National Library of Energy BETA

Sample records for binary floating-point number

  1. Multi-input and binary reproducible, high bandwidth floating point adder in a collective network

    DOE Patents [OSTI]

    Chen, Dong; Eisley, Noel A; Heidelberger, Philip; Steinmacher-Burow, Burkhard

    2015-03-10

    To add floating point numbers in a parallel computing system, a collective logic device receives the floating point numbers from computing nodes. The collective logic devices converts the floating point numbers to integer numbers. The collective logic device adds the integer numbers and generating a summation of the integer numbers. The collective logic device converts the summation to a floating point number. The collective logic device performs the receiving, the converting the floating point numbers, the adding, the generating and the converting the summation in one pass. One pass indicates that the computing nodes send inputs only once to the collective logic device and receive outputs only once from the collective logic device.

  2. Floating Point Control Library

    Energy Science and Technology Software Center (OSTI)

    2007-08-02

    Floating Point Control is a Library that allows for the manipulation of floating point unit exception masking funtions control exceptions in both the Streaming "Single Instruction, Multiple Data" Extension 2 (SSE2) unit and the floating point unit simultaneously. FPC also provides macros to set floating point rounding and precision control.

  3. T-561: IBM and Oracle Java Binary Floating-Point Number Conversion Denial of Service Vulnerability

    Broader source: Energy.gov [DOE]

    IBM and Oracle Java products contain a vulnerability that could allow an unauthenticated, remote attacker to cause a denial of service (DoS) condition on a targeted system.

  4. Double-Precision Floating-Point Cores V1.9

    Energy Science and Technology Software Center (OSTI)

    2005-10-15

    In studying the acceleration of scientific computing applications with reconfigurable hardware, such as field programmable gate arrays, one finds that many scientific applications require high-precision, floating-point arithmetic that is not innately supported in reconfigurable hardware. Consequently, we have written VDL code that describes hardware for performing double-precision (64-bit) floating-point arithmetic. From this code, it is possible for users to implement double-precision floating-point operations on FPGAs or any other hardware device to which VHDL code canmore » be synthesized. Specifically, we have written code for four floating-point cores. Each core performs one operation: one performs addition/subtraction, one performs multiplication, one performs division, and one performs square root. The code includes parameters that determine the features of the floating-point cores, such as what types of floating-point numbers are supported and what roudning modes are supported. These parameters influence the frequency achievable by the designs as well as the chip area required for the designs. The parameters are chosen so that the floating-point cores have varyinig amounts of compliance with the industry standard for floating-point cores have varying amounts of compliance with the industry standard for floating-point arithmetic, IEEE standard 754. There is an additional parameter that determines the number of pipelining stages in the floating-point cores.« less

  5. Improvements in floating point addition/subtraction operations

    DOE Patents [OSTI]

    Farmwald, P.M.

    1984-02-24

    Apparatus is described for decreasing the latency time associated with floating point addition and subtraction in a computer, using a novel bifurcated, pre-normalization/post-normalization approach that distinguishes between differences of floating point exponents.

  6. Generating and executing programs for a floating point single...

    Office of Scientific and Technical Information (OSTI)

    set architecture Citation Details In-Document Search Title: Generating and executing programs for a floating point single instruction multiple data instruction set architecture ...

  7. Quantifying the Impact of Single Bit Flips on Floating Point Arithmetic

    SciTech Connect (OSTI)

    Elliott, James J; Mueller, Frank; Stoyanov, Miroslav K; Webster, Clayton G

    2013-08-01

    In high-end computing, the collective surface area, smaller fabrication sizes, and increasing density of components have led to an increase in the number of observed bit flips. If mechanisms are not in place to detect them, such flips produce silent errors, i.e. the code returns a result that deviates from the desired solution by more than the allowed tolerance and the discrepancy cannot be distinguished from the standard numerical error associated with the algorithm. These phenomena are believed to occur more frequently in DRAM, but logic gates, arithmetic units, and other circuits are also susceptible to bit flips. Previous work has focused on algorithmic techniques for detecting and correcting bit flips in specific data structures, however, they suffer from lack of generality and often times cannot be implemented in heterogeneous computing environment. Our work takes a novel approach to this problem. We focus on quantifying the impact of a single bit flip on specific floating-point operations. We analyze the error induced by flipping specific bits in the most widely used IEEE floating-point representation in an architecture-agnostic manner, i.e., without requiring proprietary information such as bit flip rates and the vendor-specific circuit designs. We initially study dot products of vectors and demonstrate that not all bit flips create a large error and, more importantly, expected value of the relative magnitude of the error is very sensitive on the bit pattern of the binary representation of the exponent, which strongly depends on scaling. Our results are derived analytically and then verified experimentally with Monte Carlo sampling of random vectors. Furthermore, we consider the natural resilience properties of solvers based on the fixed point iteration and we demonstrate how the resilience of the Jacobi method for linear equations can be significantly improved by rescaling the associated matrix.

  8. Floating-Point Units and Algorithms for field-programmable gate arrays

    Energy Science and Technology Software Center (OSTI)

    2005-11-01

    The software that we are attempting to copyright is a package of floating-point unit descriptions and example algorithm implementations using those units for use in FPGAs. The floating point units are best-in-class implementations of add, multiply, divide, and square root floating-point operations. The algorithm implementations are sample (not highly flexible) implementations of FFT, matrix multiply, matrix vector multiply, and dot product. Together, one could think of the collection as an implementation of parts of themore » BLAS library or something similar to the FFTW packages (without the flexibility) for FPGAs. Results from this work has been published multiple times and we are working on a publication to discuss the techniques we use to implement the floating-point units, For some more background, FPGAS are programmable hardware. "Programs" for this hardware are typically created using a hardware description language (examples include Verilog, VHDL, and JHDL). Our floating-point unit descriptions are written in JHDL, which allows them to include placement constraints that make them highly optimized relative to some other implementations of floating-point units. Many vendors (Nallatech from the UK, SRC Computers in the US) have similar implementations, but our implementations seem to be somewhat higher performance. Our algorithm implementations are written in VHDL and models of the floating-point units are provided in VHDL as well. FPGA "programs" make multiple "calls" (hardware instantiations) to libraries of intellectual property (IP), such as the floating-point unit library described here. These programs are then compiled using a tool called a synthesizer (such as a tool from Synplicity, Inc.). The compiled file is a netlist of gates and flip-flops. This netlist is then mapped to a particular type of FPGA by a mapper and then a place- and-route tool. These tools assign the gates in the netlist to specific locations on the specific type of FPGA chip used

  9. Fixed-rate compressed floating-point arrays

    Energy Science and Technology Software Center (OSTI)

    2014-03-30

    ZFP is a library for lossy compression of single- and double-precision floating-point data. One of the unique features of ZFP is its support for fixed-rate compression, which enables random read and write access at the granularity of small blocks of values. Using a C++ interface, this allows declaring compressed arrays (1D, 2D, and 3D arrays are supported) that through operator overloading can be treated just like conventional, uncompressed arrays, but which allow the user tomore » specify the exact number of bits to allocate to the array. ZFP also has variable-rate fixed-precision and fixed-accuracy modes, which allow the user to specify a tolerance on the relative or absolute error.« less

  10. Quantifying the Impact of Single Bit Flips on Floating Point...

    Office of Scientific and Technical Information (OSTI)

    floating-point representation in an architecture-agnostic manner, i.e., without requiring proprietary information such as bit flip rates and the vendor-specific circuit designs. ...

  11. On the binary expansions of algebraic numbers

    SciTech Connect (OSTI)

    Bailey, David H.; Borwein, Jonathan M.; Crandall, Richard E.; Pomerance, Carl

    2003-07-01

    Employing concepts from additive number theory, together with results on binary evaluations and partial series, we establish bounds on the density of 1's in the binary expansions of real algebraic numbers. A central result is that if a real y has algebraic degree D > 1, then the number {number_sign}(|y|, N) of 1-bits in the expansion of |y| through bit position N satisfies {number_sign}(|y|, N) > CN{sup 1/D} for a positive number C (depending on y) and sufficiently large N. This in itself establishes the transcendency of a class of reals {summation}{sub n{ge}0} 1/2{sup f(n)} where the integer-valued function f grows sufficiently fast; say, faster than any fixed power of n. By these methods we re-establish the transcendency of the Kempner--Mahler number {summation}{sub n{ge}0}1/2{sup 2{sup n}}, yet we can also handle numbers with a substantially denser occurrence of 1's. Though the number z = {summation}{sub n{ge}0}1/2{sup n{sup 2}} has too high a 1's density for application of our central result, we are able to invoke some rather intricate number-theoretical analysis and extended computations to reveal aspects of the binary structure of z{sup 2}.

  12. Bifurcated method and apparatus for floating point addition with decreased latency time

    DOE Patents [OSTI]

    Farmwald, Paul M.

    1987-01-01

    Apparatus for decreasing the latency time associated with floating point addition and subtraction in a computer, using a novel bifurcated, pre-normalization/post-normalization approach that distinguishes between differences of floating point exponents.

  13. Floating point only SIMD instruction set architecture including compare, select, Boolean, and alignment operations

    DOE Patents [OSTI]

    Gschwind, Michael K.

    2011-03-01

    Mechanisms for implementing a floating point only single instruction multiple data instruction set architecture are provided. A processor is provided that comprises an issue unit, an execution unit coupled to the issue unit, and a vector register file coupled to the execution unit. The execution unit has logic that implements a floating point (FP) only single instruction multiple data (SIMD) instruction set architecture (ISA). The floating point vector registers of the vector register file store both scalar and floating point values as vectors having a plurality of vector elements. The processor may be part of a data processing system.

  14. Generating and executing programs for a floating point single instruction multiple data instruction set architecture

    DOE Patents [OSTI]

    Gschwind, Michael K

    2013-04-16

    Mechanisms for generating and executing programs for a floating point (FP) only single instruction multiple data (SIMD) instruction set architecture (ISA) are provided. A computer program product comprising a computer recordable medium having a computer readable program recorded thereon is provided. The computer readable program, when executed on a computing device, causes the computing device to receive one or more instructions and execute the one or more instructions using logic in an execution unit of the computing device. The logic implements a floating point (FP) only single instruction multiple data (SIMD) instruction set architecture (ISA), based on data stored in a vector register file of the computing device. The vector register file is configured to store both scalar and floating point values as vectors having a plurality of vector elements.

  15. Preliminary Results of a RANS Simulation for a Floating Point Absorber Wave Energy System Under Extreme Wave Conditions

    SciTech Connect (OSTI)

    Yu, Y.; Li, Y.

    2011-10-01

    This paper presents the results of a preliminary study on the hydrodynamics of a moored floating-point absorber (FPA) wave energy system under extreme wave conditions.

  16. Software Aspects of IEEE Floating-Point Computations for Numerical Applications in High Energy Physics

    SciTech Connect (OSTI)

    2010-05-11

    Floating-point computations are at the heart of much of the computing done in high energy physics. The correctness, speed and accuracy of these computations are of paramount importance. The lack of any of these characteristics can mean the difference between new, exciting physics and an embarrassing correction. This talk will examine practical aspects of IEEE 754-2008 floating-point arithmetic as encountered in HEP applications. After describing the basic features of IEEE floating-point arithmetic, the presentation will cover: common hardware implementations (SSE, x87) techniques for improving the accuracy of summation, multiplication and data interchange compiler options for gcc and icc affecting floating-point operations hazards to be avoided About the speaker Jeffrey M Arnold is a Senior Software Engineer in the Intel Compiler and Languages group at Intel Corporation. He has been part of the Digital->Compaq->Intel compiler organization for nearly 20 years; part of that time, he worked on both low- and high-level math libraries. Prior to that, he was in the VMS Engineering organization at Digital Equipment Corporation. In the late 1980s, Jeff spent 2 years at CERN as part of the CERN/Digital Joint Project. In 2008, he returned to CERN to spent 10 weeks working with CERN/openlab. Since that time, he has returned to CERN multiple times to teach at openlab workshops and consult with various LHC experiments. Jeff received his Ph.D. in physics from Case Western Reserve University.

  17. Software Aspects of IEEE Floating-Point Computations for Numerical Applications in High Energy Physics

    ScienceCinema (OSTI)

    None

    2011-10-06

    Floating-point computations are at the heart of much of the computing done in high energy physics. The correctness, speed and accuracy of these computations are of paramount importance. The lack of any of these characteristics can mean the difference between new, exciting physics and an embarrassing correction. This talk will examine practical aspects of IEEE 754-2008 floating-point arithmetic as encountered in HEP applications. After describing the basic features of IEEE floating-point arithmetic, the presentation will cover: common hardware implementations (SSE, x87) techniques for improving the accuracy of summation, multiplication and data interchange compiler options for gcc and icc affecting floating-point operations hazards to be avoided About the speaker Jeffrey M Arnold is a Senior Software Engineer in the Intel Compiler and Languages group at Intel Corporation. He has been part of the Digital->Compaq->Intel compiler organization for nearly 20 years; part of that time, he worked on both low- and high-level math libraries. Prior to that, he was in the VMS Engineering organization at Digital Equipment Corporation. In the late 1980s, Jeff spent 2½ years at CERN as part of the CERN/Digital Joint Project. In 2008, he returned to CERN to spent 10 weeks working with CERN/openlab. Since that time, he has returned to CERN multiple times to teach at openlab workshops and consult with various LHC experiments. Jeff received his Ph.D. in physics from Case Western Reserve University.

  18. Experimental Wave Tank Test for Reference Model 3 Floating-Point Absorber Wave Energy Converter Project

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

    Experimental Wave Tank Test for Reference Model 3 Floating- Point Absorber Wave Energy Converter Project Y.-H. Yu, M. Lawson, and Y. Li National Renewable Energy Laboratory M. Previsic and J. Epler Re Vision Consulting J. Lou Oregon State University Technical Report NREL/TP-5000-62951 January 2015 NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency & Renewable Energy Operated by the Alliance for Sustainable Energy, LLC This report is available at no

  19. Experimental Investigation of the Power Generation Performance of Floating-Point Absorber Wave Energy Systems: Preprint

    SciTech Connect (OSTI)

    Li, Y.; Yu, Y.; Epler, J.; Previsic, M.

    2012-04-01

    The extraction of energy from ocean waves has gained interest in recent years. The floating-point absorber (FPA) is one of the most promising devices among a wide variety of wave energy conversion technologies. Early theoretical studies mainly focused on understanding the hydrodynamics of the system and on predicting the maximum power that could be extracted by a heaving body. These studies evolve from the investigation of floating-body interactions in offshore engineering and naval architecture disciplines. To our best knowledge, no systematic study has been reported about the investigation of the power generation performance of an FPA with a close-to-commercial design. A series of experimental tests was conducted to investigate the power extraction performance of an FPA system.

  20. Technology development and circuit design for a parallel laser programmable floating-point application specific processor. Master's thesis

    SciTech Connect (OSTI)

    Scriber, M.W.

    1989-12-01

    The laser programmable floating point application specific processor (LPASP) is a new approach at rapid development of custom VLSI chips. The LPASP is a generic application specific processor that can be programmed to perform a specific function. The effort of this thesis is to develop and test the double precision floating point adder and the laser programmable read-only memory (LPROM) that are macrocells within the LPASP. In addition, the thesis analyzes the applicability of an LPASP parallel processing system. The double precision floating point adder is an adder/subtractor macrocell designed to comply with the IEEE double precision floating point standard. An 84-pin chip of the adder was fabricated using 2 micron feature sizes. The fastest processing time was measured at 120 nanoseconds over 23 worst case test vectors. The adder uses the optimized carry multiplexed (OCM) adder that was developed at AFIT. The OCM adder is a new adder architecture that uses four parallel carry paths to attain a performance time on the order of (cubed root of M) with a gate count on the order of O (n). The redundant logic associated with the parallel propagation banks is eliminated in the OCM adder so that the largest bit-slice of the adder contains only eight 2-to-1 multiplexer gates. A 57-bit adder was fabricated using 2 micron feature sizes. The processing time for the adder is 31 nsec.

  1. RANS Simulation of the Heave Response of a Two-Body Floating Point Wave Absorber: Preprint

    SciTech Connect (OSTI)

    Yu, Y.; Li, Y.

    2011-03-01

    A preliminary study on a two-body floating wave absorbers is presented in this paper. A Reynolds-Averaged Navier-Stokes computational method is applied for analyzing the hydrodynamic heave response of the absorber in operational wave conditions. The two-body floating wave absorber contains a float section and a submerged reaction section. For validation purposes, our model is first assumed to be locked. The two sections are forced to move together with each other. The locked single body model is used in a heave decay test, where the RANS result is validated with the experimental measurement. For the two-body floating point absorber simulation, the two sections are connected through a mass-spring-damper system, which is applied to simulate the power take-off mechanism under design wave conditions. Overall, the details of the flow around the absorber and its nonlinear interaction with waves are investigated, and the power absorption efficiency of the two-body floating wave absorber in waves with a constant value spring-damper system is examined.

  2. Tongonan 1 Binary GEPP | Open Energy Information

    Open Energy Info (EERE)

    Philippine Island Arc Plant Information Facility Type Binary Cycle Power Plant Owner Energy Development Corporation Number of Units 3 1 Commercial Online Date 1997 Power...

  3. Mahanagdong A-Binary GEPP | Open Energy Information

    Open Energy Info (EERE)

    Philippine Island Arc Plant Information Facility Type Binary Cycle Power Plant Owner Energy Development Corporation Number of Units 2 1 Commercial Online Date 1997 Power...

  4. Mahanagdong B-Binary GEPP | Open Energy Information

    Open Energy Info (EERE)

    Philippine Island Arc Plant Information Facility Type Binary Cycle Power Plant Owner Energy Development Corporation Number of Units 2 1 Commercial Online Date 1997 Power...

  5. Beowawe Binary Bottoming Cycle

    Broader source: Energy.gov [DOE]

    Project objectives: Demonstrate the technical and economic feasibility of electricity generation from the nonconventional geothermal resources of 205°F by extracting waste heat from the brine to power a binary power plant.

  6. Binary classification of items of interest in a repeatable process

    DOE Patents [OSTI]

    Abell, Jeffrey A; Spicer, John Patrick; Wincek, Michael Anthony; Wang, Hui; Chakraborty, Debejyo

    2015-01-06

    A system includes host and learning machines. Each machine has a processor in electrical communication with at least one sensor. Instructions for predicting a binary quality status of an item of interest during a repeatable process are recorded in memory. The binary quality status includes passing and failing binary classes. The learning machine receives signals from the at least one sensor and identifies candidate features. Features are extracted from the candidate features, each more predictive of the binary quality status. The extracted features are mapped to a dimensional space having a number of dimensions proportional to the number of extracted features. The dimensional space includes most of the passing class and excludes at least 90 percent of the failing class. Received signals are compared to the boundaries of the recorded dimensional space to predict, in real time, the binary quality status of a subsequent item of interest.

  7. Binary ferrihydrite catalysts

    DOE Patents [OSTI]

    Huffman, G.P.; Zhao, J.; Feng, Z.

    1996-12-03

    A method of preparing a catalyst precursor comprises dissolving an iron salt and a salt of an oxoanion forming agent, in water so that a solution of the iron salt and oxoanion forming agent salt has a ratio of oxoanion/Fe of between 0.0001:1 to 0.5:1. Next is increasing the pH of the solution to 10 by adding a strong base followed by collecting of precipitate having a binary ferrihydrite structure. A binary ferrihydrite catalyst precursor is also prepared by dissolving an iron salt in water. The solution is brought to a pH of substantially 10 to obtain ferrihydrite precipitate. The precipitate is then filtered and washed with distilled water and subsequently admixed with a hydroxy carboxylic acid solution. The admixture is mixed/agitated and the binary ferrihydrite precipitate is then filtered and recovered. 3 figs.

  8. Binary ferrihydrite catalysts

    DOE Patents [OSTI]

    Huffman, Gerald P.; Zhao, Jianmin; Feng, Zhen

    1996-01-01

    A method of preparing a catalyst precursor comprises dissolving an iron salt and a salt of an oxoanion forming agent, in water so that a solution of the iron salt and oxoanion forming agent salt has a ratio of oxoanion/Fe of between 0.0001:1 to 0.5:1. Next is increasing the pH of the solution to 10 by adding a strong base followed by collecting of precipitate having a binary ferrihydrite structure. A binary ferrihydrite catalyst precursor is also prepared by dissolving an iron salt in water. The solution is brought to a pH of substantially 10 to obtain ferrihydrite precipitate. The precipitate is then filtered and washed with distilled water and subsequently admixed with a hydroxy carboxylic acid solution. The admixture is mixed/agitated and the binary ferrihydrite precipitate is then filtered and recovered.

  9. Binary Optics Toolkit

    Energy Science and Technology Software Center (OSTI)

    1996-04-02

    This software is a set of tools for the design and analysis of binary optics. It consists of a series of stand-alone programs written in C and some scripts written in an application-specific language interpreted by a CAD program called DW2000. This software can be used to optimize the design and placement of a complex lens array from input to output and produce contours, mask designs, and data exported for diffractive optic analysis.

  10. Binary power multiplier for electromagnetic energy

    DOE Patents [OSTI]

    Farkas, Zoltan D.

    1988-01-01

    A technique for converting electromagnetic pulses to higher power amplitude and shorter duration, in binary multiples, splits an input pulse into two channels, and subjects the pulses in the two channels to a number of binary pulse compression operations. Each pulse compression operation entails combining the pulses in both input channels and selectively steering the combined power to one output channel during the leading half of the pulses and to the other output channel during the trailing half of the pulses, and then delaying the pulse in the first output channel by an amount equal to half the initial pulse duration. Apparatus for carrying out each of the binary multiplication operation preferably includes a four-port coupler (such as a 3 dB hybrid), which operates on power inputs at a pair of input ports by directing the combined power to either of a pair of output ports, depending on the relative phase of the inputs. Therefore, by appropriately phase coding the pulses prior to any of the pulse compression stages, the entire pulse compression (with associated binary power multiplication) can be carried out solely with passive elements.

  11. Ultra-short period binaries from the Catalina Surveys

    SciTech Connect (OSTI)

    Drake, A. J.; Djorgovski, S. G.; Graham, M. J.; Mahabal, A. A.; Donalek, C.; Williams, R.; García-Álvarez, D.; Catelan, M.; Torrealba, G.; Prieto, J. L.; Abraham, S.; Larson, S.; Christensen, E.

    2014-08-01

    We investigate the properties of 367 ultra-short period binary candidates selected from 31,000 sources recently identified from Catalina Surveys data. Based on light curve morphology, along with WISE, Sloan Digital Sky Survey, and GALEX multi-color photometry, we identify two distinct groups of binaries with periods below the 0.22 day contact binary minimum. In contrast to most recent work, we spectroscopically confirm the existence of M dwarf+M dwarf contact binary systems. By measuring the radial velocity variations for five of the shortest-period systems, we find examples of rare cool white dwarf (WD)+M dwarf binaries. Only a few such systems are currently known. Unlike warmer WD systems, their UV flux and optical colors and spectra are dominated by the M-dwarf companion. We contrast our discoveries with previous photometrically selected ultra-short period contact binary candidates and highlight the ongoing need for confirmation using spectra and associated radial velocity measurements. Overall, our analysis increases the number of ultra-short period contact binary candidates by more than an order of magnitude.

  12. Binary Cycle Power Plant | Open Energy Information

    Open Energy Info (EERE)

    binary-cycle power plants in the future will be binary-cycle plants1 Enel's Salts Wells Geothermal Plant in Nevada: This plant is a binary system that is rated at 13 MW...

  13. THIRTY NEW LOW-MASS SPECTROSCOPIC BINARIES

    SciTech Connect (OSTI)

    Shkolnik, Evgenya L.; Hebb, Leslie; Cameron, Andrew C.; Liu, Michael C.; Neill Reid, I. E-mail: Andrew.Cameron@st-and.ac.u E-mail: mliu@ifa.hawaii.ed

    2010-06-20

    As part of our search for young M dwarfs within 25 pc, we acquired high-resolution spectra of 185 low-mass stars compiled by the NStars project that have strong X-ray emission. By cross-correlating these spectra with radial velocity standard stars, we are sensitive to finding multi-lined spectroscopic binaries. We find a low-mass spectroscopic binary fraction of 16% consisting of 27 SB2s, 2 SB3s, and 1 SB4, increasing the number of known low-mass spectroscopic binaries (SBs) by 50% and proving that strong X-ray emission is an extremely efficient way to find M-dwarf SBs. WASP photometry of 23 of these systems revealed two low-mass eclipsing binaries (EBs), bringing the count of known M-dwarf EBs to 15. BD-22 5866, the ESB4, was fully described in 2008 by Shkolnik et al. and CCDM J04404+3127 B consists of two mid-M stars orbiting each other every 2.048 days. WASP also provided rotation periods for 12 systems, and in the cases where the synchronization time scales are short, we used P{sub rot} to determine the true orbital parameters. For those with no P{sub rot}, we used differential radial velocities to set upper limits on orbital periods and semimajor axes. More than half of our sample has near-equal-mass components (q > 0.8). This is expected since our sample is biased toward tight orbits where saturated X-ray emission is due to tidal spin-up rather than stellar youth. Increasing the samples of M-dwarf SBs and EBs is extremely valuable in setting constraints on current theories of stellar multiplicity and evolution scenarios for low-mass multiple systems.

  14. Request Number:

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

    3023307 Name: Madeleine Brown Organization: nJa Address: --- -------- -------- -- Country: Phone Number: United States Fax Number: n/a E-mail: --- -------- --------_._------ --- Reasonably Describe Records Description: Please send me a copy of the emails and records relating to the decision to allow the underage son of Bill Gates to tour Hanford in June 2010. Please also send the emails and records that justify the Department of Energy to prevent other minors from visiting B Reactor. Optional

  15. Request Number:

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

    1074438 Name: Gayle Cooper Organization: nla Address: _ Country: United States Phone Number: Fax Number: nla E-mail: . ~===--------- Reasonably Describe Records Description: Information pertaining to the Department of Energy's cost estimate for reinstating pension benefit service years to the Enterprise Company (ENCO) employees who are active plan participants in the Hanford Site Pension Plan. This cost estimate was an outcome of the DOE's Worker Town Hall Meetings held on September 17-18, 2009.

  16. Dixie Valley Bottoming Binary Cycle

    Broader source: Energy.gov [DOE]

    Project objective: Prove the technical and economic feasibility of utilizing the available unused heat to generate additional electric power from a binary power plant from low-temperature brine at the Dixie Valley Geothermal Power Plant.

  17. (Document Number)

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

    A TA-53 TOUR FORM/RADIOLOGICAL LOG (Send completed form to MS H831) _____________ _____________________________ _________________________________ Tour Date Purpose of Tour or Tour Title Start Time and Approximate Duration ___________________________ ______________ _______________________ _________________ Tour Point of Contact/Requestor Z# (if applicable) Organization/Phone Number Signature Locations Visited: (Check all that apply, and list any others not shown. Prior approval must be obtained

  18. Evolution of Intermediate and Low Mass Binary Systems

    SciTech Connect (OSTI)

    Eggleton, P P

    2005-10-25

    There are a number of binaries, fairly wide and with one or even two evolved giant components, that do not agree very well with conventional stellar evolution: the secondaries are substantially larger (oversized) than they should be because their masses are quite low compared with the primaries. I discuss the possibility that these binaries are former triples, in which a merger has occurred fairly recently in a short-period binary sub-component. Some mergers are expected, and may follow a phase of contact evolution. I suggest that in contact there is substantial transfer of luminosity between the components due to differential rotation, of the character observed by helioseismology in the Sun's surface convection zone.

  19. Experimental Wave Tank Test for Reference Model 3 Floating-Point Absorber Wave Energy Converter Project

    SciTech Connect (OSTI)

    Yu, Y. H.; Lawson, M.; Li, Y.; Previsic, M.; Epler, J.; Lou, J.

    2015-01-01

    The U.S. Department of Energy established a reference model project to benchmark a set of marine and hydrokinetic technologies including current (tidal, open-ocean, and river) turbines and wave energy converters. The objectives of the project were to first evaluate the status of these technologies and their readiness for commercial applications. Second, to evaluate the potential cost of energy and identify cost-reduction pathways and areas where additional research could be best applied to accelerate technology development to market readiness.

  20. Merger of white dwarf-neutron star binaries: Prelude to hydrodynamic simulations in general relativity

    SciTech Connect (OSTI)

    Paschalidis, Vasileios; MacLeod, Morgan; Baumgarte, Thomas W.; Shapiro, Stuart L.

    2009-07-15

    White dwarf-neutron star binaries generate detectable gravitational radiation. We construct Newtonian equilibrium models of corotational white dwarf-neutron star (WDNS) binaries in circular orbit and find that these models terminate at the Roche limit. At this point the binary will undergo either stable mass transfer (SMT) and evolve on a secular time scale, or unstable mass transfer (UMT), which results in the tidal disruption of the WD. The path a given binary will follow depends primarily on its mass ratio. We analyze the fate of known WDNS binaries and use population synthesis results to estimate the number of LISA-resolved galactic binaries that will undergo either SMT or UMT. We model the quasistationary SMT epoch by solving a set of simple ordinary differential equations and compute the corresponding gravitational waveforms. Finally, we discuss in general terms the possible fate of binaries that undergo UMT and construct approximate Newtonian equilibrium configurations of merged WDNS remnants. We use these configurations to assess plausible outcomes of our future, fully relativistic simulations of these systems. If sufficient WD debris lands on the NS, the remnant may collapse, whereby the gravitational waves from the inspiral, merger, and collapse phases will sweep from LISA through LIGO frequency bands. If the debris forms a disk about the NS, it may fragment and form planets.

  1. Binary and ternary gas mixtures with temperature enhanced diffuse...

    Office of Scientific and Technical Information (OSTI)

    Binary and ternary gas mixtures with temperature enhanced diffuse glow discharge characteristics for use in closing switches Title: Binary and ternary gas mixtures with temperature ...

  2. Tailored Working Fluids for Enhanced Binary Geothermal Power...

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

    Tailored Working Fluids for Enhanced Binary Geothermal Power Plants Tailored Working Fluids for Enhanced Binary Geothermal Power Plants DOE Geothermal Program Peer Review 2010 - ...

  3. High-potential Working Fluids for Next Generation Binary Cycle...

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

    High-potential Working Fluids for Next Generation Binary Cycle Geothermal Power Plants High-potential Working Fluids for Next Generation Binary Cycle Geothermal Power Plants DOE ...

  4. A Flashing Binary Combined Cycle For Geothermal Power Generation...

    Open Energy Info (EERE)

    Flashing Binary Combined Cycle For Geothermal Power Generation Jump to: navigation, search OpenEI Reference LibraryAdd to library Journal Article: A Flashing Binary Combined Cycle...

  5. Mak-Ban Binary 1 GEPP | Open Energy Information

    Open Energy Info (EERE)

    Home Mak-Ban Binary 1 GEPP General Information Name Mak-Ban Binary 1 GEPP Facility Power Plant Sector Geothermal energy Location Information Coordinates 14.087741209723,...

  6. Dixie Valley Bottoming Binary Unit

    SciTech Connect (OSTI)

    McDonald, Dale

    2014-12-21

    This binary plant is the first air cooled, high-output refrigeration based waste heat recovery cycle in the industry. Its working fluid is environmentally friendly and as such, the permits that would be required with a hydrocarbon based cycle are not necessary. The unit is largely modularized, meaning that the unit’s individual skids were assembled in another location and were shipped via truck to the plant site. The Air Cooled Condensers (ACC), equipment piping, and Balance of Plant (BOP) piping were constructed at site. This project further demonstrates the technical feasibility of using low temperature brine for geothermal power utilization. The development of the unit led to the realization of low temperature, high output, and environmentally friendly heat recovery systems through domestic research and engineering. The project generates additional renewable energy, resulting in cleaner air and reduced carbon dioxide emissions. Royalty and tax payments to governmental agencies will increase, resulting in reduced financial pressure on local entities. The major components of the unit were sourced from American companies, resulting in increased economic activity throughout the country.

  7. Binary module test. Final report

    SciTech Connect (OSTI)

    Schilling, J.R.; Colley, T.C.; Pundyk, J.

    1980-12-01

    The objective of this project was to design and test a binary loop module representative of and scaleable to commercial size units. The design was based on state-of-the-art heat exchanger technology, and the purpose of the tests was to confirm performance of a supercritical boiling cycle using isobutane and a mixture of isobutane and isopentane as the secondary working fluid. The module was designed as one percent of a 50 MW unit. It was installed at Magma Power's East Mesa geothermal field and tested over a period of approximately 4 months. Most of the test runs were with isobutane but some data were collected for hydrocarbon mixtures. The results of the field tests are reported. In general these results indicate reasonably good heat balances and agreement with overall heat transfer coefficients calculated by current stream analysis methods and available fluid property data; however, measured pressure drops across the heat exchangers were 20 percent higher than estimated. System operation was stable under all conditions tested.

  8. Three-dimensional profiling with binary fringes using phase-shifting interferometry algorithms

    SciTech Connect (OSTI)

    Ayubi, Gaston A.; Di Martino, J. Matias; Alonso, Julia R.; Fernandez, Ariel; Perciante, Cesar D.; Ferrari, Jose A.

    2011-01-10

    Three-dimensional shape measurements by sinusoidal fringe projection using phase-shifting interferometry algorithms are distorted by the nonlinear response in intensity of commercial video projectors and digital cameras. To solve the problem, we present a method that consists in projecting and acquiring a temporal sequence of strictly binary patterns, whose (adequately weighted) average leads to a sinusoidal fringe pattern with the required number of bits. Since binary patterns consist of ''ones'' and ''zeros'' - and no half-tones are involved - the nonlinear response of the projector and the camera will not play a role, and a nearly unit contrast gray-level sinusoidal fringe pattern is obtained. Validation experiments are presented.

  9. Number | Open Energy Information

    Open Energy Info (EERE)

    Property:NumOfPlants Property:NumProdWells Property:NumRepWells Property:Number of Color Cameras Property:Number of Devices Deployed Property:Number of Plants included in...

  10. ROTATIONAL SYNCHRONIZATION MAY ENHANCE HABITABILITY FOR CIRCUMBINARY PLANETS: KEPLER BINARY CASE STUDIES

    SciTech Connect (OSTI)

    Mason, Paul A.; Zuluaga, Jorge I.; Cuartas-Restrepo, Pablo A.; Clark, Joni M.

    2013-09-10

    We report a mechanism capable of reducing (or increasing) stellar activity in binary stars, thereby potentially enhancing (or destroying) circumbinary habitability. In single stars, stellar aggression toward planetary atmospheres causes mass-loss, which is especially detrimental for late-type stars, because habitable zones are very close and activity is long lasting. In binaries, tidal rotational breaking reduces magnetic activity, thus reducing harmful levels of X-ray and ultraviolet (XUV) radiation and stellar mass-loss that are able to erode planetary atmospheres. We study this mechanism for all confirmed circumbinary (p-type) planets. We find that main sequence twins provide minimal flux variation and in some cases improved environments if the stars rotationally synchronize within the first Gyr. Solar-like twins, like Kepler 34 and Kepler 35, provide low habitable zone XUV fluxes and stellar wind pressures. These wide, moist, habitable zones may potentially support multiple habitable planets. Solar-type stars with lower mass companions, like Kepler 47, allow for protected planets over a wide range of secondary masses and binary periods. Kepler 38 and related binaries are marginal cases. Kepler 64 and analogs have dramatically reduced stellar aggression due to synchronization of the primary, but are limited by the short lifetime. Kepler 16 appears to be inhospitable to planets due to extreme XUV flux. These results have important implications for estimates of the number of stellar systems containing habitable planets in the Galaxy and allow for the selection of binaries suitable for follow-up searches for habitable planets.

  11. NSR Key Number Retrieval

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

    NSR Key Number Retrieval Pease enter key in the box Submit

  12. BINARIES MIGRATING IN A GASEOUS DISK: WHERE ARE THE GALACTIC CENTER BINARIES?

    SciTech Connect (OSTI)

    Baruteau, C.; Lin, D. N. C.; Cuadra, J. E-mail: lin@ucolick.org

    2011-01-01

    The massive stars in the Galactic center inner arcsecond share analogous properties with the so-called Hot Jupiters. Most of these young stars have highly eccentric orbits and were probably not formed in situ. It has been proposed that these stars acquired their current orbits from the tidal disruption of compact massive binaries scattered toward the proximity of the central supermassive black hole. Assuming a binary star formed in a thin gaseous disk beyond 0.1 pc from the central object, we investigate the relevance of disk-satellite interactions to harden the binding energy of the binary, and to drive its inward migration. A massive, equal-mass binary star is found to become more tightly wound as it migrates inward toward the central black hole. The migration timescale is very similar to that of a single-star satellite of the same mass. The binary's hardening is caused by the formation of spiral tails lagging the stars inside the binary's Hill radius. We show that the hardening timescale is mostly determined by the mass of gas inside the binary's Hill radius and that it is much shorter than the migration timescale. We discuss some implications of the binary's hardening process. When the more massive (primary) components of close binaries eject most their mass through supernova explosion, their secondary stars may attain a range of eccentricities and inclinations. Such processes may provide an alternative unified scenario for the origin of the kinematic properties of the central cluster and S-stars in the Galactic center as well as the high-velocity stars in the Galactic halo.

  13. Binary translation using peephole translation rules

    DOE Patents [OSTI]

    Bansal, Sorav; Aiken, Alex

    2010-05-04

    An efficient binary translator uses peephole translation rules to directly translate executable code from one instruction set to another. In a preferred embodiment, the translation rules are generated using superoptimization techniques that enable the translator to automatically learn translation rules for translating code from the source to target instruction set architecture.

  14. T-694: IBM Tivoli Federated Identity Manager Products Multiple Vulnerabilities

    Broader source: Energy.gov [DOE]

    This Security Alert addresses a serious security issue CVE-2010-4476 (Java Runtime Environment hangs when converting "2.2250738585072012e-308" to a binary floating-point number). This vulnerability might cause the Java Runtime Environment to hang, be in infinite loop, and/or crash resulting in a denial of service exposure. This same hang might occur if the number is written without scientific notation (324 decimal places). In addition to the Application Server being exposed to this attack, any Java program using the Double.parseDouble method is also at risk of this exposure including any customer written application or third party written application.

  15. LOW-MASS ECLIPSING BINARIES IN THE INITIAL KEPLER DATA RELEASE

    SciTech Connect (OSTI)

    Coughlin, J. L.; Harrison, T. E.; Ule, N.; Lopez-Morales, M.; Hoffman, D. I.

    2011-03-15

    We identify 231 objects in the newly released Cycle 0 data set from the Kepler Mission as double-eclipse, detached eclipsing binary systems with T{sub eff} < 5500 K and orbital periods shorter than {approx}32 days. We model each light curve using the JKTEBOP code with a genetic algorithm to obtain precise values for each system. We identify 95 new systems with both components below 1.0 M{sub sun} and eclipses of at least 0.1 mag, suitable for ground-based follow-up. Of these, 14 have periods less than 1.0 day, 52 have periods between 1.0 and 10.0 days, and 29 have periods greater than 10.0 days. This new sample of main-sequence, low-mass, double-eclipse, detached eclipsing binary candidates more than doubles the number of previously known systems and extends the sample into the completely heretofore unexplored P > 10.0 day period regime. We find preliminary evidence from these systems that the radii of low-mass stars in binary systems decrease with period. This supports the theory that binary spin-up is the primary cause of inflated radii in low-mass binary systems, although a full analysis of each system with radial-velocity and multi-color light curves is needed to fully explore this hypothesis. Also, we present seven new transiting planet candidates that do not appear among the list of 706 candidates recently released by the Kepler team, or in the Kepler False Positive Catalog, along with several other new and interesting systems. We also present novel techniques for the identification, period analysis, and modeling of eclipsing binaries.

  16. Automated pupil remapping with binary optics

    DOE Patents [OSTI]

    Neal, D.R.; Mansell, J.

    1999-01-26

    Methods and apparatuses are disclosed for pupil remapping employing non-standard lenslet shapes in arrays; divergence of lenslet focal spots from on-axis arrangements; use of lenslet arrays to resize two-dimensional inputs to the array; and use of lenslet arrays to map an aperture shape to a different detector shape. Applications include wavefront sensing, astronomical applications, optical interconnects, keylocks, and other binary optics and diffractive optics applications. 24 figs.

  17. Automated pupil remapping with binary optics

    DOE Patents [OSTI]

    Neal, Daniel R.; Mansell, Justin

    1999-01-01

    Methods and apparatuses for pupil remapping employing non-standard lenslet shapes in arrays; divergence of lenslet focal spots from on-axis arrangements; use of lenslet arrays to resize two-dimensional inputs to the array; and use of lenslet arrays to map an aperture shape to a different detector shape. Applications include wavefront sensing, astronomical applications, optical interconnects, keylocks, and other binary optics and diffractive optics applications.

  18. New York Natural Gas Number of Commercial Consumers (Number of...

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

    Commercial Consumers (Number of Elements) New York Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers New York Number of Natural Gas ...

  19. New Mexico Natural Gas Number of Commercial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Commercial Consumers (Number of Elements) New Mexico Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers New Mexico Number of Natural ...

  20. North Dakota Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) North Dakota Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers North Dakota Number of Natural ...

  1. Massive binaries in the vicinity of Sgr A*

    SciTech Connect (OSTI)

    Pfuhl, O.; Gillessen, S.; Genzel, R.; Eisenhauer, F.; Fritz, T. K.; Ott, T.; Alexander, T.; Martins, F.

    2014-02-20

    A long-term spectroscopic and photometric survey of the most luminous and massive stars in the vicinity of the supermassive black hole Sgr A* revealed two new binaries: a long-period Ofpe/WN9 binary, IRS 16NE, with a modest eccentricity of 0.3 and a period of 224 days, and an eclipsing Wolf-Rayet binary with a period of 2.3 days. Together with the already identified binary IRS 16SW, there are now three confirmed OB/WR binaries in the inner 0.2 pc of the Galactic center. Using radial velocity change upper limits, we were able to constrain the spectroscopic binary fraction in the Galactic center to F{sub SB}=0.30{sub −0.21}{sup +0.34} at a confidence level of 95%, a massive binary fraction close to that observed in dense clusters. The fraction of eclipsing binaries with photometric amplitudes Δm > 0.4 is F{sub EB}{sup GC}=3%±2%, which is consistent with local OB star clusters (F {sub EB} = 1%). Overall, the Galactic center binary fraction seems to be similar to the binary fraction in comparable young clusters.

  2. Quantum random number generator

    DOE Patents [OSTI]

    Pooser, Raphael C.

    2016-05-10

    A quantum random number generator (QRNG) and a photon generator for a QRNG are provided. The photon generator may be operated in a spontaneous mode below a lasing threshold to emit photons. Photons emitted from the photon generator may have at least one random characteristic, which may be monitored by the QRNG to generate a random number. In one embodiment, the photon generator may include a photon emitter and an amplifier coupled to the photon emitter. The amplifier may enable the photon generator to be used in the QRNG without introducing significant bias in the random number and may enable multiplexing of multiple random numbers. The amplifier may also desensitize the photon generator to fluctuations in power supplied thereto while operating in the spontaneous mode. In one embodiment, the photon emitter and amplifier may be a tapered diode amplifier.

  3. BINARY CEPHEIDS: SEPARATIONS AND MASS RATIOS IN 5 M {sub ?} BINARIES

    SciTech Connect (OSTI)

    Evans, Nancy Remage; Karovska, Margarita; Tingle, Evan; Bond, Howard E.; Schaefer, Gail H.; Mason, Brian D. E-mail: heb11@psu.edu

    2013-10-01

    Deriving the distribution of binary parameters for a particular class of stars over the full range of orbital separations usually requires the combination of results from many different observing techniques (radial velocities, interferometry, astrometry, photometry, direct imaging), each with selection biases. However, Cepheidscool, evolved stars of ?5 M {sub ?}are a special case because ultraviolet (UV) spectra will immediately reveal any companion star hotter than early type A, regardless of the orbital separation. We have used International Ultraviolet Explorer UV spectra of a complete sample of all 76 Cepheids brighter than V = 8 to create a list of all 18 Cepheids with companions more massive than 2.0 M {sub ?}. Orbital periods of many of these binaries are available from radial-velocity studies, or can be estimated for longer-period systems from detected velocity variability. In an imaging survey with the Hubble Space Telescope Wide Field Camera 3, we resolved three of the companions (those of ? Aql, S Nor, and V659 Cen), allowing us to make estimates of the periods out to the long-period end of the distribution. Combining these separations with orbital data in the literature, we derive an unbiased distribution of binary separations, orbital periods, and mass ratios. The distribution of orbital periods shows that the 5 M {sub ?} binaries have systematically shorter periods than do 1 M {sub ?} stars. Our data also suggest that the distribution of mass ratios depends on both binary separation and system multiplicity. The distribution of mass ratios as a function of orbital separation, however, does not depend on whether a system is a binary or a triple.

  4. Report number codes

    SciTech Connect (OSTI)

    Nelson, R.N.

    1985-05-01

    This publication lists all report number codes processed by the Office of Scientific and Technical Information. The report codes are substantially based on the American National Standards Institute, Standard Technical Report Number (STRN)-Format and Creation Z39.23-1983. The Standard Technical Report Number (STRN) provides one of the primary methods of identifying a specific technical report. The STRN consists of two parts: The report code and the sequential number. The report code identifies the issuing organization, a specific program, or a type of document. The sequential number, which is assigned in sequence by each report issuing entity, is not included in this publication. Part I of this compilation is alphabetized by report codes followed by issuing installations. Part II lists the issuing organization followed by the assigned report code(s). In both Parts I and II, the names of issuing organizations appear for the most part in the form used at the time the reports were issued. However, for some of the more prolific installations which have had name changes, all entries have been merged under the current name.

  5. An improved catalog of halo wide binary candidates

    SciTech Connect (OSTI)

    Allen, Christine; Monroy-Rodríguez, Miguel A.

    2014-08-01

    We present an improved catalog of halo wide binaries compiled from an extensive literature search. Most of our binaries stem from the common proper motion binary catalogs by Allen et al. and Chanamé and Gould, but we have also included binaries from the lists of Ryan and Zapatero-Osorio and Martín. All binaries were carefully checked and their distances and systemic radial velocities are included when available. Probable membership to the halo population was tested by means of reduced proper motion diagrams for 251 candidate halo binaries. After eliminating obvious disk binaries, we ended up with 211 probable halo binaries, 150 of which have radial velocities available. We compute galactic orbits for these 150 binaries and calculate the time they spend within the galactic disk. Considering the full sample of 251 candidate halo binaries as well as several subsamples, we find that the distribution of angular separations (or expected major semiaxes) follows a power law f(a) ∼ a {sup –1} (Oepik's relation) up to different limits. For the 50 most disk-like binaries, those that spend their entire lives within z = ±500 pc, this limit is found to be 19,000 AU (0.09 pc), while for the 50 most halo-like binaries, those that spend on average only 18% of their lives within z = ±500 pc, the limit is 63,000 AU (0.31 pc). In a companion paper, we employ this catalog to establish limits on the masses of the halo massive perturbers (massive compact halo objects).

  6. Quantum random number generation

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

    Ma, Xiongfeng; Yuan, Xiao; Cao, Zhu; Zhang, Zhen; Qi, Bing

    2016-06-28

    Here, quantum physics can be exploited to generate true random numbers, which play important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum system reveals the inherent nature of quantumness -- coherence, an important feature that differentiates quantum mechanics from classical physics. The generation of genuine randomness is generally considered impossible with only classical means. Based on the degree of trustworthiness on devices, quantum random number generators (QRNGs) can be grouped into three categories. The first category, practical QRNG, is built on fully trusted and calibrated devices and typically can generate randomness at amore » high speed by properly modeling the devices. The second category is self-testing QRNG, where verifiable randomness can be generated without trusting the actual implementation. The third category, semi-self-testing QRNG, is an intermediate category which provides a tradeoff between the trustworthiness on the device and the random number generation speed.« less

  7. Controlling phase separation of binary Bose-Einstein condensates...

    Office of Scientific and Technical Information (OSTI)

    Controlling phase separation of binary Bose-Einstein condensates via mixed-spin-channel Feshbach resonance Citation Details In-Document Search Title: Controlling phase separation ...

  8. Project Profile: Binary Metal Chalcogenides for High Temperature...

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

    Under this project, researchers are developing a thermochemical energy storage system that uses binary metal chalcogenides in a modular reactor operating at temperatures of at ...

  9. Transport in a highly asymmetric binary fluid mixture (Journal...

    Office of Scientific and Technical Information (OSTI)

    Journal Article: Transport in a highly asymmetric binary fluid mixture Citation Details ... Language: English Subject: 71 CLASSICAL AND QUANTUMM MECHANICS, GENERAL PHYSICS; MIXTURES; ...

  10. SEARCH FOR SUPERMASSIVE BLACK HOLE BINARIES IN THE SLOAN DIGITAL...

    Office of Scientific and Technical Information (OSTI)

    THE SLOAN DIGITAL SKY SURVEY SPECTROSCOPIC SAMPLE Citation Details In-Document Search Title: SEARCH FOR SUPERMASSIVE BLACK HOLE BINARIES IN THE SLOAN DIGITAL SKY SURVEY ...

  11. ALARA notes, Number 8

    SciTech Connect (OSTI)

    Khan, T.A.; Baum, J.W.; Beckman, M.C.

    1993-10-01

    This document contains information dealing with the lessons learned from the experience of nuclear plants. In this issue the authors tried to avoid the `tyranny` of numbers and concentrated on the main lessons learned. Topics include: filtration devices for air pollution abatement, crack repair and inspection, and remote handling equipment.

  12. Document Details Document Number

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

    Document Details Document Number Date of Document Document Title/Description [Links below to each document] D195066340 Not listed. N/A REVISIONS IN STRATIGRAPHIC NOMENCLATURE OF COLUMBIA RIVER BASALT GROUP D196000240 Not listed. N/A EPA DENIAL OF LINER LEACHATE COLLECTION SYSTEM REQUIREMENTS D196005916 Not listed. N/A LATE CENOZOIC STRATIGRAPHY AND TECTONIC EVOLUTION WITHIN SUBSIDING BASIN SOUTH CENTRAL WASHINGTON D196025993 RHO-BWI-ST-14 N/A SUPRABASALT SEDIMENTS OF COLD CREEK SYNCLINE AREA

  13. Binary classification of items of interest in a repeatable process

    SciTech Connect (OSTI)

    Abell, Jeffrey A.; Spicer, John Patrick; Wincek, Michael Anthony; Wang, Hui; Chakraborty, Debejyo

    2014-06-24

    A system includes host and learning machines in electrical communication with sensors positioned with respect to an item of interest, e.g., a weld, and memory. The host executes instructions from memory to predict a binary quality status of the item. The learning machine receives signals from the sensor(s), identifies candidate features, and extracts features from the candidates that are more predictive of the binary quality status relative to other candidate features. The learning machine maps the extracted features to a dimensional space that includes most of the items from a passing binary class and excludes all or most of the items from a failing binary class. The host also compares the received signals for a subsequent item of interest to the dimensional space to thereby predict, in real time, the binary quality status of the subsequent item of interest.

  14. Binary and ternary gas mixtures for use in glow discharge closing...

    Office of Scientific and Technical Information (OSTI)

    Highly efficient binary and ternary gas mixtures for use in diffuse glow discharge closing ... discharge; closing; switches; highly; efficient; binary; ternary; gas; mixtures; ...

  15. Binary Solid Propellants for Constant Momentum Missions

    SciTech Connect (OSTI)

    Pakhomov, Andrew V.; Mahaffy, Kevin E.

    2008-04-28

    A constant momentum mission is achieved when the speed of the vehicle in the inertial frame of reference is equal to the speed of exhaust relative to the vehicle. Due to 100% propulsive efficiency such missions are superior to traditional constant specific impulse missions. A new class of solid binary propellants for constant momentum missions is under development. A typical propellant column is prepared as a solid solution of two components, with composition gradually changing from 100% of a propellant of high coupling coefficient (C{sub m}) to one which has high specific impulse (I{sub sp}). The high coupling component is ablated first, gradually giving way to the high I{sub sp} component, as the vehicle accelerates. This study opens new opportunities for further design of complex propellants for laser propulsion, providing variable C{sub m} and I{sub sp} during missions.

  16. Modular redundant number systems

    SciTech Connect (OSTI)

    1998-05-31

    With the increased use of public key cryptography, faster modular multiplication has become an important cryptographic issue. Almost all public key cryptography, including most elliptic curve systems, use modular multiplication. Modular multiplication, particularly for the large public key modulii, is very slow. Increasing the speed of modular multiplication is almost synonymous with increasing the speed of public key cryptography. There are two parts to modular multiplication: multiplication and modular reduction. Though there are fast methods for multiplying and fast methods for doing modular reduction, they do not mix well. Most fast techniques require integers to be in a special form. These special forms are not related and converting from one form to another is more costly than using the standard techniques. To this date it has been better to use the fast modular reduction technique coupled with standard multiplication. Standard modular reduction is much more costly than standard multiplication. Fast modular reduction (Montgomery`s method) reduces the reduction cost to approximately that of a standard multiply. Of the fast multiplication techniques, the redundant number system technique (RNS) is one of the most popular. It is simple, converting a large convolution (multiply) into many smaller independent ones. Not only do redundant number systems increase speed, but the independent parts allow for parallelization. RNS form implies working modulo another constant. Depending on the relationship between these two constants; reduction OR division may be possible, but not both. This paper describes a new technique using ideas from both Montgomery`s method and RNS. It avoids the formula problem and allows fast reduction and multiplication. Since RNS form is used throughout, it also allows the entire process to be parallelized.

  17. Extracting the three- and four-graviton vertices from binary pulsars and coalescing binaries

    SciTech Connect (OSTI)

    Cannella, Umberto; Foffa, Stefano; Maggiore, Michele; Sanctuary, Hillary; Sturani, Riccardo

    2009-12-15

    Using a formulation of the post-Newtonian expansion in terms of Feynman graphs, we discuss how various tests of general relativity (GR) can be translated into measurement of the three- and four-graviton vertices. In problems involving only the conservative dynamics of a system, a deviation of the three-graviton vertex from the GR prediction is equivalent, to lowest order, to the introduction of the parameter {beta}{sub PPN} in the parametrized post-Newtonian formalism, and its strongest bound comes from lunar laser ranging, which measures it at the 0.02% level. Deviation of the three-graviton vertex from the GR prediction, however, also affects the radiative sector of the theory. We show that the timing of the Hulse-Taylor binary pulsar provides a bound on the deviation of the three-graviton vertex from the GR prediction at the 0.1% level. For coalescing binaries at interferometers we find that, because of degeneracies with other parameters in the template such as mass and spin, the effects of modified three- and four-graviton vertices is just to induce an error in the determination of these parameters and, at least in the restricted PN approximation, it is not possible to use coalescing binaries for constraining deviations of the vertices from the GR prediction.

  18. ON THE RARITY OF X-RAY BINARIES WITH NAKED HELIUM DONORS

    SciTech Connect (OSTI)

    Linden, T.; Valsecchi, F.; Kalogera, V.

    2012-04-01

    The paucity of known high-mass X-ray binaries (HMXBs) with naked He donor stars (hereafter He star) in the Galaxy has been noted over the years as a surprising fact, given the significant number of Galactic HMXBs containing H-rich donors, which are expected to be their progenitors. This contrast has further sharpened in light of recent observations uncovering a preponderance of HMXBs hosting loosely bound Be donors orbiting neutron stars (NSs), which would be expected to naturally evolve into He-HMXBs through dynamical mass transfer onto the NS and a common-envelope (CE) phase. Hence, reconciling the large population of Be-HMXBs with the observation of only one He-HMXB can help constrain the dynamics of CE physics. Here, we use detailed stellar structure and evolution models and show that binary mergers of HMXBs during CE events must be common in order to resolve the tension between these observed populations. We find that, quantitatively, this scenario remains consistent with the typically adopted energy parameterization of CE evolution, yielding expected populations which are not at odds with current observations. However, future observations which better constrain the underlying population of loosely bound O/B-NS binaries are likely to place significant constraints on the efficiency of CE ejection.

  19. KOI-54: THE KEPLER DISCOVERY OF TIDALLY EXCITED PULSATIONS AND BRIGHTENINGS IN A HIGHLY ECCENTRIC BINARY

    SciTech Connect (OSTI)

    Welsh, William F.; Orosz, Jerome A.; Aerts, Conny; Zima, Wolfgang; Brown, Timothy M.; Brugamyer, Erik; Cochran, William D.; Gilliland, Ronald L.; Guzik, Joyce Ann; Kurtz, D. W.; Latham, David W.; Quinn, Samuel N.; Marcy, Geoffrey W.; Allen, Christopher; Bryson, Steve; Caldwell, Douglas A.; Howell, Steve B.; Gautier, Thomas N.

    2011-11-01

    Kepler observations of the star HD 187091 (KIC 8112039, hereafter KOI-54) revealed a remarkable light curve exhibiting sharp periodic brightening events every 41.8 days with a superimposed set of oscillations forming a beating pattern in phase with the brightenings. Spectroscopic observations revealed that this is a binary star with a highly eccentric orbit, e = 0.83. We are able to match the Kepler light curve and radial velocities with a nearly face-on (i = 5.{sup 0}5) binary star model in which the brightening events are caused by tidal distortion and irradiation of nearly identical A stars during their close periastron passage. The two dominant oscillations in the light curve, responsible for the beating pattern, have frequencies that are the 91st and 90th harmonic of the orbital frequency. The power spectrum of the light curve, after removing the binary star brightening component, reveals a large number of pulsations, 30 of which have a signal-to-noise ratio {approx}>7. Nearly all of these pulsations have frequencies that are either integer multiples of the orbital frequency or are tidally split multiples of the orbital frequency. This pattern of frequencies unambiguously establishes the pulsations as resonances between the dynamic tides at periastron and the free oscillation modes of one or both of the stars. KOI-54 is only the fourth star to show such a phenomenon and is by far the richest in terms of excited modes.

  20. New Hampshire Natural Gas Number of Commercial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Commercial Consumers (Number of Elements) New Hampshire Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  1. New Hampshire Natural Gas Number of Industrial Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Industrial Consumers (Number of Elements) New Hampshire Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  2. New Hampshire Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) New Hampshire Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  3. Virginia Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) Virginia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  4. Utah Natural Gas Number of Industrial Consumers (Number of Elements...

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

    Industrial Consumers (Number of Elements) Utah Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 ...

  5. Wisconsin Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) Wisconsin Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  6. Virginia Natural Gas Number of Commercial Consumers (Number of...

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

    Commercial Consumers (Number of Elements) Virginia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  7. Utah Natural Gas Number of Residential Consumers (Number of Elements...

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

    Residential Consumers (Number of Elements) Utah Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  8. Vermont Natural Gas Number of Residential Consumers (Number of...

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

    Residential Consumers (Number of Elements) Vermont Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  9. Utah Natural Gas Number of Commercial Consumers (Number of Elements...

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

    Commercial Consumers (Number of Elements) Utah Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 ...

  10. Virginia Natural Gas Number of Industrial Consumers (Number of...

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

    Industrial Consumers (Number of Elements) Virginia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  11. West Virginia Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) West Virginia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  12. Wisconsin Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) Wisconsin Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  13. Vermont Natural Gas Number of Commercial Consumers (Number of...

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

    Commercial Consumers (Number of Elements) Vermont Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  14. West Virginia Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) West Virginia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  15. Washington Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) Washington Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  16. Washington Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) Washington Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  17. Washington Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) Washington Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  18. Wisconsin Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) Wisconsin Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  19. Vermont Natural Gas Number of Industrial Consumers (Number of...

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

    Industrial Consumers (Number of Elements) Vermont Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  20. West Virginia Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) West Virginia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  1. New York Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) New York Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  2. New Mexico Natural Gas Number of Residential Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Residential Consumers (Number of Elements) New Mexico Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  3. New Jersey Natural Gas Number of Residential Consumers (Number...

    Gasoline and Diesel Fuel Update (EIA)

    Residential Consumers (Number of Elements) New Jersey Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  4. New Mexico Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) New Mexico Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  5. North Carolina Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) North Carolina Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  6. North Carolina Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) North Carolina Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  7. North Dakota Natural Gas Number of Industrial Consumers (Number...

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

    Industrial Consumers (Number of Elements) North Dakota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  8. North Dakota Natural Gas Number of Residential Consumers (Number...

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

    Residential Consumers (Number of Elements) North Dakota Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  9. North Carolina Natural Gas Number of Commercial Consumers (Number...

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

    Commercial Consumers (Number of Elements) North Carolina Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  10. Project Profile: Binary Metal Chalcogenides for High Temperature Thermal

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

    Storage (SuNLaMP) | Department of Energy Project Profile: Binary Metal Chalcogenides for High Temperature Thermal Storage (SuNLaMP) Project Profile: Binary Metal Chalcogenides for High Temperature Thermal Storage (SuNLaMP) Funding Program: SuNLaMP SunShot Subprogram: CSP Location: Los Alamos National Laboratory, Los Alamos, NM SunShot Award Amount: $3,450,000 Under this project, researchers are developing a thermochemical energy storage system that uses binary metal chalcogenides in a

  11. MULTIPLE INPUT BINARY ADDER EMPLOYING MAGNETIC DRUM DIGITAL COMPUTING APPARATUS

    DOE Patents [OSTI]

    Cooke-Yarborough, E.H.

    1960-12-01

    A digital computing apparatus is described for adding a plurality of multi-digit binary numbers. The apparatus comprises a rotating magnetic drum, a recording head, first and second reading heads disposed adjacent to the first and second recording tracks, and a series of timing signals recorded on the first track. A series of N groups of digit-representing signals is delivered to the recording head at time intervals corresponding to the timing signals, each group consisting of digits of the same significance in the numbers, and the signal series is recorded on the second track of the drum in synchronism with the timing signals on the first track. The multistage registers are stepped cyclically through all positions, and each of the multistage registers is coupled to the control lead of a separate gate circuit to open the corresponding gate at only one selected position in each cycle. One of the gates has its input coupled to the bistable element to receive the sum digit, and the output lead of this gate is coupled to the recording device. The inputs of the other gates receive the digits to be added from the second reading head, and the outputs of these gates are coupled to the adding register. A phase-setting pulse source is connected to each of the multistage registers individually to step the multistage registers to different initial positions in the cycle, and the phase-setting pulse source is actuated each N time interval to shift a sum digit to the bistable element, where the multistage register coupled to bistable element is operated by the phase- setting pulse source to that position in its cycle N steps before opening the first gate, so that this gate opens in synchronism with each of the shifts to pass the sum digits to the recording head.

  12. Terra-Gen Power and TAS Celebrate Innovative Binary Geothermal...

    Open Energy Info (EERE)

    Terra-Gen Power and TAS Celebrate Innovative Binary Geothermal Technology Jump to: navigation, search OpenEI Reference LibraryAdd to library Web Site: Terra-Gen Power and TAS...

  13. Properties OF M31. V. 298 eclipsing binaries from PAndromeda

    SciTech Connect (OSTI)

    Lee, C.-H.; Koppenhoefer, J.; Seitz, S.; Bender, R.; Riffeser, A.; Kodric, M.; Hopp, U.; Snigula, J.; Gssl, C.; Kudritzki, R.-P.; Burgett, W.; Chambers, K.; Hodapp, K.; Kaiser, N.; Waters, C.

    2014-12-10

    The goal of this work is to conduct a photometric study of eclipsing binaries in M31. We apply a modified box-fitting algorithm to search for eclipsing binary candidates and determine their period. We classify these candidates into detached, semi-detached, and contact systems using the Fourier decomposition method. We cross-match the position of our detached candidates with the photometry from Local Group Survey and select 13 candidates brighter than 20.5 mag in V. The relative physical parameters of these detached candidates are further characterized with the Detached Eclipsing Binary Light curve fitter (DEBiL) by Devor. We will follow up the detached eclipsing binaries spectroscopically and determine the distance to M31.

  14. Hydrodynamic 'memory' of binary fluid mixtures

    SciTech Connect (OSTI)

    Kalashnik, M. V.; Ingel, L. Kh.

    2006-07-15

    A theoretical analysis is presented of hydrostatic adjustment in a two-component fluid system, such as seawater stratified with respect to temperature and salinity. Both linear approximation and nonlinear problem are investigated. It is shown that scenarios of relaxation to a hydrostatically balanced state in binary fluid mixtures may substantially differ from hydrostatic adjustment in fluids that can be stratified only with respect to temperature. In particular, inviscid two-component fluids have 'memory': a horizontally nonuniform disturbance in the initial temperature or salinity distribution does not vanish even at the final stage, transforming into a persistent thermohaline 'trace.' Despite stability of density stratification and convective stability of the fluid system by all known criteria, an initial temperature disturbance may not decay and may even increase in amplitude. Moreover, its sign may change (depending on the relative contributions of temperature and salinity to stable background density stratification). Hydrostatic adjustment may involve development of discontinuous distributions from smooth initial temperature or concentration distributions. These properties of two-component fluids explain, in particular, the occurrence of persistent horizontally or vertically nonuniform temperature and salinity distributions in the ocean, including discontinuous ones.

  15. Tailored Working Fluids for Enhanced Binary Geothermal Power Plants |

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

    Department of Energy Tailored Working Fluids for Enhanced Binary Geothermal Power Plants Tailored Working Fluids for Enhanced Binary Geothermal Power Plants DOE Geothermal Program Peer Review 2010 - Presentation. Project Objective: To improve the utilization of available energy in geothermal resources and increase the energy conversion efficiency of systems employed by a) tailoring the subcritical and/or supercritical glide of enhanced working fluids to best match thermal resources, and b)

  16. MICROLENSING BINARIES DISCOVERED THROUGH HIGH-MAGNIFICATION CHANNEL

    SciTech Connect (OSTI)

    Shin, I.-G.; Choi, J.-Y.; Park, S.-Y.; Han, C.; Gould, A.; Gaudi, B. S.; Sumi, T.; Udalski, A.; Beaulieu, J.-P.; Dominik, M.; Allen, W.; Bos, M.; Christie, G. W.; Depoy, D. L.; Dong, S.; Drummond, J.; Gal-Yam, A.; Hung, L.-W.; Janczak, J.; Kaspi, S.; Collaboration: muFUN Collaboration; MOA Collaboration; OGLE Collaboration; PLANET Collaboration; RoboNet Collaboration; MiNDSTEp Consortium; and others

    2012-02-20

    Microlensing can provide a useful tool to probe binary distributions down to low-mass limits of binary companions. In this paper, we analyze the light curves of eight binary-lensing events detected through the channel of high-magnification events during the seasons from 2007 to 2010. The perturbations, which are confined near the peak of the light curves, can be easily distinguished from the central perturbations caused by planets. However, the degeneracy between close and wide binary solutions cannot be resolved with a 3{sigma} confidence level for three events, implying that the degeneracy would be an important obstacle in studying binary distributions. The dependence of the degeneracy on the lensing parameters is consistent with a theoretical prediction that the degeneracy becomes severe as the binary separation and the mass ratio deviate from the values of resonant caustics. The measured mass ratio of the event OGLE-2008-BLG-510/MOA-2008-BLG-369 is q {approx} 0.1, making the companion of the lens a strong brown dwarf candidate.

  17. Molecular Design of Branched and Binary Molecules at Ordered Interfaces

    SciTech Connect (OSTI)

    Kirsten Larson Genson

    2005-12-27

    This study examined five different branched molecular architectures to discern the effect of design on the ability of molecules to form ordered structures at interfaces. Photochromic monodendrons formed kinked packing structures at the air-water interface due to the cross-sectional area mismatch created by varying number of alkyl tails and the hydrophilic polar head group. The lower generations formed orthorhombic unit cell with long range ordering despite the alkyl tails tilted to a large degree. Favorable interactions between liquid crystalline terminal groups and the underlying substrate were observed to compel a flexible carbosilane dendrimer core to form a compressed elliptical conformation which packed stagger within lamellae domains with limited short range ordering. A twelve arm binary star polymer was observed to form two dimensional micelles at the air-water interface attributed to the higher polystyrene block composition. Linear rod-coil molecules formed a multitude of packing structures at the air-water interface due to the varying composition. Tree-like rod-coil molecules demonstrated the ability to form one-dimensional structures at the air-water interface and at the air-solvent interface caused by the preferential ordering of the rigid rod cores. The role of molecular architecture and composition was examined and the influence chemically competing fragments was shown to exert on the packing structure. The amphiphilic balance of the different molecular series exhibited control on the ordering behavior at the air-water interface and within bulk structures. The shell nature and tail type was determined to dictate the preferential ordering structure and molecular reorganization at interfaces with the core nature effect secondary.

  18. Number

    Office of Legacy Management (LM)

    engaged in the production of thorium compounds. The purpose of the trip vas to: l 1. Learn the type of chemical processes employed in the thorium industry (thorium nitrate). 2. ...

  19. DISTRIBUTION OF HIGH-MASS X-RAY BINARIES IN THE MILKY WAY

    SciTech Connect (OSTI)

    Coleiro, Alexis; Chaty, Sylvain E-mail: chaty@cea.fr

    2013-02-20

    Observations of the high-energy sky, particularly with the INTEGRAL satellite, have quadrupled the number of supergiant X-ray binaries observed in the Galaxy and revealed new populations of previously hidden high-mass X-ray binaries (HMXBs), raising new questions about their formation and evolution. The number of detected HMXBs of different types is now high enough to allow us to carry out a statistical analysis of their distribution in the Milky Way. For the first time, we derive the distance and absorption of a sample of HMXBs using a spectral energy distribution fitting procedure, and we examine the correlation with the distribution of star-forming complexes (SFCs) in the Galaxy. We show that HMXBs are clustered with SFCs with a typical cluster size of 0.3 {+-} 0.05 kpc and a characteristic distance between clusters of 1.7 {+-} 0.3 kpc. Furthermore, we present an investigation of the expected offset between the position of spiral arms and HMXBs, allowing us to constrain age and migration distance due to supernova kick for 13 sources. These new methods will allow us to assess the influence of the environment on these high-energy objects with unprecedented reliability.

  20. Alaska Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Alaska Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 10 11 8 1990's 8 8 10 11 11 9 202 7 7 9 2000's 9 8 9 9 10 12 11 11 6 3 2010's 3 5 3 3 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring Pages: Number of Natural

  1. Hawaii Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Hawaii Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 27 26 29 2000's 28 28 29 29 29 28 26 27 27 25 2010's 24 24 22 22 23 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring Pages: Number of Natural Gas Industrial

  2. Determining the Porosity and Saturated Hydraulic Conductivity of Binary Mixtures

    SciTech Connect (OSTI)

    Zhang, Z. F.; Ward, Anderson L.; Keller, Jason M.

    2009-09-27

    Gravels and coarse sands make up significant portions of some environmentally important sediments, while the hydraulic properties of the sediments are typically obtained in the laboratory using only the fine fraction (e.g., <2 mm or 4.75 mm). Researchers have found that the content of gravel has significant impacts on the hydraulic properties of the bulk soils. Laboratory experiments were conducted to measure the porosity and the saturated hydraulic conductivity of binary mixtures with different fractions of coarse and fine components. We proposed a mixing-coefficient model to estimate the porosity and a power-averaging method to determine the effective particle diameter and further to predict the saturated hydraulic conductivity of binary mixtures. The proposed methods could well estimate the porosity and saturated hydraulic conductivity of the binary mixtures for the full range of gravel contents and was successfully applied to two data sets in the literature.

  3. Optical analogue of relativistic Dirac solitons in binary waveguide arrays

    SciTech Connect (OSTI)

    Tran, Truong X.; Longhi, Stefano; Biancalana, Fabio; School of Engineering and Physical Sciences, Heriot-Watt University, EH14 4AS Edinburgh

    2014-01-15

    We study analytically and numerically an optical analogue of Dirac solitons in binary waveguide arrays in the presence of Kerr nonlinearity. Pseudo-relativistic soliton solutions of the coupled-mode equations describing dynamics in the array are analytically derived. We demonstrate that with the found soliton solutions, the coupled mode equations can be converted into the nonlinear relativistic 1D Dirac equation. This paves the way for using binary waveguide arrays as a classical simulator of quantum nonlinear effects arising from the Dirac equation, something that is thought to be impossible to achieve in conventional (i.e. linear) quantum field theory. -- Highlights: •An optical analogue of Dirac solitons in nonlinear binary waveguide arrays is suggested. •Analytical solutions to pseudo-relativistic solitons are presented. •A correspondence of optical coupled-mode equations with the nonlinear relativistic Dirac equation is established.

  4. Higher-order Dirac solitons in binary waveguide arrays

    SciTech Connect (OSTI)

    Tran, Truong X.; Duong, Dũng C.

    2015-10-15

    We study optical analogues of higher-order Dirac solitons (HODSs) in binary waveguide arrays. Like higher-order solitons obtained from the well-known nonlinear Schrödinger equation governing the pulse propagation in an optical fiber, these HODSs have amplitude profiles which are numerically shown to be periodic over large propagation distances. At the same time, HODSs possess some unique features. Firstly, the period of a HODS depends on its order parameter. Secondly, the discrete nature in binary waveguide arrays imposes the upper limit on the order parameter of HODSs. Thirdly, the order parameter of HODSs can vary continuously in a certain range. - Highlights: • Higher-order Dirac solitons in nonlinear binary waveguide arrays are numerically demonstrated. • Amplitude profiles of higher-order Dirac solitons are periodic during propagation. • The period of higher-order Dirac solitons decreases when the soliton order increases.

  5. Photometric study of the pulsating, eclipsing binary OO DRA

    SciTech Connect (OSTI)

    Zhang, X. B.; Deng, L. C.; Tian, J. F.; Wang, K.; Yan, Z. Z.; Luo, C. Q.; Sun, J. J.; Liu, Q. L.; Xin, H. Q.; Zhou, Q.; Luo, Z. Q.

    2014-12-01

    We present a comprehensive photometric study of the pulsating, eclipsing binary OO Dra. Simultaneous B- and V-band photometry of the star was carried out on 14 nights. A revised orbital period and a new ephemeris were derived from the data. The first photometric solution of the binary system and the physical parameters of the component stars are determined. They reveal that OO Dra could be a detached system with a less-massive secondary component nearly filling its Roche lobe. By subtracting the eclipsing light changes from the data, we obtained the intrinsic pulsating light curves of the hotter, massive primary component. A frequency analysis of the residual light yields two confident pulsation modes in both B- and V-band data with the dominant frequency detected at 41.865 c/d. A brief discussion concerning the evolutionary status and the pulsation nature of the binary system is finally given.

  6. Binary fish passage models for uniform and nonuniform flows

    SciTech Connect (OSTI)

    Neary, Vincent S

    2011-01-01

    Binary fish passage models are considered by many fisheries managers to be the best 21 available practice for culvert inventory assessments and for fishway and barrier design. 22 Misunderstandings between different binary passage modeling approaches often arise, 23 however, due to differences in terminology, application and presentation. In this paper 24 one-dimensional binary fish passage models are reviewed and refined to clarify their 25 origins and applications. For uniform flow, a simple exhaustion-threshold (ET) model 26 equation is derived that predicts the flow speed threshold in a fishway or velocity barrier 27 that causes exhaustion at a given maximum distance of ascent. Flow speeds at or above 28 the threshold predict failure to pass (exclusion). Flow speeds below the threshold predict 29 passage. The binary ET model is therefore intuitive and easily applied to predict passage 30 or exclusion. It is also shown to be consistent with the distance-maximizing model. The 31 ET model s limitation to uniform flow is addressed by deriving a passage model that 32 accounts for nonuniform flow conditions more commonly found in the field, including 33 backwater profiles and drawdown curves. Comparison of these models with 34 experimental observations of volitional passage for Gambusia affinis in uniform and 35 nonuniform flows indicates reasonable prediction of binary outcomes (passage or 36 exclusion) if the flow speed is not near the threshold flow velocity. More research is 37 needed on fish behavior, passage strategies under nonuniform flow regimes and 38 stochastic methods that account for individual differences in swimming performance at or 39 near the threshold flow speed. Future experiments should track and measure ground 40 speeds of ascending fish to test nonuniform flow passage strategies and to improve model 41 predictions. Stochastic models, such as Monte-Carlo techniques, that account for 42 different passage performance among individuals and allow

  7. COMPACT BINARY PROGENITORS OF SHORT GAMMA-RAY BURSTS

    SciTech Connect (OSTI)

    Giacomazzo, Bruno; Perna, Rosalba; Rezzolla, Luciano; Troja, Eleonora; Lazzati, Davide

    2013-01-10

    In recent years, detailed observations and accurate numerical simulations have provided support to the idea that mergers of compact binaries containing either two neutron stars (NSs) or an NS and a black hole (BH) may constitute the central engine of short gamma-ray bursts (SGRBs). The merger of such compact binaries is expected to lead to the production of a spinning BH surrounded by an accreting torus. Several mechanisms can extract energy from this system and power the SGRBs. Here we connect observations and numerical simulations of compact binary mergers, and use the current sample of SGRBs with measured energies to constrain the mass of their powering tori. By comparing the masses of the tori with the results of fully general-relativistic simulations, we are able to infer the properties of the binary progenitors that yield SGRBs. By assuming a constant efficiency in converting torus mass into jet energy, {epsilon}{sub jet} = 10%, we find that most of the tori have masses smaller than 0.01 M{sub Sun }, favoring 'high-mass' binary NSs mergers, i.e., binaries with total masses {approx}> 1.5 the maximum mass of an isolated NS. This has important consequences for the gravitational wave signals that may be detected in association with SGRBs, since 'high-mass' systems do not form a long-lived hypermassive NS after the merger. While NS-BH systems cannot be excluded to be the engine of at least some of the SGRBs, the BH would need to have an initial spin of {approx}0.9 or higher.

  8. BINARY QUASARS IN THE SLOAN DIGITAL SKY SURVEY: EVIDENCE FOR EXCESS CLUSTERING ON SMALL SCALES

    SciTech Connect (OSTI)

    Hennawi, J F; Strauss, M A; Oguri, M; Inada, N; Richards, G T; Pindor, B; Schneider, D P; Becker, R H; Gregg, M D; Hall, P B; Johnston, D E; Fan, X; Burles, S; Schlegel, D J; Gunn, J E; Lupton, R; Bahcall, N A; Brunner, R J; Brinkman, J

    2005-11-10

    We present a sample of 218 new quasar pairs with proper transverse separations R{sub prop} < 1 h{sup -1} Mpc over the redshift range 0.5 < z < 3.0, discovered from an extensive follow up campaign to find companions around the Sloan Digital Sky Survey and 2dF Quasar Redshift Survey quasars. This sample includes 26 new binary quasars with separations R{sub prop} < 50 h{sup -1} kpc ({theta} < 10''), more than doubling the number of such systems known. We define a statistical sample of binaries selected with homogeneous criteria and compute its selection function, taking into account sources of incompleteness. The first measurement of the quasar correlation function on scales 10 h{sup -1} kpc < R{sub prop} < 400 h{sup -1} kpc is presented. For R{sub prop} {approx}< 40 h{sup -1} kpc, we detect an order of magnitude excess clustering over the expectation from the large scale (R{sub prop} {approx}> 3 h{sup -1} Mpc) quasar correlation function, extrapolated down as a power law to the separations probed by our binaries. The excess grows to {approx}30 at R{sub prop} {approx} 10 h{sup -1} kpc, and provides compelling evidence that the quasar autocorrelation function gets progressively steeper on sub-Mpc scales. This small scale excess can likely be attributed to dissipative interaction events which trigger quasar activity in rich environments. Recent small scale measurements of galaxy clustering and quasar-galaxy clustering are reviewed and discussed in relation to our measurement of small scale quasar clustering.

  9. ARM - Measurement - Particle number concentration

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

    number concentration ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Particle number concentration The number of particles present in any given volume of air. Categories Aerosols Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including those

  10. Total Number of Operable Refineries

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

    Data Series: Total Number of Operable Refineries Number of Operating Refineries Number of Idle Refineries Atmospheric Crude Oil Distillation Operable Capacity (B/CD) Atmospheric Crude Oil Distillation Operating Capacity (B/CD) Atmospheric Crude Oil Distillation Idle Capacity (B/CD) Atmospheric Crude Oil Distillation Operable Capacity (B/SD) Atmospheric Crude Oil Distillation Operating Capacity (B/SD) Atmospheric Crude Oil Distillation Idle Capacity (B/SD) Vacuum Distillation Downstream Charge

  11. Compendium of Experimental Cetane Numbers

    SciTech Connect (OSTI)

    Yanowitz, J.; Ratcliff, M. A.; McCormick, R. L.; Taylor, J. D.; Murphy, M. J.

    2014-08-01

    This report is an updated version of the 2004 Compendium of Experimental Cetane Number Data and presents a compilation of measured cetane numbers for pure chemical compounds. It includes all available single compound cetane number data found in the scientific literature up until March 2014 as well as a number of unpublished values, most measured over the past decade at the National Renewable Energy Laboratory. This Compendium contains cetane values for 389 pure compounds, including 189 hydrocarbons and 201 oxygenates. More than 250 individual measurements are new to this version of the Compendium. For many compounds, numerous measurements are included, often collected by different researchers using different methods. Cetane number is a relative ranking of a fuel's autoignition characteristics for use in compression ignition engines; it is based on the amount of time between fuel injection and ignition, also known as ignition delay. The cetane number is typically measured either in a single-cylinder engine or a constant volume combustion chamber. Values in the previous Compendium derived from octane numbers have been removed, and replaced with a brief analysis of the correlation between cetane numbers and octane numbers. The discussion on the accuracy and precision of the most commonly used methods for measuring cetane has been expanded and the data has been annotated extensively to provide additional information that will help the reader judge the relative reliability of individual results.

  12. Measuring tides and binary parameters from gravitational wave data and eclipsing timings of detached white dwarf binaries

    SciTech Connect (OSTI)

    Shah, Sweta; Nelemans, Gijs

    2014-08-20

    The discovery of the most compact detached white dwarf (WD) binary SDSS J065133.33+284423.3 has been discussed in terms of probing the tidal effects in WDs. This system is also a verification source for the space-based gravitational wave (GW) detector, eLISA, or the evolved Laser Interferometer Space Antenna, which will observe short-period compact Galactic binaries with P {sub orb} ≲ 5 hr. We address the prospects of performing tidal studies using eLISA binaries by showing the fractional uncertainties in the orbital decay rate, f-dot , and the rate of that decay, f{sup ¨} expected from both the GW and electromagnetic (EM) data for some of the high-f binaries. We find that f-dot and f{sup ¨} can be measured using GW data only for the most massive WD binaries observed at high frequencies. From timing the eclipses for ∼10 yr, we find that f-dot can be known to ∼0.1% for J0651. We find that from GW data alone, measuring the effects of tides in binaries is (almost) impossible. We also investigate the improvement in the knowledge of the binary parameters by combining the GW amplitude and inclination with EM data with and without f-dot . In our previous work, we found that EM data on distance constrained the 2σ uncertainty in chirp mass to 15%-25% whereas adding f-dot reduces it to 0.11%. EM data on f-dot also constrain the 2σ uncertainty in distance to 35%-19%. EM data on primary mass constrain the secondary mass m {sub 2} to factors of two to ∼40% whereas adding f-dot reduces this to 25%. Finally, using single-line spectroscopic data constrains 2σ uncertainties in both the m {sub 2}, d to factors of two to ∼40%. Adding EM data on f-dot reduces these 2σ uncertainties to ≤25% and 6%-19%, respectively. Thus we find that EM measurements of f-dot and radial velocity are valuable in constraining eLISA binary parameters.

  13. THE PHASES DIFFERENTIAL ASTROMETRY DATA ARCHIVE. II. UPDATED BINARY STAR ORBITS AND A LONG PERIOD ECLIPSING BINARY

    SciTech Connect (OSTI)

    Muterspaugh, Matthew W.; O'Connell, J.; Hartkopf, William I.; Lane, Benjamin F.; Williamson, M.; Kulkarni, S. R.; Konacki, Maciej; Burke, Bernard F.; Colavita, M. M.; Shao, M.; Wiktorowicz, Sloane J. E-mail: wih@usno.navy.mi E-mail: maciej@ncac.torun.p

    2010-12-15

    Differential astrometry measurements from the Palomar High-precision Astrometric Search for Exoplanet Systems have been combined with lower precision single-aperture measurements covering a much longer timespan (from eyepiece measurements, speckle interferometry, and adaptive optics) to determine improved visual orbits for 20 binary stars. In some cases, radial velocity observations exist to constrain the full three-dimensional orbit and determine component masses. The visual orbit of one of these binaries-{alpha} Com (HD 114378)-shows that the system is likely to have eclipses, despite its very long period of 26 years. The next eclipse is predicted to be within a week of 2015 January 24.

  14. Maine Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Maine Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 73 73 74 1990's 80 81 80 66 89 74 87 81 110 108 2000's 178 233 66 65 69 69 73 76 82 85 2010's 94 102 108 120 126 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016 Referring

  15. Montana Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Montana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 435 435 428 1990's 457 452 459 462 453 463 466 462 454 397 2000's 71 73 439 412 593 716 711 693 693 396 2010's 384 381 372 372 369 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  16. Wyoming Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Wyoming Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 190 200 230 1990's 284 228 244 194 135 126 170 194 317 314 2000's 308 295 877 179 121 127 133 133 155 130 2010's 120 123 127 132 131 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  17. Nevada Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Nevada Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 93 98 100 1990's 100 113 114 117 119 120 121 93 93 109 2000's 90 90 96 97 179 192 207 220 189 192 2010's 184 177 177 195 218 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date: 09/30/2016

  18. Arizona Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Arizona Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 358 344 354 1990's 526 532 532 526 519 530 534 480 514 555 2000's 526 504 488 450 414 425 439 395 383 390 2010's 368 371 379 383 386 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  19. Delaware Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Delaware Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 241 233 235 1990's 240 243 248 249 252 253 250 265 257 264 2000's 297 316 182 184 186 179 170 185 165 112 2010's 114 129 134 138 141 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  20. Florida Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Florida Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 575 552 460 1990's 452 377 388 433 481 515 517 561 574 573 2000's 520 518 451 421 398 432 475 467 449 607 2010's 581 630 507 528 520 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  1. Idaho Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Idaho Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 219 132 64 1990's 62 65 66 75 144 167 183 189 203 200 2000's 217 198 194 191 196 195 192 188 199 187 2010's 184 178 179 183 189 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016 Next Release Date:

  2. Rhode Island Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) Rhode Island Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,158 1,152 1,122 1990's 1,135 1,107 1,096 1,066 1,064 359 363 336 325 302 2000's 317 283 54 236 223 223 245 256 243 260 2010's 249 245 248 271 266 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release

  3. South Dakota Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) South Dakota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 261 267 270 1990's 275 283 319 355 381 396 444 481 464 445 2000's 416 402 533 526 475 542 528 548 598 598 2010's 580 556 574 566 575 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016

  4. Production and Injection data for NV Binary facilities

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

    Mines, Greg

    Excel files are provided with well production and injection data for binary facilities in Nevada. The files contain the data that reported montly to the Nevada Bureau of Mines and Geology (NBMG) by the facility operators. this data has been complied into Excel spreadsheets for each of the facilities given on the NBMG web site.

  5. BINARY STAR ORBITS. IV. ORBITS OF 18 SOUTHERN INTERFEROMETRIC PAIRS

    SciTech Connect (OSTI)

    Mason, Brian D.; Hartkopf, William I.; Tokovinin, Andrei E-mail: wih@usno.navy.mi

    2010-09-15

    First orbits are presented for 3 interferometric pairs and revised solutions for 15 others, based in part on first results from a recently initiated program of speckle interferometric observations of neglected southern binaries. Eight of these systems contain additional components, with multiplicity ranging up to 6.

  6. Dixie Valley Binary Cycle Production Data 2013 YTD

    SciTech Connect (OSTI)

    Lee, Vitaly

    2013-10-18

    Proving the technical and economic feasibility of utilizing the available unused heat to generate additional electric power from a binary power plant from the low-temperature brine at the Dixie Valley Geothermal Power Plant. Monthly data for Jan 2013-September 2013

  7. Coal liquefaction process using pretreatment with a binary solvent mixture

    DOE Patents [OSTI]

    Miller, Robert N.

    1986-01-01

    An improved process for thermal solvent refining or hydroliquefaction of non-anthracitic coal at elevated temperatures under hydrogen pressure in a hydrogen donor solvent comprises pretreating the coal with a binary mixture of an aromatic hydrocarbon and an aliphatic alcohol at a temperature below 300.degree. C. before the hydroliquefaction step. This treatment generally increases both conversion of coal and yields of oil.

  8. Production and Injection data for NV Binary facilities

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

    Mines, Greg

    2013-12-24

    Excel files are provided with well production and injection data for binary facilities in Nevada. The files contain the data that reported montly to the Nevada Bureau of Mines and Geology (NBMG) by the facility operators. this data has been complied into Excel spreadsheets for each of the facilities given on the NBMG web site.

  9. KEPLER ECLIPSING BINARY STARS. III. CLASSIFICATION OF KEPLER ECLIPSING BINARY LIGHT CURVES WITH LOCALLY LINEAR EMBEDDING

    SciTech Connect (OSTI)

    Matijevic, Gal; Prsa, Andrej; Orosz, Jerome A.; Welsh, William F.; Bloemen, Steven; Barclay, Thomas E-mail: andrej.prsa@villanova.edu

    2012-05-15

    We present an automated classification of 2165 Kepler eclipsing binary (EB) light curves that accompanied the second Kepler data release. The light curves are classified using locally linear embedding, a general nonlinear dimensionality reduction tool, into morphology types (detached, semi-detached, overcontact, ellipsoidal). The method, related to a more widely used principal component analysis, produces a lower-dimensional representation of the input data while preserving local geometry and, consequently, the similarity between neighboring data points. We use this property to reduce the dimensionality in a series of steps to a one-dimensional manifold and classify light curves with a single parameter that is a measure of 'detachedness' of the system. This fully automated classification correlates well with the manual determination of morphology from the data release, and also efficiently highlights any misclassified objects. Once a lower-dimensional projection space is defined, the classification of additional light curves runs in a negligible time and the method can therefore be used as a fully automated classifier in pipeline structures. The classifier forms a tier of the Kepler EB pipeline that pre-processes light curves for the artificial intelligence based parameter estimator.

  10. UNDERSTANDING THE EVOLUTION OF CLOSE BINARY SYSTEMS WITH RADIO PULSARS

    SciTech Connect (OSTI)

    Benvenuto, O. G.; De Vito, M. A.

    2014-05-01

    We calculate the evolution of close binary systems (CBSs) formed by a neutron star (behaving as a radio pulsar) and a normal donor star, which evolve either to a helium white dwarf (HeWD) or to ultra-short orbital period systems. We consider X-ray irradiation feedback and evaporation due to radio pulsar irradiation. We show that irradiation feedback leads to cyclic mass transfer episodes, allowing CBSs to be observed in between episodes as binary radio pulsars under conditions in which standard, non-irradiated models predict the occurrence of a low-mass X-ray binary. This behavior accounts for the existence of a family of eclipsing binary systems known as redbacks. We predict that redback companions should almost fill their Roche lobe, as observed in PSR J1723-2837. This state is also possible for systems evolving with larger orbital periods. Therefore, binary radio pulsars with companion star masses usually interpreted as larger than expected to produce HeWDs may also result in such quasi-Roche lobe overflow states, rather than hosting a carbon-oxygen WD. We found that CBSs with initial orbital periods of P{sub i} < 1day evolve into redbacks. Some of them produce low-mass HeWDs, and a subgroup with shorter P{sub i} becomes black widows (BWs). Thus, BWs descend from redbacks, although not all redbacks evolve into BWs. There is mounting observational evidence favoring BW pulsars to be very massive (? 2 M {sub ?}). As they should be redback descendants, redback pulsars should also be very massive, since most of the mass is transferred before this stage.

  11. Departmental Business Instrument Numbering System

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

    2005-01-27

    The Order prescribes the procedures for assigning identifying numbers to all Department of Energy (DOE) and National Nuclear Security Administration (NNSA) business instruments. Cancels DOE O 540.1. Canceled by DOE O 540.1B.

  12. Departmental Business Instrument Numbering System

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

    2000-12-05

    To prescribe procedures for assigning identifying numbers to all Department of Energy (DOE), including the National Nuclear Security Administration, business instruments. Cancels DOE 1331.2B. Canceled by DOE O 540.1A.

  13. Constraints on the binary properties of mid- to late T dwarfs from Hubble space telescope WFC3 observations

    SciTech Connect (OSTI)

    Aberasturi, M.; Solano, E.; Burgasser, A. J.; Mora, A.; Martín, E. L.; Reid, I. N.; Looper, D.

    2014-12-01

    We used Hubble Space Telescope/Wide Field Camera 3 (WFC3) observations of a sample of 26 nearby (≤20 pc) mid- to late T dwarfs to search for cooler companions and measure the multiplicity statistics of brown dwarfs (BDs). Tightly separated companions were searched for using a double point-spread-function-fitting algorithm. We also compared our detection limits based on simulations to other prior T5+ BD binary programs. No new wide or tight companions were identified, which is consistent with the number of known T5+ binary systems and the resolution limits of WFC3. We use our results to add new constraints to the binary fraction (BF) of T-type BDs. Modeling selection effects and adopting previously derived separation and mass ratio distributions, we find an upper limit total BF of <16% and <25% assuming power law and flat mass ratio distributions, respectively, which are consistent with previous results. We also characterize a handful of targets around the L/T transition.

  14. SECULAR EVOLUTION OF BINARIES NEAR MASSIVE BLACK HOLES: FORMATION OF COMPACT BINARIES, MERGER/COLLISION PRODUCTS AND G2-LIKE OBJECTS

    SciTech Connect (OSTI)

    Prodan, Snezana; Antonini, Fabio; Perets, Hagai B. E-mail: antonini@cita.utoronto.ca

    2015-02-01

    Here we discuss the evolution of binaries around massive black holes (MBHs) in nuclear stellar clusters. We focus on their secular evolution due to the perturbation by the MBHs, while simplistically accounting for their collisional evolution. Binaries with highly inclined orbits with respect to their orbits around MBHs are strongly affected by secular processes, which periodically change their eccentricities and inclinations (e.g., Kozai-Lidov cycles). During periapsis approach, dissipative processes such as tidal friction may become highly efficient, and may lead to shrinkage of a binary orbit and even to its merger. Binaries in this environment can therefore significantly change their orbital evolution due to the MBH third-body perturbative effects. Such orbital evolution may impinge on their later stellar evolution. Here we follow the secular dynamics of such binaries and its coupling to tidal evolution, as well as the stellar evolution of such binaries on longer timescales. We find that stellar binaries in the central parts of nuclear stellar clusters (NSCs) are highly likely to evolve into eccentric and/or short-period binaries, and become strongly interacting binaries either on the main sequence (at which point they may even merge), or through their later binary stellar evolution. The central parts of NSCs therefore catalyze the formation and evolution of strongly interacting binaries, and lead to the enhanced formation of blue stragglers, X-ray binaries, gravitational wave sources, and possible supernova progenitors. Induced mergers/collisions may also lead to the formation of G2-like cloud-like objects such as the one recently observed in the Galactic center.

  15. Indiana Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Indiana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 116,571 119,458 122,803 1990's 124,919 128,223 129,973 131,925 134,336 137,162 139,097 140,515 141,307 145,631 2000's 148,411 148,830 150,092 151,586 151,943 159,649 154,322 155,885 157,223 155,615 2010's 156,557 161,293 158,213 158,965 159,596 - = No Data Reported; -- = Not Applicable; NA = Not

  16. Indiana Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Indiana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,497 5,696 6,196 1990's 6,439 6,393 6,358 6,508 6,314 6,250 6,586 6,920 6,635 19,069 2000's 10,866 9,778 10,139 8,913 5,368 5,823 5,350 5,427 5,294 5,190 2010's 5,145 5,338 5,204 5,178 5,098 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  17. Indiana Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Indiana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,250,476 1,275,401 1,306,747 1990's 1,327,772 1,358,640 1,377,023 1,402,770 1,438,483 1,463,640 1,489,647 1,509,142 1,531,914 1,570,253 2000's 1,604,456 1,613,373 1,657,640 1,644,715 1,588,738 1,707,195 1,661,186 1,677,857 1,678,158 1,662,663 2010's 1,669,026 1,707,148 1,673,132 1,681,841 1,693,267

  18. Iowa Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Iowa Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 80,797 81,294 82,549 1990's 83,047 84,387 85,325 86,452 86,918 88,585 89,663 90,643 91,300 92,306 2000's 93,836 95,485 96,496 96,712 97,274 97,767 97,823 97,979 98,144 98,416 2010's 98,396 98,541 99,113 99,017 99,182 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  19. Iowa Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Iowa Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,033 1,937 1,895 1990's 1,883 1,866 1,835 1,903 1,957 1,957 2,066 1,839 1,862 1,797 2000's 1,831 1,830 1,855 1,791 1,746 1,744 1,670 1,651 1,652 1,626 2010's 1,528 1,465 1,469 1,491 1,572 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  20. Iowa Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Iowa Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 690,532 689,655 701,687 1990's 706,842 716,088 729,081 740,722 750,678 760,848 771,109 780,746 790,162 799,015 2000's 812,323 818,313 824,218 832,230 839,415 850,095 858,915 865,553 872,980 875,781 2010's 879,713 883,733 892,123 895,414 900,420 - = No Data Reported; -- = Not Applicable; NA = Not

  1. Kansas Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Kansas Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 82,934 83,810 85,143 1990's 85,539 86,874 86,840 87,735 86,457 88,163 89,168 85,018 89,654 86,003 2000's 87,007 86,592 87,397 88,030 86,640 85,634 85,686 85,376 84,703 84,715 2010's 84,446 84,874 84,673 84,969 85,867 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  2. Kansas Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Kansas Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 4,440 4,314 4,366 1990's 4,357 3,445 3,296 4,369 3,560 3,079 2,988 7,014 10,706 5,861 2000's 8,833 9,341 9,891 9,295 8,955 8,300 8,152 8,327 8,098 7,793 2010's 7,664 7,954 7,970 7,877 7,429 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  3. Kansas Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Kansas Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 725,676 733,101 731,792 1990's 747,081 753,839 762,545 777,658 773,357 797,524 804,213 811,975 841,843 824,803 2000's 833,662 836,486 843,353 850,464 855,272 856,761 862,203 858,304 853,125 855,454 2010's 853,842 854,730 854,800 858,572 861,092 - = No Data Reported; -- = Not Applicable; NA = Not

  4. Kentucky Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Kentucky Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 63,024 63,971 65,041 1990's 67,086 68,461 69,466 71,998 73,562 74,521 76,079 77,693 80,147 80,283 2000's 81,588 81,795 82,757 84,110 84,493 85,243 85,236 85,210 84,985 83,862 2010's 84,707 84,977 85,129 85,999 85,318 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  5. Kentucky Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Kentucky Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,391 1,436 1,443 1990's 1,544 1,587 1,608 1,585 1,621 1,630 1,633 1,698 1,864 1,813 2000's 1,801 1,701 1,785 1,695 1,672 1,698 1,658 1,599 1,585 1,715 2010's 1,742 1,705 1,720 1,767 1,780 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  6. Kentucky Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Kentucky Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 596,320 606,106 614,058 1990's 624,477 633,942 644,281 654,664 668,774 685,481 696,989 713,509 726,960 735,371 2000's 744,816 749,106 756,234 763,290 767,022 770,080 770,171 771,047 753,531 754,761 2010's 758,129 759,584 757,790 761,575 760,131 - = No Data Reported; -- = Not Applicable; NA = Not

  7. Louisiana Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Louisiana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 67,382 66,472 64,114 1990's 62,770 61,574 61,030 62,055 62,184 62,930 62,101 62,270 63,029 62,911 2000's 62,710 62,241 62,247 63,512 60,580 58,409 57,097 57,127 57,066 58,396 2010's 58,562 58,749 63,381 59,147 58,611 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  8. Louisiana Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Louisiana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,617 1,503 1,531 1990's 1,504 1,469 1,452 1,592 1,737 1,383 1,444 1,406 1,380 1,397 2000's 1,318 1,440 1,357 1,291 1,460 1,086 962 945 988 954 2010's 942 920 963 916 883 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  9. Louisiana Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Louisiana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 952,079 946,970 934,472 1990's 934,007 936,423 940,403 941,294 945,387 957,558 945,967 962,786 962,436 961,925 2000's 964,133 952,753 957,048 958,795 940,400 905,857 868,353 879,612 886,084 889,570 2010's 893,400 897,513 963,688 901,635 899,378 - = No Data Reported; -- = Not Applicable; NA = Not

  10. Maine Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Maine Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3,435 3,731 3,986 1990's 4,250 4,455 4,838 4,979 5,297 5,819 6,414 6,606 6,662 6,582 2000's 6,954 6,936 7,375 7,517 7,687 8,178 8,168 8,334 8,491 8,815 2010's 9,084 9,681 10,179 11,415 11,810 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  11. Maine Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Maine Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 12,134 11,933 11,902 1990's 12,000 12,424 13,766 13,880 14,104 14,917 14,982 15,221 15,646 15,247 2000's 17,111 17,302 17,921 18,385 18,707 18,633 18,824 18,921 19,571 20,806 2010's 21,142 22,461 23,555 24,765 27,047 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  12. Maryland Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Maryland Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 51,252 53,045 54,740 1990's 55,576 61,878 62,858 63,767 64,698 66,094 69,991 69,056 67,850 69,301 2000's 70,671 70,691 71,824 72,076 72,809 73,780 74,584 74,856 75,053 75,771 2010's 75,192 75,788 75,799 77,117 77,846 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  13. Maryland Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Maryland Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,222 5,397 5,570 1990's 5,646 520 514 496 516 481 430 479 1,472 536 2000's 329 795 1,434 1,361 1,354 1,325 1,340 1,333 1,225 1,234 2010's 1,255 1,226 1,163 1,173 1,179 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release

  14. Maryland Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Maryland Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 755,294 760,754 767,219 1990's 774,707 782,373 894,677 807,204 824,137 841,772 871,012 890,195 901,455 939,029 2000's 941,384 959,772 978,319 987,863 1,009,455 1,024,955 1,040,941 1,053,948 1,057,521 1,067,807 2010's 1,071,566 1,077,168 1,078,978 1,099,272 1,101,292 - = No Data Reported; -- = Not

  15. Massachusetts Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) Massachusetts Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 84,636 93,005 92,252 1990's 85,775 88,746 85,873 102,187 92,744 104,453 105,889 107,926 108,832 113,177 2000's 117,993 120,984 122,447 123,006 125,107 120,167 126,713 128,965 242,693 153,826 2010's 144,487 138,225 142,825 144,246 139,556 - = No Data Reported; -- = Not Applicable;

  16. Massachusetts Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) Massachusetts Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,626 7,199 13,057 1990's 6,539 5,006 8,723 7,283 8,019 10,447 10,952 11,058 11,245 8,027 2000's 8,794 9,750 9,090 11,272 10,949 12,019 12,456 12,678 36,928 19,208 2010's 12,751 10,721 10,840 11,063 10,946 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  17. Massachusetts Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Massachusetts Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,082,777 1,100,635 1,114,920 1990's 1,118,429 1,127,536 1,137,911 1,155,443 1,179,869 1,180,860 1,188,317 1,204,494 1,212,486 1,232,887 2000's 1,278,781 1,283,008 1,295,952 1,324,715 1,306,142 1,297,508 1,348,848 1,361,470 1,236,480 1,370,353 2010's 1,389,592 1,408,314 1,447,947

  18. Michigan Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Michigan Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 178,469 185,961 191,474 1990's 195,766 198,890 201,561 204,453 207,629 211,817 214,843 222,726 224,506 227,159 2000's 230,558 225,109 247,818 246,123 246,991 253,415 254,923 253,139 252,382 252,017 2010's 249,309 249,456 249,994 250,994 253,127 - = No Data Reported; -- = Not Applicable; NA = Not

  19. Michigan Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Michigan Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 10,885 11,117 11,452 1990's 11,500 11,446 11,460 11,425 11,308 11,454 11,848 12,233 11,888 14,527 2000's 11,384 11,210 10,468 10,378 10,088 10,049 9,885 9,728 10,563 18,186 2010's 9,332 9,088 8,833 8,497 8,156 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  20. Michigan Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Michigan Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,452,554 2,491,149 2,531,304 1990's 2,573,570 2,609,561 2,640,579 2,677,085 2,717,683 2,767,190 2,812,876 2,859,483 2,903,698 2,949,628 2000's 2,999,737 3,011,205 3,110,743 3,140,021 3,161,370 3,187,583 3,193,920 3,188,152 3,172,623 3,169,026 2010's 3,152,468 3,153,895 3,161,033 3,180,349

  1. Minnesota Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Minnesota Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 88,789 90,256 92,916 1990's 95,474 97,388 99,707 93,062 102,857 103,874 105,531 108,686 110,986 114,127 2000's 116,529 119,007 121,751 123,123 125,133 126,310 129,149 128,367 130,847 131,801 2010's 132,163 132,938 134,394 135,557 136,382 - = No Data Reported; -- = Not Applicable; NA = Not Available;

  2. Minnesota Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Minnesota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,585 2,670 2,638 1990's 2,574 2,486 2,515 2,477 2,592 2,531 2,564 2,233 2,188 2,267 2000's 2,025 1,996 2,029 2,074 2,040 1,432 1,257 1,146 1,131 2,039 2010's 2,106 1,770 1,793 1,870 1,878 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  3. Minnesota Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Minnesota Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 872,148 894,380 911,001 1990's 946,107 970,941 998,201 1,074,631 1,049,263 1,080,009 1,103,709 1,134,019 1,161,423 1,190,190 2000's 1,222,397 1,249,748 1,282,751 1,308,143 1,338,061 1,364,237 1,401,362 1,401,623 1,413,162 1,423,703 2010's 1,429,681 1,436,063 1,445,824 1,459,134 1,472,663 - = No

  4. Mississippi Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Mississippi Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 43,362 44,170 44,253 1990's 43,184 43,693 44,313 45,310 43,803 45,444 46,029 47,311 45,345 47,620 2000's 50,913 51,109 50,468 50,928 54,027 54,936 55,741 56,155 55,291 50,713 2010's 50,537 50,636 50,689 50,153 50,238 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  5. Mississippi Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Mississippi Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,312 1,263 1,282 1990's 1,317 1,314 1,327 1,324 1,313 1,298 1,241 1,199 1,165 1,246 2000's 1,199 1,214 1,083 1,161 996 1,205 1,181 1,346 1,132 1,141 2010's 980 982 936 933 943 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  6. Mississippi Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Mississippi Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 370,094 372,238 376,353 1990's 382,251 386,264 392,155 398,472 405,312 415,123 418,442 423,397 415,673 426,352 2000's 434,501 438,069 435,146 438,861 445,212 445,856 437,669 445,043 443,025 437,715 2010's 436,840 442,479 442,840 445,589 444,423 - = No Data Reported; -- = Not

  7. Missouri Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Missouri Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 96,711 97,939 99,721 1990's 105,164 117,675 125,174 125,571 132,378 130,318 133,445 135,553 135,417 133,464 2000's 133,969 135,968 137,924 140,057 141,258 142,148 143,632 142,965 141,529 140,633 2010's 138,670 138,214 144,906 142,495 143,024 - = No Data Reported; -- = Not Applicable; NA = Not

  8. Missouri Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Missouri Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,832 2,880 3,063 1990's 3,140 3,096 2,989 3,040 3,115 3,033 3,408 3,097 3,151 3,152 2000's 3,094 3,085 2,935 3,115 3,600 3,545 3,548 3,511 3,514 3,573 2010's 3,541 3,307 3,692 3,538 3,497 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  9. Missouri Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Missouri Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,180,546 1,194,985 1,208,523 1990's 1,213,305 1,211,342 1,220,203 1,225,921 1,281,007 1,259,102 1,275,465 1,293,032 1,307,563 1,311,865 2000's 1,324,282 1,326,160 1,340,726 1,343,614 1,346,773 1,348,743 1,353,892 1,354,173 1,352,015 1,348,781 2010's 1,348,549 1,342,920 1,389,910 1,357,740

  10. Montana Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Montana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 21,382 22,246 22,219 1990's 23,331 23,185 23,610 24,373 25,349 26,329 26,374 27,457 28,065 28,424 2000's 29,215 29,429 30,250 30,814 31,357 31,304 31,817 32,472 33,008 33,731 2010's 34,002 34,305 34,504 34,909 35,205 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  11. Montana Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Montana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 167,883 171,785 171,156 1990's 174,384 177,726 182,641 188,879 194,357 203,435 205,199 209,806 218,851 222,114 2000's 224,784 226,171 229,015 232,839 236,511 240,554 245,883 247,035 253,122 255,472 2010's 257,322 259,046 259,957 262,122 265,849 - = No Data Reported; -- = Not Applicable; NA = Not

  12. Wyoming Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Wyoming Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 15,342 15,093 14,012 1990's 13,767 14,931 15,064 15,315 15,348 15,580 17,036 15,907 16,171 16,317 2000's 16,366 16,027 16,170 17,164 17,490 17,904 18,016 18,062 19,286 19,843 2010's 19,977 20,146 20,387 20,617 20,894 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  13. Wyoming Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Wyoming Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 113,175 112,126 113,129 1990's 113,598 113,463 114,793 116,027 117,385 119,544 131,910 125,740 127,324 127,750 2000's 129,274 129,897 133,445 135,441 137,434 140,013 142,385 143,644 152,439 153,062 2010's 153,852 155,181 157,226 158,889 160,896 - = No Data Reported; -- = Not Applicable; NA = Not

  14. Nebraska Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Nebraska Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 60,707 61,365 60,377 1990's 60,405 60,947 61,319 60,599 62,045 61,275 61,117 51,661 63,819 53,943 2000's 55,194 55,692 56,560 55,999 57,087 57,389 56,548 55,761 58,160 56,454 2010's 56,246 56,553 56,608 58,005 57,191 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  15. Nebraska Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Nebraska Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 675 684 702 1990's 712 718 696 718 766 2,432 2,234 11,553 10,673 10,342 2000's 10,161 10,504 9,156 9,022 8,463 7,973 7,697 7,668 11,627 7,863 2010's 7,912 7,955 8,160 8,495 8,791 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  16. Nebraska Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Nebraska Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 400,218 403,657 406,723 1990's 407,094 413,354 418,611 413,358 428,201 427,720 439,931 444,970 523,790 460,173 2000's 475,673 476,275 487,332 492,451 497,391 501,279 499,504 494,005 512,013 512,551 2010's 510,776 514,481 515,338 527,397 522,408 - = No Data Reported; -- = Not Applicable; NA = Not

  17. Nevada Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Nevada Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 18,294 18,921 19,924 1990's 20,694 22,124 22,799 23,207 24,521 25,593 26,613 27,629 29,030 30,521 2000's 31,789 32,782 33,877 34,590 35,792 37,093 38,546 40,128 41,098 41,303 2010's 40,801 40,944 41,192 41,710 42,338 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  18. Nevada Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Nevada Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 213,422 219,981 236,237 1990's 256,119 283,307 295,714 305,099 336,353 364,112 393,783 426,221 458,737 490,029 2000's 520,233 550,850 580,319 610,756 648,551 688,058 726,772 750,570 758,315 760,391 2010's 764,435 772,880 782,759 794,150 808,970 - = No Data Reported; -- = Not Applicable; NA = Not

  19. Ohio Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Ohio Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 213,601 219,257 225,347 1990's 233,075 236,519 237,861 240,684 245,190 250,223 259,663 254,991 258,076 266,102 2000's 269,561 269,327 271,160 271,203 272,445 277,767 270,552 272,555 272,899 270,596 2010's 268,346 268,647 267,793 269,081 269,758 - = No Data Reported; -- = Not Applicable; NA = Not

  20. Ohio Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Ohio Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 7,929 8,163 8,356 1990's 8,301 8,479 8,573 8,678 8,655 8,650 8,672 7,779 8,112 8,136 2000's 8,267 8,515 8,111 8,098 7,899 8,328 6,929 6,858 6,806 6,712 2010's 6,571 6,482 6,381 6,554 6,526 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  1. Ohio Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Ohio Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,648,972 2,678,838 2,714,839 1990's 2,766,912 2,801,716 2,826,713 2,867,959 2,921,536 2,967,375 2,994,891 3,041,948 3,050,960 3,111,108 2000's 3,178,840 3,195,584 3,208,466 3,225,908 3,250,068 3,272,307 3,263,062 3,273,791 3,262,716 3,253,184 2010's 3,240,619 3,236,160 3,244,274 3,271,074 3,283,869 -

  2. Oklahoma Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Oklahoma Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 87,824 86,666 86,172 1990's 85,790 86,744 87,120 88,181 87,494 88,358 89,852 90,284 89,711 80,986 2000's 80,558 79,045 80,029 79,733 79,512 78,726 78,745 93,991 94,247 94,314 2010's 92,430 93,903 94,537 95,385 96,004 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  3. Oklahoma Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Oklahoma Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,772 2,689 2,877 1990's 2,889 2,840 2,859 2,912 2,853 2,845 2,843 2,531 3,295 3,040 2000's 2,821 3,403 3,438 3,367 3,283 2,855 2,811 2,822 2,920 2,618 2010's 2,731 2,733 2,872 2,958 3,063 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  4. Oklahoma Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Oklahoma Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 809,171 805,107 806,875 1990's 814,296 824,172 832,677 842,130 845,448 856,604 866,531 872,454 877,236 867,922 2000's 859,951 868,314 875,338 876,420 875,271 880,403 879,589 920,616 923,650 924,745 2010's 914,869 922,240 927,346 931,981 937,237 - = No Data Reported; -- = Not Applicable; NA = Not

  5. Oregon Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Oregon Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 40,967 41,998 43,997 1990's 47,175 55,374 50,251 51,910 53,700 55,409 57,613 60,419 63,085 65,034 2000's 66,893 68,098 69,150 74,515 71,762 73,520 74,683 80,998 76,868 76,893 2010's 77,370 77,822 78,237 79,276 80,480 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  6. Oregon Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Oregon Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 676 1,034 738 1990's 699 787 740 696 765 791 799 704 695 718 2000's 717 821 842 926 907 1,118 1,060 1,136 1,075 1,051 2010's 1,053 1,066 1,076 1,085 1,099 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 08/31/2016

  7. Oregon Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Oregon Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 280,670 288,066 302,156 1990's 326,177 376,166 354,256 371,151 391,845 411,465 433,638 456,960 477,796 502,000 2000's 523,952 542,799 563,744 625,398 595,495 626,685 647,635 664,455 674,421 675,582 2010's 682,737 688,681 693,507 700,211 707,010 - = No Data Reported; -- = Not Applicable; NA = Not

  8. Pennsylvania Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) Pennsylvania Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 166,901 172,615 178,545 1990's 186,772 191,103 193,863 198,299 206,812 209,245 214,340 215,057 216,519 223,732 2000's 228,037 225,911 226,957 227,708 231,051 233,132 231,540 234,597 233,462 233,334 2010's 233,751 233,588 235,049 237,922 239,681 - = No Data Reported; -- = Not

  9. Pennsylvania Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) Pennsylvania Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 6,089 6,070 6,023 1990's 6,238 6,344 6,496 6,407 6,388 6,328 6,441 6,492 6,736 7,080 2000's 6,330 6,159 5,880 5,577 5,726 5,577 5,241 4,868 4,772 4,745 2010's 4,624 5,007 5,066 5,024 5,084 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  10. Pennsylvania Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Pennsylvania Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,237,877 2,271,801 2,291,242 1990's 2,311,795 2,333,377 2,363,575 2,386,249 2,393,053 2,413,715 2,431,909 2,452,524 2,493,639 2,486,704 2000's 2,519,794 2,542,724 2,559,024 2,572,584 2,591,458 2,600,574 2,605,782 2,620,755 2,631,340 2,635,886 2010's 2,646,211 2,667,392 2,678,547

  11. Alabama Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Alabama Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 53 54,306 55,400 56,822 1990's 56,903 57,265 58,068 57,827 60,320 60,902 62,064 65,919 76,467 64,185 2000's 66,193 65,794 65,788 65,297 65,223 65,294 66,337 65,879 65,313 67,674 2010's 68,163 67,696 67,252 67,136 67,806 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  12. Alabama Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Alabama Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2 2,313 2,293 2,380 1990's 2,431 2,523 2,509 2,458 2,477 2,491 2,512 2,496 2,464 2,620 2000's 2,792 2,781 2,730 2,743 2,799 2,787 2,735 2,704 2,757 3,057 2010's 3,039 2,988 3,045 3,143 3,244 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  13. Alabama Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Alabama Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 656 662,217 668,432 683,528 1990's 686,149 700,195 711,043 730,114 744,394 751,890 766,322 781,711 788,464 775,311 2000's 805,689 807,770 806,389 809,754 806,660 809,454 808,801 796,476 792,236 785,005 2010's 778,985 772,892 767,396 765,957 769,418 - = No Data Reported; -- = Not Applicable; NA = Not

  14. Alaska Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Alaska Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 11 11,484 11,649 11,806 1990's 11,921 12,071 12,204 12,359 12,475 12,584 12,732 12,945 13,176 13,409 2000's 13,711 14,002 14,342 14,502 13,999 14,120 14,384 13,408 12,764 13,215 2010's 12,998 13,027 13,133 13,246 13,399 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  15. Alaska Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Alaska Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 66 67,648 68,612 69,540 1990's 70,808 72,565 74,268 75,842 77,670 79,474 81,348 83,596 86,243 88,924 2000's 91,297 93,896 97,077 100,404 104,360 108,401 112,269 115,500 119,039 120,124 2010's 121,166 121,736 122,983 124,411 126,416 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  16. Arizona Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Arizona Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 46 46,702 46,636 46,776 1990's 47,292 53,982 47,781 47,678 48,568 49,145 49,693 50,115 51,712 53,022 2000's 54,056 54,724 56,260 56,082 56,186 56,572 57,091 57,169 57,586 57,191 2010's 56,676 56,547 56,532 56,585 56,649 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  17. Arizona Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Arizona Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 545 567,962 564,195 572,461 1990's 586,866 642,659 604,899 610,337 635,335 661,192 689,597 724,911 764,167 802,469 2000's 846,016 884,789 925,927 957,442 993,885 1,042,662 1,088,574 1,119,266 1,128,264 1,130,047 2010's 1,138,448 1,146,286 1,157,688 1,172,003 1,186,794 - = No Data Reported; -- = Not

  18. Arkansas Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Arkansas Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 60 60,355 61,630 61,848 1990's 61,530 61,731 62,221 62,952 63,821 65,490 67,293 68,413 69,974 71,389 2000's 72,933 71,875 71,530 71,016 70,655 69,990 69,475 69,495 69,144 69,043 2010's 67,987 67,815 68,765 68,791 69,011 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  19. Arkansas Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Arkansas Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1 1,410 1,151 1,412 1990's 1,396 1,367 1,319 1,364 1,417 1,366 1,488 1,336 1,300 1,393 2000's 1,414 1,122 1,407 1,269 1,223 1,120 1,120 1,055 1,104 1,025 2010's 1,079 1,133 990 1,020 1,009 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  20. Arkansas Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Arkansas Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 475 480,839 485,112 491,110 1990's 488,850 495,148 504,722 513,466 521,176 531,182 539,952 544,460 550,017 554,121 2000's 560,055 552,716 553,192 553,211 554,844 555,861 555,905 557,966 556,746 557,355 2010's 549,970 551,795 549,959 549,764 549,034 - = No Data Reported; -- = Not Applicable; NA =

  1. California Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) California Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 413 404,507 407,435 410,231 1990's 415,073 421,278 412,467 411,648 411,140 411,535 408,294 406,803 588,224 416,791 2000's 413,003 416,036 420,690 431,795 432,367 434,899 442,052 446,267 447,160 441,806 2010's 439,572 440,990 442,708 444,342 443,115 - = No Data Reported; -- = Not Applicable; NA =

  2. California Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) California Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 31 44,764 44,680 46,243 1990's 46,048 44,865 40,528 42,748 38,750 38,457 36,613 35,830 36,235 36,435 2000's 35,391 34,893 33,725 34,617 41,487 40,226 38,637 39,134 39,591 38,746 2010's 38,006 37,575 37,686 37,996 37,548 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  3. California Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) California Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 7,626 7,904,858 8,113,034 8,313,776 1990's 8,497,848 8,634,774 8,680,613 8,726,187 8,790,733 8,865,541 8,969,308 9,060,473 9,181,928 9,331,206 2000's 9,370,797 9,603,122 9,726,642 9,803,311 9,957,412 10,124,433 10,329,224 10,439,220 10,515,162 10,510,950 2010's 10,542,584 10,625,190 10,681,916

  4. Colorado Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Colorado Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 108 109,770 110,769 112,004 1990's 112,661 113,945 114,898 115,924 115,994 118,502 121,221 123,580 125,178 129,041 2000's 131,613 134,393 136,489 138,621 138,543 137,513 139,746 141,420 144,719 145,624 2010's 145,460 145,837 145,960 150,145 150,235 - = No Data Reported; -- = Not Applicable; NA = Not

  5. Colorado Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Colorado Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1 896 923 976 1990's 1,018 1,074 1,108 1,032 1,176 1,528 2,099 2,923 3,349 4,727 2000's 4,994 4,729 4,337 4,054 4,175 4,318 4,472 4,592 4,816 5,084 2010's 6,232 6,529 6,906 7,293 7,823 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  6. Colorado Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Colorado Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 925 942,571 955,810 970,512 1990's 983,592 1,002,154 1,022,542 1,044,699 1,073,308 1,108,899 1,147,743 1,183,978 1,223,433 1,265,032 2000's 1,315,619 1,365,413 1,412,923 1,453,974 1,496,876 1,524,813 1,558,911 1,583,945 1,606,602 1,622,434 2010's 1,634,587 1,645,716 1,659,808 1,672,312 1,690,581 -

  7. Connecticut Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Connecticut Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 38 40,886 41,594 43,703 1990's 45,364 45,925 46,859 45,529 45,042 45,935 47,055 48,195 47,110 49,930 2000's 52,384 49,815 49,383 50,691 50,839 52,572 52,982 52,389 53,903 54,510 2010's 54,842 55,028 55,407 55,500 56,591 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  8. Connecticut Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Connecticut Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2 2,709 2,818 2,908 1990's 3,061 2,921 2,923 2,952 3,754 3,705 3,435 3,459 3,441 3,465 2000's 3,683 3,881 3,716 3,625 3,470 3,437 3,393 3,317 3,196 3,138 2010's 3,063 3,062 3,148 4,454 4,217 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  9. Connecticut Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Connecticut Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 400 411,349 417,831 424,036 1990's 428,912 430,078 432,244 427,761 428,157 431,909 433,778 436,119 438,716 442,457 2000's 458,388 458,404 462,574 466,913 469,332 475,221 478,849 482,902 487,320 489,349 2010's 490,185 494,970 504,138 513,492 522,658 - = No Data Reported; -- = Not

  10. Delaware Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Delaware Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 6 6,180 6,566 7,074 1990's 7,485 7,895 8,173 8,409 8,721 9,133 9,518 9,807 10,081 10,441 2000's 9,639 11,075 11,463 11,682 11,921 12,070 12,345 12,576 12,703 12,839 2010's 12,861 12,931 12,997 13,163 13,352 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  11. Delaware Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Delaware Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 81 82,829 84,328 86,428 1990's 88,894 91,467 94,027 96,914 100,431 103,531 106,548 109,400 112,507 115,961 2000's 117,845 122,829 126,418 129,870 133,197 137,115 141,276 145,010 147,541 149,006 2010's 150,458 152,005 153,307 155,627 158,502 - = No Data Reported; -- = Not Applicable; NA = Not

  12. Florida Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Florida Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 41 42,376 43,178 43,802 1990's 43,674 45,012 45,123 47,344 47,851 46,459 47,578 48,251 46,778 50,052 2000's 50,888 53,118 53,794 55,121 55,324 55,479 55,259 57,320 58,125 59,549 2010's 60,854 61,582 63,477 64,772 67,460 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  13. Florida Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Florida Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 442 444,848 446,690 452,544 1990's 457,648 467,221 471,863 484,816 497,777 512,365 521,674 532,790 542,770 556,628 2000's 571,972 590,221 603,690 617,373 639,014 656,069 673,122 682,996 679,265 674,090 2010's 675,551 679,199 686,994 694,210 703,535 - = No Data Reported; -- = Not Applicable; NA = Not

  14. Georgia Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Georgia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 94 98,809 102,277 106,690 1990's 108,295 109,659 111,423 114,889 117,980 120,122 123,200 123,367 126,050 225,020 2000's 128,275 130,373 128,233 129,867 128,923 128,389 127,843 127,832 126,804 127,347 2010's 124,759 123,454 121,243 126,060 122,573 - = No Data Reported; -- = Not Applicable; NA = Not

  15. Georgia Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Georgia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3 3,034 3,144 3,079 1990's 3,153 3,124 3,186 3,302 3,277 3,261 3,310 3,310 3,262 5,580 2000's 3,294 3,330 3,219 3,326 3,161 3,543 3,053 2,913 2,890 2,254 2010's 2,174 2,184 2,112 2,242 2,481 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  16. Georgia Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Georgia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,190 1,237,201 1,275,128 1,308,972 1990's 1,334,935 1,363,723 1,396,860 1,430,626 1,460,141 1,495,992 1,538,458 1,553,948 1,659,730 1,732,865 2000's 1,680,749 1,737,850 1,735,063 1,747,017 1,752,346 1,773,121 1,726,239 1,793,650 1,791,256 1,744,934 2010's 1,740,587 1,740,006 1,739,543 1,805,425

  17. Hawaii Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Hawaii Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,896 2,852 2,842 1990's 2,837 2,786 2,793 3,222 2,805 2,825 2,823 2,783 2,761 2,763 2000's 2,768 2,777 2,781 2,804 2,578 2,572 2,548 2,547 2,540 2,535 2010's 2,551 2,560 2,545 2,627 2,789 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  18. Hawaii Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Hawaii Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 28,502 28,761 28,970 1990's 29,137 29,701 29,805 29,984 30,614 30,492 31,017 30,990 30,918 30,708 2000's 30,751 30,794 30,731 30,473 26,255 26,219 25,982 25,899 25,632 25,466 2010's 25,389 25,305 25,184 26,374 28,919 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  19. Idaho Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Idaho Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 17,482 18,454 18,813 1990's 19,452 20,328 21,145 21,989 22,999 24,150 25,271 26,436 27,697 28,923 2000's 30,018 30,789 31,547 32,274 33,104 33,362 33,625 33,767 37,320 38,245 2010's 38,506 38,912 39,202 39,722 40,229 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  20. Idaho Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Idaho Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 104,824 111,532 113,898 1990's 113,954 126,282 136,121 148,582 162,971 175,320 187,756 200,165 213,786 227,807 2000's 240,399 251,004 261,219 274,481 288,380 301,357 316,915 323,114 336,191 342,277 2010's 346,602 350,871 353,963 359,889 367,394 - = No Data Reported; -- = Not Applicable; NA = Not

  1. Illinois Natural Gas Number of Commercial Consumers (Number of Elements)

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

    Commercial Consumers (Number of Elements) Illinois Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 241,367 278,473 252,791 1990's 257,851 261,107 263,988 268,104 262,308 264,756 265,007 268,841 271,585 274,919 2000's 279,179 278,506 279,838 281,877 273,967 276,763 300,606 296,465 298,418 294,226 2010's 291,395 293,213 297,523 282,743 294,391 - = No Data Reported; -- = Not Applicable; NA = Not

  2. Illinois Natural Gas Number of Industrial Consumers (Number of Elements)

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

    Industrial Consumers (Number of Elements) Illinois Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 19,460 20,015 25,161 1990's 25,991 26,489 27,178 27,807 25,788 25,929 29,493 28,472 28,063 27,605 2000's 27,348 27,421 27,477 26,698 29,187 29,887 26,109 24,000 23,737 23,857 2010's 25,043 23,722 23,390 23,804 23,829 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  3. Illinois Natural Gas Number of Residential Consumers (Number of Elements)

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

    Residential Consumers (Number of Elements) Illinois Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3,170,364 3,180,199 3,248,117 1990's 3,287,091 3,320,285 3,354,679 3,388,983 3,418,052 3,452,975 3,494,545 3,521,707 3,556,736 3,594,071 2000's 3,631,762 3,670,693 3,688,281 3,702,308 3,754,132 3,975,961 3,812,121 3,845,441 3,869,308 3,839,438 2010's 3,842,206 3,855,942 3,878,806 3,838,120

  4. Rhode Island Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) Rhode Island Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 15,128 16,096 16,924 1990's 17,765 18,430 18,607 21,178 21,208 21,472 21,664 21,862 22,136 22,254 2000's 22,592 22,815 23,364 23,270 22,994 23,082 23,150 23,007 23,010 22,988 2010's 23,049 23,177 23,359 23,742 23,934 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  5. Rhode Island Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) Rhode Island Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 180,656 185,861 190,796 1990's 195,100 196,438 197,926 198,563 200,959 202,947 204,259 212,777 208,208 211,097 2000's 214,474 216,781 219,769 221,141 223,669 224,320 225,027 223,589 224,103 224,846 2010's 225,204 225,828 228,487 231,763 233,786 - = No Data Reported; -- = Not

  6. South Carolina Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) South Carolina Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 35,414 37,075 38,856 1990's 39,904 39,999 40,968 42,191 45,487 47,293 48,650 50,817 52,237 53,436 2000's 54,794 55,257 55,608 55,909 56,049 56,974 57,452 57,544 56,317 55,850 2010's 55,853 55,846 55,908 55,997 56,172 - = No Data Reported; -- = Not Applicable; NA = Not Available; W

  7. South Carolina Natural Gas Number of Industrial Consumers (Number of

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

    Elements) Industrial Consumers (Number of Elements) South Carolina Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,256 1,273 1,307 1990's 1,384 1,400 1,568 1,625 1,928 1,802 1,759 1,764 1,728 1,768 2000's 1,715 1,702 1,563 1,574 1,528 1,535 1,528 1,472 1,426 1,358 2010's 1,325 1,329 1,435 1,452 1,426 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  8. South Carolina Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) South Carolina Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 302,321 313,831 327,527 1990's 339,486 344,763 357,818 370,411 416,773 412,259 426,088 443,093 460,141 473,799 2000's 489,340 501,161 508,686 516,362 527,008 541,523 554,953 570,213 561,196 565,774 2010's 570,797 576,594 583,633 593,286 604,743 - = No Data Reported; -- = Not

  9. South Dakota Natural Gas Number of Commercial Consumers (Number of

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

    Elements) Commercial Consumers (Number of Elements) South Dakota Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 12,480 12,438 12,771 1990's 13,443 13,692 14,133 16,523 15,539 16,285 16,880 17,432 17,972 18,453 2000's 19,100 19,378 19,794 20,070 20,457 20,771 21,149 21,502 21,819 22,071 2010's 22,267 22,570 22,955 23,214 23,591 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  10. South Dakota Natural Gas Number of Residential Consumers (Number of

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

    Elements) Residential Consumers (Number of Elements) South Dakota Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 101,468 102,084 103,538 1990's 105,436 107,846 110,291 128,029 119,544 124,152 127,269 130,307 133,095 136,789 2000's 142,075 144,310 147,356 150,725 148,105 157,457 160,481 163,458 165,694 168,096 2010's 169,838 170,877 173,856 176,204 179,042 - = No Data Reported; -- = Not