

: Perfect Matching Graph Algorithms 6 #12;Edge Covering An edge covering, EC E, is a set of edges #12;Example: Edge Covering Graph Algorithms 8 #12;Example: Minimal Edge Covering Graph Algorithms 9 #12;Example: Minimum Size Edge Covering Graph Algorithms 10 #12;Matching and Edge Covering Definition

Bar-Noy, Amotz

19

Graph Algorithms Robert Elsasser  

E-Print Network [OSTI]

-regular bipartite graph has a perfect matching. Definition 3: A vertex cover of a graph G = (V, E) is a set Q VGraph Algorithms Robert Els¨asser 10 November 2011 Program of the day: · Matchings in bipartite graphs Robert Els¨asser Universit¨at Paderborn Graph Algorithms WS 11/12 0 #12;5. Matchings in bipartite

Elsässer, Robert

20

PDSF Utilization Graphs  

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

Graphs Graphs Utilization Graphs This page contains a series of graphs 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 approximately every 15 minutes. This graph shows the aggregate cluster CPU availablity and usage according to sgeload: 24 hour rolling usage graph (click to see long term averages) This graph shows the number of jobs being run by each group: Rolling 24 Running Jobs by Group (click to see long term averages) This is the same graph as above weighted by the clockspeed (GHz) of the node used for the job: Rolling 24 Running Jobs by Group (click to see long term averages) This graph show the number of pending jobs by group: Rolling 24 Pending Jobs

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Graph Visualization API Library for Application Builders  

Science Journals Connector (OSTI)

Founded in 1991, Tom Sawyer Software produces quality graph-based architectures for application developers. These technologies include graph management, graph layout, graph diagramming, and graph visualization...

Franois Bertault; Wendy Feng; Uli Feier; Gabe Grigorescu

2002-01-01T23:59:59.000Z

22

Graph Algorithms Vertex Coloring  

E-Print Network [OSTI]

Coloring Definition I: A disjoint collection of independent sets that cover all the vertices in the graphGraph Algorithms Vertex Coloring Graph Algorithms #12;The Input Graph G = (V, E) a simple and undirected graph: V : a set of n vertices. E: a set of m edges. A B EF C D A B C D E F A 0 1 1 1 0 0 B 1 0

Bar-Noy, Amotz

23

Graph algorithms experimentation facility  

E-Print Network [OSTI]

minimum vertex cover and maximum clique size heuristics and some visibility and circle graph related methods. As a by-product of our implementation we obtained several results about the structure of maximum independent sets for several classes of graphs...

Sonom, Donald George

2012-06-07T23:59:59.000Z

24

Graphs, Trees Pebbles, Robots  

E-Print Network [OSTI]

Graphs, Trees Pebbles, Robots 1 #12;Outline I. Robot Arms. II. Rigid Graphs. III. Characterizations. Applications: (a) Rigid Components. 2 #12;I. Robot arms and the Carpenter's Rule Problem. Can a robot arm

Haas, Ruth

25

Parasupersymmetry in Quantum Graphs  

E-Print Network [OSTI]

We study hidden parasupersymmetry structures in purely bosonic quantum mechanics on compact equilateral graphs. We consider a single free spinless particle on the graphs and show that the Huang-Su parasupersymmetry algebra is hidden behind degenerate spectra.

Satoshi Ohya

2012-10-29T23:59:59.000Z

26

Parasupersymmetry in Quantum Graphs  

E-Print Network [OSTI]

We study hidden parasupersymmetry structures in purely bosonic quantum mechanics on compact equilateral graphs. We consider a single free spinless particle on the graphs and show that the Rubakov-Spiridonov-Khare-Tomiya parasupersymmetries are hidden behind degenerate spectra.

Ohya, Satoshi

2012-01-01T23:59:59.000Z

27

Graph Algorithms Robert Elsasser  

E-Print Network [OSTI]

. Definition 3: A vertex cover of a graph G = (V, E) is a set Q V , such that each edge of E is incidentGraph Algorithms Robert Els¨asser 17 November 2011 Program of the day: · Matchings in bipartite graphs Robert Els¨asser Universit¨at Paderborn Graph Algorithms WS 11/12 0 #12;5. Matchings in bipartite

Elsässer, Robert

28

Spectral characterizations of sun graphs and broken sun graphs  

E-Print Network [OSTI]

Spectral characterizations of sun graphs and broken sun graphs Romain Boulet 10 Dec 2009 Abstract- cyclic graphs. An odd (resp. even) sun is a graph obtained by appending a pendant vertex to each vertex of an odd (resp. even) cycle. A broken sun is a graph obtained by deleting pendant vertices of a sun

Paris-Sud XI, Université de

29

Convex Graph Invariants  

E-Print Network [OSTI]

Dec 2, 2010 ... where A represents the adjacency matrix of a graph, and the maximum is taken over all ...... SDPT3 - a MATLAB software package for.

2010-12-02T23:59:59.000Z

30

Spectral Graph Theory  

E-Print Network [OSTI]

REU this summer was also to examine the brain of. Caenorhabditis elegans (C. Elegans). Chklovskii formed a Laplacian matrix of the graph representing.

*D. J. Kelleher

2011-09-30T23:59:59.000Z

31

Graphs associated with semigroups  

E-Print Network [OSTI]

the empty graph is not td d t b pl t . A ~b* h 1 g ph G graph having all of its vertices and edges in G. The citations on the following pages follow the style f th ~fdt f th A t M th tt 1 ~S1 t A path is a sequence of distinct vertices, V , V... , . . . , V n' where V and V are adjacent for i 1, 2, . . . , n-l. If there exists a path between two vertices, the pair is said to be connected. A connected ~ra h is a graph in which every pair of vertices is joined by a path. The empty graph...

Baber, Stephen Asa

2012-06-07T23:59:59.000Z

32

GraphState - a tool for graph identification and labelling  

E-Print Network [OSTI]

We present python libraries for Feynman graphs manipulation. The key feature of these libraries is usage of generalization of graph representation offered by B. G. Nickel et al. In this approach graph is represented in some unique 'canonical' form that depends only on its combinatorial type. The uniqueness of graph representation gives an efficient way for isomorphism finding, searching for subgraphs and other graph manipulation tasks. Though offered libraries were originally designed for Feynman graphs, they might be useful for more general graph problems.

Batkovich, D; Kompaniets, M; Novikov, S

2014-01-01T23:59:59.000Z

33

GraphState - a tool for graph identification and labelling  

E-Print Network [OSTI]

We present python libraries for Feynman graphs manipulation. The key feature of these libraries is usage of generalization of graph representation offered by B. G. Nickel et al. In this approach graph is represented in some unique 'canonical' form that depends only on its combinatorial type. The uniqueness of graph representation gives an efficient way for isomorphism finding, searching for subgraphs and other graph manipulation tasks. Though offered libraries were originally designed for Feynman graphs, they might be useful for more general graph problems.

D. Batkovich; Yu. Kirienko; M. Kompaniets; S. Novikov

2014-09-29T23:59:59.000Z

34

Querying graphs with data  

E-Print Network [OSTI]

Graph data is becoming more and more pervasive. Indeed, services such as Social Networks or the Semantic Web can no longer rely on the traditional relational model, as its structure is somewhat too rigid for the applications ...

Vrgoc, Domagoj

2014-06-27T23:59:59.000Z

35

Graph degree linkage: agglomerative clustering on a directed graph  

Science Journals Connector (OSTI)

This paper proposes a simple but effective graph-based agglomerative algorithm, for clustering high-dimensional data. We explore the different roles of two fundamental concepts in graph theory, indegree and outdegree, in the context of clustering. The ...

Wei Zhang; Xiaogang Wang; Deli Zhao; Xiaoou Tang

2012-10-01T23:59:59.000Z

36

Kinetic Pie Delaunay Graph and Its Applications  

Science Journals Connector (OSTI)

We construct a new proximity graph, called the Pie Delaunay graph, on a set of n points which is a super graph of Yao graph and Euclidean minimum spanning tree (EMST). We efficiently maintain the Pie

Mohammad Ali Abam; Zahed Rahmati; Alireza Zarei

2012-01-01T23:59:59.000Z

37

Natural Gas Monthly (NGM) - Energy Information Administration - November  

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

SEE CURRENT NATURAL GAS MONTHLY UPDATE SEE CURRENT NATURAL GAS MONTHLY UPDATE Natural Gas Monthly Data for September 2013 | Release Date: December 12, 2013 | Next Release: January 7, 2014 | full report  | Previous Issues Month: October 2013 September 2013 August 2013 July 2013 June 2013 May 2013 April 2013 March 2013 February 2013 January 2013 December 2012 November 2012 October 2012 September 2012 prior issues Go Table of Contentsall tables Tables 1 Summary of Natural Gas Supply and Disposition in the United States, 2008-2013 XLS PDF CSV 2 Natural Gas Consumption in the United States, 2008-2013 XLS PDF CSV 3 Selected National Average Natural Gas Prices, 2008-2013 XLS PDF CSV 4 U.S. Natural Gas Imports, 2011-2013 XLS PDF CSV 5 U.S. Natural Gas Exports, 2011-2013 XLS PDF CSV

38

Densities in graphs and matroids  

E-Print Network [OSTI]

|E(H)| |V (H)|?1 ? |E(T)| |V (T)|?1 = 1 for all non-trivial subgraphs of T. In general, a balanced graph G is a graph such that |E(H)| |V (H)| ? |E(G)| |V (G)| and a 1-balanced graph is a graph such that |E(H)| |V (H)|?1 ? |E(G)| |V (G)|?1 for all non...

Kannan, Lavanya

2009-05-15T23:59:59.000Z

39

Exploring the role of graph spectra in graph coloring algorithm performance  

Science Journals Connector (OSTI)

This paper considers the challenge of recognizing how the properties of a graph determine the performance of graph coloring algorithms. In particular, we examine how spectral properties of the graph make the graph coloring task easy or hard. We address ... Keywords: Algorithm selection, Branch and bound, DSATUR, Graph coloring, Graph invariants, Graph spectra, LP-relaxation

Kate Smith-Miles, Davaatseren Baatar

2014-10-01T23:59:59.000Z

40

Exact algorithm for graph homomorphism and locally injective graph homomorphism  

Science Journals Connector (OSTI)

For graphs G and H, a homomorphism from G to H is a function @f:V(G)->V(H), which maps vertices adjacent in G to adjacent vertices of H. A homomorphism is locally injective if no two vertices with a common neighbor are mapped to a single vertex in H. ... Keywords: Exact algorithm, Graph algorithms, Graph homomorphism, H(2,1)-labeling, Locally injective homomorphism

Pawe? Rzewski

2014-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Extremal Graph Numbers of Graphs on Few May 4, 2012  

E-Print Network [OSTI]

Extremal Graph Numbers of Graphs on Few Vertices John Kim May 4, 2012 1 Introduction Let H this number to be the extremal graph number of H on n vertices, and we denote it by ex(n, H). When H(n, K3) n 2 2 . A precise formula for ex(n, K3) is given by: ex(n, K3) = n 2 n + 1 2 . The extremal

Zeilberger, Doron

42

Monthly Energy Review - June 2008  

Gasoline and Diesel Fuel Update (EIA)

Monthly Publications: Other monthly EIA reports are Petroleum Supply Monthly Publications: Other monthly EIA reports are Petroleum Supply Monthly, Petroleum Marketing Monthly, Natural Gas Monthly, Electric Power Monthly, and Inter- national Petroleum Monthly. For more information, contact the National Energy Information Center at 202-586-8800 or InfoCtr@eia.doe.gov. Electronic Access The MER is available on EIA's Web site in a variety of formats at: http://www.eia.doe.gov/mer. Complete MER, and individual MER sections: Portable Document Format (PDF) files. Individual table and graph pages: PDF files. Data files for individual tables: Excel (XLS) files and ASCII comma-delimited (CSV) files. Note: PDF files display selected annual and monthly data. Excel and CSV files display all avail- able annual and monthly data, often at a greater level of precision than the PDF files.

43

How to Resum Feynman Graphs  

E-Print Network [OSTI]

In this paper we reformulate in a simpler way the combinatoric core of constructive quantum field theory We define universal rational combinatoric weights for pairs made of a graph and one of its spanning trees. These weights are nothing but the percentage of Hepp's sectors in which the tree is leading the ultraviolet analysis. We explain how they allow to reshuffle the divergent series formulated in terms of Feynman graphs into convergent series indexed by the trees that these graphs contain. The Feynman graphs to be used are not the ordinary ones but those of the intermediate field representation, and the result of the reshuffling is called the Loop Vertex Expansion.

Vincent Rivasseau; Zhituo Wang

2013-09-24T23:59:59.000Z

44

Fast iterative graph computation with block updates  

Science Journals Connector (OSTI)

Scaling iterative graph processing applications to large graphs is an important problem. Performance is critical, as data scientists need to execute graph programs many times with varying parameters. The need for a high-level, high-performance programming ...

Wenlei Xie; Guozhang Wang; David Bindel; Alan Demers; Johannes Gehrke

2013-09-01T23:59:59.000Z

45

L21: "Irregular" Graph Algorithms  

E-Print Network [OSTI]

11/11/10 1 L21: "Irregular" Graph Algorithms November 11, 2010 Administrative ·Class cancelled Monday, November 22, 11:59 PM Today we will cover Successive Over Relaxation. Here is the sequential code ·Irregular parallel computation - Sparse matrix operations (last time) and graph algorithms (this time

Hall, Mary W.

46

Phylogenetic Toric Varieties on Graphs  

E-Print Network [OSTI]

We define the phylogenetic model of a trivalent graph as a generalization of a binary symmetric model of a trivalent phylogenetic tree. If the underlining graph is a tree, the model has a parametrization that can be expressed in terms of the tree...

Buczynska, Weronika J.

2010-10-12T23:59:59.000Z

47

Contraction semigroups on metric graphs  

E-Print Network [OSTI]

The main objective of the present work is to study contraction semigroups generated by Laplace operators on metric graphs, which are not necessarily self-adjoint. We prove criteria for such semigroups to be continuity and positivity preserving. Also we provide a characterization of generators of Feller semigroups on metric graphs.

Vadim Kostrykin; Jurgen Potthoff; Robert Schrader

2008-02-26T23:59:59.000Z

48

Contractions of planar graphs in polynomial time?  

E-Print Network [OSTI]

Contractions of planar graphs in polynomial time? Marcin Kami´nski??1 , Dani¨el Paulusma2 that for every graph H, there exists a polyno- mial-time algorithm deciding if a planar graph can be contracted to H. We introduce contractions and topological minors of embedded (plane) graphs and show that a plane

Dimitrios, Thilikos

49

Some Remarks on Definability of Process Graphs  

E-Print Network [OSTI]

them in the context of the well- known process algebras BPA and BPP. For a process graph G, the density going from s to infinity" exist in G. For BPA-graphs we discuss some tentative findings about-definability results, stating that certain process graphs are not BPA-graphs, and stronger, not even BPA

Klop, Jan Willem

50

Extremal Graph Problems, Degenerate Extremal Problems,  

E-Print Network [OSTI]

Extremal Graph Problems, Degenerate Extremal Problems, and Supersaturated Graphs Mikl´os Simonovits´an-type extremal problem. The graphs attaining the maximum will be called extremal and their family will be denoted and multi- ple edges. In 1940, P. Tur´an posed and solved the extremal problem of Kp+1, the complete graph

Simonovits, Miklós

51

CP(Graph): Introducing a Graph Computation Domain in Constraint Programming  

E-Print Network [OSTI]

CP(Graph): Introducing a Graph Computation Domain in Constraint Programming Gregoire Dooms, Yves constraint programming by introducing CP(Graph), a new computation domain focused on graphs including a new and its associated propagator are sketched. CP(Graph) is in- tegrated with finite domain and finite sets

Deville, Yves

52

Transforming a graph into a 1-balanced graph  

Science Journals Connector (OSTI)

Let G be a non-trivial, loopless graph and for each non-trivial subgraph H of G, let g(H)=|E(H)||V(H)|-@w(H). The graph G is 1-balanced if @c(G), the maximum among g(H), taken over all non-trivial subgraphs H of G, is attained when H=G. This quantity ... Keywords: Fractional arboricity, Molecular, Strongly balanced, Uniformly dense

Lavanya Kannan; Arthur Hobbs; Hong-Jian Lai; Hongyuan Lai

2009-01-01T23:59:59.000Z

53

Standards for graph algorithm primitives  

E-Print Network [OSTI]

It is our view that the state of the art in constructing a large collection of graph algorithms in terms of linear algebraic operations is mature enough to support the emergence of a standard set of primitive building ...

Mattson, Tim

54

Graph anomalies in cyber communications  

SciTech Connect (OSTI)

Enterprises monitor cyber traffic for viruses, intruders and stolen information. Detection methods look for known signatures of malicious traffic or search for anomalies with respect to a nominal reference model. Traditional anomaly detection focuses on aggregate traffic at central nodes or on user-level monitoring. More recently, however, traffic is being viewed more holistically as a dynamic communication graph. Attention to the graph nature of the traffic has expanded the types of anomalies that are being sought. We give an overview of several cyber data streams collected at Los Alamos National Laboratory and discuss current work in modeling the graph dynamics of traffic over the network. We consider global properties and local properties within the communication graph. A method for monitoring relative entropy on multiple correlated properties is discussed in detail.

Vander Wiel, Scott A [Los Alamos National Laboratory; Storlie, Curtis B [Los Alamos National Laboratory; Sandine, Gary [Los Alamos National Laboratory; Hagberg, Aric A [Los Alamos National Laboratory; Fisk, Michael [Los Alamos National Laboratory

2011-01-11T23:59:59.000Z

55

Are Pixel Graphs Are Better at Representing Information than Pie Graphs?  

Science Journals Connector (OSTI)

This study investigates whether pixel graphs more accurately represent percentage based data than pie graphs or bar graphs. Participants were asked ... representing large quantities of percentage based data than

Jolie Bell; Jim Davies

2010-01-01T23:59:59.000Z

56

Multilevel spectral clustering : graph partitions and image segmentation  

E-Print Network [OSTI]

While the spectral graph partitioning method gives high quality segmentation, segmenting large graphs by the spectral method is computationally expensive. Numerous multilevel graph partitioning algorithms are proposed to ...

Kong, Tian Fook

2008-01-01T23:59:59.000Z

57

Petroleum Supply Annual 2005, Volume 1  

Gasoline and Diesel Fuel Update (EIA)

Tables National Statistics 1 U.S. Supply, Disposition, and Ending Stocks of Crude Oil and Petroleum Products PDF CSV XLS 2 U.S. Daily Average Supply and Disposition of...

58

Algebraic connectivity and graph robustness.  

SciTech Connect (OSTI)

Recent papers have used Fiedler's definition of algebraic connectivity to show that network robustness, as measured by node-connectivity and edge-connectivity, can be increased by increasing the algebraic connectivity of the network. By the definition of algebraic connectivity, the second smallest eigenvalue of the graph Laplacian is a lower bound on the node-connectivity. In this paper we show that for circular random lattice graphs and mesh graphs algebraic connectivity is a conservative lower bound, and that increases in algebraic connectivity actually correspond to a decrease in node-connectivity. This means that the networks are actually less robust with respect to node-connectivity as the algebraic connectivity increases. However, an increase in algebraic connectivity seems to correlate well with a decrease in the characteristic path length of these networks - which would result in quicker communication through the network. Applications of these results are then discussed for perimeter security.

Feddema, John Todd; Byrne, Raymond Harry; Abdallah, Chaouki T. (University of New Mexico)

2009-07-01T23:59:59.000Z

59

SLQ: a user-friendly graph querying system  

Science Journals Connector (OSTI)

Querying complex graph databases such as knowledge graphs is a challenging task for non-professional users. In this demo, we present SLQ, a user-friendly graph querying system enabling schemales and structures graph querying, where a user need not describe ... Keywords: graph databases, keyword query, schemaless graph querying

Shengqi Yang; Yanan Xie; Yinghui Wu; Tianyu Wu; Huan Sun; Jian Wu; Xifeng Yan

2014-06-01T23:59:59.000Z

60

NLS ground states on graphs  

E-Print Network [OSTI]

We investigate the existence of ground states for the subcritical NLS energy on metric graphs. In particular, we find out a topological assumption that guarantees the nonexistence of ground states, and give an example in which the assumption is not fulfilled and ground states actually exist. In order to obtain the result, we introduce a new rearrangement technique, adapted to the graph where it applies. Owing to such a technique, the energy level of the rearranged function is improved by conveniently mixing the symmetric and monotone rearrangement procedures.

Riccardo Adami; Enrico Serra; Paolo Tilli

2014-06-16T23:59:59.000Z

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

On Edge Szeged Index of Bridge Graphs  

Science Journals Connector (OSTI)

Corollary 2. Let H be any graph with fixed vertex $$ v $$ .... Then the edge Szeged index of the bridge

Fuqin Zhan; Youfu Qiao

2013-01-01T23:59:59.000Z

62

A heuristic algorithm for graph isomorphism  

E-Print Network [OSTI]

polynomial time algorithm O(n?), ISO-MT, that seems' to solve the graph isomorphism decision problem correctly for all classes of graphs. Our algorithm is extremely useful from the practical point of view since counter examples (pairs of graphs for which our...

Torres Navarro, Luz

1999-01-01T23:59:59.000Z

63

Hybrid motion graph for character motion synthesis  

Science Journals Connector (OSTI)

Objective: This paper proposes a novel framework of Hybrid Motion Graph (HMG) for creating character animations, which enhances the graph-based structural control by motion field representations for efficient motion synthesis of diverse and interactive ... Keywords: Motion fields, Motion graph, Motion synthesis, Motion template, Motion transition

Weiwei Xing; Xiang Wei; Jian Zhang; Cheng Ren; Wei Lu

2014-02-01T23:59:59.000Z

64

THE TUKEY ORDER FOR GRAPHS 1. Introduction  

E-Print Network [OSTI]

THE TUKEY ORDER FOR GRAPHS 1. Introduction Given a graph G, we let VG stand for the vertex set of G. For graphs G without isolated vertices, the Tukey order can be characterized thus: () G H iff there exist) is called a (generalized) Galois-Tukey connection (abbreviated GT-connection) from R to S if the following

Nyikos, Peter J.

65

Constrained Graph Optimization: Interdiction and Preservation Problems  

SciTech Connect (OSTI)

The maximum flow, shortest path, and maximum matching problems are a set of basic graph problems that are critical in theoretical computer science and applications. Constrained graph optimization, a variation of these basic graph problems involving modification of the underlying graph, is equally important but sometimes significantly harder. In particular, one can explore these optimization problems with additional cost constraints. In the preservation case, the optimizer has a budget to preserve vertices or edges of a graph, preventing them from being deleted. The optimizer wants to find the best set of preserved edges/vertices in which the cost constraints are satisfied and the basic graph problems are optimized. For example, in shortest path preservation, the optimizer wants to find a set of edges/vertices within which the shortest path between two predetermined points is smallest. In interdiction problems, one deletes vertices or edges from the graph with a particular cost in order to impede the basic graph problems as much as possible (for example, delete edges/vertices to maximize the shortest path between two predetermined vertices). Applications of preservation problems include optimal road maintenance, power grid maintenance, and job scheduling, while interdiction problems are related to drug trafficking prevention, network stability assessment, and counterterrorism. Computational hardness results are presented, along with heuristic methods for approximating solutions to the matching interdiction problem. Also, efficient algorithms are presented for special cases of graphs, including on planar graphs. The graphs in many of the listed applications are planar, so these algorithms have important practical implications.

Schild, Aaron V [Los Alamos National Laboratory

2012-07-30T23:59:59.000Z

66

Security of graph data: hashing schemes and definitions  

Science Journals Connector (OSTI)

Use of graph-structured data models is on the rise - in graph databases, in representing biological and healthcare data as well as geographical data. In order to secure graph-structured data, and develop cryptographically secure schemes for graph databases, ... Keywords: graphs, hash functions, integrity, perfectly secure hash functions, privacy

Muhammad U. Arshad, Ashish Kundu, Elisa Bertino, Krishna Madhavan, Arif Ghafoor

2014-03-01T23:59:59.000Z

67

Locating-total domination in graphs  

Science Journals Connector (OSTI)

In this paper, we continue the study of locating-total domination in graphs. A set S of vertices in a graph G is a total dominating set in G if every vertex of G is adjacent to a vertex in S . We consider total dominating sets S which have the additional property that distinct vertices in V ( G ) ? S are totally dominated by distinct subsets of the total dominating set. Such a set S is called a locating-total dominating set in G , and the locating-total domination number of G is the minimum cardinality of a locating-total dominating set in G . We obtain new lower and upper bounds on the locating-total domination number of a graph. Interpolation results are established, and the locating-total domination number in special families of graphs, including cubic graphs and grid graphs, is investigated.

Michael A. Henning; Nader Jafari Rad

2012-01-01T23:59:59.000Z

68

API Requirements for Dynamic Graph Prediction  

SciTech Connect (OSTI)

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.

Gallagher, B; Eliassi-Rad, T

2006-10-13T23:59:59.000Z

69

To make a circle graph (pie graph) in Excel 2010 1. Enter the data ...  

E-Print Network [OSTI]

To make a circle graph (pie graph) in Excel 2010. 1. Enter the data into Excel in rows, with the data labels followed by the numerical data. 2. Select all cells that...

Dave

2012-03-20T23:59:59.000Z

70

On real number labelings and graph invertibility  

Science Journals Connector (OSTI)

For non-negative real x"0 and simple graph G, @l"x"""0","1(G) is the minimum span over all labelings that assign real numbers to the vertices of G such that adjacent vertices receive labels that differ by at least x"0 and vertices at distance two receive ... Keywords: ?-invertible, ?j,k-labeling, ?x,1-labeling, Distance-constrained labeling, Kneser graphs, Self-complementary graphs

Jeong-Ok Choi; John Georges; David Mauro; Yan Wang

2012-10-01T23:59:59.000Z

71

Some algorithmic results in graph imbeddings  

E-Print Network [OSTI]

new technique called double bar amalgamation is developed. The second problem deals with constructing graph imbeddings on a sur- face of genus c (where c is an integer) less than the marimum genus 7, (G) the given graph G. We develop a polynomial... time algorithm that constructs an imbedding of a given upper imbbedable graph G with even Betti number, on an orientable surface of genus (7, (G) ? 1). TABLE OF CONTENTS CHAPTER Page I INTRODUCTION 1. 1 Overview 1. 2 Graphs and Relationships Used...

Joshi, Sanjay

1990-01-01T23:59:59.000Z

72

Generating Reports & Graphs in Portfolio Manager  

Broader source: Energy.gov [DOE]

This presentation, given through the DOE's Technical Assitance Program (TAP), provides information on how to generate reports and graphs in Portfolio Manager.

73

Nuclear reactor multiphysics via bond graph formalism  

E-Print Network [OSTI]

This work proposes a simple and effective approach to modeling nuclear reactor multiphysics problems using bond graphs. Conventional multiphysics simulation paradigms normally use operator splitting, which treats the ...

Sosnovsky, Eugeny

2014-01-01T23:59:59.000Z

74

Hamilton Decompositions of Graphs with Primitive Complements .  

E-Print Network [OSTI]

??A graph G is a pair (V, E) where V is the set of vertices(or nodes) and E is the set of edges connecting the (more)

OZKAN, SIBEL

2007-01-01T23:59:59.000Z

75

Generation of graph-state streams  

E-Print Network [OSTI]

We propose a protocol to generate a stream of mobile qubits in a graph state through a single stationary parent qubit and discuss two types of its physical implementation, namely, the generation of photonic graph states through an atom-like qubit and those of flying atoms through a cavity-mode photonic qubit. The generated graph states fall into an important class that can hugely reduce the resource requirement of fault-tolerant linear optics quantum computation, which was previously known to be far from realistic. In regard to the flying atoms, we also propose a heralded generation scheme, which allows for high-fidelity graph states even under the photon loss.

Daniel Ballester; Jaeyoon Cho; M. S. Kim

2010-12-08T23:59:59.000Z

76

On Products and Line Graphs of Signed Graphs, their Eigenvalues and Energy  

E-Print Network [OSTI]

On Products and Line Graphs of Signed Graphs, their Eigenvalues and Energy K.A. Germina, Shahul and Laplacian matrices and their eigenvalues and energies of the general product (non-complete extended p- sum product and the eigenvalues and energy of the product in terms of those of the factor graphs

Zaslavsky, Thomas

77

3D Graph Visualization with the Oculus Rift Virtual Graph Reality  

E-Print Network [OSTI]

3D Graph Visualization with the Oculus Rift Virtual Graph Reality Farshad Barahimi, Stephen Wismath regarding three- dimensional (3D) representations of graphs. However, the actual usefulness of such 3D reality environment such as a CAVE, or · printed as a physical model with a 3D printer. Early studies

Wismath, Stephen

78

Graph-Theoretic Generation of Assembly Plans Part I: Correct Generation of Precedence Graphs  

E-Print Network [OSTI]

1 Graph-Theoretic Generation of Assembly Plans Part I: Correct Generation of Precedence Graphs Lehigh University Bethlehem, Pennsylvania Abstract Automatic generation and selection of assembly plans a graph-theoretic scheme for the generation of assembly plans. Our scheme involves decomposing the CSP

Wu, David

79

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

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

Ion Beams Available Beams Beam Change Times Measurements Useful Graphs Useful Graphs and Charts LET vs. Range in Si Graphs: 15 MeVu Beams 24.8 MeVu Beams 40 MeVu Beams...

80

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

National Nuclear Security Administration (NNSA)

on Graph 500 and new techniques for solving large graph problems on small high performance computing (HPC) systems, all the way down to a single server. Lawrence Livermore's...

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

LD-graphs and global location-domination in bipartite graphs  

Science Journals Connector (OSTI)

Abstract A dominating set S of a graph G is a locating-dominating-set, LD-set for short, if every vertex v not in S is uniquely determined by the set of neighbors of v belonging to S. Locating-dominating sets of minimum cardinality are called LD-codes and the cardinality of an LD-code is the location-domination number, ? ( G ) . An LD-set S of a graph G is global if it is an LD-set for both G and its complement, G . One of the main contributions of this work is the definition of the LD-graph, an edge-labeled graph associated to an LD-set, that will be very helpful to deduce some properties of location-domination in graphs. Concretely, we use LD-graphs to study the relation between the location-domination number in a bipartite graph and its complement.

C. Hernando; M. Mora; I.M. Pelayo

2014-01-01T23:59:59.000Z

82

Fuzzy Mathematics Fuzzy -Sets, -Relations, -Logic, -Graphs,  

E-Print Network [OSTI]

Fuzzy Mathematics Fuzzy -Sets, -Relations, -Logic, -Graphs, -Mappings and The Extension Principle . . . . . . . . . . . . . . . . . . 8 2 The Extension Principle 10 3 Fuzzy Graphs 16 4 Fuzzy Logic 19 Back View #12;Section 1: Fuzzy Olaf Wolkenhauer Control Systems Centre UMIST o.wolkenhauer@umist.ac.uk www

Rostock, Universität

83

Extremal optimization for graph partitioning Stefan Boettcher*  

E-Print Network [OSTI]

­4 and of fast-folding protein confor- mations 5 are but two examples. In cases where the relation between-temperature properties of disordered systems. In the present work we focus on the intrinsic features of the method on the graph bipartitioning problem. We consider various kinds of graph ensembles, both with geometric

Percus, Allon

84

Graph searching and a generalized parking function  

E-Print Network [OSTI]

introduced a new generalization, the G-multiparking function, where G is a simple graph on a totally ordered vertex set {1, 2, . . . , n}. We give an algorithm that converts a G-multiparking function into a rooted spanning forest of G by using a graph...

Kostic, Dimitrije Nenad

2009-05-15T23:59:59.000Z

85

Feature Tracking Using Reeb Graphs  

SciTech Connect (OSTI)

Tracking features and exploring their temporal dynamics can aid scientists in identifying interesting time intervals in a simulation and serve as basis for performing quantitative analyses of temporal phenomena. In this paper, we develop a novel approach for tracking subsets of isosurfaces, such as burning regions in simulated flames, which are defined as areas of high fuel consumption on a temperature isosurface. Tracking such regions as they merge and split over time can provide important insights into the impact of turbulence on the combustion process. However, the convoluted nature of the temperature isosurface and its rapid movement make this analysis particularly challenging. Our approach tracks burning regions by extracting a temperature isovolume from the four-dimensional space-time temperature field. It then obtains isosurfaces for the original simulation time steps and labels individual connected 'burning' regions based on the local fuel consumption value. Based on this information, a boundary surface between burning and non-burning regions is constructed. The Reeb graph of this boundary surface is the tracking graph for burning regions.

Weber, Gunther H.; Bremer, Peer-Timo; Day, Marcus S.; Bell, John B.; Pascucci, Valerio

2010-08-02T23:59:59.000Z

86

Path Integral on Star Graph  

E-Print Network [OSTI]

In this paper we study path integral for a single spinless particle on a star graph with N edges, whose vertex is known to be described by U(N) family of boundary conditions. After carefully studying the free particle case, both at the critical and off-critical levels, we propose a new path integral formulation that correctly captures all the scale-invariant subfamily of boundary conditions realized at fixed points of boundary renormalization group flow. Our proposal is based on the folding trick, which maps a scalar-valued wave function on star graph to an N-component vector-valued wave function on half-line. All the parameters of scale-invariant subfamily of boundary conditions are encoded into the momentum independent weight factors, which appear to be associated with the two distinct path classes on half-line that form the cyclic group Z_2. We show that, when bulk interactions are edge-independent, these weight factors are generally given by an N-dimensional unitary representation of Z_2. Generalization to momentum dependent weight factors and applications to worldline formalism are briefly discussed.

Satoshi Ohya

2011-04-28T23:59:59.000Z

87

Path Integral on Star Graph  

E-Print Network [OSTI]

In this paper we study path integral for a single spinless particle on a star graph with N edges, whose vertex is known to be described by U(N) family of boundary conditions. After carefully studying the free particle case, both at the critical and off-critical levels, we propose new path integral formulation that correctly captures all the scale-invariant subfamily of boundary conditions realized at fixed points of boundary renormalization group flow. Our proposal is based on the folding trick, which maps a scalar-valued wave function on star graph to an N-component vector-valued wave function on half-line. All the parameters of scale-invariant subfamily of boundary conditions are encoded into the momentum independent weight factors, which appear to be associated with the two distinct path classes on half-line that form the cyclic group Z_2. We show that, when bulk interactions are edge-independent, these weight factors are generally given by an N-dimensional unitary representation of Z_2. Generalization to ...

Ohya, Satoshi

2011-01-01T23:59:59.000Z

88

Approximate von Neumann entropy for directed graphs  

Science Journals Connector (OSTI)

In this paper, we develop an entropy measure for assessing the structural complexity of directed graphs. Although there are many existing alternative measures for quantifying the structural properties of undirected graphs, there are relatively few corresponding measures for directed graphs. To fill this gap in the literature, we explore an alternative technique that is applicable to directed graphs. We commence by using Chung's generalization of the Laplacian of a directed graph to extend the computation of von Neumann entropy from undirected to directed graphs. We provide a simplified form of the entropy which can be expressed in terms of simple node in-degree and out-degree statistics. Moreover, we find approximate forms of the von Neumann entropy that apply to both weakly and strongly directed graphs, and that can be used to characterize network structure. We illustrate the usefulness of these simplified entropy forms defined in this paper on both artificial and real-world data sets, including structures from protein databases and high energy physics theory citation networks.

Cheng Ye; Richard C. Wilson; Csar H. Comin; Luciano da F. Costa; Edwin R. Hancock

2014-05-12T23:59:59.000Z

89

Measuring extremal dependencies in Web graphs Yana Volkovich  

E-Print Network [OSTI]

Measuring extremal dependencies in Web graphs Yana Volkovich University of Twente P.O. Box 217 dependencies in power law graph data (Web sample, Wikipedia sample and a preferential attachment graph) using of the proposed methods have never been applied to the Web graph data. This paper fills this gap. The new insights

Boucherie, Richard J.

90

Measuring Extremal Dependencies in Web Graphs Yana Volkovich  

E-Print Network [OSTI]

Measuring Extremal Dependencies in Web Graphs Yana Volkovich University of Twente P.O. Box 217 graph data (Web sample, Wikipedia sample and a preferential attachment graph) using statistical of the proposed meth- ods have never been used in the Web graph data mining. The present work fills this gap

Boucherie, Richard J.

91

What Energy Functions Can Be Minimized via Graph Cuts?  

E-Print Network [OSTI]

What Energy Functions Can Be Minimized via Graph Cuts? Vladimir Kolmogorov, Member, IEEE, and Ramin been developed to solve energy minimization problems in computer vision. Each of these techniques constructs a graph such that the minimum cut on the graph also minimizes the energy. Yet, because these graph

Field, David

92

What Energy Functions can be Minimized via Graph Cuts?  

E-Print Network [OSTI]

What Energy Functions can be Minimized via Graph Cuts? Vladimir Kolmogorov and Ramin Zabih Computer. In the last few years, several new algorithms based on graph cuts have been developed to solve energy cut on the graph also minimizes the energy. Yet because these graph constructions are complex

Field, David

93

A Note on Hamilton Cycles in Kneser Graphs Ian Shields  

E-Print Network [OSTI]

A Note on Hamilton Cycles in Kneser Graphs Ian Shields IBM P.O. Box 12195 Research Triangle Park) have Hamilton cycles when n #20; 27. A similar result is shown for bipartite Kneser graphs. 1 for Hamilton cycles in Kneser graphs, K(n; k), and bipartite Kneser graphs, H(n; k). With the exception

Savage, Carla D.

94

Optimal acyclic edge colouring of grid like graphs  

Science Journals Connector (OSTI)

We determine the values of the acyclic chromatic index of a class of graphs referred to as d-dimensional partial tori. These are graphs which can be expressed as the cartesian product of d graphs each of which is an induced path or cycle. This class ... Keywords: Acyclic chromatic index, Acyclic edge colouring, Graph, Hypercube, Mesh

Rahul Muthu, N. Narayanan, C. R. Subramanian

2010-11-01T23:59:59.000Z

95

Discrete Mathematics Algebraic and Topological Methods in Graph Theory  

E-Print Network [OSTI]

symmetrical trivalent graphs which lead to negative currature carbon and bovon nitrie chemical structures. (D

Mohar, Bojan

96

Fibonacci-like cubes as Z-transformation graphs  

Science Journals Connector (OSTI)

The Fibonacci cube @C"n is a subgraph of n-dimensional hypercube induced by the vertices without two consecutive ones. Klavzar and Zigert [Fibonacci cubes are the resonance graphs of fibonaccenes, Fibonacci Quart. 43 (2005) 269-276] proved that Fibonacci ... Keywords: Fibonacci cube, Lucas cube, Perfect matching, Plane bipartite graph, Resonance graph, Z-transformation graph

Heping Zhang, Lifeng Ou, Haiyuan Yao

2009-04-01T23:59:59.000Z

97

Discrete Applied Mathematics 121 (2002) 139153 NeST graphs  

E-Print Network [OSTI]

Discrete Applied Mathematics 121 (2002) 139­153 NeST graphs Ryan B. Haywarda; , Paul E. Kearneyb; received in revised form 14 March 2001; accepted 26 March 2001 Abstract We establish results on NeST graphs show the equivalence of proper NeST graphs and unit NeST graphs, the equivalence of ÿxed distance NeST

Hayward, Ryan B.

98

A role for matrices in graph theory  

E-Print Network [OSTI]

A ROLE FOR MATRICES IN GRAPH THEORY A Thesis by John Patrick McLean Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE May 1971 Ma]or Subject: Mathematics... A ROLE FOR MATRICES IN GRAPH THEORY A Thesis by John Patrick McLean Approved as to style and content by: (Chairman of Committee) (Head of Department) I (Member) (Member) May 1971 tp Qey $ ABSTRACT A Role for Matrices in Graph Theory...

McLean, John Patrick

1971-01-01T23:59:59.000Z

99

3-Rainbow Domination Number in Graphs  

Science Journals Connector (OSTI)

The k-rainbow domination is a location problem in operations research. Give an undirected graph G as the natural model of location problem. We have a set of k colors and assign an arbitrary subset of these col...

Kung-Jui Pai; Wei-Jai Chiu

2013-01-01T23:59:59.000Z

100

Graph Summarization with Bounded Error Saket Navlakha  

E-Print Network [OSTI]

of Maryland College Park, MD, USA-20742 saket@cs.umd.edu Rajeev Rastogi Yahoo! Labs Bangalore, India rrastogi@yahoo-inc Graphs are a fundamental abstraction that have been em- ployed for centuries to model real-world systems

Gruner, Daniel S.

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

On semidefinite programming bounds for graph bandwidth  

E-Print Network [OSTI]

May 24, 2011 ... We propose two new lower bounds on graph bandwidth and cyclic ... matrix computations, parallel computations, VLSI layout, etc; see, for example [19]. ...... problems by SeDuMi [30] using the Yalmip interface [22] with Matlab.

2011-05-24T23:59:59.000Z

102

Graph Implementations for Nonsmooth Convex Programs  

E-Print Network [OSTI]

Summary. We describe graph implementations, a generic method for represent- ... object-oriented features of Matlab to turn it into an optimization modeling language: ..... For matrix and array expressions, these rules are applied on an elemen-.

2007-09-07T23:59:59.000Z

103

The Minimum Rank Problem for Outerplanar Graphs.  

E-Print Network [OSTI]

??Given a simple graph G with vertex set V(G)={1,2,...,n} define S(G) to be the set of all real symmetric matrices A such that for all (more)

Sinkovic, John Henry

2013-01-01T23:59:59.000Z

104

Minimum rank of graphs that allow loops.  

E-Print Network [OSTI]

??The traditional "minimum rank problem" for simple graphs associates a set of symmetric matrices, the zero-nonzero pattern of whose off-diagonal entries are described by the (more)

Mikkelson, Rana C.

2008-01-01T23:59:59.000Z

105

Bipartite graph partitioning and data clustering  

SciTech Connect (OSTI)

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.

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

2001-05-07T23:59:59.000Z

106

Hamilton Paths in Generalized Petersen Graphs.  

E-Print Network [OSTI]

??This thesis puts forward the conjecture that for n > 3k with k > 2, the generalized Petersen graph, GP(n,k) is Hamilton-laceable if n is (more)

Pensaert, William

2006-01-01T23:59:59.000Z

107

Progressive transitions using body part motion graphs  

Science Journals Connector (OSTI)

In this work we describe a preliminary method for progressive transitions in human locomotions. To achieve this, motion graphs have been used to synthesize body part transitions and every part has been synchronized with the other parts using time scaling. ...

Adso Fernndez-Baena; David Miralles

2011-12-01T23:59:59.000Z

108

A Faster Algorithm for Computing Motorcycle Graphs  

Science Journals Connector (OSTI)

We present a new algorithm for computing motorcycle graphs that runs in $$O(n^{4/3+\\varepsilon })$$O(n4/3+) time for any $$\\varepsilon >0$$>0, improving on all previously known algorithms. The main application of this result is to computing the straight ... Keywords: 65D18, 68Q25, 68U05, Algorithms design and analysis, Medial axis, Motorcycle graph, Polygon, Straight skeleton

Antoine Vigneron, Lie Yan

2014-10-01T23:59:59.000Z

109

About equivalent interval colorings of weighted graphs  

Science Journals Connector (OSTI)

Given a graph G=(V,E) with strictly positive integer weights @w"i on the vertices i@?V, a k-interval coloring of G is a function I that assigns an interval I(i)@?{1,...,k} of @w"i consecutive integers (called colors) to each vertex i@?V. If two adjacent ... Keywords: Equivalent colorings, Interval coloring problem, Weighted graphs

Mathieu Bouchard; Mirjana angalovi?; Alain Hertz

2009-10-01T23:59:59.000Z

110

Accelerating semantic graph databases on commodity clusters  

SciTech Connect (OSTI)

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.

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

2013-10-06T23:59:59.000Z

111

Monthly Energy Review - January 2007  

Gasoline and Diesel Fuel Update (EIA)

publications: Other monthly EIA reports are Petroleum Supply Monthly, Petroleum publications: Other monthly EIA reports are Petroleum Supply Monthly, Petroleum Marketing Monthly, Natural Gas Monthly, Electric Power Monthly, and International Petroleum Monthly. Readers of the MER may also be interested in EIA's Annual Energy Review, where many of the same data series are provided annually beginning with 1949. For more information, contact the National Energy Information Center at 202-586-8800 or InfoCtr@eia.doe.gov. Electronic Access The MER is available on EIA's Web site in a variety of formats at: http://www.eia.doe.gov/mer. Complete MER, and individual MER sections: Portable Document Format (PDF) files. Individual table and graph pages: PDF files. Data files for individual tables: Excel (XLS) files and ASCII comma-delimited (CSV) files.

112

Graph representation of protein free energy landscape  

SciTech Connect (OSTI)

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.

Li, Minghai; Duan, Mojie; Fan, Jue; Huo, Shuanghong, E-mail: shuo@clarku.edu [Gustaf H. Carlson School of Chemistry and Biochemistry, Clark University, 950 Main Street, Worcester, Massachusetts 01610 (United States)] [Gustaf H. Carlson School of Chemistry and Biochemistry, Clark University, 950 Main Street, Worcester, Massachusetts 01610 (United States); Han, Li [Department of Mathematics and Computer Science, Clark University, 950 Main Street, Worcester, Massachusetts 01610 (United States)] [Department of Mathematics and Computer Science, Clark University, 950 Main Street, Worcester, Massachusetts 01610 (United States)

2013-11-14T23:59:59.000Z

113

table10.xls  

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

1,112 1,079 1,014 979 1,067 1,143 Household Characteristics Census Region and Division Northeast........................... 1,044 972 917 886 982 1,027 New England....................... 1,019 972 942 911 1,006 1,086 Middle Atlantic .................. 1,054 971 909 877 973 1,001 Midwest ............................ 1,104 1,070 1,016 1,008 1,104 1,176 East North Central................ 1,082 1,025 996 1,008 1,102 1,164 West North Central ............... 1,149 1,163 1,062 1,008 1,110 1,205 South............................... 1,178 1,137 1,046 1,008 1,109 1,193 South Atlantic.................... 1,177 1,099 1,028 963 1,111 1,146 East South Central................ 1,160 1,164 1,036 1,083 1,167 1,273 West South Central................ 1,192 1,185 1,081 1,033 1,073 1,244 West................................

114

b28.xls  

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

4,645 4,645 3,982 1,258 1,999 282 63 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 2,100 699 955 171 Q 5,001 to 10,000 ................................. 889 782 233 409 58 Q 10,001 to 25,000 ............................... 738 659 211 372 32 Q 25,001 to 50,000 ............................... 241 225 63 140 8 9 50,001 to 100,000 ............................. 129 123 32 73 6 8 100,001 to 200,000 ........................... 65 62 15 33 Q 9 200,001 to 500,000 ........................... 25 24 5 13 Q 4 Over 500,000 .................................... 7 6 1 3 Q 2 Principal Building Activity Education .......................................... 386 382 141 172 14 24 Food Sales ....................................... 226 188 94 68 Q N Food Service ..................................... 297 282

115

b16.xls  

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

64,783 64,783 15,492 6,166 7,803 10,989 7,934 6,871 9,528 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 4,659 1,264 689 155 Q Q N 5,001 to 10,000 ................................. 6,585 3,323 1,373 1,109 689 Q Q N 10,001 to 25,000 ............................... 11,535 4,006 2,075 2,456 2,113 692 Q N 25,001 to 50,000 ............................... 8,668 1,222 836 1,327 2,920 1,648 667 Q 50,001 to 100,000 ............................. 9,057 704 291 1,157 2,865 2,151 1,518 371 100,001 to 200,000 ........................... 9,064 804 Q Q 1,558 2,014 2,455 1,452 200,001 to 500,000 ........................... 7,176 Q Q Q 533 1,077 1,706 2,571 Over 500,000 .................................... 5,908 Q N N Q Q Q 5,087 Principal Building Activity Education ..........................................

116

b4.xls  

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

East East South Central West South Central Mountain Pacific All Buildings* .................................. 4,645 233 493 696 571 874 348 553 299 580 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 127 237 369 356 457 215 294 165 333 5,001 to 10,000 ................................. 889 48 101 117 97 189 56 116 56 110 10,001 to 25,000 ............................... 738 37 90 122 75 139 51 88 54 81 25,001 to 50,000 ............................... 241 10 26 44 27 47 15 26 14 32 50,001 to 100,000 ............................. 129 7 21 24 10 21 10 18 5 13 100,001 to 200,000 ........................... 65 3 12 12 5 16 Q 8 Q 6 200,001 to 500,000 ........................... 25 Q 6 6 1 4 Q 2 1 3 Over 500,000 .................................... 7 Q 1 1 Q 1 Q Q Q 1 Principal Building Activity Education ..........................................

117

table13.xls  

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

736 736 722 550 650 668 787 Household Characteristics Census Region and Division Northeast............................................................... 731 NA 532 660 647 766 New England........................................................ 706 NA 526 687 637 810 Middle Atlantic ..................................................... 740 NA 534 651 651 746 Midwest ................................................................. 738 NA 539 651 644 793 East North Central............................................... 751 NA 539 650 639 792 West North Central ............................................. 714 NA 538 654 656 793 South..................................................................... 758 NA 575 663 673 776 South Atlantic.......................................................

118

b23.xls  

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

64,783 64,783 63,343 63,307 43,468 15,157 5,443 2,853 7,076 1,401 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 6,362 6,346 3,084 600 Q Q 806 199 5,001 to 10,000 ................................. 6,585 6,212 6,197 3,692 716 Q Q 725 Q 10,001 to 25,000 ............................... 11,535 11,370 11,370 7,053 966 289 Q 1,014 Q 25,001 to 50,000 ............................... 8,668 8,385 8,385 6,025 825 369 240 638 Q 50,001 to 100,000 ............................. 9,057 9,031 9,031 6,683 1,740 574 332 925 Q 100,001 to 200,000 ........................... 9,064 9,018 9,018 6,645 2,927 1,399 793 989 Q 200,001 to 500,000 ........................... 7,176 7,056 7,051 5,679 3,400 1,018 495 1,165 Q Over 500,000 .................................... 5,908 5,908 5,908 4,606 3,981 1,693 822 Q Q Principal Building Activity

119

b41.xls  

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

64,783 64,783 56,940 11,035 9,041 12,558 2,853 11,636 29,969 1,561 1,232 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 5,007 1,568 675 972 Q Q 1,957 179 Q 5,001 to 10,000 ................................. 6,585 5,408 1,523 563 1,012 Q Q 2,741 207 Q 10,001 to 25,000 ............................... 11,535 9,922 2,173 1,441 1,740 Q 456 5,260 378 Q 25,001 to 50,000 ............................... 8,668 7,776 1,683 1,155 2,301 240 729 4,264 Q Q 50,001 to 100,000 ............................. 9,057 8,331 1,388 1,440 1,958 332 1,722 4,732 Q Q 100,001 to 200,000 ........................... 9,064 8,339 993 1,158 2,259 793 2,366 4,504 Q Q 200,001 to 500,000 ........................... 7,176 6,565 1,136 1,273 1,223 495 3,023 3,834 Q Q Over 500,000 .................................... 5,908 5,591 569 1,334 1,095

120

a2.xls  

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

North North east Mid- west South West All Buildings North- east Mid- west South West All Buildings .................................... 4,859 761 1,305 1,873 920 71,658 13,995 18,103 26,739 12,820 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,586 374 728 985 499 6,922 1,059 1,908 2,618 1,337 5,001 to 10,000 ................................. 948 155 228 386 179 7,033 1,169 1,676 2,844 1,343 10,001 to 25,000 ............................... 810 138 211 308 152 12,659 2,122 3,317 4,859 2,361 25,001 to 50,000 ............................... 261 39 75 96 50 9,382 1,388 2,712 3,474 1,808 50,001 to 100,000 ............................. 147 31 35 58 22 10,291 2,272 2,376 4,059 1,584 100,001 to 200,000 ........................... 74 15 18 30 10 10,217 2,238 2,486 4,140 1,353 200,001 to 500,000 ...........................

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

table6.xls  

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

.4 .4 9.9 10.2 10.6 11.4 12.0 Household Characteristics Census Region and Division Northeast............................................................... 9.5 NA 10.3 10.9 11.3 11.9 New England........................................................ 9.6 NA 10.2 11.4 11.1 12.3 Middle Atlantic ..................................................... 9.5 NA 10.3 10.8 11.3 11.7 Midwest ................................................................. 9.2 NA 10.0 10.5 11.6 11.9 East North Central............................................... 9.3 NA 10.1 10.7 11.6 11.9 West North Central ............................................. 8.8 NA 9.8 10.0 11.8 11.9 South..................................................................... 9.7 NA 10.6 10.8 11.7 12.4 South Atlantic.......................................................

122

b11.xls  

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

Lodging Lodging Retail (Other Than Mall) Table B11. Selected Principal Building Activity: Part 1, Number of Buildings for Non- Mall Buildings, 2003 Principal Building Activity Number of Buildings (thousand) Health Care All Buildings* Education Food Sales Food Service Energy Information Administration 2003 Commercial Buildings Energy Consumption Survey: Building Characteristics Tables Released: June 2006 Next CBECS will be conducted in 2007 Inpatient Outpatient All Buildings* .................................. 4,645 386 226 297 8 121 142 443 Lodging Retail (Other Than Mall) Table B11. Selected Principal Building Activity: Part 1, Number of Buildings for Non- Mall Buildings, 2003 Principal Building Activity Number of Buildings (thousand) Health Care All Buildings* Education Food Sales Food

123

a6.xls  

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

71,658 71,658 6,922 7,033 12,659 9,382 10,291 10,217 7,494 7,660 Principal Building Activity Education .......................................... 9,874 409 399 931 1,756 2,690 2,167 1,420 Q Food Sales ....................................... 1,255 409 356 Q Q Q Q N N Food Service ..................................... 1,654 544 442 345 Q Q N Q N Health Care ....................................... 3,163 165 280 313 157 364 395 514 973 Inpatient .......................................... 1,905 N N Q Q Q Q 467 973 Outpatient ....................................... 1,258 165 280 312 Q 206 Q Q N Lodging ............................................. 5,096 99 160 631 803 841 930 1,185 Q Mercantile ......................................... 11,192 771 1,173 2,409 1,291 1,505 1,677 462 1,905 Retail (Other Than Mall) .................. 4,317 638

124

b34.xls  

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

Revised June 2006 Revised June 2006 178 Released: Dec 2006 Next CBECS will be conducted in 2007 All Build- ings* Not Heated 1 to 50 Percent Heated 51 to 99 Percent Heated 100 Percent Heated All Build- ings* Not Heated 1 to 50 Percent Heated 51 to 99 Percent Heated 100 Percent Heated All Buildings* .................................. 4,645 663 523 498 2,962 64,783 4,756 6,850 8,107 45,071 Table B34. Percent of Floorspace Heated, Number of Buildings and Floorspace for Non- Mall Buildings, 2003 Number of Buildings (thousand) Total Floorspace (million square feet) Number of Floors One ................................................... 3,136 570 353 292 1,921 25,981 3,237 3,336 2,534 16,875 Two ................................................... 1,031 70 135 111 714 16,270 862 2,027 1,643 11,739 Three ................................................

125

c5.xls  

Gasoline and Diesel Fuel Update (EIA)

71 71 1,690 1,948 911 12,905 17,080 23,489 11,310 98.5 98.9 82.9 80.6 Building Floorspace (Square Feet) 1,001 to 5,000 ................................. 118 206 240 108 1,025 1,895 2,533 1,336 115.1 108.5 94.9 80.6 5,001 to 10,000 ............................... 102 117 185 112 1,123 1,565 2,658 1,239 90.7 74.7 69.5 90.8 10,001 to 25,000 ............................. 148 228 250 150 1,972 3,098 4,378 2,087 75.3 73.6 57.2 71.7 25,001 to 50,000 ............................. 106 247 205 114 1,292 2,567 3,168 1,643 82.4 96.3 64.8 69.4 50,001 to 100,000 ........................... 203 212 255 89 2,040 2,260 3,435 1,322 99.4 93.6 74.3 67.6 100,001 to 200,000 ......................... 209 252 375 97 2,117 2,296 3,475 1,177 98.8 109.8 107.9 82.7 200,001 to 500,000 ......................... 189 244 191 100 1,781 2,196 1,914 1,286 106.3 111.1 99.9 78.1 Over 500,000 ..................................

126

c32.xls  

Gasoline and Diesel Fuel Update (EIA)

571 571 871 427 12,097 19,763 11,608 47.2 44.1 36.8 Building Floorspace (Square Feet) 1,001 to 5,000 .................................. 85 98 59 1,222 1,214 648 69.5 81.0 91.5 5,001 to 10,000 ................................ 56 90 56 1,131 1,733 828 49.8 51.9 67.7 10,001 to 25,000 .............................. 103 141 57 2,392 2,909 1,752 42.9 48.4 32.3 25,001 to 50,000 .............................. 90 102 58 1,827 2,700 1,498 49.3 37.7 38.7 50,001 to 100,000 ............................ 68 112 57 1,636 3,178 1,869 41.4 35.1 30.5 100,001 to 200,000 .......................... 63 120 59 1,501 2,745 2,399 42.0 43.6 24.5 200,001 to 500,000 .......................... 45 104 50 1,496 2,748 1,435 30.1 37.8 34.8 Over 500,000 ................................... 62 105 Q 893 2,535 Q 69.1 41.4 Q Principal Building Activity Education .........................................

127

january2008.xls  

Gasoline and Diesel Fuel Update (EIA)

Chris Cassar at 202-586-5448, or at Christopher.Cassar@eia.doe.gov. Chris Cassar at 202-586-5448, or at Christopher.Cassar@eia.doe.gov. Monthly Flash Estimates of Data for: November 2007 Section 1. Commentary Electric Power Data According to the National Oceanic and Atmospheric Administration, November 2007 was the twenty-fifth warmest November over the 1895-2007 time period. Heating degree days were 3.3 percent below the average for the month of November, but 11.6 percent higher than what was recorded in a fairly mild November 2006. In November 2007, electricity generation was 1.4 percent higher than what was observed in November 2006, while retail sales of electricity increased 2.6 percent when compared to November 2006. The higher growth rate for sales of electricity relative to generation is influenced by the fact that the utility billing cycles tend to lag electricity production in many areas.

128

natgas1980.xls  

Gasoline and Diesel Fuel Update (EIA)

Household Member Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 51.6 39.7 88.5 125 56 96.2 34 497 0.22 383 137 Census Region and Division Northeast 10.9 6.5 18.8 144 50 86.6 31 771 0.27 463 168 New England 1.9 0.9 3.1 162 47 78.9 28 971 0.28 472 169 Middle Atlantic 9.0 5.6 15.7 141 51 88.1 32 739 0.27 461 168 Midwest 15.5 12.4 29.4 164 70 131.6 46 586 0.25 470 165 East North Central 10.9 8.5 20.0 175 75 136.5 47 646 0.28 503 174 West North Central 4.6 3.9 9.4 141 59 120.0 44 456 0.19 389 143 South 13.3 11.4 21.1 99 53 84.4 30 389 0.21 333 118 South Atlantic 4.9 3.8 8.3 111 51 87.5 30 519 0.24 408 140 East South Central 2.3 2.0 3.7 102 55 86.4 33 371 0.2 314 119 West South Central 6.1 5.5 9.1 89 54 81.1 29 306 0.19 279 99 West 11.9 9.4 19.3 91 44 71.9 26

129

sup_rci.xls  

Gasoline and Diesel Fuel Update (EIA)

1 1 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Equipment Stock (million units) Main Space Heaters Electric Heat Pumps 10.38 10.71 11.03 11.32 11.60 11.83 12.09 12.35 12.60 12.86 13.13 13.39 13.64 Electric Other 21.53 21.59 21.64 21.69 21.72 21.78 21.87 21.96 22.07 22.18 22.30 22.41 22.53 Natural Gas Heat Pumps 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Natural Gas Other 59.99 60.71 61.44 62.11 62.81 63.56 64.34 65.12 65.90 66.68 67.46 68.22 68.97 Distillate 8.02 8.02 8.03 8.04 8.04 8.05 8.06 8.07 8.07 8.08 8.09 8.10 8.11 Liquefied Petroleum Gas 4.95 5.00 5.03 5.05 5.08 5.12 5.17 5.21 5.26 5.31 5.36 5.41 5.45 Kerosene 0.82 0.81 0.80 0.79 0.78 0.77 0.76 0.75 0.75 0.74 0.74 0.74 0.73 Wood Stoves 2.05 2.05 2.04 2.03 2.02 2.00 1.99 1.98 1.97 1.96 1.95 1.94 1.94 Geothermal Heat Pumps 0.06 0.07 0.09 0.10 0.12 0.13 0.15

130

november2006.xls  

Gasoline and Diesel Fuel Update (EIA)

Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Monthly Flash Estimates of Data for: September 2006 Section 1. Commentary Electric Power Data September is a transitional month between summer and fall, when decreased electricity use coincides with a decline in cooling demand. In contrast to recent Septembers, which have been warmer than normal, cooling and heating degree days for September 2006 were each within 10 percent of the norm. In September 2006, cooling degree days were 35.0 percent lower than September 2005 and 57.1 percent lower than August 2006. The changes in temperature translated into a 5.2 percent decline in September 2006 net electricity generation when compared to September 2005, and an 18.2 percent decline when compared to August 2006. Similarly, September 2006 retail sales of electricity

131

P4.xls  

Gasoline and Diesel Fuel Update (EIA)

P4. Energy Production Estimates in Physical Units, Ranked by State, 2011 P4. Energy Production Estimates in Physical Units, Ranked by State, 2011 United States 1,095,628 United States e 24,036,351 United States f 2,062,932 United States 331,646 1 Wyoming 438,673 Texas 7,112,863 Texas 531,524 Iowa 87,314 2 West Virginia 134,785 Louisiana 3,029,206 Alaska 204,829 Nebraska 47,120 3 Kentucky 108,971 Wyoming 2,159,422 California 193,691 Illinois 30,068 4 Pennsylvania 59,899 Oklahoma 1,888,870 North Dakota 152,985 Minnesota 27,536 5 Texas 45,904 Colorado 1,637,576 Oklahoma 76,681 South Dakota 24,850 6 Montana 42,008 Pennsylvania 1,310,592 New Mexico 71,274 Indiana 22,547 7 Illinois 37,938 New Mexico 1,237,303 Louisiana 68,984 Wisconsin 12,278 8 Indiana 37,544 Arkansas 1,072,212 Wyoming 54,710 Ohio 10,811 9 North Dakota 28,231 Utah 457,525 Kansas 41,503 Kansas 10,676 10 Ohio 28,175 West Virginia 394,125 Colorado

132

october2006.xls  

Gasoline and Diesel Fuel Update (EIA)

Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Monthly Flash Estimates of Data for: August 2006 Section 1. Commentary Electric Power Data Year-to-date net electric generation through August 2006 was 0.8 percent higher compared to year-to-date generation through August 2005. Comparing month-to-month, August 2006 net generation was 0.1 percent higher than August 2005, and 2.4 percent lower than July 2006. The higher net generation above last year was influenced by a continued strong economy and warmer than normal August weather. The index of industrial production was 4.7 percent higher comparing August 2006 to August 2005, but eased down, by 0.2 percent, between July 2006 and August 2006. Setting a new high, the national average retail price of electricity for August 2006 was 9.52 cents per kilowatthour. Comparing year-to-

133

september2006.xls  

Gasoline and Diesel Fuel Update (EIA)

Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Monthly Flash Estimates of Data for: July 2006 Section 1. Commentary Electric Power Data According to the National Climatic Data Center, the United States had its second hottest July on record due to a blistering heat wave throughout the country. The first seven months of 2006 was also the warmest on record in the Nation since recordkeeping began in 1895. July 2006 cooling degree days were near their historical high and more than 21 percent above normal. Year-to-date cooling degree days through July 2006 were 9.1 percent higher than in 2005. In July 2006 net generation, retail sales and retail prices of electricity all reached new highs. Year-to-date net generation for July 2006 was up 1.3

134

july2006.xls  

Gasoline and Diesel Fuel Update (EIA)

Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Monthly Flash Estimates of Data for: May 2006 Section 1. Commentary Electric Power Data The weather through May 2006 continued to be warmer than in 2005. According to the National Climatic Data Center, the first half of 2006 was the warmest on record in the U.S. since record keeping began in 1895. Year-to-date, heating degree days were down 10.2 percent and cooling degree days were up 44.7 percent through May. For May alone heating degree days were down 22.5 percent, and cooling degree days were 38.5 percent higher than last May. Year-to-date net generation through May was 0.7 percent higher than in 2005. Because of the advent of the summer cooling season and strong seasonal economic activity, May 2006 generation was up 5.1 percent compared to May 2005, and up 11.5 percent

135

august2007.xls  

Gasoline and Diesel Fuel Update (EIA)

June 2007 Section 1. Commentary Electric Power Data The U.S. National Oceanic and Atmospheric Administration (NOAA) reports that warmer- and drier-than-average conditions dominated much of the United States during the first half of 2007. June 2007 was the 23rd warmest June on record, increasing the cooling needs of the residential and commercial customers in the Nation. Cooling degree days for June 2007 were 9.3 percent above the average, but unchanged from June 2006. June 2007 electricity generation and retail sales of electricity were little changed from June 2006. Retail sales of electricity for the month of June 2007 increased only 0.2 percent compared to June 2006, while June 2007 generation for electric power was down 0.4 percent. The average U.S. retail price of electricity (all sectors) for June 2007 showed a 2.4-percent increase from

136

09 budget.xls  

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

Office of Electricity Delivery and Energy Reliability Budget Information Office of Electricity Delivery and Energy Reliability Budget Information FY 2007 FY 2009 Operating Plan Request Appropriation Request Research and Development High Temperature Superconductivity 45,750 28,186 27,930 28,186 Visualization and Controls 24,388 25,305 25,075 25,305 Energy Storage and Power Electronics 2,823 6,803 6,741 13,403 Renewable and Distributed Systems Integration 23,546 25,700 25,466 33,306 Congressionally Directed Activities - - 24,290 - SUBTOTAL, Research and Development

137

july2009.xls  

Gasoline and Diesel Fuel Update (EIA)

May 2009 Section 1. Commentary Electric Power Data In May 2009, the contiguous United States as a whole experienced temperatures that were above the monthly average. However, regional differences in temperature occurred as the West, Southwest, and Northwest all experienced above normal temperatures while the rest of the United States experienced near normal temperatures. Heating degree days for the contiguous United States were 20.8 percent below the average for the month of May and 31.1 percent below a much colder May 2008. Likewise, cooling degree days for the contiguous United States were 12.4 percent above the average for the month of May and 19.8 percent above May 2008. Retail sales of electricity decreased 5.0 percent in May 2009 compared to May 2008. This decrease in retail sales was caused mainly

138

october2007.xls  

Gasoline and Diesel Fuel Update (EIA)

August 2007 Section 1. Commentary Electric Power Data For the second month in a row, record warmth was observed throughout a majority of the country while the heavily populated Northeast experienced near average temperatures. Accordingly, cooling degree days for August 2007 were 26.0 percent above the average for the month of August, and 9.2 percent higher than August 2006. August 2007 electricity generation and retail sales of electricity were both up when compared to August 2006. Retail sales of electricity were 1.2 percent higher when compared to August 2006. However, residential retail sales of electricity decreased by 0.1 percent compared to August 2006. Generation for electric power was 3.8 percent higher than what was recorded in August

139

c1.xls  

Gasoline and Diesel Fuel Update (EIA)

Number of Number of Buildings (thousand) Floorspace (million square feet) Sum of Major Fuels Electricity Natural Gas Fuel Oil District Heat All Buildings* .................................. 4,645 64,783 92,577 69,032 14,525 1,776 7,245 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 6,789 12,812 10,348 2,155 292 Q 5,001 to 10,000 ................................. 889 6,585 9,398 7,296 1,689 307 Q 10,001 to 25,000 ............................... 738 11,535 13,140 10,001 2,524 232 Q 25,001 to 50,000 ............................... 241 8,668 10,392 7,871 1,865 127 Q 50,001 to 100,000 ............................. 129 9,057 11,897 8,717 1,868 203 Q 100,001 to 200,000 ........................... 65 9,064 13,391 9,500 1,737 272 Q 200,001 to 500,000 ........................... 25 7,176 10,347

140

sup_tran.xls  

Gasoline and Diesel Fuel Update (EIA)

(Trillion Btu) 2000- 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2020 Energy Use by Mode Highway Light-Duty Vehicles 14970.8 15191.3 15547.6 16054.3 16397.0 16743.0 17049.5 17379.1 17749.7 18129.3 18485.4 18843.9 19193.1 19518.8 19800.2 20071.6 20352.6 20620.8 20874.5 21140.7 21367.4 1.8% Automobiles 8641.2 8557.7 8554.5 8628.8 8632.3 8639.0 8622.6 8629.9 8669.2 8715.0 8763.0 8824.1 8891.3 8958.2 9010.9 9065.1 9131.3 9196.1 9258.6 9330.1 9387.4 0.4% Light Trucks 6304.8 6609.0 6968.5 7400.7 7739.9 8079.1 8402.1 8724.4 9055.5 9389.2 9697.2 9994.5 10276.3 10534.9 10763.4 10980.5 11195.1 11398.3 11589.2 11783.8 11953.0 3.3% Motorcycles 24.8 24.6 24.6 24.8 24.8 24.8 24.8 24.8 24.9 25.0 25.2 25.3 25.5 25.7 25.9 26.0 26.2 26.4 26.6 26.8 27.0 0.4% Commercial Light Trucks 1/ 637.6 624.1

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

c13.xls  

Gasoline and Diesel Fuel Update (EIA)

25th 25th Per- centile Median 75th Per- centile per Building (thousand dollars) per Square Foot (dollars) per kWh (dollars) All Buildings* .................................. 202 14.1 12.2 3.6 8.2 17.1 15.7 1.09 0.078 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 47 17.8 11.4 3.8 8.9 20.3 4.3 1.63 0.092 5,001 to 10,000 ................................. 92 12.4 10.3 3.8 7.4 14.5 8.7 1.18 0.095 10,001 to 25,000 ............................... 164 10.5 11.1 2.9 6.3 13.4 13.8 0.88 0.084 25,001 to 50,000 ............................... 439 12.2 11.6 3.8 8.8 16.2 33.6 0.94 0.077 50,001 to 100,000 ............................. 927 13.1 14.1 4.5 9.9 17.0 68.0 0.97 0.073 100,001 to 200,000 ........................... 2,181 15.7 12.2 5.3 13.0 23.4 146.4 1.05 0.067 200,001 to 500,000 ...........................

142

c16.xls  

Gasoline and Diesel Fuel Update (EIA)

,262 ,262 14,172 25,540 15,057 0.10 0.07 0.07 0.10 1.11 0.85 1.12 1.37 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 1,617 2,401 4,142 2,188 0.12 0.08 0.08 0.12 1.62 1.39 1.78 1.69 5,001 to 10,000 ................................. 1,202 1,212 2,721 2,160 0.12 0.08 0.08 0.12 1.11 0.84 1.11 1.78 10,001 to 25,000 ............................... 1,795 2,145 3,763 2,299 0.10 0.07 0.08 0.10 0.92 0.69 0.88 1.11 25,001 to 50,000 ............................... 1,168 2,042 2,864 1,797 0.10 0.07 0.07 0.10 0.90 0.82 0.95 1.12 50,001 to 100,000 ............................. 2,130 1,777 3,190 1,620 0.09 0.06 0.06 0.10 1.04 0.79 0.93 1.25 100,001 to 200,000 ........................... 2,286 1,963 3,810 1,440 0.09 0.06 0.06 0.08 1.08 0.86 1.11 1.22 200,001 to 500,000 ........................... 1,985 1,497 2,312 1,530

143

c21.xls  

Gasoline and Diesel Fuel Update (EIA)

Square Square Feet All Buildings* .................................. 190 341 360 12,543 28,786 21,977 15.1 11.8 16.4 Principal Building Activity Education .......................................... 9 55 45 806 5,378 3,687 11.1 10.2 12.2 Food Sales ....................................... 36 24 Q 747 467 Q 48.8 51.1 Q Food Service ..................................... 47 16 Q 986 664 Q 47.8 24.5 Q Health Care ....................................... 6 17 50 445 835 1,883 13.1 20.5 26.3 Inpatient .......................................... N Q 47 N Q 1,723 N Q 27.0 Outpatient ....................................... 6 11 Q 445 652 Q 13.1 17.4 Q Lodging ............................................. 4 31 34 260 2,274 2,563 14.0 13.5 13.5 Retail (Other Than Mall)..................... 17 28 18 1,363 2,133 821 12.2 12.9 21.5 Office ................................................

144

Fig1.xls  

Gasoline and Diesel Fuel Update (EIA)

December 2009 December 2009 1 December 2009 Short-Term Energy Outlook December 8, 2009 Release Highlights  EIA expects the price of West Texas Intermediate (WTI) crude oil will average about $76 per barrel this winter (October-March). The forecast for the monthly average WTI price dips to $75 early next year then rises to $82 per barrel by December 2010, assuming U.S. and world economic conditions continue to improve. EIA's forecast assumes that U.S. real gross domestic product (GDP) grows by 1.9 percent in 2010 and world oil-consumption-weighted real GDP grows by 2.6 percent.  Rising crude oil prices contribute to an increase in the annual average regular-

145

sup_tran.xls  

Gasoline and Diesel Fuel Update (EIA)

Type Type (Trillion Btu) 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Energy Use by Mode Highway Light-Duty Vehicles 15161.1 15575.7 15906.8 16472.8 16956.1 17383.6 17761.0 18145.3 18523.6 18909.9 19286.4 19680.7 20088.4 Automobiles 8876.0 8832.9 8766.0 8824.8 8847.8 8851.9 8868.7 8891.4 8906.8 8939.0 8971.8 9011.9 9058.7 Light Trucks 6259.5 6717.3 7115.4 7622.5 8082.6 8506.0 8866.5 9228.1 9591.0 9945.0 10288.6 10642.6 11003.3 Motorcycles 25.6 25.5 25.4 25.6 25.7 25.7 25.8 25.8 25.9 26.0 26.0 26.2 26.3 Commercial Light Trucks 1/ 583.8 586.5 584.4 605.0 624.7 637.7 648.0 658.6 670.4 683.6 696.8 709.8 724.5 Buses 251.1 238.9 239.8 242.3 244.6 246.6 248.7 250.7 252.8 254.8 256.6 258.2 259.4 Transit 98.9 94.1 94.5 95.5 96.4 97.2 98.0 98.8 99.6 100.4 101.1 101.7 102.2 Intercity 36.6 34.7 34.8 35.2 35.5 35.8 36.1 36.4 36.7

146

c23.xls  

Gasoline and Diesel Fuel Update (EIA)

25th 25th Per- centile Median 75th Per- centile per Building (thousand dollars) per Square Foot (dollars) per Thousand Cubic Feet (dollars) All Buildings* ................................. 782 43.0 36.0 17.6 37.1 70.9 6.1 0.33 7.77 Building Floorspace (Square Feet) 1,001 to 5,000 ................................. 219 78.7 42.6 23.7 46.3 92.0 1.9 0.70 8.88 5,001 to 10,000 ............................... 408 54.8 42.5 13.9 28.8 65.7 3.4 0.46 8.34 10,001 to 25,000 ............................. 667 42.5 40.8 14.4 29.2 52.1 5.6 0.36 8.41 25,001 to 50,000 ............................. 1,483 41.5 39.1 16.0 31.5 55.3 11.1 0.31 7.46 50,001 to 100,000 ............................ 2,498 35.4 39.1 10.1 27.6 48.8 19.7 0.28 7.90 100,001 to 200,000 .......................... 5,029 36.3 26.1 6.1 23.6 55.2 36.2 0.26 7.19 200,001 to 500,000 ..........................

147

february2008.xls  

Gasoline and Diesel Fuel Update (EIA)

7 7 Section 1. Commentary Electric Power Data While average temperatures prevailed across the majority of the Nation in December 2007, warmer-than-average temperatures in the more heavily populated eastern United States led to a decrease in total heating degree-days for the contiguous U.S. of 3.3 percent below the average for the month of December. However, heating degree days were still 14.5 percent above the level from December 2006, leading to an increase in electricity demand from a year ago. Retail sales of electricity for the month of December 2007 increased 2.1 percent compared to December 2006. The average U.S. retail price of electricity for December 2007 showed a 4.2-percent increase from December 2006 and a 0.8-percent decrease from

148

Attachment B.xls  

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

Competitive Sourcing Studies, 2002-2003 Competitive Sourcing Studies, 2002-2003 (Full-Time Equivalent Positions Under Review) DOE Organization State(s) I n f o r m a t i o n T e c h n o l o g y H u m a n R e s o u r c e s F i n a n c i a l S e r v i c e s P e r s o n n e l S e c u r i t y I n v e s t i g a t i o n s L o g i s t i c s G r a p h i c s C i v i l R i g h t s R e v i e w s P a r a l e g a l S u p p o r t T O T A L Headquarters Office of Management, Budget and Evaluation/CFO MD, DC 6 15 60 86 13 180 Chief Information Officer MD, DC 113 113 Economic Impact and Diversity MD, DC 2 2 8 2 14 Energy Efficiency and Renewable Energy MD, DC 7 1 8 Environment, Safety, and Health MD, DC 7 4 11 Energy Information Administration MD, DC 28 28 Environmental Management MD, DC 22 5 27 General Counsel MD, DC 7 7 Fossil Energy MD, DC 6 2 8 Hearings and Appeals MD, DC 7 7 Inspector General MD, DC 2 1 3 Nuclear Energy Science and Technology MD, DC 1 1 Oversight and Performance Assurance

149

b35.xls  

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

Cooled Cooled 1 to 50 Percent Cooled 51 to 99 Percent Cooled 100 Percent Cooled All Build- ings* Not Cooled 1 to 50 Percent Cooled 51 to 99 Percent Cooled 100 Percent Cooled All Buildings* .................................. 4,645 1,020 985 629 2,011 64,783 7,843 16,598 13,211 27,132 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 710 407 279 1,155 6,789 1,782 1,206 781 3,021 5,001 to 10,000 ................................. 889 157 226 133 374 6,585 1,177 1,704 995 2,710 10,001 to 25,000 ............................... 738 109 225 126 277 11,535 1,612 3,517 2,034 4,372 25,001 to 50,000 ............................... 241 25 64 43 109 8,668 893 2,369 1,479 3,928 50,001 to 100,000 ............................. 129 11 41 25 52 9,057 726 2,926 1,751 3,654 100,001 to 200,000 ...........................

150

eia912.xls  

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

Month Month 2 0 Address 2: City: State: Zip: - to meet the due date.) (Volume of gas in the reservoir that is in addition to the base gas.) Working Gas as of Friday 9:00 AM (Million Cubic Feet) Producing Region Complete and return form no later than 5:00 p.m. Eastern Standard Time on Monday. If this is a resubmission, enter an "X" in the box: EIA ID NUMBER: ATTN: EIA-912 Energy Information Administration, EI-45 U. S. Department of Energy (202) 586-2849 912 Company Name: oog.eia912@eia.gov Fax No.: Email: Ext: Form may be submitted using one of the following methods: Fax to: Address 1: Secure File Transfer: https://signon.eia.doe.gov/upload/notice912.jsp Questions? Email address: Comments: Please explain in this section any unusual data reports. For example, explain any change in working gas as a result of changes in the number or capacity

151

b1.xls  

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

Released: Dec 2006 Next CBECS will be conducted in 2007 Number of Buildings (thousand) Total Floorspace (million square feet) Total Workers in All Buildings (thousand) Mean Square Feet per Building (thousand) Mean Square Feet per Worker Mean Hours per Week All Buildings*................................... 4,645 64,783 72,807 13.9 890 61 Table B1. Summary Table: Total and Means of Floorspace, Number of Workers, and Hours of Operation for Non-Mall Buildings, 2003 Climate Zone: 30-Year Average Under 2,000 CDD and -- More than 7,000 HDD ..................... 855 10,622 10,305 12.4 1,031 60 5,500-7,000 HDD ............................ 1,173 17,335 17,340 14.8 1,000 63 4,000-5,499 HDD ............................ 673 11,504 14,007 17.1 821 66 Fewer than 4,000 HDD ................... 1,276

152

a7.xls  

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

Buildings .................................... Buildings .................................... 4,859 3,754 762 117 47 22 157 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,586 2,131 338 Q Q N 100 5,001 to 10,000 ................................. 948 720 182 Q N Q Q 10,001 to 25,000 ............................... 810 590 140 51 13 Q Q 25,001 to 50,000 ............................... 261 163 54 19 12 Q Q 50,001 to 100,000 ............................. 147 87 29 8 13 4 Q 100,001 to 200,000 ........................... 74 43 13 6 5 4 Q 200,001 to 500,000 ........................... 26 15 5 Q 1 3 Q Over 500,000 .................................... 8 3 1 Q Q 3 Q Principal Building Activity Education .......................................... 386 360 21 Q N N N Food Sales ....................................... 226 203 Q N N Q N Food Service .....................................

153

eia910.xls  

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

Address 2: Address 2: City: State: Zip: - 1. Report State (Enter one of the following States in the box): Georgia, New York, 2. To how many end-use customers did you sell natural gas? 3. 4. For companies reporting sales in all States except Georgia: 5. For companies reporting sales in Georgia: PART 2. SUBMISSION INFORMATION (Dollars) Do not report negative numbers or decimals. You may report in either Thousand cubic feet (Mcf) or in Therms. Indicate unit of measure by placing an "X" in the appropriate box. Commercial Residential Commercial Residential Form may be submitted using one of the following methods: Mail to: ATTN: EIA-910 (Dollars) Commercial Residential Mcf Call: Email address: (877) 800 - 5261 Secure File Transfer: https://signon.eia.doe.gov/upload/noticeoog.jsp

154

b46.xls  

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

64,783 64,783 52,974 26,768 20,254 10,425 17,218 38,884 35,335 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 4,333 1,310 916 366 935 3,174 830 5,001 to 10,000 ................................. 6,585 4,738 1,406 909 497 894 3,609 1,407 10,001 to 25,000 ............................... 11,535 8,646 2,230 1,188 614 1,665 6,725 4,072 25,001 to 50,000 ............................... 8,668 7,068 2,829 1,626 676 1,933 5,289 4,910 50,001 to 100,000 ............................. 9,057 8,038 4,291 3,124 1,354 2,438 5,760 6,342 100,001 to 200,000 ........................... 9,064 8,096 5,116 4,148 1,926 3,302 5,667 6,578 200,001 to 500,000 ........................... 7,176 6,238 4,606 4,199 2,034 2,685 4,524 5,691 Over 500,000 .................................... 5,908 5,816 4,979 4,146 2,958

155

c37.xls  

Gasoline and Diesel Fuel Update (EIA)

per per Building (million Btu) per Square Foot (thousand Btu) per Worker (million Btu) per Building (thousand dollars) per Square Foot (dollars) per Thousand Pounds (dollars) All Buildings* .................................. 9,475 116.44 62.2 108.3 1.33 11.43 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... Q Q Q Q Q Q 5,001 to 10,000 ................................. Q Q Q Q Q Q 10,001 to 25,000 ............................... Q Q Q Q Q Q 25,001 to 50,000 ............................... Q Q Q Q Q Q 50,001 to 100,000 ............................. Q Q Q Q Q Q 100,001 to 200,000 ........................... 17,452 118.10 Q Q Q Q 200,001 to 500,000 ........................... 34,658 121.16 143.2 Q Q Q Over 500,000 .................................... 85,182 99.92 52.4 911.2 1.07 10.70 Principal Building Activity

156

c28.xls  

Gasoline and Diesel Fuel Update (EIA)

171 171 210 99 3,593 6,326 2,281 47.6 33.2 43.3 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 23 25 11 346 325 209 66.6 75.3 53.5 5,001 to 10,000 ................................. 13 34 Q 305 620 Q 44.0 54.9 Q 10,001 to 25,000 ............................... 29 28 Q 756 987 565 37.9 28.6 Q 25,001 to 50,000 ............................... 44 17 12 840 714 363 52.6 24.4 Q 50,001 to 100,000 ............................. Q 27 Q Q 806 Q Q 33.1 Q 100,001 to 200,000 ........................... 19 Q Q 512 1,238 Q 37.8 30.8 Q 200,001 to 500,000 ........................... Q 23 Q Q 786 Q Q 28.9 Q Over 500,000 .................................... Q 18 Q Q Q Q Q 21.6 Q Principal Building Activity Education .......................................... 14 25 Q 380 1,274 Q 38.1 19.6 Q Food Sales .......................................

157

c18.xls  

Gasoline and Diesel Fuel Update (EIA)

62 62 210 50 5,328 12,097 3,220 11.7 17.4 15.5 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 10 26 7 821 1,157 472 12.4 22.9 15.5 5,001 to 10,000 ................................. 7 18 4 666 1,308 359 10.7 13.9 12.0 10,001 to 25,000 ............................... 8 27 11 1,164 2,207 791 7.3 12.2 14.2 25,001 to 50,000 ............................... 15 24 5 949 1,672 442 16.1 14.4 10.9 50,001 to 100,000 ............................. 8 25 10 642 1,470 650 12.8 16.7 14.8 100,001 to 200,000 ........................... 8 39 Q 614 2,087 Q 12.3 18.9 Q 200,001 to 500,000 ........................... Q 22 Q Q 1,072 Q Q 20.4 Q Over 500,000 .................................... Q 29 Q Q 1,123 Q Q 25.6 Q Principal Building Activity Education .......................................... 5 39 Q 549 2,445 Q 8.8 16.0 Q Food Sales .......................................

158

Fig1.xls  

Gasoline and Diesel Fuel Update (EIA)

June 2010 June 2010 1 June 2010 Short-Term Energy Outlook June 8, 2010 Release Highlights  Crude oil prices fluctuated considerably last month, with the West Texas Intermediate (WTI) spot price ranging from a high of $86 per barrel on May 3 to a low of $65 on May 25, before ending the month at $74. According to some market analysts, uncertainty over the global economic recovery, particularly with respect to Europe's debt crisis and the tightening of credit by China, and liquidation of futures contracts contributed to the crude price decline. Moreover, WTI prices fell further than most other crudes because of record high inventories in Cushing, Oklahoma. EIA projects WTI crude oil spot prices

159

Grantsdown.xls  

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

American Recovery and Reinvestment Act American Recovery and Reinvestment Act Funding Opportunity Announcement Table TITLE FOA # Demonstration of Integrated Biorefinery Operations DE-FOA-0000096 Expansion of Infrastructure for Ethanol Blends DE-FOA-0000125 Development of Algal / Advanced Biofuels Consortia DE-FOA-0000123 Geothermal Technologies Program: Ground Source Heat Pumps DE-FOA-0000116 Enhanced Geothermal Systems Component Research and Development/Analysis DE-FOA-0000075 Geothermal Technologies Program: Validation of Innovative Exploration Technologies; Geothermal Energy Production; Geothermal Data Development, Collection, and Maintenance DE-FOA-0000109 Enhanced Geothermal Systems Demonstrations DE-FOA-0000092 Hydroelectric Facility Modernization DE-FOA-0000120

160

september2007.xls  

Gasoline and Diesel Fuel Update (EIA)

July 2007 Section 1. Commentary Electric Power Data According to the National Oceanic and Atmospheric Administration (NOAA), July 2007 brought record warmth to many of the states in the western U.S. However, cooler than average temperatures observed in the heavily populated eastern half of the country kept residential energy demand in the contiguous United States close to normal, with cooling degree days 1.2 percent below the average for the month of July. Due to the below normal temperatures observed in the heavily populated eastern United States, July 2007 electricity generation and retail sales of electricity were down when compared to July 2006. Retail sales of electricity was 1.6 percent lower when compared to July 2006, with residential retail sales decreasing the most at 4.9 percent. Furthermore, generation for electric

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

a1.xls  

Gasoline and Diesel Fuel Update (EIA)

2003 Commercial Buildings 2003 Commercial Buildings Energy Consumption Survey Detailed Tables October 2006 Energy Information Administration 2003 Commercial Buildings Energy Consumption Survey Detailed Tables Introduction................................................................................................................................ vii Change in Data Collection Procedures in Malls ........................................................................ viii Guide to the 2003 CBECS Detailed Tables............................................................................... ix Building Characteristics Tables All Buildings (Including Malls) Table A1. Summary Table for All Buildings (Including Malls) ............................................... 1 Table A2. Census Region, Number of Buildings and Floorspace for All Buildings

162

c19.xls  

Gasoline and Diesel Fuel Update (EIA)

14 14 56 96 7,449 3,633 7,397 15.3 15.4 13.0 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 17 7 12 696 437 857 24.1 15.7 14.0 5,001 to 10,000 ................................. 11 5 14 787 404 810 13.4 12.0 16.9 10,001 to 25,000 ............................... 11 10 13 1,267 831 1,232 8.9 11.7 10.3 25,001 to 50,000 ............................... 12 7 12 897 511 1,088 13.6 13.2 11.0 50,001 to 100,000 ............................. 16 5 12 1,314 374 922 12.1 12.7 13.3 100,001 to 200,000 ........................... 20 Q 13 1,096 Q 895 18.2 Q 14.5 200,001 to 500,000 ........................... 12 5 11 659 Q 827 18.4 14.3 13.5 Over 500,000 .................................... Q Q 9 Q Q 766 Q Q 12.4 Principal Building Activity Education .......................................... 15 6 11 1,198 640 1,027 12.8 9.4

163

P3.xls  

Gasoline and Diesel Fuel Update (EIA)

P3. Energy Production and Consumption Estimates in Trillion Btu, 2011 P3. Energy Production and Consumption Estimates in Trillion Btu, 2011 Alabama 1,401 1,931 530 Alaska 1,642 638 -1,004 Arizona 618 1,431 814 Arkansas 1,390 1,117 -273 California 2,625 7,858 5,234 Colorado 2,747 1,481 -1,266 Connecticut 197 742 545 Delaware 4 272 268 District of Columbia 0 180 180 Florida 524 4,217 3,693 Georgia 544 3,002 2,458 Hawaii 19 286 267 Idaho 180 526 345 Illinois 2,200 3,978 1,777 Indiana 1,063 2,869 1,806 Iowa 701 1,513 812 Kansas 780 1,162 382 Kentucky 2,841 1,911 -929 Louisiana 3,976 4,055 79 Maine 154 413 258 Maryland 273 1,426 1,153 Massachusetts 101 1,395 1,294 Michigan 673 2,803 2,130 Minnesota 429 1,867 1,438 Mississippi 441 1,163 723 Missouri 200 1,878 1,678 Montana 1,105 398 -707 Nebraska 397 871 475 Nevada 54 633 579 New Hampshire 130 292 162 New Jersey 387 2,438 2,052 New Mexico 2,261 688 -1,573 New York 873 3,615 2,742 North Carolina

164

c3.xls  

Gasoline and Diesel Fuel Update (EIA)

trillion trillion Btu) per Building (million Btu) per Square Foot (thousand Btu) per Worker (million Btu) All Buildings* .................................. 4,645 64,783 13.9 5,820 1,253 89.8 79.9 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 6,789 2.7 672 263 98.9 67.6 5,001 to 10,000 ................................. 889 6,585 7.4 516 580 78.3 68.7 10,001 to 25,000 ............................... 738 11,535 15.6 776 1,052 67.3 72.0 25,001 to 50,000 ............................... 241 8,668 35.9 673 2,790 77.6 75.8 50,001 to 100,000 ............................. 129 9,057 70.4 759 5,901 83.8 90.0 100,001 to 200,000 ........................... 65 9,064 138.8 934 14,300 103.0 80.3 200,001 to 500,000 ........................... 25 7,176 289.0 725 29,189 101.0 105.3 Over 500,000 ....................................

165

september2010.xls  

Gasoline and Diesel Fuel Update (EIA)

July 2010 July 2010 Section 1. Commentary Electric Power Data The contiguous United States, as a whole, experienced temperatures that were significantly above average in July 2010. Accordingly, the total population-weighted cooling degree days for the United States were 19.9 percent above the July normal. Retail sales of electricity increased 9.5 percent compared to July 2009. Over the same period, the average U.S. retail price of electricity increased 1.3 percent. For the 12-month period ending July 2010, the U.S. average retail price of electricity decreased 1.4 percent over the previous 12-month period ending July 2009. In July 2010, total electric power generation in the United States increased 9.2 percent compared to July 2009. Over the same period, coal generation increased 12.4 percent, and natural gas generation increased 11.4 percent. Petroleum

166

february2006.xls  

Gasoline and Diesel Fuel Update (EIA)

and Stock Trends and Stock Trends Page 5 6. Month-to-Month Comparisons: Electric Power Retail Sales and Average Prices Page 6 7. Retail Sales Trends Page 7 8. Average Retail Price Trends Page 8 9. Heating and Cooling Degree Days Page 9 10. Documentation Page 10 Monthly Flash Estimates of Data for: December 2005 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy of the Department of Energy or any other organization. For additional information, contact Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov.

167

c1.xls  

Gasoline and Diesel Fuel Update (EIA)

October 2006 October 2006 Next CBECS will be conducted in 2007 Primary Site All Buildings* .................................. 4,645 64,783 5,820 9,168 3,037 1,928 222 634 District Heat Table C1. Total Energy Consumption by Major Fuel for Non-Mall Buildings, 2003 All Buildings* Total Energy Consumption (trillion Btu) Number of Buildings (thousand) Floorspace (million square feet) Sum of Major Fuels Electricity Natural Gas Fuel Oil Climate Zone: 30-Year Average Under 2,000 CDD and -- More than 7,000 HDD ..................... 855 10,622 990 1,232 408 431 63 88 5,500-7,000 HDD ............................ 1,173 17,335 1,761 2,305 763 679 63 255 4,000-5,499 HDD ............................ 673 11,504 1,134 1,713 567 337 90 140 Fewer than 4,000 HDD ................... 1,276 15,739 1,213 2,259 748 358 6 101 2,000 CDD or More and --

168

february2007.xls  

Gasoline and Diesel Fuel Update (EIA)

Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Monthly Flash Estimates of Data for: December 2006 Section 1. Commentary Electric Power Data The National Oceanic and Atmospheric Administration (NOAA) Climatic Data Center reports 2006 as the warmest year on record for the contiguous United States, with El Niño contributing to milder winter temperatures. NOAA also reports that December 2006 was the fourth warmest December since 1895. (For more information see http://www.noaanews.noaa.gov/stories2007/s2772.htm.) As a consequence of the warmer weather, December 2006 generation lagged behind the December 2005 generation by 3.6 percent, although it increased 8.7 percent from November 2006. Mirroring generation, December 2006 retail sales of electricity were up 8.4

169

c29.xls  

Gasoline and Diesel Fuel Update (EIA)

51 51 162 149 4,704 2,797 5,016 32.2 57.9 29.7 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 29 18 Q 334 265 363 87.9 68.4 60.2 5,001 to 10,000 ................................. 23 Q Q 519 Q 496 44.2 Q 53.4 10,001 to 25,000 ............................... 14 38 22 514 630 748 28.1 61.1 29.0 25,001 to 50,000 ............................... 17 23 21 512 464 733 33.5 49.1 28.7 50,001 to 100,000 ............................. 18 Q 18 888 Q 730 20.5 Q 24.2 100,001 to 200,000 ........................... 16 Q 12 760 Q 651 21.5 Q 17.8 200,001 to 500,000 ........................... Q Q 14 470 Q 675 Q Q 20.8 Over 500,000 .................................... Q Q Q Q Q Q Q Q Q Principal Building Activity Education .......................................... 16 21 28 797 420 802 20.6 48.8 34.8 Food Sales .......................................

170

P5.xls  

Gasoline and Diesel Fuel Update (EIA)

P5. Energy Production Estimates in Trillion Btu, Ranked by State, 2011 P5. Energy Production Estimates in Trillion Btu, Ranked by State, 2011 Rank State State State State United States 22,057.2 United States d 26,489.9 United States e 11,965.0 United States 8,268.7 1 Wyoming 7,591.7 Texas 8,047.4 Texas 3,082.8 Illinois 1,002.7 2 West Virginia 3,321.1 Louisiana 3,240.2 Alaska 1,188.0 Pennsylvania 796.8 3 Kentucky 2,623.8 Wyoming 2,384.4 California 1,123.4 South Carolina 553.6 4 Pennsylvania 1,511.5 Oklahoma 2,163.4 North Dakota 887.3 New York 446.8 5 Illinois 864.2 Colorado 1,831.2 Oklahoma 444.8 North Carolina 424.1 6 Indiana 841.0 New Mexico 1,405.2 New Mexico 413.4 Texas 414.9 7 Montana 746.7 Pennsylvania 1,375.6 Louisiana 400.1 Alabama 411.8 8 Ohio 679.2 Arkansas 1,090.9 Wyoming 317.3 California 383.6 9 Texas 605.3 Utah 498.0 Kansas 240.7 New Jersey 351.7 10 Colorado 586.8 West Virginia 442.4 Colorado 226.9

171

june2007.xls  

Gasoline and Diesel Fuel Update (EIA)

April 2007 Section 1. Commentary Electric Power Data The overall temperature for the contiguous U.S. during April 2007 was 0.3ºF (0.2ºC) below the average temperature observed for the month of April over the 1971-2000 time period. A record cold outbreak was observed from April 4th to April 10th as record low temperatures were set in 1,200 locations across the contiguous U.S. before warmer weather returned later in the month. This cold snap was evident in the fact that heating degree days were 10.7 percent higher than normal as observed over the 1971-2000 time period, and 44.7 percent higher than what was recorded in April 2006. Consequently, retail sales of electricity for the month of April 2007 increased 2.7 percent compared to April 2006, while April 2007

172

b25.xls  

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

Space Space Heating Cooling Water Heating Cooking Manu- facturing All Buildings* .................................. 64,783 60,028 56,940 56,478 22,237 3,138 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 5,668 5,007 4,759 997 Q 5,001 to 10,000 ................................. 6,585 5,786 5,408 5,348 1,136 214 10,001 to 25,000 ............................... 11,535 10,387 9,922 9,562 1,954 472 25,001 to 50,000 ............................... 8,668 8,060 7,776 7,734 2,511 Q 50,001 to 100,000 ............................. 9,057 8,718 8,331 8,412 3,575 540 100,001 to 200,000 ........................... 9,064 8,710 8,339 8,300 3,991 473 200,001 to 500,000 ........................... 7,176 6,907 6,565 6,680 4,047 605 Over 500,000 .................................... 5,908 5,792

173

b13.xls  

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

4,645 4,645 824 277 71 370 622 597 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 503 119 37 152 434 294 5,001 to 10,000 ................................. 889 127 67 Q 104 100 110 10,001 to 25,000 ............................... 738 116 69 Q 83 66 130 25,001 to 50,000 ............................... 241 43 9 Q 27 17 27 50,001 to 100,000 ............................. 129 17 7 Q Q Q 21 100,001 to 200,000 ........................... 65 11 6 Q Q Q 8 200,001 to 500,000 ........................... 25 5 Q Q Q Q 4 Over 500,000 .................................... 7 2 Q Q N Q Q Year Constructed Before 1920 ...................................... 330 70 31 Q 65 Q 20 1920 to 1945 ..................................... 527 85 36 Q 52 90 39 1946 to 1959 ..................................... 562 75 45 Q 58 59 44 1960 to 1969 .....................................

174

b19.xls  

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

4,645 4,645 3,754 643 55 23 14 157 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 2,131 311 Q Q N 100 5,001 to 10,000 ................................. 889 720 136 Q N Q Q 10,001 to 25,000 ............................... 738 590 104 22 Q Q Q 25,001 to 50,000 ............................... 241 163 50 11 Q Q Q 50,001 to 100,000 ............................. 129 87 25 4 5 Q Q 100,001 to 200,000 ........................... 65 43 11 4 Q Q Q 200,001 to 500,000 ........................... 25 15 5 Q 1 2 Q Over 500,000 .................................... 7 3 1 Q Q 1 Q Principal Building Activity Education .......................................... 386 360 21 Q N N N Food Sales ....................................... 226 203 Q N N Q N Food Service ..................................... 297 270 26 Q N N N Health Care .......................................

175

b32.xls  

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

64,783 64,783 56,478 27,490 28,820 1,880 3,088 1,422 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 4,759 2,847 1,699 116 N 169 5,001 to 10,000 ................................. 6,585 5,348 2,821 2,296 Q Q 205 10,001 to 25,000 ............................... 11,535 9,562 4,809 4,470 265 Q 430 25,001 to 50,000 ............................... 8,668 7,734 3,924 4,055 Q Q Q 50,001 to 100,000 ............................. 9,057 8,412 3,659 5,005 Q 303 Q 100,001 to 200,000 ........................... 9,064 8,300 3,884 4,754 Q 822 Q 200,001 to 500,000 ........................... 7,176 6,680 2,722 4,076 Q 621 Q Over 500,000 .................................... 5,908 5,683 2,824 2,467 Q 1,064 N Principal Building Activity Education .......................................... 9,874 9,481 3,829

176

a1.xls  

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

Number of Buildings RSEs for Total Floorspace RSEs for Mean Square Feet per Building RSEs Not Available for Medians All Buildings .................................... 3.8 3.1 4.0 _ Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 5.7 5.6 1.3 _ 5,001 to 10,000 ................................. 5.6 5.5 0.8 _ 10,001 to 25,000 ............................... 4.9 4.9 0.9 _ 25,001 to 50,000 ............................... 5.5 5.8 1.2 _ 50,001 to 100,000 ............................. 6.1 6.0 1.0 _ 100,001 to 200,000 ........................... 9.9 10.0 1.5 _ 200,001 to 500,000 ........................... 9.8 10.2 1.8 _ Over 500,000 .................................... 12.6 12.8 4.2 _ Principal Building Activity Education .......................................... 7.1

177

b8.xls  

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

4,645 4,645 330 527 562 579 731 707 876 334 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 174 315 331 298 350 438 481 165 5,001 to 10,000 ................................. 889 71 107 90 120 180 98 158 66 10,001 to 25,000 ............................... 738 55 64 90 95 122 103 151 58 25,001 to 50,000 ............................... 241 19 23 26 33 48 32 39 21 50,001 to 100,000 ............................. 129 7 9 14 22 16 20 28 13 100,001 to 200,000 ........................... 65 Q 5 8 8 10 10 15 8 200,001 to 500,000 ........................... 25 Q 4 2 3 4 4 4 2 Over 500,000 .................................... 7 Q 1 1 0 1 2 1 Q Principal Building Activity Education .......................................... 386 12 26 78 60 58 44 75 32 Food Sales ....................................... 226 Q Q Q Q Q 33 56 Q Food Service .....................................

178

b30.xls  

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

District Chilled Water Elec- tricity Natural Gas District Chilled Water All Buildings* .................................. 4,645 3,625 3,589 17 33 64,783 56,940 54,321 1,018 2,853 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 1,841 1,838 Q Q 6,789 5,007 4,994 Q Q 5,001 to 10,000 ................................. 889 732 727 Q Q 6,585 5,408 5,367 Q Q 10,001 to 25,000 ............................... 738 629 618 Q Q 11,535 9,922 9,743 Q Q 25,001 to 50,000 ............................... 241 216 211 Q 6 8,668 7,776 7,557 Q 240 50,001 to 100,000 ............................. 129 118 114 Q 5 9,057 8,331 8,086 Q 332 100,001 to 200,000 ........................... 65 60 55 Q 6 9,064 8,339 7,657 Q 793 200,001 to 500,000 ........................... 25 23 21 Q 2 7,176 6,565 6,112 Q 495 Over 500,000 ....................................

179

a4.xls  

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

East East South Central West South Central Mountain Pacific All Buildings .................................... 71,658 3,452 10,543 12,424 5,680 13,999 3,719 9,022 4,207 8,613 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,922 383 676 986 922 1,283 547 788 466 871 5,001 to 10,000 ................................. 7,033 369 800 939 738 1,468 420 957 465 878 10,001 to 25,000 ............................... 12,659 674 1,448 2,113 1,204 2,443 861 1,555 933 1,429 25,001 to 50,000 ............................... 9,382 366 1,022 1,763 949 1,867 545 1,062 568 1,239 50,001 to 100,000 ............................. 10,291 590 1,682 1,712 664 1,797 749 1,514 492 1,092 100,001 to 200,000 ........................... 10,217 448 1,790 1,872 614 2,422 Q 1,426 346 1,007 200,001 to 500,000 ...........................

180

table3.xls  

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

29.3 29.3 137.3 147.5 151.2 156.8 191.0 Household Characteristics Census Region and Division Northeast............................................................... 23.9 NA 26.6 27.0 26.6 31.7 New England........................................................ 6.6 NA 6.6 6.5 7.6 10.0 Middle Atlantic ..................................................... 17.3 NA 20.1 20.5 19.0 21.7 Midwest ................................................................. 32.5 NA 37.8 38.4 41.1 47.1 East North Central............................................... 21.3 NA 26.0 27.6 29.0 32.4 West North Central ............................................. 11.3 NA 11.8 10.8 12.1 14.7 South..................................................................... 45.1 NA 50.6 52.7 56.0 70.2 South Atlantic.......................................................

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

b44.xls  

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

64,783 64,783 62,060 38,528 59,688 27,571 20,643 17,703 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 6,038 2,918 5,579 1,123 312 604 5,001 to 10,000 ................................. 6,585 6,090 3,061 5,726 1,109 686 781 10,001 to 25,000 ............................... 11,535 11,229 6,424 10,458 2,944 1,721 1,973 25,001 to 50,000 ............................... 8,668 8,297 5,176 8,001 3,662 2,191 2,013 50,001 to 100,000 ............................. 9,057 8,912 5,296 8,667 4,330 3,646 2,599 100,001 to 200,000 ........................... 9,064 8,732 6,042 8,612 5,268 4,349 3,473 200,001 to 500,000 ........................... 7,176 6,946 4,913 6,839 4,610 3,918 2,775 Over 500,000 .................................... 5,908 5,816 4,698 5,806 4,526 3,819 3,485 Principal Building Activity

182

b21.xls  

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

Buildings Buildings With Central Physical Plant All Buildings With Central Physical Plant All Buildings* .................................. 4,645 1,477 116 64,783 24,735 6,604 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 771 Q 6,789 2,009 Q 5,001 to 10,000 ................................. 889 259 Q 6,585 1,912 Q 10,001 to 25,000 ............................... 738 263 33 11,535 4,158 520 25,001 to 50,000 ............................... 241 92 18 8,668 3,277 630 50,001 to 100,000 ............................. 129 49 13 9,057 3,381 911 100,001 to 200,000 ........................... 65 28 12 9,064 3,935 1,723 200,001 to 500,000 ........................... 25 13 5 7,176 3,568 1,438 Over 500,000 .................................... 7 3 2 5,908 2,494 1,235 Principal Building Activity

183

b39.xls  

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

64,783 64,783 60,028 8,814 19,615 12,545 5,166 20,423 18,021 3,262 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 5,668 685 2,902 1,047 Q 461 1,159 330 5,001 to 10,000 ................................. 6,585 5,786 462 2,891 1,282 Q 773 1,599 Q 10,001 to 25,000 ............................... 11,535 10,387 1,400 4,653 2,129 289 2,164 2,765 456 25,001 to 50,000 ............................... 8,668 8,060 1,150 2,761 1,748 325 2,829 2,449 419 50,001 to 100,000 ............................. 9,057 8,718 1,524 2,086 1,819 549 3,497 3,328 450 100,001 to 200,000 ........................... 9,064 8,710 1,245 1,974 1,625 1,365 4,283 2,797 Q 200,001 to 500,000 ........................... 7,176 6,907 1,295 1,456 1,313 1,010 3,844 2,156 514 Over 500,000 .................................... 5,908 5,792

184

June2010.XLS  

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

-2008 -2008 2009 2010 2011 CHIEF FINANCIAL OFFICER Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec 1. Federal Loan Guarantee for Mississippi Integrated Gasification Combined Cycle, Moss Point, MS (DOE/EIS-0428) 2. Federal Loan Guarantee for Indiana Integrated Gasification Combined Cycle, Rockport, IN (DOE/EIS-0429) 3. Federal Loan Guarantee to Support Construction of the Taylorville Energy Center, Taylorville, IL (DOE/EIS-0430) 4. Federal Loan Guarantee for the Medicine Bow Fuel and Power Coal-to-Liquid Facility, Carbon County, WY (DOE/EIS-0432) ELECTRICITY DELIVERY AND ENERGY RELIABILITY 5. Presidential Permit Application, Energia Sierra Juarez

185

july2006.xls  

Gasoline and Diesel Fuel Update (EIA)

Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy of the Department of Energy or any other organization. For additional information, contact Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Section 1. Commentary Electric Power Data Monthly Flash Estimates of Data for: April 2006 The weather through April 2006 continued to be warmer than in 2005. Year-to-date heating degree days were down almost 9.3 percent through April. For April alone heating degree days were down 13.8 percent from last year and were 24.0 percent lower than normal. Cooling degree days for April 2006 were 97 percent higher than last year, although April is not a significant month for space heating.

186

c12.xls  

Gasoline and Diesel Fuel Update (EIA)

1,488 1,488 2,794 1,539 17,685 29,205 17,893 84.1 95.7 86.0 Building Floorspace (Square Feet) 1,001 to 5,000 ................................. 191 290 190 2,146 2,805 1,838 89.1 103.5 103.5 5,001 to 10,000 ............................... 131 231 154 1,972 2,917 1,696 66.2 79.2 91.0 10,001 to 25,000 ............................. 235 351 191 3,213 4,976 3,346 73.1 70.5 57.0 25,001 to 50,000 ............................. 172 328 173 2,449 4,128 2,091 70.4 79.4 82.5 50,001 to 100,000 ............................ 150 380 228 2,060 4,018 2,979 73.0 94.6 76.7 100,001 to 200,000 .......................... 214 438 281 2,124 3,947 2,993 100.7 111.1 94.0 200,001 to 500,000 .......................... 219 354 152 2,155 3,427 1,593 101.7 103.2 95.3 Over 500,000 ................................... 176 421 Q 1,566 2,986 1,357 112.1 141.2 Q Principal Building Activity

187

c2.xls  

Gasoline and Diesel Fuel Update (EIA)

Buildings* .................................. Buildings* .................................. 4,645 64,783 92,577 69,032 14,525 1,776 7,245 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 6,789 12,812 10,348 2,155 292 Q 5,001 to 10,000 ................................. 889 6,585 9,398 7,296 1,689 307 Q 10,001 to 25,000 ............................... 738 11,535 13,140 10,001 2,524 232 Q 25,001 to 50,000 ............................... 241 8,668 10,392 7,871 1,865 127 Q 50,001 to 100,000 ............................. 129 9,057 11,897 8,717 1,868 203 Q 100,001 to 200,000 ........................... 65 9,064 13,391 9,500 1,737 272 Q 200,001 to 500,000 ........................... 25 7,176 10,347 7,323 1,343 272 Q Over 500,000 .................................... 7 5,908 11,201 7,977 1,344 71 1,810 Principal Building Activity

188

c11.xls  

Gasoline and Diesel Fuel Update (EIA)

Buildings* ................................. Buildings* ................................. 1,188 2,208 2,425 13,374 29,260 22,149 88.8 75.5 109.5 Principal Building Activity Education ........................................ 63 423 334 808 5,378 3,687 78.3 78.6 90.7 Food Sales ...................................... 144 Q Q 765 467 Q 188.5 Q Q Food Service ................................... 318 108 Q 986 664 Q 322.9 163.2 Q Health Care ..................................... 32 104 457 445 835 1,883 71.8 125.1 242.9 Inpatient ........................................ N Q 436 N 182 1,723 N Q 252.9 Outpatient ...................................... 32 66 Q 445 652 160 71.8 100.5 Q Lodging ........................................... 29 207 273 260 2,274 2,563 111.0 91.2 106.7 Retail (Other Than Mall)................... 110 137 72 1,363 2,133 821 80.9 64.1 87.8 Office ...............................................

189

c17.xls  

Gasoline and Diesel Fuel Update (EIA)

32 32 116 153 2,942 9,867 11,373 10.8 11.7 13.5 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 4 9 20 345 652 908 12.7 13.8 22.0 5,001 to 10,000 ................................. 3 7 8 350 732 781 7.7 9.6 10.7 10,001 to 25,000 ............................... Q 16 20 Q 1,390 1,934 Q 11.2 10.5 25,001 to 50,000 ............................... Q 8 16 Q 944 1,534 Q 8.5 10.4 50,001 to 100,000 ............................. Q 15 21 Q 1,524 1,618 Q 10.2 12.9 100,001 to 200,000 ........................... Q 17 26 Q 1,703 1,671 Q 10.1 15.5 200,001 to 500,000 ........................... Q 22 24 Q 1,673 1,801 Q 13.1 13.1 Over 500,000 .................................... Q 22 18 Q 1,248 1,126 Q 17.3 16.4 Principal Building Activity Education .......................................... Q 12 16 Q 1,384 1,990 Q 8.4 7.9 Food Sales .......................................

190

march2007.xls  

Gasoline and Diesel Fuel Update (EIA)

Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Monthly Flash Estimates of Data for: January 2007 Section 1. Commentary Electric Power Data According to the National Oceanic and Atmospheric Administration (NOAA) Climatic Data Center, after "the 11th record warmest December on record in 2006", more typical winter conditions returned, particularly in the Eastern United States, in the latter part of January 2007. For the month, heating degree days were 26.1 percent higher than January 2006, but still 8.9 percent lower than normal. In January 2007, increased demand for winter heating, coupled with economic strength, as observed by growth in industrial production, resulted in a 7.7 percent growth in electricity generation compared to January 2006. (Industrial production increased 1.92

191

c38.xls  

Gasoline and Diesel Fuel Update (EIA)

Worker Worker (million Btu) per Building (thousand dollars) per Square Foot (dollars) per Thousand Pounds (dollars) All Buildings* .................................. 9,475 116.44 62.2 108.3 1.33 11.43 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... Q Q Q Q Q Q 5,001 to 10,000 ................................. Q Q Q Q Q Q 10,001 to 25,000 ............................... Q Q Q Q Q Q 25,001 to 50,000 ............................... Q Q Q Q Q Q 50,001 to 100,000 ............................. Q Q Q Q Q Q 100,001 to 200,000 ........................... 17,452 118.10 Q Q Q Q 200,001 to 500,000 ........................... 34,658 121.16 143.2 Q Q Q Over 500,000 .................................... 85,182 99.92 52.4 911.2 1.07 10.70 Principal Building Activity Education ..........................................

192

c6.xls  

Gasoline and Diesel Fuel Update (EIA)

21,344 21,521 31,595 18,118 16.79 12.74 16.22 19.88 1.65 1.26 1.35 1.60 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 2,298 3,235 4,752 2,526 19.47 15.74 19.77 23.48 2.24 1.71 1.88 1.89 5,001 to 10,000 .............................. 1,806 1,694 3,368 2,529 17.72 14.50 18.24 22.49 1.61 1.08 1.27 2.04 10,001 to 25,000 ............................ 2,606 3,157 4,530 2,846 17.56 13.85 18.09 19.03 1.32 1.02 1.03 1.36 25,001 to 50,000 ............................ 1,768 3,033 3,422 2,170 16.61 12.27 16.67 19.02 1.37 1.18 1.08 1.32 50,001 to 100,000 .......................... 3,479 2,592 3,959 1,866 17.16 12.25 15.52 20.88 1.71 1.15 1.15 1.41 100,001 to 200,000 ......................... 3,292 3,029 5,328 1,743 15.74 12.02 14.20 17.92 1.55 1.32 1.53 1.48 200,001 to 500,000 ......................... 2,877 2,798

193

august2006.xls  

Gasoline and Diesel Fuel Update (EIA)

Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Monthly Flash Estimates of Data for: June 2006 Section 1. Commentary Electric Power Data According to the National Climatic Data Center, the first half of 2006 was the warmest on record in the U.S. since recordkeeping began in 1895. Year-to-date cooling degree days through June 2006 were 11.7% higher than in 2005, and June cooling degree days were 12.7 percent higher than normal. As a result, retail sales of electricity through June were up 1.0 percent year-to-date, and increased 1.1 percent compared to June 2005. The average retail price of electricity was up 11.3 percent year-to-date, largely due to higher fuel prices. Year-to-date net generation through June was 0.7 percent higher than in 2005. June 2006 generation was up 0.5 percent compared

194

P1.xls  

Gasoline and Diesel Fuel Update (EIA)

P1. Energy Production Estimates in Physical Units, 2011 P1. Energy Production Estimates in Physical Units, 2011 Alabama 19,381 195,581 8,374 0 Alaska 2,149 356,225 204,829 0 Arizona 8,111 168 37 1,345 Arkansas 133 1,072,212 5,877 0 California 0 250,177 193,691 4,321 Colorado 26,890 1,637,576 39,125 3,057 Connecticut 0 0 0 0 Delaware 0 0 0 0 District of Columbia 0 0 0 0 Florida 0 15,125 2,023 0 Georgia 0 0 0 2,456 Hawaii 0 0 0 0 Idaho 0 0 0 1,321 Illinois 37,938 2,121 9,234 30,068 Indiana 37,544 9,075 1,987 22,547 Iowa 0 0 0 87,314 Kansas 37 309,124 41,503 10,676 Kentucky 108,971 124,243 2,326 866 Louisiana 3,865 3,029,206 68,984 37 Maine 0 0 0 0 Maryland 2,937 34 0 0 Massachusetts 0 0 0 0 Michigan 0 138,162 6,977 6,543 Minnesota 0 0 0 27,536 Mississippi 2,747 81,487 24,216 1,321 Missouri 465 0 118 6,261 Montana 42,008 74,624 24,151 0 Nebraska 0 1,959 2,542 47,120 Nevada 0 3 408 0 New Hampshire 0 0 0 0 New Jersey 0 0 0 0 New Mexico 21,922 1,237,303 71,274

195

january2007.xls  

Gasoline and Diesel Fuel Update (EIA)

Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Monthly Flash Estimates of Data for: November 2006 Section 1. Commentary Electric Power Data November is typically the month when generation reaches a trough before the winter season heating demand picks up in December. November 2006 was also warmer than normal and the heating degree days were 12.9 percent lower than normal. Consequently, total net generation in November 2006 was down 3.9 percent from October 2006, but was up 0.8 percent from November 2005. Similarly, retail sales of electricity in November 2006 were down 4.8 percent from October 2006, but were up 0.8 percent from November 2005. Year-to-date, through November 2006, total net generation rose 0.3 percent and retail sales of electricity were up 0.4 percent,

196

c20.xls  

Gasoline and Diesel Fuel Update (EIA)

120 120 224 166 219 161 10,393 17,076 11,375 15,172 9,290 11.5 13.1 14.6 14.5 17.3 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 19 26 14 31 23 1,204 1,595 918 1,759 871 15.7 16.5 14.9 17.8 26.3 5,001 to 10,000 .............................. 11 17 12 24 13 1,124 1,547 950 1,738 839 9.9 10.9 12.8 13.7 15.3 10,001 to 25,000 ............................ 18 29 23 25 24 2,183 3,140 1,402 2,822 1,823 8.3 9.2 16.1 9.0 13.3 25,001 to 50,000 ............................ 18 24 15 25 22 1,451 2,199 1,272 2,027 1,435 12.2 10.8 11.6 12.3 15.1 50,001 to 100,000 .......................... 15 32 24 28 19 1,295 2,549 1,823 2,037 1,327 11.8 12.6 13.2 13.8 14.3 100,001 to 200,000 ......................... 15 40 24 41 22 1,206 2,641 1,752 2,259 1,160 12.4 15.3 13.5 17.9 18.8 200,001 to 500,000 ......................... 14 27 21 25 19 1,115 1,943 1,619

197

november2005.xls  

Gasoline and Diesel Fuel Update (EIA)

and Stock Trends and Stock Trends Page 5 6. Month-to-Month Comparisons: Electric Power Retail Sales and Average Prices Page 6 7. Retail Sales Trends Page 7 8. Average Retail Price Trends Page 8 9. Heating and Cooling Degree Days Page 9 10. Documentation Page 10 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy of the Department of Energy or any other organization. For additional information, contact Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Section 1. Commentary Electric Power Data

198

april2005.xls  

Gasoline and Diesel Fuel Update (EIA)

February February 2005 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy of the Department of Energy or any other organization. For additional information, contact Stan Kaplan at 202-287-1803, or at stan.kaplan@eia.doe.gov. * Change in total consumption or generation for the latest 12 month period (March 2004 to February 2005) compared to the prior 12 month period ( March 2003 to February 2004). Latest 12 Month Period* 6.0% 0.8% n/a Year to Date: -2.9% -1.4% n/a February 2004 -11.9% -2.7% -8.4% January 2005

199

c7.xls  

Gasoline and Diesel Fuel Update (EIA)

294 294 978 1,254 2,964 9,941 11,595 99.0 98.3 108.1 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 33 85 146 360 666 974 91.2 128.1 149.7 5,001 to 10,000 ................................. Q 64 73 359 764 843 Q 83.7 86.8 10,001 to 25,000 ............................... Q 115 163 553 1,419 1,934 Q 81.2 84.3 25,001 to 50,000 ............................... Q 74 140 347 944 1,618 Q 78.7 86.8 50,001 to 100,000 ............................. Q 134 148 516 1,524 1,618 Q 87.8 91.5 100,001 to 200,000 ........................... Q 150 203 414 1,703 1,682 Q 87.9 120.8 200,001 to 500,000 ........................... Q 177 214 Q 1,673 1,801 Q 105.8 118.8 Over 500,000 .................................... Q Q Q Q 1,248 1,126 Q Q Q Principal Building Activity Education .......................................... Q 143

200

c35.xls  

Gasoline and Diesel Fuel Update (EIA)

65 65 170 104 63 6,080 2,832 4,122 2,123 0.21 0.06 0.03 Q Building Floorspace (Square Feet) 1,001 to 10,000 ............................... 381 Q Q Q 757 Q 255 Q 0.50 Q 0.10 Q 10,001 to 100,000 ........................... 375 63 Q Q 1,704 643 833 351 0.22 0.10 Q Q Over 100,000 .................................. 509 20 44 Q 3,618 1,983 3,034 1,673 0.14 0.01 0.01 Q Principal Building Activity Education ........................................ 282 Q Q Q 933 Q Q Q 0.30 Q Q Q Health Care...................................... Q Q 17 7 Q 492 786 262 Q Q 0.02 0.03 Office .............................................. 105 6 14 1 1,379 714 1,235 748 0.08 0.01 0.01 0.00 All Others ........................................ 837 Q 44 40 3,426 1,281 1,644 984 0.24 Q 0.03 Q Year Constructed 1945 or Before ................................ 555 Q Q Q 2,126 Q Q Q 0.26 Q Q Q 1946 to 1959 ...................................

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

c24.xls  

Gasoline and Diesel Fuel Update (EIA)

Buildings* ................................. Buildings* ................................. 782 43.0 36.0 17.6 37.1 70.9 6.1 0.33 7.77 Building Floorspace (Square Feet) 1,001 to 5,000 ................................. 219 78.7 42.6 23.7 46.3 92.0 1.9 0.70 8.88 5,001 to 10,000 ............................... 408 54.8 42.5 13.9 28.8 65.7 3.4 0.46 8.34 10,001 to 25,000 ............................. 667 42.5 40.8 14.4 29.2 52.1 5.6 0.36 8.41 25,001 to 50,000 ............................. 1,483 41.5 39.1 16.0 31.5 55.3 11.1 0.31 7.46 50,001 to 100,000 ............................ 2,498 35.4 39.1 10.1 27.6 48.8 19.7 0.28 7.90 100,001 to 200,000 .......................... 5,029 36.3 26.1 6.1 23.6 55.2 36.2 0.26 7.19 200,001 to 500,000 .......................... 10,234 35.0 35.5 10.0 22.7 47.2 69.2 0.24 6.76 Over 500,000 ................................... 39,551 43.0 28.8 2.8 20.0

202

c27.xls  

Gasoline and Diesel Fuel Update (EIA)

73 73 343 512 1,465 7,716 9,570 49.5 44.4 53.5 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... Q 41 68 Q 417 729 Q 99.5 93.6 5,001 to 10,000 ................................. Q 31 43 Q 482 654 Q 64.8 66.0 10,001 to 25,000 ............................... Q 45 90 Q 931 1,681 Q 47.9 53.6 25,001 to 50,000 ............................... Q 39 70 Q 829 1,422 Q 47.4 49.5 50,001 to 100,000 ............................. Q 43 73 Q 1,263 1,554 Q 34.1 47.2 100,001 to 200,000 ........................... Q 41 67 Q 1,445 1,264 Q 28.3 52.7 200,001 to 500,000 ........................... Q 55 56 Q 1,484 1,277 Q 37.3 44.1 Over 500,000 .................................... Q 47 44 Q 865 989 Q 54.0 44.4 Principal Building Activity Education .......................................... Q 49 99 Q 1,247 1,804 Q 39.5 54.6 Food Sales .......................................

203

c4.xls  

Gasoline and Diesel Fuel Update (EIA)

Buildings* .................................. Buildings* .................................. 4,645 64,783 13.9 92,577 19.9 1.43 15.91 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 6,789 2.7 12,812 5.0 1.89 19.08 5,001 to 10,000 ................................. 889 6,585 7.4 9,398 10.6 1.43 18.22 10,001 to 25,000 ............................... 738 11,535 15.6 13,140 17.8 1.14 16.93 25,001 to 50,000 ............................... 241 8,668 35.9 10,392 43.1 1.20 15.44 50,001 to 100,000 ............................. 129 9,057 70.4 11,897 92.5 1.31 15.68 100,001 to 200,000 ........................... 65 9,064 138.8 13,391 205.1 1.48 14.34 200,001 to 500,000 ........................... 25 7,176 289.0 10,347 416.7 1.44 14.28 Over 500,000 .................................... 7 5,908 896.1 11,201 1698.8 1.90 14.62 Principal Building Activity

204

c33.xls  

Gasoline and Diesel Fuel Update (EIA)

per per Building (gallons) per Square Foot (gallons) per Worker (gallons) per Building (thousand dollars) per Square Foot (dollars) per Gallon (dollars) All Buildings* .................................. 3,555 0.11 81.6 3.9 0.12 1.11 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 1,187 0.41 315.2 1.4 0.49 1.18 5,001 to 10,000 ................................. 2,639 0.37 456.4 3.1 0.43 1.17 10,001 to 25,000 ............................... 3,238 0.20 218.5 3.8 0.24 1.18 25,001 to 50,000 ............................... 5,383 0.14 109.4 5.8 0.15 1.08 50,001 to 100,000 ............................. 8,163 0.11 78.4 8.8 0.12 1.08 100,001 to 200,000 ........................... 12,681 0.09 80.6 13.1 0.09 1.03 200,001 to 500,000 ........................... 22,353 0.08 62.1 23.6 0.08

205

october2005.xls  

Gasoline and Diesel Fuel Update (EIA)

and Stock Trends and Stock Trends Page 5 6. Month-to-Month Comparisons: Electric Power Retail Sales and Average Prices Page 6 7. Retail Sales Trends Page 7 8. Average Retail Price Trends Page 8 9. Heating and Cooling Degree Days Page 9 10. Documentation Page 10 Monthly Flash Estimates of Data for: August 2005 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy of the Department of Energy or any other organization. For additional information, contact Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov.

206

P2.xls  

Gasoline and Diesel Fuel Update (EIA)

P2. Energy Production Estimates in Trillion Btu, 2011 P2. Energy Production Estimates in Trillion Btu, 2011 Alabama 468.7 226.8 48.6 411.8 0.0 245.3 245.3 1,401.2 Alaska 33.5 404.7 1,188.0 0.0 0.0 15.7 15.7 1,641.9 Arizona 174.8 0.2 0.2 327.3 7.8 107.4 115.2 617.7 Arkansas 3.0 1,090.9 34.1 148.5 0.0 113.5 113.5 1,390.0 California 0.0 279.7 1,123.4 383.6 25.0 812.8 837.8 2,624.6 Colorado 586.8 1,831.2 226.9 0.0 17.7 84.0 101.7 2,746.7 Connecticut 0.0 0.0 0.0 166.7 0.0 29.9 29.9 196.5 Delaware 0.0 0.0 0.0 0.0 0.0 3.8 3.8 3.8 District of Columbia 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 Florida 0.0 15.4 11.7 230.4 0.0 266.7 266.7 524.2 Georgia 0.0 0.0 0.0 338.1 14.2 192.1 206.3 544.4 Hawaii 0.0 0.0 0.0 0.0 0.0 19.1 19.1 19.1 Idaho 0.0 0.0 0.0 0.0 7.6 172.8 180.4 180.4 Illinois 864.2 3.7 53.6 1,002.7 174.0 102.3 276.3 2,200.5 Indiana 841.0 9.2 11.5 0.0 130.5 71.2 201.7 1,063.4 Iowa 0.0 0.0 0.0 54.6 505.3 140.7 645.9 700.5 Kansas 0.8 356.8 240.7 76.6 61.8

207

june2005.xls  

Gasoline and Diesel Fuel Update (EIA)

and Stock Trends and Stock Trends Page 5 6. Month-to-Month Comparisons: Electric Power Retail Sales and Average Prices Page 6 7. Retail Sales Trends Page 7 8. Average Retail Price Trends Page 8 9. Heating and Cooling Degree Days Page 9 10. Documentation Page 10 Monthly Flash Estimates of Data for: April 2005 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy of the Department of Energy or any other organization. For additional information, contact Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov.

208

oil1993.xls  

Gasoline and Diesel Fuel Update (EIA)

(thousand Household Member (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 13.8 11.6 29.8 92 36 77.5 28 604 0.23 506 186 Census Region and Division Northeast 7.9 5.9 17.2 133 45 98.7 36 854 0.29 636 234 New England 2.8 2.4 6.6 125 45 105.6 40 819 0.30 691 262 Middle Atlantic 5.0 3.5 10.6 138 45 94.8 34 878 0.29 605 219 Midwest 2.3 2.2 6.0 60 22 58.4 21 378 0.14 370 132 East North Central 1.5 1.5 4.1 51 19 49.3 18 328 0.12 318 116 West North Central 0.7 0.7 2.0 78 29 77.8 27 481 0.18 481 165 South 3.1 2.9 5.4 43 24 41.0 15 306 0.17 292 108 South Atlantic 2.6 2.5 4.6 47 26 44.4 16 334 0.18 316 116 East South Central 0.4 0.4 0.6 24 14 23.8 9 168 0.10 168 65 West South Central Q Q Q 5 2 4.8 2 47 0.02 47 18 West 0.6 0.5 1.2 61 27 58.8 23 444 0.20 427 164 Mountain

209

april2006.xls  

Gasoline and Diesel Fuel Update (EIA)

Monthly Flash Estimates of Monthly Flash Estimates of Data for: February 2006 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy of the Department of Energy or any other organization. For additional information, contact Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Section 1. Commentary Electric Power Data After an unusually warm January, February weather reverted to a historically more normal seasonal pattern. February 2006 heating degree days were, however, still 8 percent higher than in February 2005, which had been warmer than normal.

210

sup_elec.xls  

Gasoline and Diesel Fuel Update (EIA)

0. Electric Power Projections for EMM Region 0. Electric Power Projections for EMM Region East Central Area Reliability Coordination Agreement 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Electricity Generating Capacity 1/ (gigawatts) Coal Steam 84.34 84.34 84.33 84.17 83.59 82.17 81.85 81.85 81.32 81.32 81.32 81.32 81.32 Other Fossil Steam 2/ 3.83 3.83 3.83 3.83 3.83 3.83 3.83 3.83 3.81 3.81 3.81 3.81 3.81 Combined Cycle 4.24 8.72 11.97 12.95 12.95 12.95 12.95 12.95 12.91 12.91 13.96 14.60 15.67 Combustion Turbine/Diesel 13.84 19.59 21.22 21.22 21.14 21.14 21.11 21.08 18.97 19.21 19.83 19.93 20.20 Nuclear Power 7.68 7.69 7.72 7.72 7.72 7.72 7.72 7.72 7.72 7.72 7.72 7.72 7.72 Pumped Storage/Other 3/ 3.36 3.36 3.36 3.36 3.36 3.36 3.36 3.36 3.36 3.36 3.36 3.36 3.36 Fuel Cells 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Renewable Sources 4/ 1.72

211

march2007.xls  

Gasoline and Diesel Fuel Update (EIA)

7 7 Section 1. Commentary Electric Power Data During March 2007, the contiguous U.S. experienced the second warmest March over the 1895-2007 time period. Heating degree days were 15.7 percent lower than normal, as measured over the 1971-2000 time period, and 16.7 percent lower than March 2006. Despite the unseasonably warm March, retail sales of electricity increased 0.8 percent compared to March 2006, while March 2007 generation of electric power increased 0.9 percent over March 2006. These increases were primarily due to economic growth, evident by a 2.1-percent increase in the real gross domestic product for the U.S. in the first quarter of 2007 over the first quarter of 2006. The average U.S. retail price of electricity for March 2007 showed a 5.0-percent

212

2010 APS.xls  

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

Allison to Marcinowski SUBJECT: NEPA 2010 APS for DOE-SRS Allison to Marcinowski SUBJECT: NEPA 2010 APS for DOE-SRS *Title, Location Estimated Cost Description Determination Date: uncertain Transmittal to State: uncertain EA Approval: uncertain tbd FONSI: uncertain Total Estimated Cost tbd Annual NEPA Planning Summary Environmental Assessments (EAs) Expected to be Initiated in the Next 12 Months Department of Energy (DOE) Savannah River Site (SRS) Jan-10 Estimated Schedule (**NEPA Milestones) DOE SRS expects to initiate one or more new EAs over the next 12 months. * Please include projected NEPA milestones, if planned. 1 of 6 Annual NEPA Planning Summary (2010) DOE Savannah River Site Attachment: Memo, Allison to Marcinowski SUBJECT: NEPA 2010 APS for DOE-SRS *Title, Location Estimated Cost Description Determination Date:

213

LNG 2006.xls  

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

6 6 Jan Feb March April May June July Aug Sept Oct Nov Dec TOTAL Algeria 3.0 2.8 3.0 2.8 0.0 2.8 3.0 0.0 0.0 0.0 0.0 0.0 17.4 Malaysia 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Nigeria 3.0 3.1 0.0 6.0 3.1 6.0 6.1 6.2 6.0 9.0 5.7 3.1 57.3 Oman 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Trinidad 30.5 27.6 30.2 36.4 44.3 38.6 33.4 37.0 25.2 24.7 24.6 36.7 389.3 Egypt 3.0 5.3 0.0 13.6 19.8 14.3 15.0 8.9 8.8 2.6 16.9 11.4 119.5 Qatar 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 TOTAL 39.5 38.7 33.2 58.8 67.3 61.7 57.6 52.1 40.0 36.2 47.2 51.2 583.5 LNG Imports by Receiving Terminal (Bcf) 2006 Jan Feb March April May June July Aug Sept Oct Nov Dec TOTAL Cove Point, MD 11.9 11.0 8.9 14.4 11.6 14.6 12.0 11.8 5.4 3.0 3.0 9.0 116.6 Elba Island, GA 7.9 7.9 7.9 13.4 13.7 13.8 13.6 16.8 13.9 10.4 13.5 14.0 146.8 Everett, MA 16.6 16.8 16.4 13.9 16.6 13.6 14.3 14.2 9.1 13.9 14.0 16.6 176.1 Lake Charles, LA 3.0 3.1

214

Webinar Schedule.xls  

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

Session Session Date Time Conference Number iPortal Web Conference ID Session 1 Monday, September 14 12:00 PM ET 202-287-5293 259443 Session 2 Monday, September 14 03:00 PM ET 301-903-7073 259451 Session 3 Tuesday, September 15 12:00 PM ET 202-586-9248 259463 Session 4 Tuesday, September 15 03:00 PM ET 301-903-7073 259476 Session 5 Wednesday, September 16 12:00 PM ET 301-903-7073 259481 Session 6 Wednesday, September 16 03:00 PM ET 301-903-7073 259491 Session 7 Thursday, September 17 12:00 PM ET 202-287-5293 259505 Session 8 Thursday, September 17 03:00 PM ET 301-903-7073 259519 Session 9 Friday, September 18 12:00 PM ET 202-287-5293 259522 Session 10 Friday, September 18 03:00 PM ET 301-903-7073 259540 Session 11 Monday, September 21 12:00 PM ET 202-287-5293 259557 Session 12 Monday, September 21 03:00 PM ET 301-903-7073

215

VSC's.xls  

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

e e Description of Organization VSC name VSC e-mail Phone # DOE - Bonneville Power Administration Carolyn Stokke ccstokke@bpa.gov 360-418-2330 DOE - Southeastern Power Administration Carol Rice carolr@sepa.doe.gov 706-213-3822 DOE - Southwestern Power Administration Cheryl Crosswell & Shirley Shumate cheryl.crosswell@swpa.gov; shirley.shumate@swpa.gov 918/595-6616; 918/595-6686 DOE - Western Area Power Administration Frances Hamada hamada@wapa.gov 801/524-6379 DOE - Office of the CFO Teresa Collins Teresa.Collins@hq.doe.gov 202/586-4459 DOE - Congressional and Intergovernmental Affairs Liz Renner elizabeth.renner@hq.doe.gov 202/586-5450 DOE - Office of Economic Impact and Diversity Dan Broehl daniel.broehl@hq.doe.gov 202-586-0696 DOE - Office of Energy Efficiency and Renewable Energy Nicole McGowan

216

b12.xls  

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

64,783 64,783 9,874 1,255 1,654 1,905 1,258 5,096 4,317 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 409 409 544 N 165 99 638 5,001 to 10,000 ................................. 6,585 399 356 442 N 280 160 725 10,001 to 25,000 ............................... 11,535 931 Q 345 Q 312 631 1,284 25,001 to 50,000 ............................... 8,668 1,756 Q Q Q Q 803 578 50,001 to 100,000 ............................. 9,057 2,690 Q Q Q 206 841 Q 100,001 to 200,000 ........................... 9,064 2,167 Q N Q Q 930 524 200,001 to 500,000 ........................... 7,176 1,420 N Q 467 Q 1,185 Q Over 500,000 .................................... 5,908 Q N N 973 N Q Q Year Constructed Before 1920 ...................................... 3,769 410 Q 281 Q Q Q 220 1920 to 1945 .....................................

217

eia176.xls  

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

1 1 7 6 EIA-176 Ben Franklin Station Address 2: City: State: Zip: - Distribution company - investor owned Storage operator Distribution company - municipally owned Synthetic natural gas (SNG) plant operator Distribution company - privately owned Producer Distribution company - cooperative Distribution company - other ownership Interstate pipeline (FERC regulated) Intrastate pipeline B. Vehicles Powered by Alternative Fuels Does your company's vehicle fleet include vehicles powered by alternative fuels? No D. Sales/Acquisitions No or sale this year? If Yes, please describe the sale or acquisition in the Comments box below. Page 1 C. Customer Choice Program Participating Eligible If there is a Customer Choice program available in your service territory, enter the number

218

Table 2.xls  

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

Project-level Reductions and Sequestration Reported, Data Year 2005 Project-level Reductions and Sequestration Reported, Data Year 2005 (Metric Tons Carbon Dioxide Equivalent) 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Indirect 1 85 621 699 3,129 3,411 4,120 3,850 5,988 4,211 6,193 4,890 4,102 6,243 Sequestration 1,540,000 1,540,000 1,540,000 1,540,000 1,540,000 1,540,000 1,540,000 1,540,000 1,540,000 1,540,000 1,540,000 1,540,000 1,540,000 1,540,000 Direct 16 Indirect 16,191 14,656 17,745 17,748 17,859 19,897 18,925 21,070 85,711 118,115 156,534 236,368 215,033 214,678 220,420 Sequestration 4,150,000 4,150,000 4,150,000 4,150,000 4,150,000 4,150,000 4,150,000 4,150,000 4,150,000 4,150,000 4,150,000 4,150,000 4,150,000 Sequestration 550,000 70,000 290,000 370,000 480,000 440,000 440,000 590,000 530,000 370,000 410,000 410,000 410,000 410,000 410,000 Direct 1,091 38,702 44,227

219

schedule_2006.xls  

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

6 Long Range Operations Schedule 6 Long Range Operations Schedule (October 2005 - September 2006) 1 1 1 1 → 1 1 1 4 → 1 1 1 1 1 1 2 2 4 → 2 1 → 2 2 2 4 2 2 2 2 2 1 → 2 3 3 4 3 1 → 3 3 3 4 3 3 3 3 3 1 → 3 4 4 4 4 1 → 4 4 4 4 4 4 4 4 4 1 → 4 5 5 4 5 1 → 5 5 5 4 5 5 5 5 5 1 → 5 6 6 4 6 1 6 6 6 4 6 6 6 6 6 1 → 6 7 7 4 7 1 → 7 7 7 4 7 7 7 7 7 1 → 7 8 8 4 8 1 → 8 8 8 4 → 8 8 8 8 8 1 8 9 9 9 1 → 9 9 9 4 9 9 9 9 9 1 → 9 10 10 10 1 → 10 10 10 4 10 10 10 10 10 1 → 10 11 11 11 1 → 11 11 11 4 11 11 11 11 11 1 → 11 12 12 12 1 → 12 12 12 4 12 1 → 12 12 12 4 → 12 1 → 12 13 13 13 1 13 13 13 4 13 1 → 13 13 13 4 13 1 → 13 14 14 14 5 → 14 14 14 14 1 → 14 14 14 4 14 1 → 14 15 15 15 5 15 15 15 15 1 → 15 15 15 4 15 1 15 16 16 16 5 16 16 16 16 1

220

table14.xls  

Gasoline and Diesel Fuel Update (EIA)

Table 14. Natural Gas Wellhead Prices, Actual vs. Reference Case Projections Table 14. Natural Gas Wellhead Prices, Actual vs. Reference Case Projections (current dollars per thousand cubic feet) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 AEO 1982 4.32 5.47 6.67 7.51 8.04 8.57 AEO 1983 2.93 3.11 3.46 3.93 4.56 5.26 12.74 AEO 1984 2.77 2.90 3.21 3.63 4.13 4.79 9.33 AEO 1985 2.60 2.61 2.66 2.71 2.94 3.35 3.85 4.46 5.10 5.83 6.67 AEO 1986 1.73 1.96 2.29 2.54 2.81 3.15 3.73 4.34 5.06 5.90 6.79 7.70 8.62 9.68 10.80 AEO 1987 1.83 1.95 2.11 2.28 2.49 2.72 3.08 3.51 4.07 7.54 AEO 1989* 1.62 1.70 1.91 2.13 2.58 3.04 3.48 3.93 4.76 5.23 5.80 6.43 6.98 AEO 1990 1.78 1.88 2.93 5.36 AEO 1991 1.77 1.90 2.11 2.30 2.42 2.51 2.60 2.74 2.91 3.29 3.75 4.31 5.07 5.77 6.45 AEO 1992 1.69 1.85 2.03 2.15 2.35 2.51 2.74 3.01 3.40 3.81 4.24 4.74 5.25 5.78 AEO 1993 1.85 1.94 2.09 2.30 2.44 2.60 2.85 3.12 3.47 3.84 4.31 4.81 5.28

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

crib.xls  

Buildings Energy Data Book [EERE]

August 2003 August 2003 D I S C L A I M E R This document was designed for the internal use of the United States Department of Energy. This document will be occasionally updated and, therefore, this copy may not reflect the most current version. This document was prepared as account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or

222

recommendations.xls  

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

6, 2003 Electric System Working Group Technical Conference, Philadelphia PA 6, 2003 Electric System Working Group Technical Conference, Philadelphia PA Rec Type Recommendations/Comments Name Organization Communication The reliability coordinator needs an understanding from others, from a broad perspective, what's going on. Sometimes you may not have all the information, and this is what happens most times in blackout situations. Michael Calimano New York ISO System Operations Reliability coordination needs to have authority in real time to order actions to be taken by control areas or operators under emergency conditions. Authorities and procedures have to be spelled out well beforehand. Michael Calimano New York ISO Emergency Response We have to look at how we can do this better, how we can let other people know better and faster. In our shop, when there is an emergency going, everybody's involved in

223

c15.xls  

Gasoline and Diesel Fuel Update (EIA)

7 7 216 375 152 12,809 16,701 22,766 11,030 11.5 12.9 16.5 13.8 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 13 30 50 19 997 1,729 2,324 1,295 13.4 17.5 21.7 14.6 5,001 to 10,000 ................................. 10 15 33 19 1,083 1,447 2,454 1,214 9.0 10.7 13.4 15.3 10,001 to 25,000 ............................... 19 29 49 22 1,944 3,098 4,266 2,063 9.6 9.3 11.6 10.9 25,001 to 50,000 ............................... 12 31 41 19 1,292 2,483 3,012 1,599 9.0 12.6 13.7 11.7 50,001 to 100,000 ............................. 22 29 50 17 2,040 2,260 3,435 1,296 11.0 12.9 14.6 13.1 100,001 to 200,000 ........................... 25 33 66 18 2,117 2,285 3,439 1,177 11.6 14.6 19.1 15.0 200,001 to 500,000 ........................... 24 28 38 16 1,781 2,196 1,909 1,166 13.3 12.7 20.1 13.7 Over 500,000 ....................................

224

oil1987.xls  

Gasoline and Diesel Fuel Update (EIA)

7.4 7.4 14.0 33.3 87 37 70.3 27 513 0.22 414 156 Census Region and Division Northeast 9.1 6.3 17.8 140 49 96.0 37 808 0.28 556 212 New England 2.6 2.0 5.8 130 46 102.1 39 770 0.27 604 233 Middle Atlantic 6.5 4.2 12.1 144 51 93.6 36 826 0.29 537 204 Midwest 3.1 3.0 7.1 53 23 51.8 19 318 0.13 309 113 East North Central 2.5 2.4 5.9 56 23 54.2 19 334 0.14 326 116 West North Central 0.6 0.6 1.2 43 21 41.6 17 250 0.12 239 96 South 4.6 4.2 7.0 41 24 37.0 14 257 0.15 233 87 South Atlantic 3.6 3.2 5.3 46 27 41.1 15 285 0.17 256 95 East South Central 1.0 0.9 1.5 27 16 25.8 10 175 0.11 168 63 West South Central Q Q Q 10 4 6.9 4 73 0.03 49 26 West 0.6 0.6 1.4 32 13 31.1 12 195 0.08 190 76 Mountain 0.2 0.2 0.3 26 12 26.1 11 144 0.07 144 62 Pacific 0.4 0.4 1.1 34 14 32.9 13 213 0.08 207 81 Metropolitan Statistical Area Urban 12.6 9.4 24.6 102 39 75.9 29 596 0.23 444 167 Central City 5.0 2.8 7.2 119 47 66.9 29 664 0.26 372 160 Suburban 7.6 6.6 17.4 94 36

225

c8.xls  

Gasoline and Diesel Fuel Update (EIA)

436 436 1,064 309 5,485 12,258 3,393 79.5 86.8 91.1 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 60 116 36 922 1,207 538 64.9 96.5 67.8 5,001 to 10,000 ................................. 44 103 Q 722 1,387 393 60.5 74.0 Q 10,001 to 25,000 ............................... 65 126 Q 1,164 2,240 810 55.9 56.4 Q 25,001 to 50,000 ............................... 107 112 Q 949 1,672 498 112.5 67.3 Q 50,001 to 100,000 ............................. 64 123 59 642 1,470 650 99.0 83.4 91.3 100,001 to 200,000 ........................... 49 237 Q 614 2,087 Q 79.8 113.5 Q 200,001 to 500,000 ........................... Q 110 Q 395 1,072 Q Q 102.2 Q Over 500,000 .................................... Q 137 Q Q 1,123 Q Q 122.1 Q Principal Building Activity Education .......................................... 45 198 Q 552 2,445

226

c30.xls  

Gasoline and Diesel Fuel Update (EIA)

418 418 659 327 347 119 7,645 12,850 8,113 10,509 4,350 54.7 51.3 40.3 33.0 27.3 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 56 81 35 55 16 660 979 421 789 234 85.0 82.9 82.5 69.8 66.6 5,001 to 10,000 .............................. 47 53 27 59 16 644 944 526 1,212 367 72.5 56.5 51.2 49.0 43.9 10,001 to 25,000 ............................ 88 103 50 47 13 1,679 2,134 958 1,781 501 52.4 48.0 51.7 26.4 25.9 25,001 to 50,000 ............................ 59 87 52 34 18 1,251 1,839 1,031 1,441 463 47.2 47.2 50.4 23.7 38.6 50,001 to 100,000 .......................... 55 88 42 41 11 1,043 2,129 1,300 1,569 642 52.4 41.5 32.3 26.0 16.5 100,001 to 200,000 ......................... 35 114 31 Q 9 970 2,090 1,320 1,550 714 36.2 54.5 23.4 34.0 12.4 200,001 to 500,000 ......................... 54 61 38 31 15 1,001 1,471 1,380 1,161 666 53.6 41.7 27.3

227

wf01.xls  

Gasoline and Diesel Fuel Update (EIA)

-00 -00 00-01 01-02 02-03 03-04 Average 99-04 04-05 Warm Base Cold Warm Base Cold Natural Gas Northeast Consumption (mcf**) 81.7 87.3 67.7 87.4 79.9 80.8 79.8 71.9 78.8 85.7 -9.9 -1.3 7.4 Price ($/mcf) 8.39 10.01 9.41 9.74 11.47 9.81 12.90 16.82 17.18 17.73 30.4 33.2 37.4 Expenditures ($) 685 874 637 851 917 793 1,029 1,208 1,353 1,518 17.5 31.6 47.6 Natural Gas (Midwest) Consumption (mcf) 88.3 99.1 78.2 92.3 85.7 88.7 85.3 81.1 88.9 96.7 -4.9 4.2 13.3 Price ($/mcf) 5.74 8.77 6.26 7.61 8.76 7.48 10.01 14.71 15.48 16.36 46.9 54.6 63.4 Expenditures ($) 507 869 490 702 751 664 855 1,194 1,377 1,583 39.7 61.1 85.2 South Consumption (mcf) 55.6 67.1 52.7 60.3 55.4 58.2 53.8 52.1 56.6 61.2 -3.2 5.3 13.7 Price ($/mcf) 7.65 10.22 8.17 9.02 10.67 9.19 12.35 17.53 18.33 19.24 41.9 48.4 55.8 Expenditures ($) 425 685 431 543 591 535 664 913 1,038

228

LNG 2005.xls  

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

5 5 Jan Feb March April May June July Aug Sept Oct Nov Dec TOTAL Algeria 6.0 11.3 2.8 9.0 11.4 12.0 6.0 3.2 6.0 11.8 9.0 8.6 97.2 Malaysia 3.0 0.0 2.6 0.0 0.0 0.0 0.0 0.0 0.0 3.1 0.0 0.0 8.7 Nigeria 2.7 0.0 0.0 0.0 0.0 0.0 0.0 2.6 0.0 2.9 0.0 0.0 8.1 Oman 2.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.5 Trinidad 43.7 39.2 40.4 35.7 41.2 41.5 41.2 26.8 34.8 33.2 30.1 31.4 439.2 Egypt 0.0 0.0 0.0 2.9 0.0 2.9 5.9 11.1 11.0 8.5 18.9 11.3 72.5 Qatar 0.0 3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.0 TOTAL 57.8 53.5 45.9 47.6 52.6 56.4 53.1 43.6 51.8 59.6 58.0 51.3 631.3 LNG Imports by Receiving Terminal (Bcf) 2005 Jan Feb March April May June July Aug Sept Oct Nov Dec TOTAL Cove Point, MD 18.3 20.6 18.7 17.1 23.5 20.7 20.4 8.3 17.3 17.6 18.8 20.5 221.7 Elba Island, GA 7.9 10.6 7.9 7.8 7.9 13.3 13.1 11.1 15.6 13.6 12.5 10.7 132.1 Everett, MA 18.0 13.8 16.7 13.6 12.8 13.4 13.6 13.3 10.4 16.5 12.3 14.3 168.5 Lake Charles, LA 13.7

229

longterm.xls  

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

Operations Schedule Operations Schedule Run 2008-3 Run 2009-1 Run 2009-2 Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep 1 1 4 4 4 1 1 1 1 1 1 1 1 1 1 1 4 4 4 1 1 2 2 4 4 4 2 2 2 2 1 1 1 2 2 2 2 4 2 2 3 3 4 3 3 3 3 1 3 3 3 3 3 3 4 4 4 4 4 4 1 1 4 4 4 4 4 4 5 5 1 1 5 5 5 5 1 1 1 5 5 5 5 5 5 6 6 1 1 1 6 6 6 6 1 1 1 6 6 6 6 1 1 6 6 7 7 1 1 1 7 7 7 7 1 1 1 7 7 7 7 1 1 1 7 7 8 8 1 1 1 8 8 8 8 1 1 1 8 8 8 8 1 1 1 8 8 9 9 1 1 1 9 9 9 9 1 1 1 9 9 9 9 1 1 1 9 9 10 10 1 1 1 10 4 4 10 10 10 1 10 10 10 10 1 1 1 10 10 11 11 1 11 4 4 4 11 11 11 4 4 11 11 11 11 1 1 1 11 11 12 12 1 1 12 4 4 4 12 12 12 4 4 4 12 12 12 12 1 1 1 12 4 4 12 13 13 1 1 1 13 4 4 4 13 13 13 4 4 4 13 13 13 13 1 1 1 13

230

b11.xls  

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

Table B11. Selected Principal Building Activity: Part 1, Number of Buildings for Non- Table B11. Selected Principal Building Activity: Part 1, Number of Buildings for Non- Mall Buildings, 2003 Principal Building Activity Number of Buildings (thousand) Health Care All Buildings* Education Food Sales Food Service Lodging Retail (Other Than Mall) Energy Information Administration 2003 Commercial Buildings Energy Consumption Survey: Building Characteristics Tables Revised June 2006 81 Released: June 2006 Next CBECS will be conducted in 2007 Inpatient Outpatient All Buildings* .................................. 4,645 386 226 297 8 121 142 443 Table B11. Selected Principal Building Activity: Part 1, Number of Buildings for Non- Mall Buildings, 2003 Principal Building Activity Number of Buildings (thousand) Health Care All Buildings* Education Food Sales Food Service Lodging

231

b20.xls  

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

64,783 64,783 45,144 10,960 1,958 1,951 2,609 2,161 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 5,613 916 Q Q N 223 5,001 to 10,000 ................................. 6,585 5,304 1,031 Q N Q Q 10,001 to 25,000 ............................... 11,535 9,098 1,732 383 Q Q Q 25,001 to 50,000 ............................... 8,668 5,807 1,837 355 Q Q Q 50,001 to 100,000 ............................. 9,057 6,218 1,739 273 337 Q Q 100,001 to 200,000 ........................... 9,064 6,102 1,545 539 Q Q Q 200,001 to 500,000 ........................... 7,176 4,246 1,361 Q 389 531 Q Over 500,000 .................................... 5,908 2,756 800 Q Q 1,522 Q Principal Building Activity Education .......................................... 9,874 8,714 946 Q N N N Food Sales .......................................

232

b38.xls  

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

Revised June 2006 Revised June 2006 194 Released: Dec 2006 Next CBECS will be conducted in 2007 Heat Pumps Furnaces Individual Space Heaters District Heat Boilers Packaged Heating Units Other All Buildings* .................................. 4,645 3,982 476 1,864 819 65 579 953 205 Table B38. Heating Equipment, Number of Buildings for Non-Mall Buildings, 2003 Heating Equipment (more than one may apply) Number of Buildings (thousand) All Buildings* Heated Buildings Number of Floors One ................................................... 3,136 2,566 334 1,193 550 14 190 682 140 Two ................................................... 1,031 960 97 487 174 19 194 207 50 Three ................................................ 339 319 31 155 68 10 119 41 Q Four to Nine ...................................... 128 125 11 28 25 19 69 20 4 Ten or More ......................................

233

b37.xls  

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

Floor- Floor- space a Heated Floor- space b Total Floor- space a Cooled Floor- space b Total Floor- space a Lit Floor- space b All Buildings* .................................. 64,783 60,028 53,473 56,940 41,788 62,060 51,342 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 5,668 4,988 5,007 4,017 6,038 4,826 5,001 to 10,000 ................................. 6,585 5,786 5,010 5,408 3,978 6,090 4,974 10,001 to 25,000 ............................... 11,535 10,387 8,865 9,922 6,927 11,229 8,618 25,001 to 50,000 ............................... 8,668 8,060 7,260 7,776 5,663 8,297 6,544 50,001 to 100,000 ............................. 9,057 8,718 7,815 8,331 5,665 8,912 7,548 100,001 to 200,000 ........................... 9,064 8,710 8,012 8,339 6,462 8,732 7,470 200,001 to 500,000 ...........................

234

b2.xls  

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

Total Total Workers in All Buildings (thousand) Median Square Feet per Building (thousand) Median Square Feet per Worker Median Hours per Week Median Age of Buildings (years) All Buildings* .................................. 4,645 64,783 72,807 4.6 1,000 50 30.5 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 6,789 9,936 2.4 750 48 30.5 5,001 to 10,000 ................................. 889 6,585 7,512 7.2 1,300 50 30.5 10,001 to 25,000 ............................... 738 11,535 10,787 15.0 1,611 55 28.5 25,001 to 50,000 ............................... 241 8,668 8,881 35.0 1,364 60 30.5 50,001 to 100,000 ............................. 129 9,057 8,432 67.0 1,500 60 25.5 100,001 to 200,000 ........................... 65 9,064 11,632 130.0 1,457 75 24.5 200,001 to 500,000 ...........................

235

b1.xls  

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

1 1 Number of Buildings (thousand) Total Floorspace (million square feet) Total Workers in All Buildings (thousand) Mean Square Feet per Building (thousand) Mean Square Feet per Worker Mean Hours per Week All Buildings*................................... 4,645 64,783 72,807 13.9 890 61 Table B1. Summary Table: Total and Means of Floorspace, Number of Workers, and Hours of Operation for Non-Mall Buildings, 2003 Climate Zone: 30-Year Average Under 2,000 CDD and -- More than 7,000 HDD ..................... 855 10,622 10,305 12.4 1,031 60 5,500-7,000 HDD ............................ 1,173 17,335 17,340 14.8 1,000 63 4,000-5,499 HDD ............................ 673 11,504 14,007 17.1 821 66 Fewer than 4,000 HDD ................... 1,276 15,739 17,178 12.3 916 57 2,000 CDD or More and -- Fewer than 4,000 HDD ...................

236

a5.xls  

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

4,859 4,859 2,586 948 810 261 147 74 26 8 Principal Building Activity Education .......................................... 386 162 56 60 48 39 16 5 Q Food Sales ....................................... 226 164 44 Q Q Q Q N N Food Service ..................................... 297 202 65 23 Q Q N Q N Health Care ....................................... 129 56 38 19 5 5 3 2 1 Inpatient .......................................... 8 N N Q Q Q Q 2 1 Outpatient ....................................... 121 56 38 19 Q 3 Q Q N Lodging ............................................. 142 38 21 38 23 11 7 4 Q Mercantile ......................................... 657 275 156 155 34 21 12 2 2 Retail (Other Than Mall) .................. 443 241 97 83 14 Q 4 Q Q Enclosed and Strip Malls ................ 213 Q 59 72 20 18 8 Q 2 Office ................................................

237

b6.xls  

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

Released: June 2006 Next CBECS will be conducted in 2007 1,001 to 5,000 Square Feet 5,001 to 10,000 Square Feet 10,000 to 25,000 Square Feet 25,001 to 50,000 Square Feet 50,001 to 100,000 Square Feet 100,001 to 200,000 Square Feet 200,001 to 500,000 Square Feet Over 500,000 Square Feet All Buildings* .................................. 4,645 2,552 889 738 241 129 65 25 7 Table B6. Building Size, Number of Buildings for Non-Mall Buildings, 2003 Number of Buildings (thousand) All Buildings* Building Size Elevators and Escalators (more than one may apply) Any Elevators .................................... 309 Q 29 61 81 57 41 19 5 Number of Elevators One ................................................. 208 Q 29 57 62 29 11 4 Q Two to Five ..................................... 88 N N Q 19 28 29 9 Q Six or More .....................................

238

suptab_1.xls  

Gasoline and Diesel Fuel Update (EIA)

New England 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Energy Consumption Residential Distillate Fuel 0.349 0.344 0.362 0.371 0.371 0.372 0.370 0.369 0.366 0.364 0.362 0.360 0.357 Kerosene 0.031 0.017 0.023 0.031 0.031 0.031 0.030 0.030 0.030 0.030 0.029 0.029 0.029 Liquefied Petroleum Gas 0.032 0.032 0.031 0.031 0.032 0.032 0.033 0.033 0.033 0.033 0.034 0.034 0.034 Petroleum Subtotal 0.412 0.393 0.417 0.434 0.434 0.435 0.433 0.432 0.429 0.427 0.425 0.423 0.419 Natural Gas 0.181 0.182 0.199 0.197 0.197 0.200 0.202 0.204 0.205 0.207 0.208 0.209 0.209 Coal 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Renewable Energy 1/ 0.026 0.024 0.028 0.026 0.026 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 Electricity 0.147 0.153 0.157 0.158 0.161 0.164 0.167 0.169 0.170 0.172 0.173 0.175 0.175

239

sup_rci.xls  

Gasoline and Diesel Fuel Update (EIA)

Residential Residential Sector Equipment Stock and Efficiency (1 of 2) 2000- 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2020 Equipment Stock (million units) Main Space Heaters Electric Heat Pumps 10.23 10.58 10.86 11.14 11.44 11.72 11.93 12.14 12.36 12.57 12.77 12.98 13.18 13.37 13.56 13.76 13.96 14.17 14.38 14.59 14.78 1.9% Electric Other 20.12 20.18 20.20 20.24 20.29 20.33 20.39 20.46 20.53 20.60 20.67 20.73 20.79 20.84 20.89 20.95 21.00 21.07 21.14 21.22 21.29 0.3% Natural Gas Heat Pumps 0.02 0.02 0.03 0.03 0.04 0.04 0.05 0.05 0.06 0.06 0.07 0.07 0.07 0.08 0.08 0.09 0.09 0.10 0.10 0.11 0.11 10.2% Natural Gas Other 55.78 56.39 57.14 57.85 58.57 59.32 60.12 60.93 61.74 62.57 63.42 64.28 65.11 65.91 66.71 67.52 68.34 69.17 70.02 70.87 71.74 1.3% Distillate 9.41 9.38 9.35 9.33 9.31 9.29 9.27 9.25 9.23 9.21 9.19 9.17 9.15 9.12 9.10 9.07 9.04 9.02 8.99

240

oil1997.xls  

Gasoline and Diesel Fuel Update (EIA)

Total Total per Floor- per Square per per per Total Total space (1) Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 13.2 11.0 23.2 97 46 81.1 31 694 0.33 578 224 Census Region and Division Northeast 8.2 6.2 14.5 136 57 101.3 40 950 0.40 710 282 New England 3.1 2.7 5.8 126 60 111.5 45 902 0.43 797 321 Middle Atlantic 5.2 3.4 8.8 143 56 95.1 38 988 0.39 657 260 Midwest 1.5 1.4 3.0 75 36 72.6 26 522 0.25 504 184 East North Central 1.0 1.0 1.9 71 35 67.3 23 509 0.25 482 165 West North Central 0.5 0.5 1.1 83 38 83.5 35 548 0.25 548 232 South 2.9 2.9 4.6 34 21 33.7 13 279 0.17 275 105 South Atlantic

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

c14.xls  

Gasoline and Diesel Fuel Update (EIA)

Buildings* .................................. Buildings* .................................. 202 14.1 12.2 3.6 8.2 17.1 15.7 1.09 0.078 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 47 17.8 11.4 3.8 8.9 20.3 4.3 1.63 0.092 5,001 to 10,000 ................................. 92 12.4 10.3 3.8 7.4 14.5 8.7 1.18 0.095 10,001 to 25,000 ............................... 164 10.5 11.1 2.9 6.3 13.4 13.8 0.88 0.084 25,001 to 50,000 ............................... 439 12.2 11.6 3.8 8.8 16.2 33.6 0.94 0.077 50,001 to 100,000 ............................. 927 13.1 14.1 4.5 9.9 17.0 68.0 0.97 0.073 100,001 to 200,000 ........................... 2,181 15.7 12.2 5.3 13.0 23.4 146.4 1.05 0.067 200,001 to 500,000 ........................... 4,347 15.0 15.4 5.8 12.1 20.7 301.0 1.04 0.069 Over 500,000 .................................... 17,034 19.0 12.8 10.0

242

august2010.xls  

Gasoline and Diesel Fuel Update (EIA)

0 0 Section 1. Commentary Electric Power Data In June 2010, the contiguous United States as a whole experienced temperatures that were significantly above average. Accordingly, the total population-weighted cooling degree days for the United States were 31.0 percent above the June normal. Retail sales of electricity increased 8.0 percent compared to June 2009. Over the same period, the average U.S. retail price of electricity remained relatively unchanged. For the 12-month period ending June 2010, the U.S. average retail price of electricity decreased by 1.9 percent over the previous 12-month period ending June 2009. Total electric power generation in the United States increased 7.9 percent compared to June 2009. Over the same period, coal generation increased 12.2 percent, and natural gas generation increased 8.7 percent. Petroleum liquids

243

oil1982.xls  

Gasoline and Diesel Fuel Update (EIA)

Household Member Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 15.5 12.2 30.0 98 40 77.1 27 829 0.34 650 231 Census Region and Division Northeast 8.8 6.0 17.4 138 48 94.5 34 1,163 0.40 796 283 New England 2.5 1.9 5.9 131 43 101.9 36 1,106 0.36 863 309 Middle Atlantic 6.3 4.1 11.5 142 50 91.5 32 1,191 0.42 769 272 Midwest 2.4 2.1 4.8 74 33 66.2 24 609 0.27 548 202 East North Central 1.8 1.7 3.8 80 35 71.6 25 666 0.29 595 212 West North Central 0.5 0.5 1.0 51 24 46.6 20 410 0.20 377 160 South 3.7 3.4 6.7 52 27 48.1 17 446 0.23 409 144 South Atlantic 3.2 2.9 5.8 58 29 52.6 19 492 0.25 447 163 East South Central 0.4 0.4 0.8 22 10 21.2 6 183 0.08 179 52 West South Central Q Q Q Q Q Q Q Q Q Q Q West 0.6 0.6 1.2 48 25 46.8 16 412 0.22 402 138 Mountain 0.2 0.2 0.3 48 24

244

november2007.xls  

Gasoline and Diesel Fuel Update (EIA)

7 7 Section 1. Commentary Electric Power Data September 2007 was the eighth warmest September on record for the contiguous United States as reported by the National Oceanic and Atmospheric Administration. Accordingly, cooling degree days for the month were 24.4 percent above the average for the month of September, and 44.2 percent higher than September 2006. Retail sales of electricity and electricity generation were both higher when compared to September 2006. Electricity generation increased by 6.9 percent, while retail sales of electricity for September 2007 increased by 6.2 percent when compared to September 2006. The average U.S. retail price of electricity for September 2007 was 1.3 percent higher than September 2006 and 2.5 percent lower than the previous month, reflecting the reduced demand for electricity following the

245

may2006.xls  

Gasoline and Diesel Fuel Update (EIA)

Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy of the Department of Energy or any other organization. For additional information, contact Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Section 1. Commentary Electric Power Data Monthly Flash Estimates of Data for: March 2006 The weather through March 2006 continued to be warmer than in 2005. Year-to-date heating degree days were down almost 9 percent through March. For March alone heating degree days were down 7.8 percent from last year and were 2.2 percent lower than normal. Because of the warmer weather, year-to-date net generation through March was 1.3 percent less than in 2005, and

246

oil2001.xls  

Gasoline and Diesel Fuel Update (EIA)

Total per Square per per per Total Total Floorspace Building Foot per Household per Square per Household Households Number (billion (million (thousand Household Member Building Foot Household Member Characteristics (million) (million) sq. ft.) Btu) Btu) (million Btu) (million Btu) (dollars) (dollars) (dollars) (dollars) Total U.S. Households 11.2 9.4 26.0 80 29 67.1 26 723 0.26 607 236 Census Region and Division Northeast 7.1 5.4 16.8 111 36 84.7 33 992 0.32 757 297 New England 2.9 2.5 8.0 110 35 96.3 39 1,001 0.32 875 350 Middle Atlantic 4.2 2.8 8.8 112 36 76.6 30 984 0.32 675 260 Midwest 1.3 1.3 3.5 48 18 48.1 18 434 0.16 431 162 East North Central 0.9 0.9 2.3 41 15 40.3 15 364 0.13 360 137 West North Central 0.5 0.5 1.2 63 25 62.9 23 565 0.23 565 208 South 2.3 2.2 4.5 34 17 32.4 12 338 0.16 320 120 South Atlantic 1.8 1.7 3.5 40 19 37.2

247

c36.xls  

Gasoline and Diesel Fuel Update (EIA)

,393 ,393 176 125 81 1.10 1.03 1.21 1.28 0.23 0.06 0.03 Q Building Floorspace (Square Feet) 1,001 to 10,000 ................................. 460 Q Q Q 1.21 Q Q Q 0.61 Q Q Q 10,001 to 100,000 ............................. 408 70 Q Q 1.09 1.12 1.29 1.31 0.24 0.11 Q Q Over 100,000 .................................... 524 21 47 Q 1.03 1.05 1.07 1.26 0.14 0.01 0.02 Q Principal Building Activity Education .......................................... 293 Q Q Q 1.04 Q Q Q 0.31 Q Q Q Health Care........................................ Q Q 19 8 Q 1.06 1.08 1.16 Q Q 0.02 0.03 Office ................................................ 122 8 18 Q 1.16 1.32 1.26 1.44 0.09 0.01 0.01 0.00 All Others .......................................... 936 Q 59 50 1.12 1.01 1.34 1.26 0.27 0.11 0.04 Q Year Constructed 1945 or Before .................................. 612 Q Q Q 1.10 Q Q Q 0.29

248

december2005.xls  

Gasoline and Diesel Fuel Update (EIA)

and Stock Trends and Stock Trends Page 5 6. Month-to-Month Comparisons: Electric Power Retail Sales and Average Prices Page 6 7. Retail Sales Trends Page 7 8. Average Retail Price Trends Page 8 9. Heating and Cooling Degree Days Page 9 10. Documentation Page 10 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy of the Department of Energy or any other organization. For additional information, contact Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Section 1. Commentary Electric Power Data

249

december2007.xls  

Gasoline and Diesel Fuel Update (EIA)

7 7 Section 1. Commentary Electric Power Data In the contiguous United States, October 2007 was the ninth warmest October on record as reported by the National Oceanic and Atmospheric Administration. Accordingly, heating degree days were 32.3 percent below the average for the month of October, and 37.2 percent lower than what was recorded in October 2006. As a further indicator of the warmer-than-normal temperatures observed across the United States, cooling degree days were 55.4 percent above the average for the month of October, and 89.1 percent higher than October 2006. In October 2007, electricity generation was 3.4 percent higher than what was observed in October 2006, while retail sales of electricity increased 5.0 percent when compared to October 2006. The higher growth rate for sales of electricity relative to

250

c26.xls  

Gasoline and Diesel Fuel Update (EIA)

3,553 3,553 4,844 3,866 2,261 8.56 7.09 8.40 7.28 0.39 0.37 0.29 0.29 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 456 782 599 317 9.84 8.57 9.21 7.94 0.89 0.73 0.69 0.51 5,001 to 10,000 ................................. 348 427 582 332 9.15 7.54 9.08 7.60 0.56 0.45 0.43 0.44 10,001 to 25,000 ............................... 502 945 656 422 9.74 7.96 9.41 7.02 0.43 0.39 0.32 0.31 25,001 to 50,000 ............................... 408 738 402 317 9.14 6.44 8.60 7.24 0.42 0.33 0.25 0.27 50,001 to 100,000 ............................. 531 662 493 182 9.08 7.04 8.39 7.26 0.32 0.34 0.23 0.19 100,001 to 200,000 ........................... 454 573 555 156 6.94 6.66 Q 6.59 0.27 0.32 0.25 0.17 200,001 to 500,000 ........................... 457 423 286 178 7.64 5.97 7.05 6.46 0.29 0.25 0.20 0.18 Over 500,000 ....................................

251

oil1980.xls  

Gasoline and Diesel Fuel Update (EIA)

5.4 5.4 11.6 29.7 131 51 99.0 36 1,053 0.41 795 287 Census Region and Division Northeast 9.2 6.0 18.2 176 59 116.2 42 1,419 0.47 934 335 New England 2.7 2.0 6.0 161 53 118.3 42 1,297 0.43 954 336 Middle Atlantic 6.5 4.1 12.2 184 61 115.3 42 1,478 0.49 926 335 Midwest 2.0 1.9 4.4 92 39 84.5 28 728 0.31 669 220 East North Central 1.5 1.4 3.3 92 39 84.4 28 731 0.31 673 220 West North Central 0.5 0.5 1.1 93 40 85.0 29 720 0.31 657 220 South 3.6 3.2 6.0 79 42 68.8 26 637 0.34 558 214 South Atlantic 3.5 3.0 5.6 80 43 70.0 27 651 0.35 568 218 East South Central 0.1 0.1 0.3 45 23 45.3 15 365 0.18 365 123 West South Central Q Q Q 68 50 41.1 41 521 0.39 317 317 West 0.6 0.5 1.2 67 30 64.0 24 522 0.24 501 187 Mountain 0.1 0.1 0.2 70 30 64.7 24 534 0.23 494 185 Pacific 0.5 0.5 1.0 66 30 63.8 24 519 0.24 503 187 Metropolitan Statistical Area Urban 9.5 6.0 17.2 170 60 107.5 40 1,372 0.48 865 324 Central City 4.8 2.1 6.8 249 77 109.3 41 2,014 0.62

252

oil1981.xls  

Gasoline and Diesel Fuel Update (EIA)

4.6 4.6 11.0 28.9 116 44 87.9 32 1,032 0.39 781 283 Census Region and Division Northeast 8.9 5.9 18.0 158 51 103.5 36 1,405 0.46 923 323 New England 2.4 1.7 5.1 148 50 105.3 36 1,332 0.45 946 327 Middle Atlantic 6.5 4.1 12.8 161 52 102.9 36 1,435 0.46 915 322 Midwest 2.3 2.2 5.1 86 37 79.5 29 751 0.32 693 254 East North Central 1.7 1.7 3.8 79 35 76.8 28 688 0.31 672 243 West North Central 0.6 0.4 1.3 115 40 87.7 33 993 0.35 759 286 South 2.8 2.5 4.7 56 30 50.2 20 497 0.27 448 180 South Atlantic 2.5 2.2 4.2 56 30 49.7 20 500 0.27 445 182 East South Central 0.3 0.3 0.5 55 31 55.4 20 482 0.27 482 171 West South Central Q Q Q 48 56 48.0 11 425 0.49 425 99 West 0.5 0.5 1.2 63 27 58.4 23 548 0.24 511 197 Mountain 0.1 0.1 0.2 45 24 44.6 18 384 0.20 384 153 Pacific 0.5 0.4 1.0 66 27 60.9 23 580 0.24 534 205 Metropolitan Statistical Area Urban 8.9 5.5 16.3 157 53 97.4 37 1,402 0.47 868 331 Central City 4.2 1.8 5.9 229 70 98.5 39 2,051 0.62

253

c22.xls  

Gasoline and Diesel Fuel Update (EIA)

Buildings* .................................. Buildings* .................................. 155 447 288 17,163 28,766 17,378 9.0 15.5 16.6 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 23 52 37 2,049 2,668 1,628 11.3 19.6 23.0 5,001 to 10,000 ................................. 15 35 27 1,859 2,854 1,484 8.1 12.2 18.1 10,001 to 25,000 ............................... 27 55 37 3,141 4,907 3,322 8.5 11.3 11.2 25,001 to 50,000 ............................... 16 56 31 2,344 3,994 2,047 6.7 13.9 15.3 50,001 to 100,000 ............................. 15 58 46 2,060 4,018 2,953 7.5 14.3 15.5 100,001 to 200,000 ........................... 19 69 53 2,113 3,911 2,993 9.2 17.7 17.7 200,001 to 500,000 ........................... 21 57 27 2,030 3,427 1,593 10.5 16.6 17.2 Over 500,000 .................................... 18 65 29 1,566 2,986 1,357 11.4 21.9

254

december2006.xls  

Gasoline and Diesel Fuel Update (EIA)

Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Monthly Flash Estimates of Data for: October 2006 Section 1. Commentary Electric Power Data As the transition from the summer into the fall season continues, October 2006 total net generation declined 2.9 percent from September 2006 due to declining cooling needs. Similarly, October 2006 retail sales of electricity were down 8.4 percent from September 2006. Comparing October 2006 to October 2005, however, net generation increased by 1.8 percent, due to a cooler October in 2006, leading to higher heating demand. October 2006 heating degree days were up 27.4 percent from October 2005. Year-to-date, through October 2006, both total net generation and retail sales of electricity were up 0.3 percent, compared to the first

255

c20.xls  

Gasoline and Diesel Fuel Update (EIA)

76 148 129 143 100 5,673 9,426 7,813 8,157 5,269 13.4 15.7 16.5 17.5 19.1 Laser Printers ... 67 113 84 109 82 5,811 8,950 5,910 7,675...

256

c8.xls  

Gasoline and Diesel Fuel Update (EIA)

Servers ... 274 684 200 2,796 6,839 1,606 97.9 99.9 124.7 Laser Printers ... 228 525 163 2,784 6,059 1,813 81.9 86.7...

257

c3.xls  

Gasoline and Diesel Fuel Update (EIA)

Dedicated Servers ... 1,175 36,338 30.9 3,760 3,201 103.5 71.6 Laser Printers ... 1,970 33,012 16.8 3,009 1,528 91.2 75.1...

258

c22.xls  

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

Servers ... 84 322 190 8,136 17,936 10,265 10.4 17.9 18.5 Laser Printers ... 77 233 145 9,240 15,256 8,516 8.3 15.2...

259

c15.xls  

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

... 113 142 241 100 8,143 9,252 12,649 6,294 13.9 15.3 19.1 16.0 Laser Printers ... 76 104 188 86 7,095 8,463 11,566 5,888...

260

c6.xls  

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

15,313 13,036 19,117 11,911 16.84 12.69 15.39 20.51 1.88 1.41 1.51 1.89 Laser Printers ... 11,298 10,344 15,714 10,523 16.49 12.40...

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

c10.xls  

Gasoline and Diesel Fuel Update (EIA)

592 1,099 851 762 456 5,673 9,426 7,813 8,157 5,269 104.4 116.6 108.9 93.4 86.6 Laser Printers ... 558 924 565 585 377 5,811 8,950 5,910 7,675...

262

c7.xls  

Gasoline and Diesel Fuel Update (EIA)

Servers ... 202 707 754 1,656 6,486 6,456 121.9 109.1 116.8 Laser Printers ... 160 525 606 1,569 5,526 5,678 102.1 95.0...

263

c5.xls  

Gasoline and Diesel Fuel Update (EIA)

909 1,028 1,242 581 8,143 9,252 12,649 6,294 111.7 111.1 98.2 92.3 Laser Printers ... 685 834 966 524 7,095 8,463 11,566 5,888...

264

c4.xls  

Gasoline and Diesel Fuel Update (EIA)

Dedicated Servers ... 1,175 36,338 30.9 59,377 50.6 1.63 15.79 Laser Printers ... 1,970 33,012 16.8 47,880 24.3 1.45 15.91...

265

c16.xls  

Gasoline and Diesel Fuel Update (EIA)

10,454 9,056 15,375 10,055 0.09 0.06 0.06 0.10 1.28 0.98 1.22 1.60 Laser Printers ... 7,450 7,000 12,900 8,681 0.10 0.07 0.07...

266

c12.xls  

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

... 771 1,959 1,031 8,136 17,936 10,265 94.7 109.2 100.4 Laser Printers ... 766 1,460 783 9,240 15,256 8,516 82.9 95.7...

267

c9.xls  

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

Servers ... 359 228 353 4,204 1,959 4,335 85.3 116.6 81.3 Laser Printers ... 278 227 297 3,694 2,165 3,723 75.2 105.0...

268

c14.xls  

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

Servers ... 508 16.4 11.4 6.9 12.3 20.7 38.3 1.24 0.075 Laser Printers ... 231 13.8 11.3 4.7 9.0 17.6 18.3 1.09...

269

OMBDOEFAIR2005.xls  

Energy Savers [EERE]

US 1 R999 I 1999 214 019 05 AL NNSA NM ALBUQUERQUE US 1 R999 I 2005 215 019 05 AL NNSA TN OAK RIDGE US 1 S000 I 1999 216 019 05 AL NNSA TN OAK RIDGE US 1 S000 I 1999 217 019 05 AL...

270

AAA-CLIMATE.XLS  

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

DATE MAXIMUM MINIMUM AVERAGE DEPARTURE FROM NORMAL HEATING DEGREE DAYS (BASE 65F) COOLING DEGREE DAYS (BASE 65F) TOTAL (WATER EQUIVALENT IN IN.) SNOW, ICE PELLETS (SLEET)...

271

Climat.xls  

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

DATE MAXIMUM MINIMUM AVERAGE DEPARTURE FROM NORMAL HEATING DEGREE DAYS (BASE 65F) COOLING DEGREE DAYS (BASE 65F) TOTAL (WATER EQUIVALENT IN IN.) SNOW, ICE PELLETS (SLEET)...

272

b3.xls  

Gasoline and Diesel Fuel Update (EIA)

94 185 272 113 14,357 3,476 3,114 5,157 2,611 Heating Equipment (more than one may apply) Heat Pumps ... 476 47 45 304 80 8,814 1,213 1,058 4,942...

273

b15.xls  

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

... 149 23 Q 21 31 23 22 16 Heating Equipment (more than one may apply) Heat Pumps ... 476 236 89 64 42 23 16 5 Packaged Heat...

274

c38.xls  

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

Heat Consumption District Heat Expenditures Heating Equipment (more than one may apply) Heat Pumps ... Q Q Q Q Q Q Packaged Heat Pumps...

275

b27.xls  

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

45,071 20,168 28,197 4,370 4,541 2,272 679 Heating Equipment (more than one may apply) Heat Pumps ... 8,814 8,814 8,688 4,643 295 413 516 Q...

276

b34.xls  

Gasoline and Diesel Fuel Update (EIA)

386 276 Q Q 68 3,210 1,767 Q Q 1,068 Heating Equipment (more than one may apply) Heat Pumps ... 476 N 37 61 378 8,814 N 670 1,497 6,647...

277

c27.xls  

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

22 125 214 410 2,418 3,741 53.1 51.6 57.3 Heating Equipment (more than one may apply) Heat Pumps ... Q 37 22 Q 799 591 Q 46.2 36.7 Packaged...

278

c2.xls  

Gasoline and Diesel Fuel Update (EIA)

664 14,357 27,349 19,987 4,409 468 2,486 Heating Equipment (more than one may apply) Heat Pumps ... 476 8,814 14,249 11,629 1,804 50 Q...

279

c33.xls  

Gasoline and Diesel Fuel Update (EIA)

3,996 0.12 86.6 4.4 0.13 1.10 Heating Equipment (more than one may apply) Heat Pumps ... 2,093 0.02 11.1 2.4 0.02 1.13 Packaged...

280

c37.xls  

Gasoline and Diesel Fuel Update (EIA)

Heat Consumption District Heat Expenditures Heating Equipment (more than one may apply) Heat Pumps ... Q Q Q Q Q Q Packaged Heat Pumps...

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

table_13.xls  

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

Coal Production, Projected vs. Actual Projected million short tons 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 AEO 1994 999...

282

nstec_home.xls  

National Nuclear Security Administration (NNSA)

2309 NSTec Employees Home Address Counts by State and Zip Code State Postal Total AL 35811 1 AL Total 1 AZ 85032 1 85282 1 85331 1 85353 1 86004 1 86045 1 86305 1 86413 1 86432 1...

283

b33.xls  

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

Propane Elec- tricity Natural Gas Propane All Buildings* ... 4,645 801 410 457 108 64,783 22,237 13,161 15,438 1,460 Building Floorspace (Square...

284

EIA-912.xls  

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

Feet) (IL, IN, IA, KY, MI, MN, MO, TN, & WI) South Central Region (Million Cubic Feet) (AL, AR, KS, LA, MS, OK, & TX) Mountain Region (Million Cubic Feet) PART 4. INVENTORY...

285

table10.xls  

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

1,400 60 Years or More... NA NA 824 822 907 966 Race of Householder 1 White... 1,103 1,091 1,028 985 1,099 1,170 Black...

286

November 2014.xls  

Energy Savers [EERE]

Storage and Management of Elemental Mercury (DOEEIS-0423) 10. Supplemental EIS for the Storage and Management of Elemental Mercury (DOEEIS-0423-S1) 11. Hanford Natural Gas...

287

c30.xls  

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

135 246 129 127 51 2,506 4,172 2,922 2,931 2,063 53.8 59.0 44.2 43.2 24.8 Economizer Cycle ... 185 298 125 122 50 3,349 4,824 3,401 3,573 1,508...

288

c36.xls  

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

Air-Volume System ... 184 30 50 9 1.05 1.11 1.12 1.25 0.08 0.02 0.02 0.01 Economizer Cycle ... 253 21 51 5 1.09 1.08 1.08 1.26 0.11 0.01 0.02...

289

c24.xls  

Gasoline and Diesel Fuel Update (EIA)

Air-Volume System ... 2,369 47.2 29.2 19.7 37.9 83.8 17.5 0.35 7.37 Economizer Cycle ... 2,242 46.9 30.4 18.9 41.8 85.7 16.4 0.34 7.30 HVAC...

290

b36.xls  

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

14,357 1,576 2,228 3,629 6,924 Lighting Equipment Types (more than one may apply) Incandescent ... 2,184 Q 506 673 990 38,528 Q 6,483 12,947...

291

All Beams 2013.xls  

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

1598 29 1079 9 1070 3.8 3.8 20.1 78 Kr 77.920 40 3117 140 622 20 602 14.2 14.4 41.4 Proton 1.007 40 40 0.1 8148 1.2 8147 0.012 0.012 0.56 Available Beams 40 A MeV 25 A MeV 15 A MeV...

292

RangeTables.xls  

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

(MeVcmmg) LET vs. Range in Si for 25 MeV SEE Beams (low LET) 4 He 14 N 0 0.5 1 1.5 0 600 1200 1800 2400 3000 3600 4 He 14 N 22 Ne 0 1 2 3 4 5 6 7 8 9 10 0 100 200 300 400 500...

293

September 2014.xls  

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

WA (DOEEIS-0467) FOSSIL ENERGY 13. Hydrogen Energy California's Integrated Gasification Combined Cycle Project, CA (DOEEIS-0431) NATIONAL NUCLEAR SECURITY ADMINISTRATION 14....

294

eia-857.xls  

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

Electric Power Other (not included in above categories) Total of all deliveries (Lines 3.0 through 12.0) Does any information provided in lines 1-13 include prior period...

295

table14.xls  

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

Years... NA NA 1,497 1,736 1,727 2,239 Households Without Children... NA NA 882 1,011 1,100 1,241...

296

table7.xls  

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

17 Years... NA NA 28.9 28.0 29.9 34.0 Households Without Children... NA NA 16.3 16.5 18.9 19.6 One...

297

table3.xls  

Gasoline and Diesel Fuel Update (EIA)

17 Years... NA NA 13.8 13.8 15.2 18.2 Households Without Children... NA NA 87.7 86.2 92.2 111.2 One...

298

oil1984.xls  

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

21 763 0.37 468 160 Other 0.5 0.2 0.6 281 77 81.6 25 1,941 0.53 564 175 Householder of Hispanic Descent Yes 0.8 0.3 1.0 235 65 78.7 23 1,619 0.45 542 158 No 16.7 13.5 31.0 88 38...

299

table8.xls  

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

to 17 Years... NA NA 8.7 8.4 9.6 12.0 Households Without Children... NA NA 46.0 44.0 50.2 60.0 One...

300

table12.xls  

Gasoline and Diesel Fuel Update (EIA)

17 Years... NA NA 8.5 10.0 11.1 15.9 Households Without Children... NA NA 45.3 52.2 58.0 76.6 One...

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

oil1990.xls  

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

(dollars) (dollars) (dollars) (dollars) Table 1. Consumption and Expenditures in U.S. Households that Use Fuel OilKerosene, 1990 Residential Buildings Average Fuel Oil...

302

a8.xls  

Gasoline and Diesel Fuel Update (EIA)

Q N N Q N Food Service ... 1,654 1,375 246 Q N N N Health Care ... 3,163 2,004 735 Q Q Q N Inpatient...

303

c28.xls  

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

Q Q Q Q Q Q Q Food Service ... Q 42 Q Q 339 Q Q 123.8 Q Health Care ... Q Q 17 Q 508 196 Q 87.5 86.2 Inpatient...

304

c29.xls  

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

Q Q Q Q Q Q Q Food Service ... 37 Q Q 211 Q Q 175.7 Q Q Health Care ... 26 19 19 282 162 274 91.4 115.5 68.7...

305

c23.xls  

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

Service ... 870 141.2 72.0 77.0 150.3 301.8 7.1 1.16 8.20 Health Care ... 3,283 92.5 44.1 19.1 40.1 65.7 21.5 0.60...

306

b24.xls  

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

188 210 186 84 Q Food Service ... 297 282 283 297 284 Q Health Care ... 129 124 129 127 12 Q Inpatient...

307

c21.xls  

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

51.1 Q Food Service ... 47 16 Q 986 664 Q 47.8 24.5 Q Health Care ... 6 17 50 445 835 1,883 13.1 20.5 26.3...

308

c31.xls  

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

Q Q Food Service ... 149 48 N 774 622 N 192.5 77.2 N Health Care ... 12 37 187 233 520 1,792 49.5 70.8...

309

b29.xls  

Gasoline and Diesel Fuel Update (EIA)

437 568 Q N Food Service ... 1,654 1,608 436 957 Q Q Health Care ... 3,163 3,100 592 1,972 Q 388 Inpatient...

310

b18.xls  

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

N Q Q Food Service ... 1,654 1,547 489 1,058 N Q N Q Q Health Care ... 3,163 2,662 1,611 1,051 N 501 121 Q...

311

b1.xls  

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

7.5 9.5 3.5 Food Service ... 7.4 9.0 10.5 6.5 8.4 3.5 Health Care ... 10.0 6.9 8.2 11.4 3.9 5.6 Inpatient...

312

c13.xls  

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

... 213 38.4 20.3 18.8 37.4 70.3 17.4 3.13 0.082 Health Care ... 564 22.9 11.5 6.1 12.0 18.4 37.9 1.54...

313

c1.xls  

Gasoline and Diesel Fuel Update (EIA)

Q N Food Service ... 297 1,654 6,865 5,176 1,615 Q Q Health Care ... 129 3,163 7,440 4,882 1,538 79 Q...

314

c11.xls  

Gasoline and Diesel Fuel Update (EIA)

Q Q Food Service ... 318 108 Q 986 664 Q 322.9 163.2 Q Health Care ... 32 104 457 445 835 1,883 71.8 125.1...

315

table5.xls  

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

215 215 1,353 1,511 1,602 1,793 2,287 Household Characteristics Census Region and Division Northeast............................................................... 227 248 274 295 299 378 New England........................................................ 64 64 67 75 84 122 Middle Atlantic ..................................................... 164 184 208 221 215 256 Midwest ................................................................. 298 327 379 403 479 560 East North Central............................................... 198 216 263 296 335 385 West North Central ............................................. 99 111 115 108 144 175 South..................................................................... 436 486 534 571 655 871 South Atlantic.......................................................

316

b22.xls  

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

Revised June 2006 Revised June 2006 144 Released: Dec 2006 Next CBECS will be conducted in 2007 Elec- tricity Natural Gas Fuel Oil District Heat District Chilled Water Propane Other a All Buildings* .................................. 4,645 4,414 4,404 2,391 451 67 33 502 132 Table B22. Energy Sources, Number of Buildings for Non-Mall Buildings, 2003 Number of Buildings (thousand) Energy Sources Used (more than one may apply) All Buildings* Buildings Using Any Energy Source Number of Workers (main shift) Fewer than 5 ..................................... 2,653 2,425 2,415 1,082 252 20 Q 318 84 5 to 9 ................................................ 778 775 775 474 67 Q Q 75 Q 10 to 19 ............................................. 563 563 563 359 38 Q Q 59 Q 20 to 49 ............................................. 398 397 397

317

table12.xls  

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

5.1 5.1 99.1 81.1 98.2 104.7 150.3 Household Characteristics Census Region and Division Northeast............................................................... 17.5 17.6 14.2 17.8 17.2 24.3 New England........................................................ 4.7 4.4 3.5 4.5 4.8 8.1 Middle Atlantic ..................................................... 12.8 13.2 10.7 13.3 12.4 16.2 Midwest ................................................................. 24.0 24.7 20.4 25.0 26.5 37.4 East North Central............................................... 16.0 16.1 14.0 17.9 18.5 25.7 West North Central ............................................. 8.0 8.7 6.3 7.1 8.0 11.7 South..................................................................... 34.2 35.7 29.1 34.9 37.7 54.4 South Atlantic.......................................................

318

b10.xls  

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

One One Floor Two Floors Three Floors Four to Nine Floors Ten or More Floors All Build- ings* One Floor Two Floors Three Floors Four to Nine Floors Ten or More Floors All Buildings* .................................. 4,645 3,136 1,031 339 128 12 64,783 25,981 16,270 7,501 10,085 4,947 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 2,014 411 115 Q N 6,789 5,192 1,217 343 Q N 5,001 to 10,000 ................................. 889 564 239 70 Q N 6,585 4,150 1,814 504 Q N 10,001 to 25,000 ............................... 738 399 248 74 18 Q 11,535 6,160 3,966 1,115 292 Q 25,001 to 50,000 ............................... 241 92 77 46 26 Q 8,668 3,296 2,772 1,631 964 Q 50,001 to 100,000 ............................. 129 46 35 21 25 Q 9,057 3,187 2,456 1,481 1,822 Q 100,001 to 200,000 ........................... 65 16 13

319

table4.xls  

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

.8 .8 1.8 1.8 1.8 1.8 1.9 Household Characteristics Census Region and Division Northeast............................................................... 1.7 1.7 1.7 1.7 1.8 1.8 New England........................................................ 1.8 1.6 1.8 1.7 1.9 1.9 Middle Atlantic ..................................................... 1.7 1.7 1.7 1.7 1.8 1.8 Midwest ................................................................. 1.8 1.7 1.8 1.8 1.9 2.0 East North Central............................................... 1.7 1.7 1.8 1.8 1.9 2.0 West North Central ............................................. 1.9 1.9 1.9 1.8 1.9 2.0 South..................................................................... 1.8 1.8 1.8 1.8 1.9 1.9 South Atlantic.......................................................

320

b5.xls  

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

West West South Central Mountain Pacific All Buildings* .................................. 64,783 2,964 9,941 11,595 5,485 12,258 3,393 7,837 3,675 7,635 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 360 666 974 922 1,207 538 788 464 871 5,001 to 10,000 ................................. 6,585 359 764 843 722 1,387 393 879 418 820 10,001 to 25,000 ............................... 11,535 553 1,419 1,934 1,164 2,240 810 1,329 831 1,256 25,001 to 50,000 ............................... 8,668 347 944 1,618 949 1,672 498 998 511 1,132 50,001 to 100,000 ............................. 9,057 516 1,524 1,618 642 1,470 650 1,314 374 948 100,001 to 200,000 ........................... 9,064 414 1,703 1,682 614 2,087 Q 1,131 Q 895 200,001 to 500,000 ........................... 7,176 Q 1,673 1,801 395 1,072

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

b17.xls  

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

4,645 4,645 4,011 1,841 2,029 141 635 46 164 425 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 2,272 980 1,205 87 280 Q 77 183 5,001 to 10,000 ................................. 889 783 384 375 Q 106 Q Q 87 10,001 to 25,000 ............................... 738 625 320 293 Q 113 Q 40 64 25,001 to 50,000 ............................... 241 185 91 86 Q 56 Q 16 36 50,001 to 100,000 ............................. 129 82 35 40 Q 47 Q 9 37 100,001 to 200,000 ........................... 65 43 21 20 Q 22 Q 8 12 200,001 to 500,000 ........................... 25 16 7 8 Q 9 2 1 5 Over 500,000 .................................... 7 5 2 3 N 2 1 Q Q Principal Building Activity Education .......................................... 386 141 83 58 N 245 Q 59 175 Food Sales ....................................... 226 224 94 130 N Q N

322

a1.xls  

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

October 2006 October 2006 Next CBECS will be conducted in 2007 Number of Buildings (thousand) Total Floorspace (million square feet) Mean Square Feet per Building (thousand) Median Square Feet per Building (thousand) All Buildings .................................... 4,859 71,658 14.7 5.0 Table A1. Summary Table for All Buildings (Including Malls), 2003 Climate Zone: 30-Year Average Under 2,000 CDD and -- More than 7,000 HDD ..................... 882 11,529 13.1 4.8 5,500-7,000 HDD ............................ 1,229 18,808 15.3 5.0 4,000-5,499 HDD ............................ 701 12,503 17.8 4.8 Fewer than 4,000 HDD ................... 1,336 17,630 13.2 4.5 2,000 CDD or More and -- Fewer than 4,000 HDD ................... 711 11,189 15.7 5.0 Number of Establishments One ...................................................

323

table11.xls  

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

5.1 5.1 16.1 18.3 19.3 19.8 20.2 Household Characteristics Census Region and Division Northeast............................................................... 15.6 NA 19.6 20.9 20.7 20.9 New England........................................................ 16.5 NA 19.7 21.1 20.4 21.0 Middle Atlantic ..................................................... 15.3 NA 19.6 20.8 20.8 20.8 Midwest ................................................................. 14.8 NA 18.2 19.0 20.1 20.2 East North Central............................................... 14.9 NA 18.4 19.4 20.1 20.3 West North Central ............................................. 14.5 NA 17.8 17.9 20.0 20.0 South..................................................................... 15.0 NA 18.0 19.2 19.6 20.2 South Atlantic.......................................................

324

b22.xls  

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

Released: Dec 2006 Next CBECS will be conducted in 2007 Elec- tricity Natural Gas Fuel Oil District Heat District Chilled Water Propane Other a All Buildings* .................................. 4,645 4,414 4,404 2,391 451 67 33 502 132 Table B22. Energy Sources, Number of Buildings for Non-Mall Buildings, 2003 Number of Buildings (thousand) Energy Sources Used (more than one may apply) All Buildings* Buildings Using Any Energy Source Number of Workers (main shift) Fewer than 5 ..................................... 2,653 2,425 2,415 1,082 252 20 Q 318 84 5 to 9 ................................................ 778 775 775 474 67 Q Q 75 Q 10 to 19 ............................................. 563 563 563 359 38 Q Q 59 Q 20 to 49 ............................................. 398 397 397 289 36 16 6 30 13 50 to 99 .............................................

325

Table1.xls  

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

Reporting Entities, Data Year 2005 Reporting Entities, Data Year 2005 Reporter Name Sector Type of Form Number of Projects Reported (Schedule II) Entity-Wide Report (Schedule III) Commitments (Schedule IV) A&N Electric Cooperative Electric Providers 1605 2 No Yes Abe Krasne Home Furnishings, Inc. Services and Retail 1605 0 Yes No AES Hawaii, Inc. Electric Providers 1605 1 Yes No AES SeaWest, Inc. Electric Providers 1605 11 No No AES Shady Point, LLC Electric Providers 1605 1 Yes No AES Thames, LLC Electric Providers 1605 1 Yes Yes AES Warrior Run, LLC Electric Providers 1605 2 Yes No Alabama Biomass Partners, Ltd Alternative Energy 1605EZ 1 No No Alcan Primary Products Corporation, Sebree Works Industrial 1605 1 Yes Yes Algonquin Power - Cambrian Pacific Genco LLC Alternative Energy 1605 9 No No Allegheny Energy, Inc. Electric Providers

326

b45.xls  

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

4,645 4,645 3,176 1,007 666 308 696 2,370 996 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 1,591 486 332 142 353 1,159 268 5,001 to 10,000 ................................. 889 642 188 124 65 117 494 181 10,001 to 25,000 ............................... 738 548 138 75 40 103 427 250 25,001 to 50,000 ............................... 241 196 78 44 19 53 148 134 50,001 to 100,000 ............................. 129 114 60 44 19 34 81 89 100,001 to 200,000 ........................... 65 58 36 29 13 23 41 48 200,001 to 500,000 ........................... 25 21 16 14 7 9 16 19 Over 500,000 .................................... 7 6 5 5 3 3 4 6 Principal Building Activity Education .......................................... 386 254 93 59 31 54 203 113 Food Sales ....................................... 226 212

327

b9.xls  

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

64,783 64,783 3,769 6,871 7,045 8,101 10,772 10,332 12,360 5,533 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 490 796 860 690 966 1,149 1,324 515 5,001 to 10,000 ................................. 6,585 502 827 643 865 1,332 721 1,209 486 10,001 to 25,000 ............................... 11,535 804 988 1,421 1,460 1,869 1,647 2,388 958 25,001 to 50,000 ............................... 8,668 677 838 935 1,234 1,720 1,174 1,352 739 50,001 to 100,000 ............................. 9,057 491 641 927 1,483 1,146 1,390 2,058 921 100,001 to 200,000 ........................... 9,064 Q 704 1,148 1,039 1,411 1,496 1,934 1,060 200,001 to 500,000 ........................... 7,176 Q 1,288 569 947 1,243 1,237 984 609 Over 500,000 .................................... 5,908 Q 790 541 382 1,085 1,518 1,111 Q Principal Building Activity

328

Summer Tables.xls  

Gasoline and Diesel Fuel Update (EIA)

8 8 1 September 2008 Short-Term Energy Outlook September 9, 2008 Release Highlights The monthly average price of West Texas Intermediate (WTI) crude oil decreased from over $133 per barrel in June and July to about $117 per barrel in August, reflecting expectations of a slowdown in world petroleum demand growth. WTI, which averaged $72 per barrel in 2007, is projected to average $116 per barrel in 2008. Projected stronger growth in world petroleum demand is expected to increase the annual average WTI price to $126 per barrel in 2009. The weekly price of regular-grade gasoline, which peaked at $4.11 per gallon on July 14, averaged $3.65 per gallon on September 8. Annual average retail

329

july2007.xls  

Gasoline and Diesel Fuel Update (EIA)

May 2007 Section 1. Commentary Electric Power Data For the contiguous U.S., the overall temperature for May 2007 was 2.1ºF (1.2ºC) above the average temperature observed for the month of May over the 1971-2000 time period. This was the 11th warmest May on record, with most of the contiguous U.S. observing warmer-than-normal temperatures except for Texas and South Carolina. Heating degree days for May 2007 were 32.7 percent below the normal observed over the 1971-2000 time period, and 21.9 percent lower than what was recorded in May 2006. As a further indicator of the warmer-than-normal temperatures observed across the U.S., cooling degree days for May 2007 were 7.7 percent above the 1971-2000 normal, and 2.8 percent higher than what was recorded in May 2006.

330

web_comments.xls  

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

Rec Type Rec Type Recommendations/ Comments Name Organization 1/9/2004 Reliability Standards Future reliability standards must strike a balance between detailed, rigid requirements, which provide little or no latitude for deviation, and standards, which are objective-based and allow for innovation and invention to achieve intended goals. Each standard should identify its importance on the BPS reliability in terms of the potential short-term (operating time horizon) vs. long-term (planning time horizon) impacts of non-compliance. Ajay Garg, Mike Penstone Hydro One Networks Inc. 1/9/2004 Reliability Standards Core Reliability Standards: comprising a small number of technical standards designed to enable the BPS to withstand and recover from unexpected contingencies. Core Reliability

331

January 2014.XLS  

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

5 - 2012 5 - 2012 2013 2014 2015 ADVANCED RESEARCH PROJECTS AGENCY - ENERGY Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec 1. Engineered High Energy Crops Programmatic EIS (DOE/EIS-0481) ELECTRICITY DELIVERY AND ENERGY RELIABILITY 2. Presidential Permit Application, Champlain Hudson Power Express Transmission Line (DOE/EIS-0447) 3. Presidential Permit Application, Northern Pass Transmission LLC, NH (DOE/EIS-0463) 4. Plains and Eastern Clean Line Transmission Project (DOE/EIS-0486) 5. Hawaii Clean Energy Programmatic EIS (DOE/EIS-0459) ENVIRONMENTAL MANAGEMENT 6. Disposal of Greater-Than-Class C Low-Level Radioactive Waste

332

b14.xls  

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

64,783 64,783 12,208 3,939 1,090 3,754 4,050 10,078 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 6,789 1,382 336 122 416 1,034 895 5,001 to 10,000 ................................. 6,585 938 518 Q 744 722 868 10,001 to 25,000 ............................... 11,535 1,887 1,077 Q 1,235 1,021 2,064 25,001 to 50,000 ............................... 8,668 1,506 301 Q 930 560 1,043 50,001 to 100,000 ............................. 9,057 1,209 474 Q Q Q 1,494 100,001 to 200,000 ........................... 9,064 1,428 868 Q Q Q 1,162 200,001 to 500,000 ........................... 7,176 1,493 Q Q Q Q 1,322 Over 500,000 .................................... 5,908 2,365 Q Q N Q Q Year Constructed Before 1920 ...................................... 3,769 749 323 Q 586 Q 254 1920 to 1945 .....................................

333

b26.xls  

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

4,645 4,645 3,982 1,766 2,165 360 65 372 113 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 2,100 888 1,013 196 Q 243 72 5,001 to 10,000 ................................. 889 782 349 450 86 Q 72 Q 10,001 to 25,000 ............................... 738 659 311 409 46 18 38 Q 25,001 to 50,000 ............................... 241 225 114 151 11 9 11 Q 50,001 to 100,000 ............................. 129 123 60 84 8 8 Q Q 100,001 to 200,000 ........................... 65 62 29 39 9 9 Q Q 200,001 to 500,000 ........................... 25 24 11 15 4 4 Q Q Over 500,000 .................................... 7 6 3 4 1 2 Q Q Principal Building Activity Education .......................................... 386 382 180 186 21 25 36 Q Food Sales ....................................... 226 188 98 79 Q N Q Q Food Service .....................................

334

table2.xls  

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

6 6 89 89 89 87 92 Household Characteristics Census Region and Division Northeast............................................................... 77 NA 79 83 75 85 New England........................................................ 88 NA 82 83 82 89 Middle Atlantic ..................................................... 74 NA 78 82 74 84 Midwest ................................................................. 86 NA 91 90 92 91 East North Central............................................... 82 NA 89 90 92 91 West North Central ............................................. 94 NA 95 91 94 94 South..................................................................... 87 NA 91 91 89 96 South Atlantic....................................................... 87 NA 89 90 88 94 East South Central...............................................

335

Table 4.xls  

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

Emission Reductions and Sequestration Reported at Project and Entity Levels, Data Year 2005 Emission Reductions and Sequestration Reported at Project and Entity Levels, Data Year 2005 (Metric Tons Carbon Dioxide Equivalent) Report Name Sector Reduction Type Project Level Entity Level A&N Electric Cooperative Electric Providers Indirect 6,243 AES Hawaii, Inc. Electric Providers Sequestration 1,540,000 1,540,000 AES SeaWest, Inc. Electric Providers Direct 16 Indirect 220,420 AES Shady Point, LLC Electric Providers Sequestration 4,150,000 4,150,000 AES Thames, LLC Electric Providers Sequestration 410,000 410,000 AES Warrior Run, LLC Electric Providers Direct 41,386 41,386 Alabama Biomass Partners, Ltd Alternative Energy Unspecified (EZ) 77,012 Alcan Primary Products Corporation, Sebree Works Industrial Direct 457,800 457,800 Algonquin Power - Cambrian Pacific Genco LLC Alternative Energy

336

eia857.xls  

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

operational sendout to consumers of gas owned and not owned operational sendout to consumers of gas owned and not owned Residential Industrial Electric Power Other (not included in above categories) Residential Commercial (excluding vehicle fuel) Vehicle Fuel Industrial Electric Power Other (not included in above categories) Total of all deliveries (Lines 3.0 through 12.0) Heat content of gas delivered to consumers (Btu/cubic ft.): 6.0 4.1 (Specify Type) ................................................................... Deliveries of natural gas that you do not own to consumers within the report State U. S. Department of Energy Oil & Gas Survey Ben Franklin Station P.O. Box 279 Washington, DC 20044-0279 12.0 Revenue (Mcf @ 14.73 psia-60 o F) (Including taxes) Call: (Mcf @ 14.73 psia-60 o F) (877) 800-5261 Cost Questions? Volume (Including taxes)

337

b6.xls  

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

Revised June 2006 Revised June 2006 49 Released: June 2006 Next CBECS will be conducted in 2007 1,001 to 5,000 Square Feet 5,001 to 10,000 Square Feet 10,000 to 25,000 Square Feet 25,001 to 50,000 Square Feet 50,001 to 100,000 Square Feet 100,001 to 200,000 Square Feet 200,001 to 500,000 Square Feet Over 500,000 Square Feet All Buildings* .................................. 4,645 2,552 889 738 241 129 65 25 7 Table B6. Building Size, Number of Buildings for Non-Mall Buildings, 2003 Number of Buildings (thousand) All Buildings* Building Size Elevators and Escalators (more than one may apply) Any Elevators .................................... 309 Q 29 61 81 57 41 19 5 Number of Elevators One ................................................. 208 Q 29 57 62 29 11 4 Q Two to Five .....................................

338

table1.xls  

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

2.2 2.2 77.7 81.3 84.6 84.9 98.9 Household Characteristics Census Region and Division Northeast............................................................... 13.9 15.0 15.2 16.0 14.7 17.7 New England........................................................ 3.8 3.7 3.6 3.9 4.1 5.4 Middle Atlantic ..................................................... 10.1 11.3 11.6 12.1 10.7 12.3 Midwest ................................................................. 18.3 19.5 20.4 21.1 21.6 23.6 East North Central............................................... 12.3 13.2 14.3 15.1 15.1 16.3 West North Central ............................................. 6.0 6.4 6.1 6.0 6.5 7.3 South..................................................................... 24.7 27.0 28.3 29.5 30.2 36.2 South Atlantic.......................................................

339

b38.xls  

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

Released: October 2006 Next CBECS will be conducted in 2007 Heat Pumps Furnaces Individual Space Heaters District Heat Boilers Packaged Heating Units Other All Buildings* .................................. 4,645 3,982 476 1,864 819 65 579 953 205 Table B38. Heating Equipment, Number of Buildings for Non-Mall Buildings, 2003 Heating Equipment (more than one may apply) Number of Buildings (thousand) All Buildings* Heated Buildings Number of Floors One ................................................... 3,136 2,566 334 1,193 550 14 190 682 140 Two ................................................... 1,031 960 97 487 174 19 194 207 50 Three ................................................ 339 319 31 155 68 10 119 41 Q Four to Nine ...................................... 128 125 11 28 25 19 69 20 4 Ten or More ......................................

340

b43.xls  

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

4,645 4,645 4,248 2,184 3,943 941 455 565 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 2,261 1,070 2,068 382 101 205 5,001 to 10,000 ................................. 889 821 416 772 148 88 107 10,001 to 25,000 ............................... 738 716 412 665 189 105 123 25,001 to 50,000 ............................... 241 231 145 223 102 60 55 50,001 to 100,000 ............................. 129 126 75 123 60 51 37 100,001 to 200,000 ........................... 65 63 43 62 38 32 25 200,001 to 500,000 ........................... 25 24 17 24 16 13 10 Over 500,000 .................................... 7 6 5 6 5 4 4 Principal Building Activity Education .......................................... 386 384 132 368 97 59 39 Food Sales ....................................... 226 221 78 217 35 Q Q Food Service .....................................

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

table8.xls  

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

80.3 80.3 83.9 82.4 82.8 90.6 113.1 Household Characteristics Census Region and Division Northeast............................................................... 14.5 14.6 14.0 14.1 14.5 18.1 New England........................................................ 3.9 3.6 3.4 3.5 4.1 5.8 Middle Atlantic ..................................................... 10.7 11.0 10.6 10.6 10.4 12.3 Midwest ................................................................. 20.2 20.9 20.8 21.3 23.8 27.8 East North Central............................................... 13.3 13.5 14.3 15.2 16.7 19.1 West North Central ............................................. 6.8 7.4 6.5 6.0 7.2 8.7 South..................................................................... 29.1 30.7 29.6 29.8 33.5 43.2 South Atlantic.......................................................

342

b40.xls  

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

4,645 4,645 3,625 1,006 492 742 33 111 1,613 122 40 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 1,841 581 260 383 Q Q 678 58 Q 5,001 to 10,000 ................................. 889 732 207 78 134 Q Q 367 26 Q 10,001 to 25,000 ............................... 738 629 140 87 114 Q 26 332 26 Q 25,001 to 50,000 ............................... 241 216 47 33 62 6 19 119 Q Q 50,001 to 100,000 ............................. 129 118 19 20 27 5 24 67 Q Q 100,001 to 200,000 ........................... 65 60 8 8 16 6 17 32 Q Q 200,001 to 500,000 ........................... 25 23 4 4 4 2 10 13 Q Q Over 500,000 .................................... 7 6 1 1 1 1 3 3 Q Q Principal Building Activity Education .......................................... 386 352 59 63 87 14 36 139 Q Q Food Sales .......................................

343

a3.xls  

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

4,859 252 509 728 577 926 360 587 316 603 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,586 134 240 372 356 474 217 294 166 333 5,001 to 10,000 ................................. 948 49 106 128 100 200 59 127 62 117 10,001 to 25,000 ............................... 810 46 92 133 78 151 54 103 61 91 25,001 to 50,000 ............................... 261 10 29 48 27 52 16 28 16 34 50,001 to 100,000 ............................. 147 8 23 25 10 26 11 21 7 15 100,001 to 200,000 ........................... 74 3 12 14 5 18 Q 10 3 7 200,001 to 500,000 ........................... 26 Q 6 6 1 4 Q 3 1 3 Over 500,000 .................................... 8 Q 2 1 Q 2 Q Q Q 1 Principal Building Activity Education .......................................... 386 Q 21 34 29 87 Q 56 39 97 Food Sales .......................................

344

b31.xls  

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

4,645 4,645 3,472 1,910 1,445 94 27 128 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,552 1,715 1,020 617 41 N 66 5,001 to 10,000 ................................. 889 725 386 307 Q Q 27 10,001 to 25,000 ............................... 738 607 301 285 16 Q 27 25,001 to 50,000 ............................... 241 217 110 114 Q Q Q 50,001 to 100,000 ............................. 129 119 53 70 Q 5 Q 100,001 to 200,000 ........................... 65 60 27 35 Q 5 Q 200,001 to 500,000 ........................... 25 23 9 14 Q 2 Q Over 500,000 .................................... 7 6 3 3 Q 1 N Principal Building Activity Education .......................................... 386 298 144 149 10 6 15 Food Sales ....................................... 226 186 109 68 Q N Q Food Service .....................................

345

b7.xls  

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

Square Square Feet 50,001 to 100,000 Square Feet 100,001 to 200,000 Square Feet 200,001 to 500,000 Square Feet Over 500,000 Square Feet All Buildings* .................................. 64,783 6,789 6,585 11,535 8,668 9,057 9,064 7,176 5,908 Principal Building Activity Education .......................................... 9,874 409 399 931 1,756 2,690 2,167 1,420 Q Food Sales ....................................... 1,255 409 356 Q Q Q Q N N Food Service ..................................... 1,654 544 442 345 Q Q N Q N Health Care ....................................... 3,163 165 280 313 157 364 395 514 973 Inpatient .......................................... 1,905 N N Q Q Q Q 467 973 Outpatient ....................................... 1,258 165 280 312 Q 206 Q Q N Lodging ............................................. 5,096 99

346

eia-910.xls  

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

30 calendar days following the end of the report period. U. S. Department of Energy Oil & Gas Survey Ben Franklin Station P.O. Box 279 Washington, DC 20044-0279 Email: Year: If...

347

eia191.xls  

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

EIA-191 Ben Franklin Station Address 2: City: State: Zip: - Storage Field Name Reservoir Name Location State Location County Total Storage Field Capacity (Mcf) Maximum...

348

A Portrait Drawing Robot Using a Geometric Graph Approach: Furthest Neighbour Theta-Graphs  

E-Print Network [OSTI]

literature include painting robots where various type of systems were implemented [1], [2], [4]. For instanceA Portrait Drawing Robot Using a Geometric Graph Approach: Furthest Neighbour Theta-Graphs Meng drawing humanoid robot, Betty. To solve this line drawing problem we present a modified Theta

Durocher, Stephane

349

Streaming Graph Computations with a Helpful Advisor  

E-Print Network [OSTI]

Motivated by the trend to outsource work to commercial cloud computing services, we consider a variation of the streaming paradigm where a streaming algorithm can be assisted by a powerful helper that can provide annotations to the data stream. We extend previous work on such {\\em annotation models} by considering a number of graph streaming problems. Without annotations, streaming algorithms for graph problems generally require significant memory; we show that for many standard problems, including all graph problems that can be expressed with totally unimodular integer programming formulations, only a constant number of hash values are needed for single-pass algorithms given linear-sized annotations. We also obtain a protocol achieving \\textit{optimal} tradeoffs between annotation length and memory usage for matrix-vector multiplication; this result contributes to a trend of recent research on numerical linear algebra in streaming models.

Cormode, Graham; Thaler, Justin

2010-01-01T23:59:59.000Z

350

Sequoia tops Graph 500 list of 'big data' supercomputers  

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

ATL062113_graph ATL062113_graph 06/21/2013 The Livermore Lab's Sequoia supercomputer topped the biannual Graph 500 list of the world's fastest systems for "big data" this week. The Graph 500 benchmark measures the speed with which a supercomputer can "connect the dots" within a massive set of data. Sequoia traversed 15,363 connections per second. Sequoia tops Graph 500 list of 'big data' supercomputers Donald B Johnston, LLNL, (925) 423-4902, johnston19@llnl.gov LLNL's 20 petaflops Sequoia supercomputer has retained its No. 1 ranking on the Graph 500 list, a measure of a system's ability to conduct analytic calculations -- finding the proverbial needle in the haystack. An IBM Blue Gene Q system, Sequoia was able to traverse 15,363 giga edges per second on a scale of 40 graph (a graph with 2^40 vertices). The new

351

An efficient semidefinite programming relaxation for the graph ...  

E-Print Network [OSTI]

The general graph partition problem (GPP) is defined as follows. Let G = (V ... We denote by A the adjacency matrix of G. For a given partition of the graph into k.

2012-08-28T23:59:59.000Z

352

Synthesis of Parallel Hardware Implementations from Synchronous Dataflow Graph Specifications  

E-Print Network [OSTI]

Synthesis of Parallel Hardware Implementations from Synchronous Dataflow Graph Specifications, Berkeley Spring 1998 #12; Synthesis of Parallel Hardware Implementations from Synchronous Dataflow Graph Specifications Copyright © 1998 by Michael Cameron Williamson #12; 1 Abstract Synthesis of Parallel Hardware

353

Synthesis of Parallel Hardware Implementations from Synchronous Dataflow Graph Specifications  

E-Print Network [OSTI]

Synthesis of Parallel Hardware Implementations from Synchronous Dataflow Graph Specifications, Berkeley Spring 1998 #12;Synthesis of Parallel Hardware Implementations from Synchronous Dataflow Graph Specifications Copyright © 1998 by Michael Cameron Williamson #12;1 Abstract Synthesis of Parallel Hardware

354

Towards a Query-by-Example System for Knowledge Graphs  

Science Journals Connector (OSTI)

We witness an unprecedented proliferation of knowledge graphs that record millions of heterogeneous entities and their diverse relationships. While knowledge graphs are structure-flexible and content-rich, it is difficult to query them. The challenge ...

Nandish Jayaram; Arijit Khan; Chengkai Li; Xifeng Yan; Ramez Elmasri

2014-06-01T23:59:59.000Z

355

Graph Expansion, Tseitin Formulas and Resolution Proofs for CSP  

Science Journals Connector (OSTI)

We study the resolution complexity of Tseitin formulas over arbitrary rings in terms of combinatorial properties of graphs. We give some evidence that an expansion of a graph is a good characterization of the ...

Dmitry Itsykson; Vsevolod Oparin

2013-01-01T23:59:59.000Z

356

Graph isomorphism and adiabatic quantum computing  

Science Journals Connector (OSTI)

In the graph isomorphism (GI) problem two N-vertex graphs G and G? are given and the task is to determine whether there exists a permutation of the vertices of G that preserves adjacency and transforms G?G?. If yes, then G and G? are said to be isomorphic; otherwise they are nonisomorphic. The GI problem is an important problem in computer science and is thought to be of comparable difficulty to integer factorization. In this paper we present a quantum algorithm that solves arbitrary instances of GI and which also provides an approach to determining all automorphisms of a given graph. We show how the GI problem can be converted to a combinatorial optimization problem that can be solved using adiabatic quantum evolution. We numerically simulate the algorithm's quantum dynamics and show that it correctly (i) distinguishes nonisomorphic graphs; (ii) recognizes isomorphic graphs and determines the permutation(s) that connect them; and (iii) finds the automorphism group of a given graph G. We then discuss the GI quantum algorithm's experimental implementation, and close by showing how it can be leveraged to give a quantum algorithm that solves arbitrary instances of the NP-complete subgraph isomorphism problem. The computational complexity of an adiabatic quantum algorithm is largely determined by the minimum energy gap ?(N) separating the ground and first-excited states in the limit of large problem size N?1. Calculating ?(N) in this limit is a fundamental open problem in adiabatic quantum computing, and so it is not possible to determine the computational complexity of adiabatic quantum algorithms in general, nor consequently, of the specific adiabatic quantum algorithms presented here. Adiabatic quantum computing has been shown to be equivalent to the circuit model of quantum computing, and so development of adiabatic quantum algorithms continues to be of great interest.

Frank Gaitan and Lane Clark

2014-02-28T23:59:59.000Z

357

BAG: a graph theoretic sequence clustering algorithm  

Science Journals Connector (OSTI)

In this paper, we first discuss issues in clustering biological sequences with graph properties, which inspired the design of our sequence clustering algorithm BAG. BAG recursively utilises several graph properties: biconnectedness, articulation points, pquasi-completeness, and domain knowledge specific to biological sequence clustering. To reduce the fragmentation issue, we have developed a new metric called cluster utility to guide cluster splitting. Clusters are then merged back with less stringent constraints. Experiments with the entire COG database and other sequence databases show that BAG can cluster a large number of sequences accurately while keeping the number of fragmented clusters significantly low.

Sun Kim; Jason Lee

2006-01-01T23:59:59.000Z

358

Bose-Einstein condensation on quantum graphs  

E-Print Network [OSTI]

We present results on Bose-Einstein condensation (BEC) on general compact quantum graphs, i.e., one-dimensional systems with a (potentially) complex topology. We first investigate non-interacting many-particle systems and provide a complete classification of systems that exhibit condensation. We then consider models with interactions that consist of a singular part as well as a hardcore part. In this way we obtain generalisations of the Tonks-Girardeau gas to graphs. For this we find an absence of phase transitions which then indicates an absence of BEC.

Jens Bolte; Joachim Kerner

2014-03-02T23:59:59.000Z

359

Entanglement of graph states up to 8 qubits  

E-Print Network [OSTI]

The entanglement of graph states up to eight qubits is calculated in the regime of iteration calculation. The entanglement measures could be the relative entropy of entanglement, the logarithmic robustness or the geometric measure. All 146 local inequivalent graphs are classified as two categories: graphs with identical upper LOCC entanglement bound and lower bipartite entanglement bound, graphs with unequal bounds. The late may displays non-integer entanglement. The precision of iteration calculation of the entanglement is less than $10^{-14}$.

Xiao-yu Chen

2009-09-09T23:59:59.000Z

360

A survey of models of the web graph Anthony Bonato  

E-Print Network [OSTI]

A survey of models of the web graph Anthony Bonato Department of Mathematics Wilfrid Laurier University Waterloo, ON Canada, N2L 3C5 abonato@rogers.com Abstract. The web graph has been the focus of much rigorously. 1 Introduction The web graph W has nodes representing web pages, and edges rep- resenting

Bonato, Anthony

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Comparison of coarsening schemes for multilevel graph partitioning  

E-Print Network [OSTI]

Comparison of coarsening schemes for multilevel graph partitioning C´edric Chevalier1 and Ilya Laboratory, Argonne, IL, USA, safro@mcs.anl.gov Abstract. Graph partitioning is a well-known optimization as a process of graph topology learning at different scales in order to generate a better approx- imation

Safro, Ilya

362

On minimum balanced bipartitions of triangle-free graphs  

Science Journals Connector (OSTI)

A balanced bipartition of a graph G is a partition of V(G) into two subsets V 1 and V 2 that differ in cardinality by at most 1. A minimum balanced bipartition of G ... Keywords: Balanced bipartition, Planar graphs, Triangle-free graphs

Haiyan Li; Yanting Liang; Muhuo Liu; Baogang Xu

2014-04-01T23:59:59.000Z

363

Hiroshi Ishikawa A Practical Introduction to Graph Cut  

E-Print Network [OSTI]

Technology Contents Overview / Brief history Energy minimization Graphs and their minimum cuts Energy Elevation map #12;History Probablistic methods (SA, ICM,...) have been used for energy minimization OR has Overview / Brief history Energy minimization Graphs and their minimum cuts Energy minimization via graph

Ishikawa, Hiroshi

364

Hamiltonian Cycles on Symmetrical Graphs Carlo H. Squin  

E-Print Network [OSTI]

Hamiltonian Cycles on Symmetrical Graphs Carlo H. Séquin Computer Science Division, EECS Department-connected symmetrical graphs are colored so that they form Hamiltonian cycles. As an introduction we discuss is to color all edges in these graphs with multi- ple congruent copies of Hamiltonian cycles exhibiting

O'Brien, James F.

365

Compatible Hamilton cycles in Dirac graphs Michael Krivelevich  

E-Print Network [OSTI]

Compatible Hamilton cycles in Dirac graphs Michael Krivelevich Choongbum Lee Benny Sudakov system F over a Dirac graph G, there exists a Hamilton cycle compatible with F. This settles in a very strong form, a conjecture of H¨aggkvist from 1988. 1 Introduction A Hamilton cycle in a graph G

Krivelevich, Michael

366

Infinite Hamilton Cycles in Squares of Locally Finite Graphs  

E-Print Network [OSTI]

Infinite Hamilton Cycles in Squares of Locally Finite Graphs Agelos Georgakopoulos Abstract We prove Diestel's conjecture that the square G2 of a 2-connected locally finite graph G has a Hamilton if and only if they have distance at most n in G. A Hamilton cycle in a graph is a cycle containing all its

Diestel, Reinhard

367

Robust Self-assembly of Graphs Stanislav Angelov1  

E-Print Network [OSTI]

Robust Self-assembly of Graphs Stanislav Angelov1 , Sanjeev Khanna2 , and Mirk´o Visontai3 1 Google, University of Pennsylvania Philadelphia, PA 19104, USA mirko@math.upenn.edu Abstract. Self-assembly studied model of self-assembly is the Accretive Graph Assembly Model whereby an edge-weighted graph

Pennsylvania, University of

368

Simultaneous Segmentation and Filtering via Reduced Graph Cuts  

E-Print Network [OSTI]

provides small graphs while preserving thin structures but do not offer low memory usage when the amount [7,4,13]. In [7], binary energy functions are minimized for the shape fitting problem with graph cutsSimultaneous Segmentation and Filtering via Reduced Graph Cuts N. Lermé F. Malgouyres LAGA UMR CNRS

Malgouyres, François

369

Cellular Algebras and Graph Invariants Based on Quantum Walks  

E-Print Network [OSTI]

We consider two graph invariants inspired by quantum walks- one in continuous time and one in discrete time. We will associate a matrix algebra called a cellular algebra with every graph. We show that, if the cellular algebras of two graphs have a similar structure, then they are not distinguished by either of the proposed invariants.

Jamie Smith

2011-03-01T23:59:59.000Z

370

EFFECTIVE RESISTANCE ON GRAPHS AND THE EPIDEMIC QUASIMETRIC  

E-Print Network [OSTI]

EFFECTIVE RESISTANCE ON GRAPHS AND THE EPIDEMIC QUASIMETRIC JOSH ERICSON, PIETRO POGGI distance, effective resistance, and modulus of path families. 1. Introduction Consider a finite contact into "natural" communities. We begin with some preliminaries on elementary graph theory. 2. Graphs 2.1. Notation

Poggi-Corradini, Pietro

371

Bicycles and Left-Right Tours in Locally Finite Graphs  

E-Print Network [OSTI]

Bicycles and Left-Right Tours in Locally Finite Graphs von Melanie Win Myint, M. S. Dem Department-Right Tours 29 6 LRTs Generate the Bicycle Space 43 7 The ABL Planarity Criterion 53 8 Pedestrian Graphs 69 bicycles and some other concepts they relate to, such as left- right tours and pedestrian graphs

Diestel, Reinhard

372

Electricity - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Find statistics on electric power plants, capacity, generation, fuel Find statistics on electric power plants, capacity, generation, fuel consumption, sales, prices and customers. + EXPAND ALL Summary Additional formats Summary electricity statistics 2001-2011 › XLS Supply and disposition of electricity 2002-2011 › XLS Electricity overview › Generation, retail sales, electricity trade, losses PDF XLS Consumption for electricity generation › Fossil and renewable fuel consumption for electricity generation PDF XLS Generating capacity › Electric net summer capacity by specific energy source more on electricity PDF XLS Monthly electricity overview - back to 1973 CSV PDF XLS Latest month total electric power industry summary statistics › Overview XLS Year-to-date total electric power industry summary statistics ›

373

Parameterized Algorithms for Graph Partitioning Problems  

E-Print Network [OSTI]

) time algorithm for any FGPP. Parameterized by p, Max and Min k-Vertex Cover can be solved in times O (1Parameterized Algorithms for Graph Partitioning Problems Hadas Shachnai and Meirav Zehavi are constants defining the problem, and m1, m2 are the cardinalities of the edge sets having both endpoints

Shachnai, Hadas

374

Algorithms for Graphs (Locally) Bounded Treewidth  

E-Print Network [OSTI]

set, vertex cover and independent set. Others used this approach to solve other NP-hard problemsAlgorithms for Graphs of (Locally) Bounded Treewidth by MohammadTaghi Hajiaghayi A thesis presented-hard and hence there is no efficient algorithm for solving them, unless P= NP. One way to overcome this hardness

Hajiaghayi, Mohammad

375

Graph Domination, Coloring and Cliques in Telecommunications  

E-Print Network [OSTI]

Graph Domination, Coloring and Cliques in Telecommunications Balabhaskar Balasundaram and Sergiy for important problems that arise in different areas of wireless telecommunication. In particular, applications The telecommunication industry has always been a host for a wide variety of optimization problems. In recent years

Butenko, Sergiy

376

Optimizing Path Query Performance: Graph Clustering Strategies  

E-Print Network [OSTI]

ywh@us.ibm.com Ning Jingz Changsha Institute of Technology jning@eecs.umich.edu Elke A. Rundensteinerx not incur any run-time cost, requires no auxiliary data structures, and is complimentary to many of the performance of these graph clustering techniques using an actual city road network as well as randomly

377

The Web Graph of a Tourism System  

E-Print Network [OSTI]

The website network of a tourism destination is examined. The main statistical characteristics of the underlying graph are calculated. The topology of the network is similar to the one characterizing similar systems. However, some differences are found, mainly due to the relatively poor connectivity among the vertices of the network.

Baggio, R

2006-01-01T23:59:59.000Z

378

Connected obstructions to full graph homomorphisms  

Science Journals Connector (OSTI)

Minimal obstructions to full homomorphisms to a graph B have been proved to be of size at most |B|+1. This turns out to require that disconnected obstructions be allowed. In this paper we prove that the size of minimal connected obstructions is at most ...

Pavol Hell, Ale Pultr

2014-10-01T23:59:59.000Z

379

Graph Processing on an "almost" Relational Database  

Science Journals Connector (OSTI)

It would be hard to disagree with the contention that graph processing (whether it be of connections between people, shopping habits,...) allows the creation of valuable data-driven products and insights. There is less consensus on the systems that make ...

Ramesh Subramonian

2014-06-01T23:59:59.000Z

380

Betti Numbers of Graph Sean Jacques  

E-Print Network [OSTI]

ii Betti Numbers of Graph Ideals Sean Jacques Thesis submitted to the University of She but there are formulae for finding the Betti numbers (part of the information which comprises a minimal free resolution especially explicit or useful descriptions of the Betti numbers. However we restrict our attention to those

Katzman, Moty

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Graph-Theoretic Scagnostics Leland Wilkinson  

E-Print Network [OSTI]

Tukey and Tukey scagnostics and develop graph- theoretic methods for implementing their procedure, statistical graphics 1 INTRODUCTION Around 20 years ago, John and Paul Tukey developed an ex- ploratory of the method were never published. Paul Tukey did offer more detail at an IMA visualization workshop a few

Grossman, Robert

382

NEST REPRESENTATIONS OF DIRECTED GRAPH ALGEBRAS  

E-Print Network [OSTI]

NEST REPRESENTATIONS OF DIRECTED GRAPH ALGEBRAS KENNETH R. DAVIDSON AND ELIAS KATSOULIS Abstract. This paper is a comprehensive study of the nest rep- resentations for the free semigroupoid algebra LG that the finite dimensional nest representations sep- arate the points in LG, and a fortiori, in T + (G

Katsoulis, Elias G.

383

Quantum graph as a quantum spectral filter  

SciTech Connect (OSTI)

We study the transmission of a quantum particle along a straight input-output line to which a graph {Gamma} is attached at a point. In the point of contact we impose a singularity represented by a certain properly chosen scale-invariant coupling with a coupling parameter {alpha}. We show that the probability of transmission along the line as a function of the particle energy tends to the indicator function of the energy spectrum of {Gamma} as {alpha}{yields}{infinity}. This effect can be used for a spectral analysis of the given graph {Gamma}. Its applications include a control of a transmission along the line and spectral filtering. The result is illustrated with an example where {Gamma} is a loop exposed to a magnetic field. Two more quantum devices are designed using other special scale-invariant vertex couplings. They can serve as a band-stop filter and as a spectral separator, respectively.

Turek, Ondrej; Cheon, Taksu [Laboratory of Physics, Kochi University of Technology, Tosa Yamada, Kochi 782-8502 (Japan)] [Laboratory of Physics, Kochi University of Technology, Tosa Yamada, Kochi 782-8502 (Japan)

2013-03-15T23:59:59.000Z

384

A Parallel Graph Partitioner for STAPL  

E-Print Network [OSTI]

A PARALLEL GRAPH PARTITIONER FOR STAPL A Thesis by NICOLAS CASTET Submitted to the O ce of Graduate Studies of Texas A&M University in partial ful llment of the requirements for the degree of MASTER OF SCIENCE Approved by: Chair... of Committee, Nancy M. Amato Co-Chair of Committee, Lawrence Rauchwerger Committee Member, Marvin L. Adams Department Head, Duncan M. Walker May 2013 Major Subject: Computer Science Copyright 2013 Nicolas Castet ABSTRACT Multi-core architectures...

Castet, Nicolas

2013-04-26T23:59:59.000Z

385

Locating-total domination in claw-free cubic graphs  

Science Journals Connector (OSTI)

In this paper, we continue the study of locating-total domination in graphs. A set S of vertices of a graph G is a total dominating set of G if every vertex of G is adjacent to a vertex in S . We consider total dominating sets S which have the additional property that distinct vertices in V ( G ) ? S are totally dominated by distinct subsets of the total dominating set. Such a set S is called a locating-total dominating set in G , and the locating-total domination number of G is the minimum cardinality of a locating-total dominating set in G . A claw-free graph is a graph that does not contain K 1 , 3 as an induced subgraph. We show that the locating-total domination number of a claw-free cubic graph is at most one-half its order and we characterize the graphs achieving this bound.

Michael A. Henning; Christian Lwenstein

2012-01-01T23:59:59.000Z

386

Sharp thresholds for Hamiltonicity in random intersection graphs  

Science Journals Connector (OSTI)

Random Intersection Graphs, G"n","m","p, is a class of random graphs introduced in Karonski (1999) [7] where each of the n vertices chooses independently a random subset of a universal set of m elements. Each element of the universal sets is chosen independently ... Keywords: Hamilton cycles, Random intersection graph, Sharp threshold, Stochastic order relation between Gn,p and Gn,m,p

Charilaos Efthymiou; Paul G. Spirakis

2010-09-01T23:59:59.000Z

387

k-Boson Quantum Walks Do Not Distinguish Arbitrary Graphs  

E-Print Network [OSTI]

In this paper, we define k-equivalence, a relation on graphs that relies on their associated cellular algebras. We show that a k-Boson quantum walk cannot distinguish pairs of graphs that are k- equivalent. The existence of pairs of k-equivalent graphs has been shown by Ponomarenko et al. [2, 6]. This gives a negative answer to a question posed by Gamble et al. [7].

Jamie Smith

2010-04-01T23:59:59.000Z

388

Ising-like models on arbitrary graphs : the Hadamard way  

E-Print Network [OSTI]

We propose a generic framework to analyse classical Ising-like models defined on arbitrary graphs. The energy spectrum is shown to be the Hadamard transform of a suitably defined vector associated with the graph. This allows a quick computation of this spectrum owing to the existence of a fast Hadamard transform algorithm (used for instance in image ccompression processes). We than go further and apply this formalism to regular graphs, such as hypercubic graphs, for which a simple recurrence relation for the spectrum is given, which speeds up even more its determination. First attempts to analyse partition functions and transfer matrices are also discussed.

Mosseri, Rmy

2014-01-01T23:59:59.000Z

389

Computing the stability number of a graph via linear and ...  

E-Print Network [OSTI]

Throughout the paper A(G) ? Sn will denote the adjacency matrix of the graph G, that is, the (i, ..... Some matlab code that constructs the relevant semidefi-.

2006-04-27T23:59:59.000Z

390

Independent set problems and odd-hole-preserving graph reductions  

E-Print Network [OSTI]

to provide a polynomial-time reduction in the size of the input required to decide the perfection or imperfection of a graph....

Warren, Jeffrey Scott

2009-05-15T23:59:59.000Z

391

Polyhedral graph abstractions and an approach to the Linear Hirsch ...  

E-Print Network [OSTI]

March 17, 2011. Abstract. We introduce a new combinatorial abstraction for the graphs of polyhe- dra. The new abstraction is a flexible framework defined by...

2011-03-17T23:59:59.000Z

392

Isomorphism testing for circulant graphs Cn(a, b)  

E-Print Network [OSTI]

Isomorphism testing for circulant graphs Cn(a, b). Sara Nicoloso ?. Ugo Pietropaoli . March 10, 2010. Abstract. In this paper we focus on connected...

2010-03-10T23:59:59.000Z

393

A notable family of entire intrinsic minimal graph...  

E-Print Network [OSTI]

to C1(O). This notion of C2 surface obviously includes the entire intrinsic graphs ...... F. Serra Cassano, Surface measures in Carnot-Carathodory spaces, Calc.

2006-09-09T23:59:59.000Z

394

Graphs are among the most important abstract data structures in computer sci-ence, and the algorithms that operate on them are critical to modern life. Graphs  

E-Print Network [OSTI]

description that assumes a sparse matrix representation of the graph, and operates on that matrix with linear environments (e.g., Matlab ). (2) Ease of implementation. Parallel graph algorithms are notoriously difficult computation of graph algorithms. (3) Performance. Graph algorithms expressed by a series of sparse matrix

Kepner, Jeremy

395

Ising models on power-law random graphs Sander Dommers  

E-Print Network [OSTI]

Ising models on power-law random graphs Sander Dommers Cristian Giardin`a Remco van der Hofstad May 25, 2010 Abstract We study a ferromagnetic Ising model on random graphs with a power-law degree Introduction and results In this article we study the behavior of the Ising model on complex networks

Hofstad, Remco van der

396

GRAPH THEORY AND PFAFFIAN REPRESENTATIONS OF ISING PARTITION FUNCTION.  

E-Print Network [OSTI]

GRAPH THEORY AND PFAFFIAN REPRESENTATIONS OF ISING PARTITION FUNCTION. THIERRY GOBRON Abstract. A well known theorem due to Kasteleyn states that the partition function of an Ising model to the graph. This results both embodies the free fermionic nature of any planar Ising model and eventually

Recanati, Catherine

397

Human-assisted graph search: it's okay to ask questions  

Science Journals Connector (OSTI)

We consider the problem of human-assisted graph search: given a directed acyclic graph with some (unknown) target node(s), we consider the problem of finding the target node(s) by asking an omniscient human questions of the form "Is there a target ...

Aditya Parameswaran; Anish Das Sarma; Hector Garcia-Molina; Neoklis Polyzotis; Jennifer Widom

2011-02-01T23:59:59.000Z

398

Local algorithms for the prime factorization of strong product graphs  

E-Print Network [OSTI]

Local algorithms for the prime factorization of strong product graphs Marc Hellmuth, Wilfried factorization algorithms is limited in practise by unavoidable noise in the data. A first step towards error-tolerant "approximate" prime factorization, is the development of local approaches that cover the graph by factorizable

Stadler, Peter F.

399

Groups generated by bounded automata and their schreier graphs  

E-Print Network [OSTI]

that the Schreier graphs on levels of automaton groups can be constructed by an iterative procedure of inflation of graphs. This was used to associate a piecewise linear map of the form fK(v) = minA?KAv, where K is a finite set of nonnegative matrices, with every...

Bondarenko, Ievgen

2009-05-15T23:59:59.000Z

400

A SPATIAL WEB GRAPH MODEL WITH LOCAL INFLUENCE REGIONS  

E-Print Network [OSTI]

A SPATIAL WEB GRAPH MODEL WITH LOCAL INFLUENCE REGIONS W. AIELLO, A. BONATO, C. COOPER, J. JANSSEN- served in real-world networks such as the web graph. On the other hand, experimental and heuristic network can be recognized as densely linked subgraphs, or that web pages with many common neigh- bours

Pralat, Pawel

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Semidefinite programming and eigenvalue bounds for the graph ...  

E-Print Network [OSTI]

The graph partition problem is the problem of partitioning the vertex set of a graph ... In this paper we simplify a known matrix-lifting semidefinite ...... [44] Sturm, J.F.: Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones.

2013-11-26T23:59:59.000Z

402

ADAGE: A software package for analyzing graph evolution  

E-Print Network [OSTI]

graph evolution. 2.2 Using ADAGE 2.2.1 Installation ADAGE was built for use on MATLAB 2007 version. In this case input is a string. If the MATLAB matrix has already been saved, simply run > input = loadADAGE: A software package for analyzing graph evolution Mary McGlohon, Christos Faloutsos May 2007

403

MATLAB Tutorial Getting Started with Calculations, Graphing and Programming  

E-Print Network [OSTI]

MATLAB Tutorial Getting Started with Calculations, Graphing and Programming Nicholas R. Kirchner UI 2 Calculations with MATLAB Standard Calculations and Variables Matrices and Vectors 3 Graphing NRK;Matrices and Vectors, Definitions MATLAB is short for MATrix LABoratory. It was built for high-speed matrix

Weinberger, Hans

404

New approximation algorithms for minimum cycle bases of graphs  

Science Journals Connector (OSTI)

We consider the problem of computing an approximate minimum cycle basis of an undirected edge-weighted graph G with m edges and n vertices; the extension to directed graphs is also discussed. In this problem, a {0, 1} incidence vector ...

Telikepalli Kavitha; Kurt Mehlhorn; Dimitrios Michail

2007-02-01T23:59:59.000Z

405

Rank Synopses for Efficient Time Travel on the Web Graph  

E-Print Network [OSTI]

Rank Synopses for Efficient Time Travel on the Web Graph Klaus Berberich, Srikanta Bedathur}@mpi-inf.mpg.de ProblemProblem SolutionSolution ExperimentsExperiments Step 1: PageRank Normalization We normalize PageRank scores computed on Gt ( Vt, Et ) (i.e., the graph at time t ) dividing by the lower bound PageRank score

406

Algorithms to Compute Minimum Cycle Basis in Directed Graphs #  

E-Print Network [OSTI]

, . . . ,C d whose incidence vectors permit a unique linear combination of the incidence vector of any cycleAlgorithms to Compute Minimum Cycle Basis in Directed Graphs # Telikepalli Kavitha + Kurt Mehlhorn # Abstract We consider the problem of computing a minimum cycle basis in a di­ rected graph G with m arcs

Mehlhorn, Kurt

407

VIDEO SUMMARIZATION BY VIDEO STRUCTURE ANALYSIS AND GRAPH OPTIMIZATION  

E-Print Network [OSTI]

VIDEO SUMMARIZATION BY VIDEO STRUCTURE ANALYSIS AND GRAPH OPTIMIZATION Shi Lu, Irwin King video summarization method that combines video structure analysis and graph optimiza- tion. First, we analyze the structure of the video, find the boundaries of video scenes, then we calculate each scene

King, Kuo Chin Irwin

408

Video Denoising and Simplification Via Discrete Regularization on Graphs  

E-Print Network [OSTI]

Video Denoising and Simplification Via Discrete Regularization on Graphs Mahmoud Ghoniem, Youssef algorithms for video de- noising and simplification based on discrete regularization on graphs. The main difference between video and image denoising is the temporal redundancy in video sequences. Recent works

Paris-Sud XI, Université de

409

Fast top-k simple shortest paths discovery in graphs  

Science Journals Connector (OSTI)

With the wide applications of large scale graph data such as social networks, the problem of finding the top-k shortest paths attracts increasing attention. This paper focuses on the discovery of the top-k simple shortest paths (paths without ... Keywords: graphs, shortest path, top-k

Jun Gao; Huida Qiu; Xiao Jiang; Tengjiao Wang; Dongqing Yang

2010-10-01T23:59:59.000Z

410

Some Remarks on Factor Graphs Hans-Andrea Loeliger  

E-Print Network [OSTI]

be used and combined in factor graphs. Keywords: factor graphs, turbo signal processing, gradient methodsA(x)fB(x)fC(x). (2) We expand this into f(x) = fA(x)fB(x )fC(x )(x - x )(x - x ), (3) #12;fA x = x fC fB x Figure 2

Loeliger, Hans-Andrea

411

Which Codes Have Cycle-Free Tanner Graphs?  

E-Print Network [OSTI]

, 2, 4, 5, 9, 11, 16, 17, 18, 22, 29, 30]. For example, the well- known turbo codes and turbo decoding-graph representations for turbo codes were introduced in [29, 30], where it is also shown that turbo decoding asymptotically good if the underlying Tanner graph is a sufficiently strong expander. These codes were studied

Karpovsky, Mark

412

Graph-based Image Segmentation Using Weighted Color Patch  

E-Print Network [OSTI]

Graph-based Image Segmentation Using Weighted Color Patch Xiaofang Wang1 , Chao Zhu1 , Charles a new method based on the weighted color patch to compute the weight of edges in an affinity graph with color patches. Furthermore, we assign both local and global weights adaptively for each pixel in a patch

Paris-Sud XI, Université de

413

THE ELECTRICAL RESISTANCE OF A GRAPH CAPTURES ITS  

E-Print Network [OSTI]

THE ELECTRICAL RESISTANCE OF A GRAPH CAPTURES ITS COMMUTE AND COVER TIMES Ashok K. Chandra random walks and electrical networks by showing that resistance in this network is intimately connected of the graph is replaced by a unit resistance. As an example of the interplay between electrical

Borenstein, Elhanan

414

A COMBINATORIAL PROOF OF RAYLEIGH MONOTONICITY FOR GRAPHS  

E-Print Network [OSTI]

of the Rayleigh monotonicity property of graphs. Consider a (linear, resistive) electrical network, AND D.G. WAGNER Abstract. We give an elementary, self-contained, and purely com- binatorial proof allow graphs to have loops and/or mul- tiple edges. The value of ye is interpreted as the electrical

415

Bicyclic graphs with exactly two main signless Laplacian eigenvalues  

E-Print Network [OSTI]

A signless Laplacian eigenvalue of a graph $G$ is called a main signless Laplacian eigenvalue if it has an eigenvector the sum of whose entries is not equal to zero. In this paper, all connected bicyclic graphs with exactly two main eigenvalues are determined.

Huang, He

2012-01-01T23:59:59.000Z

416

Motorcycle Graphs and Straight Skeletons Siu-Wing Cheng  

E-Print Network [OSTI]

Motorcycle Graphs and Straight Skeletons Siu-Wing Cheng Antoine Vigneron March 17, 2005 Abstract We present a new algorithm to compute motorcycle graphs. It runs in O(n n log n) time when n is the number of motorcycles. We give a new characterization of the straight skeleton of a non

Vigneron, Antoine

417

On bounding the bandwidth of graphs with symmetry - Optimization ...  

E-Print Network [OSTI]

Hamming graph H(2,q) (also known as the lattice graph) has bandwidth equal to. (q+1)q. 2. ?1 .... 59. 10 3 120. 72. 75. 76. 90. Table 9: Bounds on the bandwidth of K(v,2) and K(v,3). v d meig .... Freeman, San Francisco, 1979. [19] Graham, A.

2013-08-08T23:59:59.000Z

418

International energy indicators. [Statistical tables and graphs  

SciTech Connect (OSTI)

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.

Bauer, E.K. (ed.)

1980-05-01T23:59:59.000Z

419

An Experiment on Graph Analysis Methodologies for Scenarios  

SciTech Connect (OSTI)

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.

Brothers, Alan J.; Whitney, Paul D.; Wolf, Katherine E.; Kuchar, Olga A.; Chin, George

2005-09-30T23:59:59.000Z

420

Graphical description of local Gaussian operations for continuous-variable weighted graph states  

E-Print Network [OSTI]

The form of a local Clifford (LC, also called local Gaussian (LG)) operation for the continuous-variable (CV) weighted graph states is presented in this paper, which is the counterpart of the LC operation of local complementation for qubit graph states. The novel property of the CV weighted graph states is shown, which can be expressed by the stabilizer formalism. It is distinctively different from the qubit weighted graph states, which can not be expressed by the stabilizer formalism. The corresponding graph rule, stated in purely graph theoretical terms, is described, which completely characterizes the evolution of CV weighted graph states under this LC operation. This LC operation may be applied repeatedly on a CV weighted graph state, which can generate the infinite LC equivalent graph states of this graph state. This work is an important step to characterize the LC equivalence class of CV weighted graph states.

Jing Zhang

2008-10-08T23:59:59.000Z

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

M&Ms4Graphs: Multi-scale, Multi-dimensional Graph Analytics Tools for Cyber-Security  

E-Print Network [OSTI]

ranging from micro- (host level) to macro-scale (enterprise level). Achievements · Major release of Graph Library - Exhibit at GraphLab Conference, July 2014 · Selected publications 1. "Towards A Networks-of-Networks of Machine Learning Research, 2014. Rendering of Network Traffic Data Showing Communication between IP

422

MapGraph: A High Level API for Fast Development of High Performance Graph Analytics on GPUs  

Science Journals Connector (OSTI)

High performance graph analytics are critical for a long list of application domains. In recent years, the rapid advancement of many-core processors, in particular graphical processing units (GPUs), has sparked a broad interest in developing high performance ... Keywords: GPU, Graph analytics, high-level API

Zhisong Fu; Michael Personick; Bryan Thompson

2014-06-01T23:59:59.000Z

423

Efficient broadcast on random geometric graphs  

SciTech Connect (OSTI)

A Randon Geometric Graph (RGG) is constructed by distributing n nodes uniformly at random in the unit square and connecting two nodes if their Euclidean distance is at most r, for some prescribed r. They analyze the following randomized broadcast algorithm on RGGs. At the beginning, there is only one informed node. Then in each round, each informed node chooses a neighbor uniformly at random and informs it. They prove that this algorithm informs every node in the largest component of a RGG in {Omicron}({radical}n/r) rounds with high probability. This holds for any value of r larger than the critical value for the emergence of a giant component. In particular, the result implies that the diameter of the giant component is {Theta}({radical}n/r).

Bradonjic, Milan [Los Alamos National Laboratory; Elsasser, Robert [UNIV OF PADERBORN; Friedrich, Tobias [INTERNATIONAL COMPUTER SCI.; Sauerwald, Thomas [INTERNATIONAL COMPUTER SCI.

2009-01-01T23:59:59.000Z

424

Bicyclic graphs with maximal revised Szeged index  

E-Print Network [OSTI]

The revised Szeged index $Sz^*(G)$ is defined as $Sz^*(G)=\\sum_{e=uv \\in E}(n_u(e)+ n_0(e)/2)(n_v(e)+ n_0(e)/2),$ where $n_u(e)$ and $n_v(e)$ are, respectively, the number of vertices of $G$ lying closer to vertex $u$ than to vertex $v$ and the number of vertices of $G$ lying closer to vertex $v$ than to vertex $u$, and $n_0(e)$ is the number of vertices equidistant to $u$ and $v$. Hansen used the AutoGraphiX and made the following conjecture about the revised Szeged index for a connected bicyclic graph $G$ of order $n \\geq 6$:

Li, Xueliang

2011-01-01T23:59:59.000Z

425

ASYMPTOTIC STUDY OF SUBCRITICAL GRAPH CLASSES MICHAEL DRMOTA, ERIC FUSY, MIHYUN KANG, VERONIKA KRAUS  

E-Print Network [OSTI]

ASYMPTOTIC STUDY OF SUBCRITICAL GRAPH CLASSES MICHAEL DRMOTA, ´ERIC FUSY, MIHYUN KANG, VERONIKA from the so-called "subcritical" graph classes, which include the classes of cacti graphs, outerplanar graphs chosen from subcritical classes. We show that the number gn/n! (resp. gn) of labelled (resp

Paris-Sud XI, Université de

426

THE MATCHING ENERGY OF A GRAPH IVAN GUTMAN AND STEPHAN WAGNER  

E-Print Network [OSTI]

(3) implies that the energy of a tree is a monotonically increasing function of any m(T, k) for the study of the energy of trees, we may consider it also for cycle­containing graphs. For such graphsTHE MATCHING ENERGY OF A GRAPH IVAN GUTMAN AND STEPHAN WAGNER Abstract. The energy of a graph G

Wagner, Stephan

427

Multiclass Diffuse Interface Models for Semi-supervised Learning on Graphs  

E-Print Network [OSTI]

Multiclass Diffuse Interface Models for Semi-supervised Learning on Graphs Cristina Garcia-Cardona1: Graph Segmentation, Diffuse Interfaces, Learning on Graphs. Abstract: We present a graph-based variational algorithm for multiclass classification of high-dimensional data, moti- vated by total variation

Percus, Allon

428

Locating and paired-dominating sets in graphs  

Science Journals Connector (OSTI)

In this paper, we continue the study of paired-domination in graphs introduced by Haynes and Slater [T.W. Haynes, P.J. Slater, Paired-domination in graphs, Networks 32 (1998), 199206]. A paired-dominating set of a graph G with no isolated vertex is a dominating set S of vertices whose induced subgraph has a perfect matching. We consider paired-dominating sets which are also locating sets, that is distinct vertices of G are dominated by distinct subsets of the paired-dominating set. We consider three variations of sets which are paired-dominating and locating sets and investigate their properties.

John McCoy; Michael A. Henning

2009-01-01T23:59:59.000Z

429

Geodesic Distance in Planar Graphs: An Integrable Approach  

E-Print Network [OSTI]

We discuss the enumeration of planar graphs using bijections with suitably decorated trees, which allow for keeping track of the geodesic distances between faces of the graph. The corresponding generating functions obey non-linear recursion relations on the geodesic distance. These are solved by use of stationary multi-soliton tau-functions of suitable reductions of the KP hierarchy. We obtain a unified formulation of the (multi-) critical continuum limit describing large graphs with marked points at large geodesic distances, and obtain integrable differential equations for the corresponding scaling functions. This provides a continuum formulation of two-dimensional quantum gravity, in terms of the geodesic distance.

P. Di Francesco

2005-06-27T23:59:59.000Z

430

The Graph Laplacian and the Dynamics of Complex Networks  

SciTech Connect (OSTI)

In this talk, we explore the structure of networks from a spectral graph-theoretic perspective by analyzing the properties of the Laplacian matrix associated with the graph induced by a network. We will see how the eigenvalues of the graph Laplacian relate to the underlying network structure and dynamics and provides insight into a phenomenon frequently observed in real world networks - the emergence of collective behavior from purely local interactions seen in the coordinated motion of animals and phase transitions in biological networks, to name a few.

Thulasidasan, Sunil [Los Alamos National Laboratory

2012-06-11T23:59:59.000Z

431

Local complementation rule for continuous-variable four-mode unweighted graph states  

E-Print Network [OSTI]

The local complementation rule is applied for continuous-variable (CV) graph states in the paper, which is an elementary graph transformation rule and successive application of which generates the orbit of any graph states. The corresponding local Gaussian transformations of local complementation for four-mode unweighted graph states were found, which do not mirror the form of the local Clifford unitary of qubit exactly. This work is an important step to characterize the local Gaussian equivalence classes of CV graph states.

Jing Zhang

2008-08-14T23:59:59.000Z

432

Exact Solution of Graph Coloring Problems via Constraint ...  

E-Print Network [OSTI]

of coloring the vertices of a graph so that adjacent vertices have different ..... in a vector y having always the same order corresponding to that of matrix A rows.

2011-09-21T23:59:59.000Z

433

New Lower Bounds on the Stability Number of a Graph  

E-Print Network [OSTI]

Jun 27, 2007 ... adjacency matrix of G. The complete graph on n vertices is denoted by Kn. ..... We used MATLAB to compute each of the five bounds on each of...

2007-06-27T23:59:59.000Z

434

Modeling modern network attacks and countermeasures using attack graphs  

E-Print Network [OSTI]

By accurately measuring risk for enterprise networks, attack graphs allow network defenders to understand the most critical threats and select the most effective countermeasures. This paper describes substantial enhancements ...

Ingols, Kyle W.

435

Probabilistic flooding for efficient information dissemination in random graph topologies  

Science Journals Connector (OSTI)

Probabilistic flooding has been frequently considered as a suitable dissemination information approach for limiting the large message overhead associated with traditional (full) flooding approaches that are used to disseminate globally information in ... Keywords: Information dissemination, Probabilistic flooding, Random graphs

Konstantinos Oikonomou; Dimitrios Kogias; Ioannis Stavrakakis

2010-07-01T23:59:59.000Z

436

A description of dynamical graphs associated to elementary regulatory circuits  

Science Journals Connector (OSTI)

......regulatory networks (regulatory graphs), as...for recent reviews, De Jong (2002...notion of cross-regulatory modules and a...2003)). We plan to study the...simulation of genetic regulatory systems: a literature review. J. Comput......

E. Remy; B. Moss; C. Chaouiya; D. Thieffry

2003-09-01T23:59:59.000Z

437

Drawing a Graph in a Hypercube David R. Wood  

E-Print Network [OSTI]

Drawing a Graph in a Hypercube David R. Wood #3; Departament de Matem#18;atica Aplicada II Universitat Polit#18;ecnica de Catalunya Barcelona, Spain david.wood@upc.edu Submitted: Nov 16, 2004; Accepted

Wood, David R.

438

Drawing a Graph in a Hypercube David R. Wood  

E-Print Network [OSTI]

Drawing a Graph in a Hypercube David R. Wood Departament de Matem`atica Aplicada II Universitat Polit`ecnica de Catalunya Barcelona, Spain david.wood@upc.edu Submitted: Nov 16, 2004; Accepted: Aug 11

Wood, David R.

439

Ranking Outlier Nodes in Subspaces of Attributed Graphs  

E-Print Network [OSTI]

. Our graph outlier ranking (GOutRank) introduces scoring functions based on these selected subgraphs by looking at the most promising objects first. They 1http://www.ipd.kit.edu/~muellere/GOutRank/ allow users

Antwerpen, Universiteit

440

Diamond graphs and super-reflexivity William B. Johnson  

E-Print Network [OSTI]

Diamond graphs and super-reflexivity William B. Johnson and Gideon Schechtman Abstract The main results is that dimension reduction a-la Johnson­Lindenstrauss fails in any non super reflexive space

Johnson, William B.

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Probabilistic Flooding for Efficient Information Dissemination in Random Graph  

E-Print Network [OSTI]

the benefits of the properly parameterized probabilistic flooding scheme. Simulation results sup- portProbabilistic Flooding for Efficient Information Dissemination in Random Graph Topologies 1 & Telecommunications, Athens, Greece Abstract Probabilistic flooding has been frequently considered as a suitable

Stavrakakis, Ioannis

442

Solving Steiner Tree Problems in Graphs with Lagrangian Relaxation  

Science Journals Connector (OSTI)

This paper presents an algorithm to obtain near optimal solutions for the Steiner tree problem in graphs. It is based on a Lagrangian relaxation of a multi-commodity flow formulation of the problem. An extensi...

Laura Bahiense; Francisco Barahona; Oscar Porto

2003-09-01T23:59:59.000Z

443

Technology Portfolio Planning by Weighted Graph Analysis of System Architectures  

E-Print Network [OSTI]

Technology Portfolio Planning by Weighted Graph Analysis of System Architectures Peter Davison and Bruce Cameron Massachusetts Institute of Technology, Cambridge, MA 02139 Edward F. Crawley Skolkovo Institute of Science and Technology, Skolkovo 143025, Russia Abstract5 Many systems undergo significant

de Weck, Olivier L.

444

Circuit and bond polytopes on series-parallel graphs$  

E-Print Network [OSTI]

Jul 10, 2014 ... In the literature, a circuit is sometimes called simple cycle. ... of the circuits of series-parallel graphs, combined with a theorem of Balas [2, 3].

2014-07-10T23:59:59.000Z

445

Graph Model for Carbon Dioxide Emissions from Metallurgical Plants  

Science Journals Connector (OSTI)

Mathematical models are presented for estimating carbon dioxide emissions from metallurgical processes. The article also presents ... in graph form to calculate transit and net emissions of carbon dioxide based o...

Yu. N. Chesnokov; V. G. Lisienko; A. V. Lapteva

2013-03-01T23:59:59.000Z

446

How are Feynman graphs resumed by the Loop Vertex Expansion?  

E-Print Network [OSTI]

The purpose of this short letter is to clarify which set of pieces of Feynman graphs are resummed in a Loop Vertex Expansion, and to formulate a conjecture on the $\\phi^4$ theory in non-integer dimension.

Vincent Rivasseau; Zhituo Wang

2010-06-23T23:59:59.000Z

447

LNG Monthly Summary 2008.xls  

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

8 8 Jan Feb March April May June July Aug Sept Oct Nov Dec TOTAL Algeria 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Egypt 3.0 0.0 0.0 3.1 3.1 6.3 6.4 3.0 9.0 3.0 9.2 8.7 54.8 Equatorial Guinea 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Nigeria 0.0 0.0 0.0 3.0 0.0 3.1 0.0 3.2 2.8 0.0 0.0 0.0 12.0 Norway 0.0 3.0 2.9 0.0 3.0 0.0 0.0 2.9 0.0 0.0 0.0 3.1 14.9 Qatar 0.0 0.0 0.0 0.0 0.0 3.1 0.0 0.0 0.0 0.0 0.0 0.0 3.1 Trinidad 25.5 20.6 20.8 26.1 25.5 20.6 24.6 26.3 20.0 24.4 13.6 19.0 266.8 TOTAL 28.4 23.6 23.7 32.2 31.6 33.1 31.0 35.4 31.8 27.4 22.8 30.7 351.7 LNG Imports by Receiving Terminal (Bcf) 2008 Jan Feb March April May June July Aug Sept Oct Nov Dec TOTAL Cove Point, MD 5.8 3.0 5.6 0.0 3.0 0.0 0.0 5.5 0.0 0.0 0.0 3.1 25.9 Elba Island, GA 4.9 5.0 5.3 13.8 14.0 13.7 17.1 16.8 13.9 14.0 6.1 11.2 135.7 Everett, MA 17.7 15.6 12.8 12.5 10.8 13.2 14.0 13.1 12.0 13.5 13.6 16.5 165.3

448

EIA910_Form.xls  

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

- - - - - - Address 2: City: State: Zip: - 1. Report State (Enter one of the following States in the box): District of Columbia, Florida, 2. To how many end-use customers did you sell natural gas? 3. 4. For companies reporting sales in all States except Georgia: 5. For companies reporting sales in Georgia: has sales to residential and/or commercial end-use customers. Therm Therm (Number of Customers) Comments: Identify any unusual aspects of your reporting month's activity.

449

tablehc4.3.xls  

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

33.0 33.0 8.0 3.4 5.9 14.4 1.2 Household Size 1 Person......................................................... 30.0 11.4 1.6 1.0 1.9 6.6 0.3 2 Persons........................................................ 34.8 8.0 1.9 0.8 1.5 3.5 0.3 3 Persons........................................................ 18.4 5.6 1.5 0.7 1.2 1.9 0.2 4 Persons........................................................ 15.9 4.3 1.3 0.6 0.7 1.6 Q 5 Persons........................................................ 7.9 2.0 0.9 0.2 0.3 0.4 Q 6 or More Persons........................................... 4.1 1.7 0.8 Q 0.3 0.4 Q 2005 Annual Household Income Category Less than $9,999............................................. 9.9 5.2 0.6 0.7 1.1 2.7 Q $10,000 to $14,999......................................... 8.5 4.6 0.8 0.3 0.9 2.4 Q $15,000 to $19,999.........................................

450

c32a.xls  

Gasoline and Diesel Fuel Update (EIA)

. . 580 986 471 12,407 22,762 13,304 46.8 43.3 35.4 Building Floorspace (Square Feet) 1,001 to 5,000 .................................. 86 103 61 1,245 1,271 659 69.0 81.0 92.1 5,001 to 10,000 ................................ 57 101 60 1,154 1,932 883 49.4 52.3 67.6 10,001 to 25,000 .............................. 105 174 65 2,452 3,390 1,982 42.6 51.2 32.7 25,001 to 50,000 .............................. 92 117 62 1,895 3,008 1,702 48.4 38.7 36.3 50,001 to 100,000 ............................ 70 131 69 1,672 3,629 2,198 41.6 36.0 31.2 100,001 to 200,000 .......................... 64 137 66 1,538 3,363 2,644 41.8 40.7 24.8 200,001 to 500,000 .......................... 45 108 51 1,520 2,874 1,499 29.9 37.5 34.2 Over 500,000 ................................... 62 117 38 933 3,294 1,737 66.4 35.4 22.0 Principal Building Activity Education .........................................

451

c11a.xls  

Gasoline and Diesel Fuel Update (EIA)

Buildings .................................. Buildings .................................. 1,248 2,553 2,721 13,955 32,332 25,371 89.4 79.0 107.3 Principal Building Activity Education ........................................ 63 423 334 808 5,378 3,687 78.3 78.6 90.7 Food Sales ...................................... 144 Q Q 765 467 Q 188.5 Q Q Food Service ................................... 318 108 Q 986 664 Q 322.9 163.2 Q Health Care ..................................... 32 104 457 445 835 1,883 71.8 125.1 242.9 Inpatient ........................................ N Q 436 N 182 1,723 N Q 252.9 Outpatient ...................................... 32 66 Q 445 652 160 71.8 100.5 Q Lodging ........................................... 29 207 273 260 2,274 2,563 111.0 91.2 106.7 Mercantile ........................................ 171 482 369 1,944 5,204 4,044 87.9 92.6 91.2 Retail (Other Than Mall) ................

452

1-cc June2011.xls  

Gasoline and Diesel Fuel Update (EIA)

1 1 Section 1. Commentary Electric Power Data The contiguous United States experienced temperatures that were above normal in June 2011. In particular, southern states experienced significantly above average temperatures which exacerbated drought conditions present in the region. Accordingly, the total population-weighted cooling degree days for the United States were 20.2 percent above the June normal (though still less than in June 2010; see Table 11.1). In June 2011, retail sales of electricity remained relatively unchanged from June 2010. Over the same period, the average U.S. retail price of electricity increased 0.9 percent. The average U.S. retail price of electricity for the 12- month period ending June 2011 increased 1.6 percent over the previous 12-month period ending June 2010.

453

PT2_US.xls  

Gasoline and Diesel Fuel Update (EIA)

PT2. Energy Production Estimates in Trillion Btu, United States, 1960 - 2011 PT2. Energy Production Estimates in Trillion Btu, United States, 1960 - 2011 1960 10,590 14,119 14,935 6 NA 2,928 2,928 42,578 1961 10,239 14,642 15,206 20 NA 2,952 2,952 43,060 1962 10,671 15,322 15,522 26 NA 3,117 3,117 44,658 1963 11,605 16,270 15,966 38 NA 3,096 3,096 46,976 1964 12,274 17,152 16,164 40 NA 3,225 3,225 48,854 1965 12,832 17,691 16,521 43 NA 3,396 3,396 50,483 1966 13,281 18,967 17,561 64 NA 3,432 3,432 53,305 1967 13,697 20,019 18,651 88 NA 3,690 3,690 56,146 1968 13,487 21,276 19,308 142 NA 3,773 3,773 57,986 1969 13,833 22,764 19,556 154 NA 4,095 4,095 60,402 1970 14,877 24,098 20,401 239 NA 4,070 4,070 63,686 1971 13,518 24,747 20,033 413 NA 4,262 4,262 62,972 1972 14,392 24,819 20,041 584 NA 4,382 4,382 64,218 1973 14,006 24,873 19,493 910 NA 4,411 4,411 63,694 1974 14,025 23,723 18,575 1,272 NA 4,742 4,742 62,336 1975 14,982 22,098 17,729 1,900 NA 4,687 4,687

454

c1a.xls  

Gasoline and Diesel Fuel Update (EIA)

Dec 2006 Next CBECS will be conducted in 2007 Primary Site All Buildings .................................... 4,859 71,658 6,523 10,746 3,559 2,100 228 636 District Heat Table C1A. Total Energy Consumption by Major Fuel for All Buildings, 2003 All Buildings Total Energy Consumption (trillion Btu) Number of Buildings (thousand) Floorspace (million square feet) Sum of Major Fuels Electricity Natural Gas Fuel Oil Climate Zone: 30-Year Average Under 2,000 CDD and -- More than 7,000 HDD ..................... 882 11,529 1,086 1,412 468 468 63 88 5,500-7,000 HDD ............................ 1,229 18,808 1,929 2,621 868 737 67 257 4,000-5,499 HDD ............................ 701 12,503 1,243 1,947 645 368 91 140 Fewer than 4,000 HDD ................... 1,336 17,630 1,386 2,686 890 389 6 101 2,000 CDD or More and --

455

c36a.xls  

Gasoline and Diesel Fuel Update (EIA)

,437 ,437 178 130 82 1.10 1.04 1.21 1.28 0.22 0.06 0.03 Q Building Floorspace (Square Feet) 1,001 to 10,000 ................................. 460 Q Q Q 1.21 Q Q Q 0.60 Q Q Q 10,001 to 100,000 ............................. 444 70 Q Q 1.10 1.12 1.29 1.31 0.25 0.11 Q Q Over 100,000 .................................... 533 22 48 Q 1.03 1.06 1.08 1.26 0.14 0.01 0.01 Q Principal Building Activity Education .......................................... 293 Q Q Q 1.04 Q Q Q 0.31 Q Q Q Health Care........................................ Q Q 19 8 Q 1.06 1.08 1.16 Q Q 0.02 0.03 Office ................................................ 122 8 18 Q 1.16 1.32 1.26 1.44 0.09 0.01 0.01 0.00 All Others .......................................... 980 Q 64 50 1.12 1.02 1.34 1.26 0.26 0.10 0.03 Q Year Constructed 1945 or Before .................................. 620 Q Q Q 1.10 Q Q Q 0.29

456

c29a.xls  

Gasoline and Diesel Fuel Update (EIA)

68 68 185 165 5,453 3,263 5,644 30.9 56.6 29.2 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 29 18 Q 334 266 363 87.9 68.5 60.2 5,001 to 10,000 ................................. 25 Q Q 545 291 514 45.6 62.7 54.4 10,001 to 25,000 ............................... 20 45 26 626 699 844 32.1 63.9 30.6 25,001 to 50,000 ............................... 18 25 23 552 521 831 32.8 48.4 27.4 50,001 to 100,000 ............................. 21 Q 21 992 Q 821 20.7 Q 25.9 100,001 to 200,000 ........................... 20 Q 15 958 Q 754 21.4 Q 19.3 200,001 to 500,000 ........................... Q Q 14 502 Q 687 21.0 Q 20.6 Over 500,000 .................................... Q Q Q Q Q Q Q Q Q Principal Building Activity Education .......................................... 16 21 28 797 420 802 20.6 48.8 34.8 Food Sales .......................................

457

c27a.xls  

Gasoline and Diesel Fuel Update (EIA)

85 85 364 550 1,861 8,301 10,356 45.4 43.8 53.1 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... Q 42 69 Q 427 741 Q 98.4 92.9 5,001 to 10,000 ................................. Q 32 49 Q 518 743 Q 62.1 65.5 10,001 to 25,000 ............................... Q 47 102 Q 952 1,860 Q 49.7 54.6 25,001 to 50,000 ............................... Q 42 78 Q 900 1,567 Q 47.1 49.6 50,001 to 100,000 ............................. Q 49 77 Q 1,421 1,611 Q 34.4 47.7 100,001 to 200,000 ........................... Q 44 73 Q 1,531 1,454 Q 28.4 50.4 200,001 to 500,000 ........................... Q 55 58 Q 1,484 1,323 Q 37.3 43.5 Over 500,000 .................................... Q 52 45 Q 1,068 1,056 Q 48.6 43.0 Principal Building Activity Education .......................................... Q 49 99 Q 1,247 1,804 Q 39.5 54.6 Food Sales .......................................

458

1-MFE January 2006.xls  

Gasoline and Diesel Fuel Update (EIA)

and Stock Trends and Stock Trends Page 5 6. Month-to-Month Comparisons: Electric Power Retail Sales and Average Prices Page 6 7. Retail Sales Trends Page 7 8. Average Retail Price Trends Page 8 9. Heating and Cooling Degree Days Page 9 10. Documentation Page 10 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy of the Department of Energy or any other organization. For additional information, contact Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov. Section 1. Commentary Electric Power Data

459

c9a.xls  

Gasoline and Diesel Fuel Update (EIA)

684 684 446 617 9,022 4,207 8,613 75.8 106.1 71.6 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 87 44 64 788 466 871 110.9 94.8 73.0 5,001 to 10,000 ................................. 67 39 84 957 465 878 69.7 84.8 95.1 10,001 to 25,000 ............................... 77 91 89 1,555 933 1,429 49.4 97.2 62.4 25,001 to 50,000 ............................... 70 56 71 1,062 568 1,239 65.8 98.2 57.5 50,001 to 100,000 ............................. 92 49 78 1,514 492 1,092 61.0 100.2 71.2 100,001 to 200,000 ........................... 119 Q 79 1,426 346 1,007 83.4 Q 78.0 200,001 to 500,000 ........................... 60 Q 68 749 339 977 80.4 Q 69.6 Over 500,000 .................................... Q Q Q Q Q 1,119 Q Q Q Principal Building Activity Education .......................................... 74 53 76 1,198

460

1-cc January2009.xls  

Gasoline and Diesel Fuel Update (EIA)

Chris Cassar at 202-586-5448, or at Christopher.Cassar@eia.doe.gov. Chris Cassar at 202-586-5448, or at Christopher.Cassar@eia.doe.gov. Monthly Flash Estimates of Data for: January 2009 Section 1. Commentary Electric Power Data Near normal temperatures prevailed across the contiguous United States in January 2009, marking the fifth straight month that temperatures have been close to average. However, regional differences in temperature occurred as the western United States experienced warmer than normal temperatures while the Northeast and the central United States experienced below average temperatures. Accordingly, heating degree days for the contiguous United States as a whole were 3.9 percent above the average for the month of January 2009 and 6.8 percent above a warmer January 2008. Even with the colder weather, retail sales of electricity decreased 1.8 percent compared to January 2008. This decrease in January

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

LNG Monthly Summary 2010.xls  

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

0 0 Jan Feb March April May June July Aug Sept Oct Nov Dec TOTAL Algeria 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Egypt 16.8 11.6 8.8 5.8 9.1 5.7 6.1 0.0 6.1 3.0 0.0 0.0 73.0 Equatorial Guinea 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Nigeria 0.0 0.0 2.6 8.7 8.8 11.1 5.3 0.0 2.9 2.4 0.0 0.0 41.7 Norway 5.8 5.9 5.8 2.8 0.0 0.0 0.0 0.0 0.0 5.7 0.0 0.0 26.0 Peru 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.2 3.2 3.2 6.4 16.0 Qatar 11.9 6.4 0.7 8.9 0.0 0.0 0.0 0.0 0.0 4.5 8.7 4.3 45.6 Trinidad 21.9 16.0 16.2 15.2 16.3 10.7 16.6 16.5 16.4 15.2 13.7 15.2 189.7 Yemen 0.0 5.9 3.1 0.0 2.6 5.0 8.3 5.1 0.0 0.0 6.0 2.9 38.9 TOTAL 56.4 45.8 37.1 41.6 36.8 32.5 36.3 21.6 28.6 34.1 31.6 28.7 431.0 LNG Imports by Receiving Terminal (Bcf) 2010 Jan Feb March April May June July Aug Sept Oct Nov Dec TOTAL Cameron, LA 4.2 0.0 0.0 0.0 0.0 0.0 2.8 0.0 0.0 0.0 0.0 0.0 7.0 Cove Point, MD 14.8 8.7 8.8 5.4 0.0 0.0 0.0 0.0 0.0 5.7 0.0 0.0 43.4

462

New 2001 Survey.xls  

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

1 1 Lead Defendant Cases Filed Injunctions - Remands NEPA Case Dispositions - 2001 FERC 0 0 pre-2001 2001 All Navy 2 1 Judgment for defendant 41 20 66 NRC 0 0 TRO 2 3 5 DOI - BLM 20 2 Preliminary injunction 4 5 6 - FWS 17 1 Permanent injunction 7 0 9 - BuRec 1 0 Remand 8 8 18 - NPS 7 2 Dismissal w/ settlement 16 8 24 - BIA/NIGC 3 0 Dismissal w/o settlement 23 23 41 - MMS 0 0 Other action 9 4 15 - OSM 0 0 Pending 135 USDA - FS 40 15 - APHIS 2 1 DOC - NOAA 8 3 Army - COE 7 2 Plaintiffs Army 0 0 Public Interest groups 175 DOT - FHWA 3 2 Individual/Citizen assoc. 95 - FTA 13 1 State government 11 - FAA 7 0 Local government 37 - MARAD 0 0 Business groups 52 - SLSC 0 0 Property owners/residents 15 DOE 2 0 Indian tribes 11 EPA 4 0 Combination plaintiffs* 63 HUD 0 0 * i.e. local government AND individuals;

463

c1a.xls  

Gasoline and Diesel Fuel Update (EIA)

October 2006 October 2006 Next CBECS will be conducted in 2007 Primary Site All Buildings .................................... 4,859 71,658 6,523 10,746 3,559 2,100 228 636 District Heat Table C1A. Total Energy Consumption by Major Fuel for All Buildings, 2003 All Buildings Total Energy Consumption (trillion Btu) Number of Buildings (thousand) Floorspace (million square feet) Sum of Major Fuels Electricity Natural Gas Fuel Oil Climate Zone: 30-Year Average Under 2,000 CDD and -- More than 7,000 HDD ..................... 882 11,529 1,086 1,412 468 468 63 88 5,500-7,000 HDD ............................ 1,229 18,808 1,929 2,621 868 737 67 257 4,000-5,499 HDD ............................ 701 12,503 1,243 1,947 645 368 91 140 Fewer than 4,000 HDD ................... 1,336 17,630 1,386 2,686 890 389 6 101 2,000 CDD or More and --

464

all_alpha_00.xls  

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

Green Vehicle Guide Green Vehicle Guide Model Displ Cyl Trans Drive Fuel Sales Area Stnd Stnd Description Underhood ID Veh Class Air Pollution Score City MPG Hwy MPG Cmb MPG Greenhouse Gas Score SmartWay ACURA 3.2TL 3.2 6 Auto-L5 2WD Gasoline CL ULEV ULEV YHNXV03.2GL4 midsize car 3 14 23 17 4 no ACURA 3.2TL 3.2 6 Auto-L5 2WD Gasoline NL LEV LEV YHNXV03.2GF3 midsize car 2 14 23 17 4 no ACURA 3.5RL 3.5 6 Auto-L4 2WD Gasoline CL LEV LEV YHNXV03.5YA3 midsize car 2 13 19 15 3 no ACURA Integra 1.8 4 Auto-L4 2WD Gasoline CL TLEV TLEV YHNXV01.8WA2 small car 1 17 24 19 5 no ACURA Integra 1.8 4 Man-5 2WD Gasoline CL TLEV TLEV YHNXV01.8WA2 small car 1 17 24 19 5 no ACURA Integra 1.8 4 Man-5 2WD Gasoline CL TLEV TLEV YHNXV01.8XA2 small car 1 17 24 19 5 no ACURA Integra 1.8 4 Man-5 2WD Gasoline CL T1 TIER 1 YHNXV01.8XA1 small car 0 17 24 19 5 no ACURA NSX 3 6 Auto-L4 2WD Gasoline CL LEV LEV YHNXV03.2AA3 small car 2 13 19

465

c22a.xls  

Gasoline and Diesel Fuel Update (EIA)

Buildings .................................... Buildings .................................... 162 538 343 17,509 32,945 19,727 9.2 16.3 17.4 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 24 54 38 2,072 2,767 1,640 11.4 19.4 23.0 5,001 to 10,000 ................................. 16 41 29 1,919 3,154 1,572 8.2 13.0 18.4 10,001 to 25,000 ............................... 28 69 45 3,201 5,610 3,683 8.7 12.3 12.2 25,001 to 50,000 ............................... 17 63 36 2,412 4,383 2,303 7.2 14.5 15.5 50,001 to 100,000 ............................. 16 78 59 2,095 4,763 3,406 7.8 16.4 17.3 100,001 to 200,000 ........................... 20 88 63 2,150 4,671 3,350 9.5 18.9 18.9 200,001 to 500,000 ........................... 22 61 29 2,054 3,623 1,692 10.6 16.8 17.2 Over 500,000 .................................... 19 84 44 1,606 3,974 2,080 11.6 21.1

466

c8a.xls  

Gasoline and Diesel Fuel Update (EIA)

456 456 1,241 340 5,680 13,999 3,719 80.2 88.7 91.4 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 60 123 37 922 1,283 547 64.9 96.2 67.6 5,001 to 10,000 ................................. 45 111 27 738 1,468 420 61.6 75.4 63.2 10,001 to 25,000 ............................... 71 145 74 1,204 2,443 861 59.0 59.3 Q 25,001 to 50,000 ............................... 107 133 Q 949 1,867 545 112.5 71.1 Q 50,001 to 100,000 ............................. 66 163 71 664 1,797 749 99.0 90.4 95.1 100,001 to 200,000 ........................... 49 278 Q 614 2,422 Q 79.8 114.8 Q 200,001 to 500,000 ........................... Q 118 Q 441 1,148 Q Q 102.4 Q Over 500,000 .................................... Q 171 Q Q 1,572 Q Q 109.0 Q Principal Building Activity Education .......................................... 45 198 Q

467

c12a.xls  

Gasoline and Diesel Fuel Update (EIA)

1,522 3,228 1,772 18,031 33,384 20,243 84.4 96.7 87.6 Building Floorspace (Square Feet) 1,001 to 5,000 ................................. 193 300 193 2,168 2,904 1,850 89.0 103.2 104.2 5,001 to 10,000 ............................... 134 263 165 2,032 3,217 1,784 66.0 81.9 92.5 10,001 to 25,000 ............................. 241 432 226 3,273 5,679 3,707 73.6 76.1 60.9 25,001 to 50,000 ............................. 181 370 191 2,517 4,518 2,347 71.8 81.8 81.5 50,001 to 100,000 ............................ 156 473 285 2,095 4,763 3,433 74.3 99.3 82.9 100,001 to 200,000 .......................... 219 523 323 2,161 4,706 3,350 101.1 111.1 96.5 200,001 to 500,000 .......................... 221 371 160 2,179 3,623 1,692 101.4 102.3 94.3 Over 500,000 ................................... 179 497 Q 1,606 3,974 2,080 111.2 125.0 Q Principal Building Activity

468

c31a.xls  

Gasoline and Diesel Fuel Update (EIA)

Buildings .................................... Buildings .................................... 467 882 688 7,144 21,928 19,401 65.4 40.2 35.5 Principal Building Activity Education .......................................... Q 137 101 419 3,629 2,997 53.9 37.6 33.7 Food Sales ....................................... 16 Q Q 339 Q Q 46.6 Q Q Food Service ..................................... 149 48 N 774 622 N 192.5 77.2 N Health Care ....................................... 12 37 187 233 520 1,792 49.5 70.8 104.4 Inpatient .......................................... N Q 181 N Q 1,662 N Q 109.0 Outpatient ....................................... 12 20 Q 233 377 Q 49.5 52.3 Q Lodging ............................................. Q 83 113 Q 1,750 2,374 Q 47.6 47.4 Mercantile ......................................... 60 134 61 1,094 3,572 3,205 55.2 37.6 19.1 Retail (Other Than Mall) ..................

469

c24a.xls  

Gasoline and Diesel Fuel Update (EIA)

Buildings .................................. Buildings .................................. 803 42.0 17.9 37.4 71.0 6.3 0.33 7.86 Building Floorspace (Square Feet) 1,001 to 5,000 ................................. 220 78.6 23.8 46.8 92.0 2.0 0.70 8.93 5,001 to 10,000 ............................... 410 54.8 15.0 29.6 66.2 3.4 0.46 8.41 10,001 to 25,000 ............................. 685 43.8 16.2 31.0 55.9 5.8 0.37 8.45 25,001 to 50,000 ............................. 1,464 40.9 16.0 31.0 55.4 11.1 0.31 7.60 50,001 to 100,000 ............................ 2,519 35.8 10.8 28.6 48.9 20.1 0.29 7.97 100,001 to 200,000 .......................... 4,898 35.4 6.4 23.8 51.9 36.1 0.26 7.36 200,001 to 500,000 .......................... 10,109 34.7 10.0 23.2 47.2 69.1 0.24 6.83 Over 500,000 ................................... 34,579 36.4 4.0 17.5 48.8 239.4 0.25 6.92 Principal Building Activity

470

c38a.xls  

Gasoline and Diesel Fuel Update (EIA)

Building Building (thousand dollars) per Square Foot (dollars) per Thousand Pounds (dollars) All Buildings .................................... 9,470 113.98 108.4 1.31 11.45 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... Q Q Q Q Q 5,001 to 10,000 ................................. Q Q Q Q Q 10,001 to 25,000 ............................... Q Q Q Q Q 25,001 to 50,000 ............................... Q Q Q Q Q 50,001 to 100,000 ............................. Q Q Q Q Q 100,001 to 200,000 ........................... 17,452 118.10 Q Q Q 200,001 to 500,000 ........................... 34,658 121.16 Q Q Q Over 500,000 .................................... 77,419 93.60 834.8 1.01 10.78 Principal Building Activity Education .......................................... 5,223 116.63 Q Q Q Food Sales .......................................

471

2006 NEPA Survey.xls  

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

4 4 Navy 1 0 Adverse dispositions: 120 NRC 3 1 TRO 1 DOI - BLM 21 14 Preliminary Injunction 8 - FWS 6 3 Permanent Injunction 16 - BuRec 0 1 Remand 48 - NPS 0 3 Dismissal w/ settlement 13 - BIA/NIGC 1 0 Dismissal w/o settlement 34 - MMS 0 0 Case pending, NEPA 195 - OSM 0 0 USDA - FS 30 33 - APHIS 2 1 DOC - NOAA 4 4 Army - COE 25 7 Gov't Agency Army 0 2 Jurisdictional - P prevailed 13 DOT - FHWA 7 1 Jurisdictional - D prevailed 14 - FTA 1 0 NEPA - Not required 4 - FAA 3 0 NEPA - Is required 0 - MARAD 0 0 CE - Adequate 9 - SLSC 0 0 CE - Not Adequate 4 DOE 0 1 EA - Adequate* 27 EPA 2 0 EA - Not Adequate* 23 HUD 0 0 EIS - Adequate* 29 Air Force 0 1 EIS - Not Adequate* 26 TVA 0 0 SEIS - Needed* 14 NSF 0 0 SEIS -Not Needed* 4 FCC 0 0 GSA 0 0 FDA 0 0 Total 108 72 27 Public Interest groups

472

Safety Schedule FY2013.xls  

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

29 Jan 2013 31 Jan 2013 SAF-135V HPI Event Investigation Y-12 29 Jan 2013 31 Jan 2013 SAF-135V HPI Event Investigation Y-12 4 Feb 2013 6 Feb 2013 SAF-290 Readiness Review Member Training NSO 5 Feb 2013 7 Feb 2013 SAF-385 Assessment Techniques LASO 7 Feb 2013 7 Feb 2013 SAF-291 Readiness Review Leader Training NSO 11 Feb 2013 15 Feb 2013 SAF-230 Accident Investigation Pantex 25 Feb 2013 27 Feb 2013 SAF-290 Readiness Review Member Training Y-12 28 Feb 2013 28 Feb 2013 SAF-291 Readiness Review Leader Training Y-12 5 Mar 2013 5 Mar 2013 SAF-720 Hazard Identification Y-12 6 Mar 2013 6 Mar 2013 SAF-725 Hazard Categorization Y-12 12 Mar 2013 15 Mar 2013 SAF-786 Unreviewed Safety Questions Livermore 18 Mar 2013 22 Mar 2013 SAF-220 Senior Technical Safety Managers Overview NSO

473

o_al_05.xls  

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

Destination by Method of Destination by Method of Transportation Electricity Generation Coke Plants Industrial Plants (Except Coke) Residential and Commercial Total Alabama 770 851 1,739 * 3,360 Railroad 642 1 168 - 811 River 69 - 165 - 234 Tramway, Conveyor, and Slurry Pipeline - - 15 - 15 Truck 58 850 1,392 * 2,300 Florida - - 128 - 128 Railroad - - 79 - 79 River - - 49 - 49 Georgia 708 - 15 - 724 Railroad 698 - - 698 Truck 10 - 15 - 25 Indiana - 782 1 - 783 Railroad - 782 1 - 783 Kentucky - - 2 - 2 Truck - - 2 - 2 Mississippi 26 - 52 - 78 Truck 26 - 52 - 78 Ohio - 8 1 - 9 Railroad - 8 - 8 River - - 1 - 1 Unknown State - - - 349 [1] Unknown - - - 349 [1] State Total 1,504 1,640 1,939 * 5,432 [1] Railroad 1,340 791 247 - 2,379 River 69 - 215 - 285 Tramway, Conveyor, and Slurry Pipeline - - 15 - 15 Truck 94 850 1,462 * 2,405 Unknown - - - 349

474

c34a.xls  

Gasoline and Diesel Fuel Update (EIA)

per Building per Building (thousand dollars) per Square Foot (dollars) per Gallon (dollars) All Buildings .................................... 3,533 0.10 3.9 0.11 1.11 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 1,177 0.41 1.4 0.48 1.18 5,001 to 10,000 ................................. 2,573 0.36 3.0 0.42 1.17 10,001 to 25,000 ............................... 3,045 0.19 3.6 0.23 1.18 25,001 to 50,000 ............................... 5,184 0.14 5.6 0.15 1.09 50,001 to 100,000 ............................. 8,508 0.11 9.3 0.12 1.10 100,001 to 200,000 ........................... 12,639 0.09 13.1 0.09 1.03 200,001 to 500,000 ........................... 22,181 0.08 23.4 0.08 1.05 Over 500,000 .................................... 14,248 0.02 14.7 0.02 1.03 Principal Building Activity

475

all_alpha_03.xls  

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

Green Vehicle Guide Green Vehicle Guide Model Displ Cyl Trans Drive Fuel Sales Area Stnd Underhood ID Veh Class Air Pollution Score FE Calc Appr City MPG Hwy MPG Cmb MPG Unadj Cmb MPG Greenhouse Gas Score SmartWay ACURA 3.2CL 3.2 (6 cyl) Auto-S5 2WD Gasoline CL ULEV 3HNXV03.2BYT small car 3 N/A 17 27 21 26.7143 6 no ACURA 3.2CL 3.2 (6 cyl) Man-6 2WD Gasoline CL LEV 3HNXV03.2CYC small car 2 N/A 17 26 20 26.1185 6 no ACURA 3.2CL 3.2 (6 cyl) Auto-S5 2WD Gasoline CL LEV 3HNXV03.2AYC small car 2 N/A 17 27 21 26.7143 6 no ACURA 3.2CL 3.2 (6 cyl) Auto-S5 2WD Gasoline CL LEV 3HNXV03.2CYC small car 2 N/A 17 27 21 26.7143 6 no ACURA 3.2TL 3.2 (6 cyl) Auto-S5 2WD Gasoline CL ULEV 3HNXV03.2BYT midsize car 3 N/A 17 27 21 26.7205 6 no ACURA 3.2TL 3.2 (6 cyl) Auto-S5 2WD Gasoline CL LEV 3HNXV03.2AYC midsize car 2 N/A 17 27 21 26.7205 6 no ACURA 3.2TL 3.2 (6 cyl) Auto-S5 2WD Gasoline CL LEV 3HNXV03.2CYC midsize car

476

c33a.xls  

Gasoline and Diesel Fuel Update (EIA)

2 per Building (gallons) per Square Foot (gallons) per Building (thousand dollars) per Square Foot (dollars) per Gallon (dollars) All Buildings .................................... 3,533 0.10 3.9 0.11 1.11 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 1,177 0.41 1.4 0.48 1.18 5,001 to 10,000 ................................. 2,573 0.36 3.0 0.42 1.17 10,001 to 25,000 ............................... 3,045 0.19 3.6 0.23 1.18 25,001 to 50,000 ............................... 5,184 0.14 5.6 0.15 1.09 50,001 to 100,000 ............................. 8,508 0.11 9.3 0.12 1.10 100,001 to 200,000 ........................... 12,639 0.09 13.1 0.09 1.03 200,001 to 500,000 ........................... 22,181 0.08 23.4 0.08 1.05 Over 500,000 ....................................

477

c13a.xls  

Gasoline and Diesel Fuel Update (EIA)

Dec 2006 Next CBECS will be conducted in 2007 Electricity Expenditures Primary Total (trillion Btu) Total (trillion Btu) Total (billion kWh) All Buildings .................................... 4,617 70,181 15.2 10,746 3,559 1,043 82,783 Floorspace per Building (thousand square feet) Total (million dollars) Table C13A. Total Electricity Consumption and Expenditures for All Buildings, 2003 All Buildings Using Electricity Electricity Consumption Site Number of Buildings (thousand) Floorspace (million square feet) Climate Zone: 30-Year Average Under 2,000 CDD and -- More than 7,000 HDD ..................... 836 11,300 13.5 1,412 468 137 10,479 5,500-7,000 HDD ............................ 1,185 18,549 15.7 2,621 868 254 19,181 4,000-5,499 HDD ............................ 670 12,374 18.5 1,947 645

478

1-es September2010.xls  

Gasoline and Diesel Fuel Update (EIA)

September 2010 September 2010 Section 1. Commentary Electric Power Data The contiguous United States, as a whole, experienced temperatures that were significantly above average in September 2010. Accordingly, the total population-weighted cooling degree days for the United States were 26.5 percent above the September normal. Retail sales of electricity increased 6.1 percent compared to September 2009. Over the same period, the average U.S. retail price of electricity increased 0.5 percent. For the 12-month period ending September 2010, total sales of electricity increased 3.5 percent over the previous 12-month period ending September 2009. In September 2010, total electric power generation in the United States increased 5.3 percent compared to September 2009.

479

c23a.xls  

Gasoline and Diesel Fuel Update (EIA)

2 25th Per- centile Median 75th Per- centile per Building (thousand dollars) per Square Foot (dollars) per Thousand Cubic Feet (dollars) All Buildings .................................. 803 42.0 17.9 37.4 71.0 6.3 0.33 7.86 Building Floorspace (Square Feet) 1,001 to 5,000 ................................. 220 78.6 23.8 46.8 92.0 2.0 0.70 8.93 5,001 to 10,000 ............................... 410 54.8 15.0 29.6 66.2 3.4 0.46 8.41 10,001 to 25,000 ............................. 685 43.8 16.2 31.0 55.9 5.8 0.37 8.45 25,001 to 50,000 ............................. 1,464 40.9 16.0 31.0 55.4 11.1 0.31 7.60 50,001 to 100,000 ............................ 2,519 35.8 10.8 28.6 48.9 20.1 0.29 7.97 100,001 to 200,000 .......................... 4,898 35.4 6.4 23.8 51.9 36.1 0.26 7.36 200,001 to 500,000 .......................... 10,109 34.7

480

c4a.xls  

Gasoline and Diesel Fuel Update (EIA)

Buildings .................................... Buildings .................................... 4,859 71,658 14.7 107,897 22.2 1.51 16.54 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 2,586 6,922 2.7 13,083 5.1 1.89 19.08 5,001 to 10,000 ................................. 948 7,033 7.4 10,443 11.0 1.48 18.56 10,001 to 25,000 ............................... 810 12,659 15.6 15,689 19.4 1.24 17.46 25,001 to 50,000 ............................... 261 9,382 36.0 11,898 45.6 1.27 16.04 50,001 to 100,000 ............................. 147 10,291 70.2 15,171 103.5 1.47 16.62 100,001 to 200,000 ........................... 74 10,217 138.6 16,087 218.2 1.57 15.12 200,001 to 500,000 ........................... 26 7,494 287.6 10,940 419.8 1.46 14.56 Over 500,000 .................................... 8 7,660 937.6 14,586 1785.5 1.90 16.11 Principal Building Activity

Note: This page contains sample records for the topic "xls csv graph" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

1-cc August2010.xls  

Gasoline and Diesel Fuel Update (EIA)

August 2010 August 2010 Section 1. Commentary Electric Power Data The contiguous United States, as a whole, experienced temperatures that were significantly above average in August 2010. Accordingly, the total population-weighted cooling degree days for the United States were 22.8 percent above the August normal. Retail sales of electricity increased 8.1 percent compared to August 2009. Over the same period, the average U.S. retail price of electricity increased 1.0 percent. For the 12-month period ending August 2010, the U.S. average retail price of electricity decreased 0.9 percent over the previous 12-month period ending August 2009. In August 2010, total electric power generation in the United States increased 7.3 percent compared to August 2009. Over the

482

c18a.xls  

Gasoline and Diesel Fuel Update (EIA)

66 66 254 57 5,523 13,837 3,546 12.0 18.3 16.2 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 10 28 7 821 1,233 481 12.4 22.4 15.4 5,001 to 10,000 ................................. 7 20 5 681 1,389 386 10.8 14.4 13.3 10,001 to 25,000 ............................... 9 31 12 1,204 2,411 842 7.8 12.8 14.1 25,001 to 50,000 ............................... 15 29 6 949 1,867 490 16.1 15.5 11.7 50,001 to 100,000 ............................. 9 35 13 664 1,797 749 13.1 19.2 17.0 100,001 to 200,000 ........................... 8 50 Q 614 2,422 Q 12.3 20.6 Q 200,001 to 500,000 ........................... Q 23 Q Q 1,148 Q Q 20.4 Q Over 500,000 .................................... Q 38 Q Q 1,572 Q Q 24.3 Q Principal Building Activity Education .......................................... 5 39 Q 549 2,445 Q 8.8 16.0 Q Food Sales .......................................

483

all_alpha_09.xls  

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

Green Vehicle Guide Green Vehicle Guide Model Displ Cyl Trans Drive Fuel Sales Area Stnd Stnd Description Underhood ID Veh Class Air Pollution Score City MPG Hwy MPG Cmb MPG Greenhouse Gas Score SmartWay ACURA MDX 3.7 6 Auto-S5 4WD Gasoline CA U2 LEV-II ULEV 9HNXT03.7H29 SUV 7 15 20 17 3 no ACURA MDX 3.7 6 Auto-S5 4WD Gasoline FA B5 Bin 5 9HNXT03.7H29 SUV 6 15 20 17 3 no ACURA RDX 2.3 4 Auto-S5 4WD Gasoline CA U2 LEV-II ULEV 9HNXT02.3R29 SUV 7 17 22 19 4 no ACURA RDX 2.3 4 Auto-S5 4WD Gasoline FA B5 Bin 5 9HNXT02.3R29 SUV 6 17 22 19 4 no ACURA RL 3.7 6 Auto-S5 4WD Gasoline CA U2 LEV-II ULEV 9HNXV03.7FB9 midsize car 7 16 22 18 4 no ACURA RL 3.7 6 Auto-S5 4WD Gasoline FA B5 Bin 5 9HNXV03.7FB9 midsize car 6 16 22 18 4 no ACURA TL 3.5 6 Auto-S5 2WD Gasoline CA U2 LEV-II ULEV 9HNXV03.56B9 midsize car 7 18 26 21 5 no ACURA TL 3.7 6 Auto-S5 4WD Gasoline CA U2 LEV-II ULEV 9HNXV03.7KB9 midsize car 7 17 25 20 5 no ACURA TL

484

c37a.xls  

Gasoline and Diesel Fuel Update (EIA)

2 per Building (million Btu) per Square Foot (thousand Btu) per Building (thousand dollars) per Square Foot (dollars) per Thousand Pounds (dollars) All Buildings .................................... 9,470 113.98 108.4 1.31 11.45 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... Q Q Q Q Q 5,001 to 10,000 ................................. Q Q Q Q Q 10,001 to 25,000 ............................... Q Q Q Q Q 25,001 to 50,000 ............................... Q Q Q Q Q 50,001 to 100,000 ............................. Q Q Q Q Q 100,001 to 200,000 ........................... 17,452 118.10 Q Q Q 200,001 to 500,000 ........................... 34,658 121.16 Q Q Q Over 500,000 .................................... 77,419 93.60 834.8 1.01 10.78 Principal Building Activity Education ..........................................

485

c30a.xls  

Gasoline and Diesel Fuel Update (EIA)

454 454 715 356 378 134 8,486 14,122 8,970 11,796 5,098 53.5 50.6 39.7 32.0 26.3 Building Floorspace (Square Feet) 1,001 to 5,000 ................................ 57 84 35 58 16 666 1,015 427 832 234 84.8 83.1 81.9 69.6 66.6 5,001 to 10,000 .............................. 50 57 33 61 17 666 1,030 639 1,243 392 75.2 54.9 51.2 49.2 44.0 10,001 to 25,000 ............................ 98 121 53 55 15 1,831 2,415 1,024 1,994 561 53.7 50.1 52.1 27.5 27.4 25,001 to 50,000 ............................ 61 95 56 39 19 1,340 1,963 1,138 1,662 501 45.7 48.3 49.5 23.3 37.8 50,001 to 100,000 .......................... 64 97 47 45 16 1,217 2,300 1,453 1,744 786 52.3 42.2 32.7 25.9 19.8 100,001 to 200,000 ......................... 38 123 34 Q 12 1,075 2,316 1,431 1,833 889 35.6 53.0 23.5 32.8 13.5 200,001 to 500,000 ......................... 55 62 40 31 16 1,036 1,517 1,439 1,186 714

486

PT1_US.xls  

Gasoline and Diesel Fuel Update (EIA)

PT1. Energy Production Estimates in Physical Units, United States, 1960 - 2011 PT1. Energy Production Estimates in Physical Units, United States, 1960 - 2011 1960 436,425 12,771,038 2,574,933 NA 1961 422,535 13,254,025 2,621,758 NA 1962 441,072 13,876,622 2,676,189 NA 1963 479,356 14,746,663 2,752,723 NA 1964 506,453 15,546,592 2,786,822 NA 1965 529,355 16,039,753 2,848,514 NA 1966 549,065 17,206,628 3,027,763 NA 1967 567,031 18,171,325 3,215,742 NA 1968 558,995 19,322,400 3,329,042 NA 1969 573,226 20,698,240 3,371,751 NA 1970 614,969 21,920,642 3,517,450 NA 1971 563,122 22,493,012 3,453,914 NA 1972 602,491 22,531,698 3,455,368 NA 1973 598,569 22,647,549 3,360,903 NA 1974 610,021 21,600,522 3,202,585 NA 1975 654,641 20,108,661 3,056,779 NA 1976 684,914 19,952,438 2,976,180 NA 1977 697,205 20,025,463 3,009,265 NA 1978 670,164 19,974,033 3,178,216 NA 1979 781,135 20,471,260 3,121,310 NA 1980 829,747 20,179,724 3,146,365 NA

487

c21a.xls  

Gasoline and Diesel Fuel Update (EIA)

Square Square Feet All Buildings .................................... 201 412 431 13,124 31,858 25,200 15.3 12.9 17.1 Principal Building Activity Education .......................................... 9 55 45 806 5,378 3,687 11.1 10.2 12.2 Food Sales ....................................... 36 24 Q 747 467 Q 48.8 51.1 Q Food Service ..................................... 47 16 Q 986 664 Q 47.8 24.5 Q Health Care ....................................... 6 17 50 445 835 1,883 13.1 20.5 26.3 Inpatient .......................................... N Q 47 N Q 1,723 N Q 27.0 Outpatient ....................................... 6 11 Q 445 652 Q 13.1 17.4 Q Lodging ............................................. 4 31 34 260 2,274 2,563 14.0 13.5 13.5 Mercantile ......................................... 28 99 89 1,944 5,204 4,044 14.2 19.0 21.9 Retail (Other Than Mall) ..................

488

c7a.xls  

Gasoline and Diesel Fuel Update (EIA)

345 345 1,052 1,343 3,452 10,543 12,424 99.8 99.7 108.1 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 37 86 147 383 676 986 95.9 127.9 148.9 5,001 to 10,000 ................................. 39 68 83 369 800 939 106.0 85.4 88.2 10,001 to 25,000 ............................... Q 121 187 674 1,448 2,113 Q 83.4 88.4 25,001 to 50,000 ............................... Q 84 155 366 1,022 1,763 Q 82.5 87.6 50,001 to 100,000 ............................. Q 155 160 590 1,682 1,712 Q 92.0 93.3 100,001 to 200,000 ........................... Q 161 224 448 1,790 1,872 Q 90.0 119.6 200,001 to 500,000 ........................... Q 177 218 Q 1,673 1,847 Q 105.8 117.9 Over 500,000 .................................... Q Q Q Q 1,451 1,192 Q Q Q Principal Building Activity Education ..........................................

489

ITP_Data_Centers.xls  

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

Project Description Total DOE Project Description Total DOE Funding IBM T.J. Watson Research Center HQs: Yorktown Heights, NY Project Location: Research Triangle Park, NC Reducing Data Center Cooling Energy through Software-Based Management Tools. The project will develop and field test data center and telecommunication facility management tools to reduce power consumption from cooling components. Using real-time temperature, humidity, hot-spot management, air-leakage measurement, and corrosion monitoring, this tool will optimize air conditioning systems and use of outside air in computing facilities. This technology has the potential to save 10% of average data center and telecommunication center energy requirements. $1,666,550 SeaMicro Santa Clara, CA Reducing Volume-Server Energy Use by Re-Architecting Server Components. This project will field test re-

490

EIA895_update.xls  

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

OMB No. 1905-0175 OMB No. 1905-0175 Expiration Date: 12/31/2011 Version No.: 2009.01 PART 1. RESPONDENT IDENTIFICATION DATA REPORT PERIOD: 2 0 STATE NAME: If this is a resubmission, enter an "X" in the box: If any Respondent Identification Data has changed since the last report, enter an "X" in the box: Contact Name: Phone No.: - - Ext: - Address 1: Email: Address 2: Fax: City: State: Zip: - https://signon.eia.doe.gov/upload/noticeoog.jsp

491

postkwonTable2.xls  

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

2, W.M. Post, and K.C. Kwon. 2000. Soil Carbon Sequestration and Land-Use Change: 2, W.M. Post, and K.C. Kwon. 2000. Soil Carbon Sequestration and Land-Use Change: Processes and Potential. Global Change Biology 6:317-327 http://cdiac.ornl.gov/programs/CSEQ/terrestrial/postkwon2000/postkwon2000.html Years since Soil sample Rate of change (g m -2 y -1 ) Reference agriculture depth (cm) MAX AVG Cool temperate steppe Cultivated to perennial grass 12 300 110.00 Gebhart et al. (1994) cultivated to abandoned field 50 10 3.10 Burke et al. (1995) cultivated to seeded grass 6 5 0.00 Robles & Burke (1998) cultivated to improved pasture White et al. (1976) russian wildrye 8 7 6.86 crested wheatgrass 8 7 18.87 B-I-ALF (full) 8 7 14.01 B-I-ALF (short) 8 7 34.15 Mine tailing to grass-forb meadow 5 - 80 10 60.00 4.01 Titlyanova et al. (1988) Coal mine spoil to dry grassland 28 - 40

492

all_alpha_08.xls  

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

Green Vehicle Guide Green Vehicle Guide Model Displ Cyl Trans Drive Fuel Sales Area Stnd Underhood ID Veh Class Air Pollution Score FE Calc Appr City MPG Hwy MPG Cmb MPG Unadj Cmb MPG Greenhouse Gas Score SmartWay ACURA MDX 3.7 (6 cyl) Auto-S5 4WD Gasoline CA U2 8HNXT03.7PKR SUV 7 Drv 15 20 17 22.0527 4 no ACURA MDX 3.7 (6 cyl) Auto-S5 4WD Gasoline FA B5 8HNXT03.7PKR SUV 6 Drv 15 20 17 22.0527 4 no ACURA RDX 2.3 (4 cyl) Auto-S5 4WD Gasoline CA U2 8HNXT02.3DKR SUV 7 Drv 17 22 19 24.1745 5 no ACURA RDX 2.3 (4 cyl) Auto-S5 4WD Gasoline FA B5 8HNXT02.3DKR SUV 6 Drv 17 22 19 24.1745 5 no ACURA RL 3.5 (6 cyl) Auto-S5 4WD Gasoline CA U2 8HNXV03.5HKR midsize car 7 Drv 16 24 19 24.5629 5 no ACURA RL 3.5 (6 cyl) Auto-S5 4WD Gasoline FA B5 8HNXV03.5HKR midsize car 6 Drv 16 24 19 24.5629 5 no ACURA TL 3.2 (6 cyl) Auto-S5 2WD Gasoline CA U2 8HNXV03.5HKR midsize car 7 Drv 18 26 21 27.2768 6 yes ACURA TL 3.5 (6 cyl) Auto-S5

493

vandenbygaart2003_table_2.xls  

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

Differences in SOC as a result of different agricultural management practices. VandenBygaart et al. 2003. Influence of agricultural management on soil organic Differences in SOC as a result of different agricultural management practices. VandenBygaart et al. 2003. Influence of agricultural management on soil organic carbon: A compendium and assessment of Canadian studies. Can. J. Soil Sci. 83:363-380. Location MAP MAT PET Soil Textural Duration Treatment x Depth Soil profiles SOC Net C C storage Reference (by province from west to east) Great Group z class sampled sampled control difference rate (mm) ( o C) (yrs) (cm) (Mg ha -1 ) (Mg ha -1 ) (g C m -2 yr -1 ) Summerland, BC 290 9.0 711 BC LS 4 organic fertilizer 15 8 44.6 3.1 78.7 Zebarth et al. 1999 Summerland, BC 290 9.0 711 BC LS 3 organic fertilizer 15 8 44.6 15.5 515.3 Zebarth et al. 1999 Summerland, BC 290 9.0 711 BC LS 4 organic fertilizer 15 8 44.6 54.8 1369.3 Zebarth et al. 1999 Lethbridge, AB 402 5.0 732 BC CL 41 cont. w vs. f-w

494

New 2003 Survey.xls  

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

3 3 Lead Defendant Cases Filed Injunctions - Remands NEPA Case Dispositions - 2003 FERC 0 0 pre-2003 2003 All Navy 0 0 Judgment for defendant 46 3 49 NRC 1 0 TRO 2 2 4 DOI - BLM 15 1 Preliminary injunction 7 4 11 - FWS 2 3 Permanent injunction 5 2 7 - BuRec 11 0 Remand 14 2 16 - NPS 1 1 Dismissal w/ settlement 19 3 22 - BIA/NIGC 2 1 Dismissal w/o settlement 24 5 29 - MMS 0 0 Other action 23 10 33 - OSM 1 0 Pending 107 96 205 USDA - FS 66 14 - APHIS 3 0 DOC - NOAA 6 3 Army - COE 12 4 Plaintiffs Army 2 0 Public Interest groups 191 DOT - FHWA 6 2 Individual/Citizen assoc. 82 - FTA 2 0 State government 8 - FAA 3 1 Local government 16 - MARAD 1 0 Business groups 28 - FMCSA 1 0 Property owners/residents 5 DOE 1 2 Indian tribes 9 EPA 0 0 Combination plaintiffs* 42 HUD 1 0 * i.e. local government AND individuals;

495

c5a.xls  

Gasoline and Diesel Fuel Update (EIA)

96 96 1,799 2,265 1,063 13,995 18,103 26,739 12,820 99.8 99.4 84.7 82.9 Building Floorspace (Square Feet) 1,001 to 5,000 ................................. 123 207 248 108 1,059 1,908 2,618 1,337 116.4 108.3 94.7 80.6 5,001 to 10,000 ............................... 107 128 204 123 1,169 1,676 2,844 1,343 91.9 76.5 71.7 91.6 10,001 to 25,000 ............................. 166 258 295 180 2,122 3,317 4,859 2,361 78.3 77.7 60.7 76.1 25,001 to 50,000 ............................. 117 261 236 127 1,388 2,712 3,474 1,808 84.6 96.3 67.9 70.3 50,001 to 100,000 ........................... 234 225 326 127 2,272 2,376 4,059 1,584 103.2 94.9 80.3 80.2 100,001 to 200,000 ......................... 224 273 449 118 2,238 2,486 4,140 1,353 100.3 109.7 108.4 87.5 200,001 to 500,000 ......................... 189 252 207 103 1,781 2,288 2,109 1,316 106.3 110.0 98.3 78.3

496

c16a.xls  

Gasoline and Diesel Fuel Update (EIA)

6,907 6,907 15,677 31,849 18,350 0.10 0.07 0.07 0.10 1.22 0.88 1.22 1.46 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 1,685 2,415 4,257 2,190 0.12 0.08 0.08 0.12 1.63 1.39 1.77 1.69 5,001 to 10,000 ................................. 1,364 1,347 3,064 2,424 0.12 0.08 0.08 0.12 1.21 0.86 1.16 1.84 10,001 to 25,000 ............................... 2,126 2,539 4,651 2,856 0.10 0.08 0.08 0.10 1.02 0.77 0.98 1.22 25,001 to 50,000 ............................... 1,414 2,202 3,480 2,084 0.10 0.07 0.07 0.10 1.02 0.84 1.05 1.18 50,001 to 100,000 ............................. 2,744 1,996 4,585 2,368 0.10 0.06 0.07 0.10 1.21 0.84 1.13 1.52 100,001 to 200,000 ........................... 2,640 2,261 5,238 1,823 0.10 0.06 0.06 0.08 1.18 0.91 1.28 1.35 200,001 to 500,000 ........................... 1,985 1,631 2,655 1,592

497

c25a.xls  

Gasoline and Diesel Fuel Update (EIA)

448 448 728 511 350 10,162 14,144 15,260 8,907 44.1 51.5 33.5 39.3 Building Floorspace (Square Feet) 1,001 to 5,000 ................................... 50 92 68 40 547 1,086 912 629 90.6 84.6 74.5 63.7 5,001 to 10,000 ................................. 39 63 69 46 661 1,064 1,439 806 59.2 59.4 48.1 57.4 10,001 to 25,000 ............................... 58 133 81 70 1,293 2,656 2,332 1,542 45.2 50.1 34.7 45.7 25,001 to 50,000 ............................... 48 122 52 48 1,048 2,407 1,797 1,352 45.5 50.7 29.2 35.5 50,001 to 100,000 ............................. 66 98 68 37 1,841 2,009 2,486 1,164 35.7 48.9 27.3 31.6 100,001 to 200,000 ........................... 69 93 77 28 1,816 1,967 2,685 1,077 37.9 47.1 28.6 26.4 200,001 to 500,000 ........................... 60 73 44 28 1,588 1,765 1,527 1,012 37.6 41.4 28.7 27.3 Over 500,000 ....................................

498

1-MFE March 2006.xls  

Gasoline and Diesel Fuel Update (EIA)

and Stock Trends and Stock Trends Page 5 6. Month-to-Month Comparisons: Electric Power Retail Sales and Average Prices Page 6 7. Retail Sales Trends Page 7 8. Average Retail Price Trends Page 8 9. Heating and Cooling Degree Days Page 9 10. Documentation Page 10 Monthly Flash Estimates of Data for: January 2006 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy of the Department of Energy or any other organization. For additional information, contact Orhan Yildiz at 202-287-1586, or at Orhan.Yildiz@eia.doe.gov.

499

c13a.xls  

Gasoline and Diesel Fuel Update (EIA)

Dec 2006 Dec 2006 Next CBECS will be conducted in 2007 Electricity Expenditures Primary Total (trillion Btu) Total (trillion Btu) Total (billion kWh) All Buildings .................................... 4,617 70,181 15.2 10,746 3,559 1,043 82,783 Floorspace per Building (thousand square feet) Total (million dollars) Table C13A. Total Electricity Consumption and Expenditures for All Buildings, 2003 All Buildings Using Electricity Electricity Consumption Site Number of Buildings (thousand) Floorspace (million square feet) Climate Zone: 30-Year Average Under 2,000 CDD and -- More than 7,000 HDD ..................... 836 11,300 13.5 1,412 468 137 10,479 5,500-7,000 HDD ............................ 1,185 18,549 15.7 2,621 868 254 19,181 4,000-5,499 HDD ............................ 670 12,374 18.5 1,947 645

500

c10a.xls  

Gasoline and Diesel Fuel Update (EIA)

1,086 1,929 1,243 1,386 879 11,529 18,808 12,503 17,630 11,189 94.2 102.6 99.4 78.6 78.6 Building Floorspace (Square Feet) 1,001 to 5,000 ............................... 143 187 90 170 95 1,313 1,709 1,010 1,915 975 108.7 109.6 88.8 89.0 97.9 5,001 to 10,000 ............................. 110 137 91 156 69 1,248 1,725 1,077 2,024 959 88.1 79.3 84.6 77.1 71.7 10,001 to 25,000 ........................... 183 286 146 166 118 2,406 3,506 1,498 3,176 2,073 75.9 81.6 97.6 52.3 56.9 25,001 to 50,000 ........................... 146 212 125 152 107 1,547 2,424 1,382 2,381 1,647 94.4 87.6 90.3 63.7 64.8 50,001 to 100,000 ......................... 149 273 183 191 118 1,480 2,780 2,011 2,352 1,668 100.8 98.0 90.8 81.2 70.6 100,001 to 200,000 ....................... 117 336 187 283 141 1,311 2,889 1,881 2,597 1,538 89.4 116.3 99.2 109.1 91.7 200,001 to 500,000 .......................