Sample records for total sky imager

  1. Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed

    E-Print Network [OSTI]

    2011-01-01T23:59:59.000Z

    cross-correlation method (CCM) applied to two consecutive1993). Before applying the CCM, images are projected intoof the sky image area. The CCM finds the position that best

  2. Imaging the High Energy Cosmic Ray Sky

    E-Print Network [OSTI]

    Haviland, David

    Imaging the High Energy Cosmic Ray Sky PETTER HOFVERBERG Licentiate Thesis Stockholm, Sweden 2006 #12;#12;Licentiate Thesis Imaging the High Energy Cosmic Ray Sky Petter Hofverberg Particle

  3. Aerosol effects on red blue ratio of clear sky images, and impact on solar forecasting

    E-Print Network [OSTI]

    Ghonima, Mohamed Sherif

    2011-01-01T23:59:59.000Z

    DIEGO Aerosol effects on Red Blue Ratio of Clear Sky Images,decision image (green: cloudy, blue: clear). The figure wasAerosol effects on Red Blue Ratio of Clear Sky Images, and

  4. A robust algorithm for sky background computation in CCD images

    E-Print Network [OSTI]

    F. Patat

    2003-01-27T23:59:59.000Z

    In this paper we present a non-interactive algorithm to estimate a representative value for the sky background on CCD images. The method we have devised uses the mode as a robust estimator of the background brightness in sub-windows distributed across the input frame. The presence of contaminating objects is detected through the study of the local intensity distribution function and the perturbed areas are rejected using a statistical criterion which was derived from numerical simulations. The technique has been extensively tested on a large amount of images and it is suitable for fully automatic processing of large data volumes. The implementation we discuss here has been optimized for the ESO-FORS1 instrument, but it can be easily generalized to all CCD imagers with a sufficiently large field of view. The algorithm has been successfully used for the UBVRI ESO-Paranal night sky brightness survey (Patat 2003).

  5. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

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

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-08-01T23:59:59.000Z

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. This information is then applied to stitch images together into largermore »views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  6. Session Papers The Whole Sky Imager -A Year of Progress

    E-Print Network [OSTI]

    Buckingham, Michael

    cloud is indicated by white or gray, no cloud (clear or haze) is blue, and the yellow is a preliminary daytime thick cloud fraction and calibrated radiance. Night cloud fraction and daytime thin cloud fraction cloud fraction, cloud morphology, and radiance distribution. The WSI measures the sky radiance

  7. GROUND-BASED CLOUD IMAGES AND SKY RADIANCES IN THE VISIBLE AND NEAR INFRARED REGION FROM

    E-Print Network [OSTI]

    Shields, Janet

    the atmospheric heating rates as well as the amount of solar radiation including biologically effective UV preliminary comparisons with model calculations and cloud cover data both from another type of sky imager data are of specific importance to study the role of clouds on the radiation balance of the earth

  8. Source Catalog Data from FIRST (Faint Images of the Radio Sky at Twenty-Centimeters)

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

    Becker, Robert H.; Helfand, David J.; White, Richard L.; Gregg, Michael D.; Laurent-Muehleisen, Sally A.

    FIRST, Faint Images of the Radio Sky at Twenty-Centimeters, is a project designed to produce the radio equivalent of the Palomar Observatory Sky Survey over 10,000 square degrees of the North Galactic Cap. Using the National Radio Astronomy Observatory's (NRAO) Very Large Array (VLA) in its B-configuration, the Survey acquired 3-minute snapshots covering a hexagonal grid using 2?7 3-MHz frequency channels centered at 1365 and 1435 MHz. The data were edited, self-calibrated, mapped, and CLEANed using an automated pipeline based largely on routines in the Astronomical Image Processing System (AIPS). A final atlas of maps is produced by coadding the twelve images adjacent to each pointing center. Source catalogs with flux densities and size information are generated from the coadded images also. The 2011 catalog is the latest version and has been tested to ensure reliability and completness. The catalog, generated from the 1993 through 2004 images, contains 816,000 sources and covers more than 9000 square degrees. A specialized search interface for the catalog resides at this website, and the catalog is also available as a compressed ASCII file. The user may also view earlier versions of the source catalog. The FIRST survey area was chosen to coincide with that of the Sloan Digital Sky Survey (SDSS); at the m(v)~24 limit of SDSS, ~50% of the optical counterparts to FIRST sources will be detected.

  9. Astronomical Images from the Very Large Array (VLA) FIRST Survey Images from the STScI Archive (Faint Images of the Radio Sky at Twenty-cm)

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

    FIRST, Faint Images of the Radio Sky at Twenty-Centimeters was a project designed to produce the radio equivalent of the Palomar Observatory Sky Survey over 10,000 square degrees of the North Galactic Cap. Using the National Radio Astronomy Observatory (NRAO) Very Large Array (VLA) in its B-configuration, the Survey acquired 3-minute snapshots covering a hexagonal grid. The binary data are available in detailed source catalogs, but the full images themselves, developed through special techniques, are also available for public access. Note that the images are fairly large, typically 1150x1550 pixels. Access to the images is simple through the search interface; the images are also available via anonymous ftp at ftp://archive.stsci.edu/pub/vla_first/data. Another convenient way to obtain images is through the FIRST Cutout Server, which allows an image section to be extracted from the coadded image database at a user-specified position. The cutout server is also linked to the FIRST Search Engine, so that the catalog can be searched for sources of interest and then images can be obtained for those objects. All images taken through 2011 are available through the cutout server at http://third.ucllnl.org/cgi-bin/firstcutout.

  10. all-sky x-ray image: Topics by E-print Network

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

    sky coverage each orbit, and full sky coverage each 50 days, hard x-ray studies of gamma-ray bursts, AGN, galactic transients, x-ray binaries and accretion-powered pulsars can be...

  11. all-sky panorama image: Topics by E-print Network

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

    sky coverage each orbit, and full sky coverage each 50 days, hard x-ray studies of gamma-ray bursts, AGN, galactic transients, x-ray binaries and accretion-powered pulsars can be...

  12. An Improved Photometric Calibration of the Sloan Digital SkySurvey Imaging Data

    SciTech Connect (OSTI)

    Padmanabhan, Nikhil; Schlegel, David J.; Finkbeiner, Douglas P.; Barentine, J.C.; Blanton, Michael R.; Brewington, Howard J.; Gunn, JamesE.; Harvanek, Michael; Hogg, David W.; Ivezic, Zeljko; Johnston, David; Kent, Stephen M.; Kleinman, S.J.; Knapp, Gillian R.; Krzesinski, Jurek; Long, Dan; Neilsen Jr., Eric H.; Nitta, Atsuko; Loomis, Craig; Lupton,Robert H.; Roweis, Sam; Snedden, Stephanie A.; Strauss, Michael A.; Tucker, Douglas L.

    2007-09-30T23:59:59.000Z

    We present an algorithm to photometrically calibrate widefield optical imaging surveys, that simultaneously solves for thecalibration parameters and relative stellar fluxes using overlappingobservations. The algorithm decouples the problem of "relative"calibrations from that of "absolute" calibrations; the absolutecalibration is reduced to determining a few numbers for the entiresurvey. We pay special attention to the spatial structure of thecalibration errors, allowing one to isolate particular error modes indownstream analyses. Applying this to the SloanDigital Sky Survey imagingdata, we achieve ~;1 percent relative calibration errors across 8500sq.deg/ in griz; the errors are ~;2 percent for the u band. These errorsare dominated by unmodelled atmospheric variations at Apache PointObservatory. These calibrations, dubbed ubercalibration, are now publicwith SDSS Data Release 6, and will be a part of subsequent SDSS datareleases.

  13. Ultrasound image guided acetabular implant orientation during total hip replacement

    DOE Patents [OSTI]

    Chang, John; Haddad, Waleed; Kluiwstra, Jan-Ulco; Matthews, Dennis; Trauner, Kenneth

    2003-08-19T23:59:59.000Z

    A system for assisting in precise location of the acetabular implant during total hip replacement. The system uses ultrasound imaging for guiding the placement and orientation of the implant.

  14. The Clustering of Luminous Red Galaxies in the Sloan Digital Sky Survey Imaging Data

    E-Print Network [OSTI]

    Padmanabhan, N; Seljak, U; Makarov, A; Bahcall, Neta A; Blanton, M R; Brinkmann, J; Eisenstein, D J; Finkbeiner, D P; Gunn, J E; Hogg, D W; Ivezic, Z; Knapp, G R; Loveday, J; Lupton, R H; Nichol, R C; Schneider, D P; Strauss, M A; Tegmark, M; York, D G

    2006-01-01T23:59:59.000Z

    We present the 3D real space clustering power spectrum of a sample of \\~600,000 luminous red galaxies (LRGs) measured by the Sloan Digital Sky Survey (SDSS), using photometric redshifts. This sample of galaxies ranges from redshift z=0.2 to 0.6 over 3,528 deg^2 of the sky, probing a volume of 1.5 (Gpc/h)^3, making it the largest volume ever used for galaxy clustering measurements. We measure the angular clustering power spectrum in eight redshift slices and combine these into a high precision 3D real space power spectrum from k=0.005 (h/Mpc) to k=1 (h/Mpc). We detect power on gigaparsec scales, beyond the turnover in the matter power spectrum, on scales significantly larger than those accessible to current spectroscopic redshift surveys. We also find evidence for baryonic oscillations, both in the power spectrum, as well as in fits to the baryon density, at a 2.5 sigma confidence level. The statistical power of these data to constrain cosmology is ~1.7 times better than previous clustering analyses. Varying t...

  15. MACHETE: A transit Imaging Atmospheric Cherenkov Telescope to survey half of the Very High Energy $\\gamma$-ray sky

    E-Print Network [OSTI]

    Cortina, J; Moralejo, A

    2015-01-01T23:59:59.000Z

    Current Imaging Atmospheric Cherenkov Telescopes for Very High Energy $\\gamma$-ray astrophysics are pointing instruments with a Field of View up to a few tens of sq deg. We propose to build an array of two non-steerable (drift) telescopes. Each of the telescopes would have a camera with a FOV of 5$\\times$60 sq deg oriented along the meridian. About half of the sky drifts through this FOV in a year. We have performed a Montecarlo simulation to estimate the performance of this instrument. We expect it to survey this half of the sky with an integral flux sensitivity of $\\sim$0.77\\% of the steady flux of the Crab Nebula in 5 years, an analysis energy threshold of $\\sim$150 GeV and an angular resolution of $\\sim$0.1$^{\\circ}$. For astronomical objects that transit over the telescope for a specific night, we can achieve an integral sensitivity of 12\\% of the Crab Nebula flux in a night, making it a very powerful tool to trigger further observations of variable sources using steerable IACTs or instruments at other w...

  16. Correction to ``Scanning Imaging Absorption Spectrometer for Atmospheric Chartography carbon monoxide total columns

    E-Print Network [OSTI]

    Laat, Jos de

    Correction to ``Scanning Imaging Absorption Spectrometer for Atmospheric Chartography carbon to ``Scanning Imaging Absorption Spectrometer for Atmospheric Chartography carbon monoxide total columns, doi:10.1029/2007JD009378. [1] In the paper ``Scanning Imaging Absorption Spec- trometer

  17. The Clustering of Luminous Red Galaxies in the Sloan Digital Sky Survey Imaging Data

    E-Print Network [OSTI]

    N. Padmanabhan; D. J. Schlegel; U. Seljak; A. Makarov; N. A. Bahcall; M. R. Blanton; J. Brinkmann; D. J. Eisenstein; D. P. Finkbeiner; J. E. Gunn; D. W. Hogg; Z. Ivezic; G. R. Knapp; J. Loveday; R. H. Lupton; R. C. Nichol; D. P. Schneider; M. A. Strauss; M. Tegmark; D. G. York

    2006-05-15T23:59:59.000Z

    We present the 3D real space clustering power spectrum of a sample of \\~600,000 luminous red galaxies (LRGs) measured by the Sloan Digital Sky Survey (SDSS), using photometric redshifts. This sample of galaxies ranges from redshift z=0.2 to 0.6 over 3,528 deg^2 of the sky, probing a volume of 1.5 (Gpc/h)^3, making it the largest volume ever used for galaxy clustering measurements. We measure the angular clustering power spectrum in eight redshift slices and combine these into a high precision 3D real space power spectrum from k=0.005 (h/Mpc) to k=1 (h/Mpc). We detect power on gigaparsec scales, beyond the turnover in the matter power spectrum, on scales significantly larger than those accessible to current spectroscopic redshift surveys. We also find evidence for baryonic oscillations, both in the power spectrum, as well as in fits to the baryon density, at a 2.5 sigma confidence level. The statistical power of these data to constrain cosmology is ~1.7 times better than previous clustering analyses. Varying the matter density and baryon fraction, we find \\Omega_M = 0.30 \\pm 0.03, and \\Omega_b/\\Omega_M = 0.18 \\pm 0.04, The detection of baryonic oscillations also allows us to measure the comoving distance to z=0.5; we find a best fit distance of 1.73 \\pm 0.12 Gpc, corresponding to a 6.5% error on the distance. These results demonstrate the ability to make precise clustering measurements with photometric surveys (abridged).

  18. Sky Surveys

    E-Print Network [OSTI]

    Djorgovski, S G; Drake, A J; Graham, M J; Donalek, C

    2012-01-01T23:59:59.000Z

    Sky surveys represent a fundamental data basis for astronomy. We use them to map in a systematic way the universe and its constituents, and to discover new types of objects or phenomena. We review the subject, with an emphasis on the wide-field imaging surveys, placing them in a broader scientific and historical context. Surveys are the largest data generators in astronomy, propelled by the advances in information and computation technology, and have transformed the ways in which astronomy is done. We describe the variety and the general properties of surveys, the ways in which they may be quantified and compared, and offer some figures of merit that can be used to compare their scientific discovery potential. Surveys enable a very wide range of science; that is perhaps their key unifying characteristic. As new domains of the observable parameter space open up thanks to the advances in technology, surveys are often the initial step in their exploration. Science can be done with the survey data alone or a comb...

  19. First On-Sky High Contrast Imaging with an Apodizing Phase Plate

    E-Print Network [OSTI]

    Matthew A. Kenworthy; Johanan L. Codona; Philip M. Hinz; J. Roger P. Angel; Ari Heinze; Suresh Sivanandam

    2007-02-12T23:59:59.000Z

    We present the first astronomical observations obtained with an Apodizing Phase Plate (APP). The plate is designed to suppress the stellar diffraction pattern by 5 magnitudes from 2-9 lambda/D over a 180 degree region. Stellar images were obtained in the M' band (4.85 microns) at the MMTO 6.5m telescope, with adaptive wavefront correction made with a deformable secondary mirror designed for low thermal background observations. The measured PSF shows a halo intensity of 0.1% of the stellar peak at 2 lambda/D (0.36 arcsec), tapering off as r^{-5/3} out to radius 9 lambda/D. Such a profile is consistent with residual errors predicted for servo lag in the AO system. We project a 5 sigma contrast limit, set by residual atmospheric fluctuations, of 10.2 magnitudes at 0.36 arcsec separation for a one hour exposure. This can be realised if static and quasi-static aberrations are removed by differential imaging, and is close to the sensitivity level set by thermal background photon noise for target stars with M'>3. The advantage of using the phase plate is the removal of speckle noise caused by the residuals in the diffraction pattern that remain after PSF subtraction. The APP gives higher sensitivity over the range 2-5 lambda/D compared to direct imaging techniques.

  20. A Fast Algorithm for Total Variation Image Reconstruction from ...

    E-Print Network [OSTI]

    2010-01-12T23:59:59.000Z

    small number of linear projections and then reconstructs it from the limited ... [29] regularization in recovering high quality image is not without a price.

  1. FIRST: Faint Images of the Radio Sky at Twenty-Centimeters (Data Catalogs from the Very Large Array (VLA) First Survey)

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

    Becker, Robert H.; Helfand, David J.; White, Richard L.; Gregg, Michael D.; Laurent-Muehleisen, Sally A.

    FIRST, Faint Images of the Radio Sky at Twenty-cm, is a project designed to produce the radio equivalent of the Palomar Observatory Sky Survey over 10,000 square degrees of the North Galactic Cap. Using the National Radio Astronomy Observatory (NRAO) Very Large Array (VLA) in its B-configuration, the Survey acquired 3-minute snapshots covering a hexagonal grid using 27 3-MHz frequency channels centered at 1365 and 1435 MHz. The data were edited, self-calibrated, mapped, and cleaned using an automated pipeline based largely on routines in the Astronomical Image Processing System (AIPS). Data were collected from 1993 through 2002, with enhanced images produced up through 2011. The Data Catalogs have been cleaned and reissued over time, with the latest version coming out in March, 2014. They contain maps, images, and binary data. The FIRST survey area was chosen to coincide with that of the Sloan Digital Sky Survey (SDSS); at the m(v)~24 limit of SDSS, ~50% of the optical counterparts to FIRST sources will be detected.

  2. A Total Variation Based Algorithm for Pixel Level Image Fusion

    E-Print Network [OSTI]

    Dass, Sarat C.

    -band and infrared sensors. The results clearly indicate the feasibility of the proposed approach. Index Terms Image sensors. In this approach, fusion is posed as an inverse problem and a locally affine model is used, nondestructive evaluation etc. [7]­[9]. For example, in optical remote sensing, due to physical and technical

  3. Image decomposition and restoration using total variation minimization and the H 1 norm

    E-Print Network [OSTI]

    Soatto, Stefano

    Image decomposition and restoration using total variation minimization and the H 1 norm Stanley-Osher-Fatemi, and of the results of Y. Meyer on oscillatory functions. An initial image f is decomposed into a cartoon part u. Meyer [7] proposed a new minimization problem, changing in (1) the L 2 norm of (f u) by another norm

  4. IMAGE DECOMPOSITION AND RESTORATION USING TOTAL VARIATION MINIMIZATION AND THE H-1

    E-Print Network [OSTI]

    Vese, Luminita A.

    IMAGE DECOMPOSITION AND RESTORATION USING TOTAL VARIATION MINIMIZATION AND THE H-1 NORM STANLEY results of Meyer [Oscillating Patterns in Image Processing and Nonlinear Evolution Equations, Univ #12;350 STANLEY OSHER, ANDR´ES SOL´E, AND LUMINITA VESE which is the minimizer of this convex

  5. Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed

    E-Print Network [OSTI]

    2011-01-01T23:59:59.000Z

    smoothing. Submitted to Solar Energy. Linke, F. , 1922.24th European Photovoltaic Solar Energy Conference, Hamburg,solener.2011.02.014, Solar Energy. Lave, M. , Kleissl, J. ,

  6. Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed

    E-Print Network [OSTI]

    2011-01-01T23:59:59.000Z

    solener.2011.02.014, Solar Energy. Lave, M. , Kleissl, J. ,smoothing. Submitted to Solar Energy. Linke, F. , 1922.24th European Photovoltaic Solar Energy Conference, Hamburg,

  7. Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed

    E-Print Network [OSTI]

    2011-01-01T23:59:59.000Z

    have smaller RBR than white clouds and bright regions.camera white balancing, lighting on the cloud, and differentwhite. In addition, at larger solar ZAs less sunlight scattered by clouds

  8. Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed

    E-Print Network [OSTI]

    2011-01-01T23:59:59.000Z

    solar irradiation in Brazil, Solar Energy, 68, 91- 107, ISSNmaps for Brazil under SWERA project, Solar Energy, 81, 517-

  9. Total electron and proton energy input during auroral substorms: Remote sensing with IMAGE-FUV

    E-Print Network [OSTI]

    California at Berkeley, University of

    Total electron and proton energy input during auroral substorms: Remote sensing with IMAGE-FUV B the ionospheric Pedersen conductivity and produces Joule heat- ing in the presence of an electric field. In addition, part of the energy of the auroral particles is dissipated into local heating through dissociation

  10. Modeling textures with total variation minimization and oscillating patterns in image processing

    E-Print Network [OSTI]

    Soatto, Stefano

    Luminita A. Vese #3; & Stanley J. Osher y Department of Mathematics, University of California, Los Angeles in the honor of Stanley Osher Abstract This paper is devoted to the modeling of real textured images by functional min- imization and partial di#11;erential equations. Following the ideas of Yves Meyer in a total

  11. IMAGE DECOMPOSITION, IMAGE RESTORATION, AND TEXTURE MODELING USING TOTAL VARIATION MINIMIZATION AND THE H-1

    E-Print Network [OSTI]

    Vese, Luminita A.

    AND THE H-1 NORM Stanley Osher Maths. Department UCLA, Los Angeles sjo@math.ucla.edu Andr´es Sol-Osher-Fatemi [8], and on some new tech- niques by Y. Meyer [5] for oscillatory functions. An initial image f. To overcome this, Y. Meyer [5] proposed new minimiza- tion problems, changing in (1) the L2 norm of (f - u

  12. Eigenvector Sky Subtraction

    E-Print Network [OSTI]

    Michael J. Kurtz; Douglas J. Mink

    2000-03-08T23:59:59.000Z

    We develop a new method for estimating and removing the spectrum of the sky from deep spectroscopic observations; our method does not rely on simultaneous measurement of the sky spectrum with the object spectrum. The technique is based on the iterative subtraction of continuum estimates and Eigenvector sky models derived from Singular Value Decompositions (SVD) of sky spectra, and sky spectra residuals. Using simulated data derived from small telescope observations we demonstrate that the method is effective for faint objects on large telescopes. We discuss simple methods to combine our new technique with the simultaneous measurement of sky to obtain sky subtraction very near the Poisson limit.

  13. Big Sky Carbon Atlas

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

    (Acknowledgment to the Big Sky Carbon Sequestration Partnership (BSCSP); see home page at http://www.bigskyco2.org/)

  14. Seeing the sky through Hubble's eye: The COSMOS SkyWalker

    E-Print Network [OSTI]

    K. Jahnke; S. F. Sanchez; A. Koekemoer

    2006-07-23T23:59:59.000Z

    Large, high-resolution space-based imaging surveys produce a volume of data that is difficult to present to the public in a comprehensible way. While megapixel-sized images can still be printed out or downloaded via the World Wide Web, this is no longer feasible for images with 10^9 pixels (e.g., the Hubble Space Telescope Advanced Camera for Surveys [ACS] images of the Galaxy Evolution from Morphology and SEDs [GEMS] project) or even 10^10 pixels (for the ACS Cosmic Evolution Survey [COSMOS]). We present a Web-based utility called the COSMOS SkyWalker that allows viewing of the huge ACS image data set, even through slow Internet connections. Using standard HTML and JavaScript, the application successively loads only those portions of the image at a time that are currently being viewed on the screen. The user can move within the image by using the mouse or interacting with an overview image. Using an astrometrically registered image for the COSMOS SkyWalker allows the display of calibrated world coordinates for use in science. The SkyWalker "technique" can be applied to other data sets. This requires some customization, notably the slicing up of a data set into small (e.g., 256^2 pixel) subimages. An advantage of the SkyWalker is the use of standard Web browser components; thus, it requires no installation of any software and can therefore be viewed by anyone across many operating systems.

  15. Ground Water Ground Sky Sky Water Vegetation Ground Vegetation Water

    E-Print Network [OSTI]

    Chen, Tsuhan

    Bear Snow Vegetation RhinoWater Vegetation Ground Water Ground Sky Sky Rhino Water Vegetation Ground Vegetation Water Rhino Water Vegetation Ground Rhino Water Rhino Water Ground Ground Vegetation Water Rhino Vegetation Rhino Vegetation Ground Rhino Vegetation Ground Sky Rhino Vegetation Ground Sky

  16. Wide Blue Sky

    E-Print Network [OSTI]

    Collins, Caroline Imani

    2011-01-01T23:59:59.000Z

    dressed neatly in a dark blue dress, its high neck trimmedIt was covered in a light blue fabric embellished with softOF CALIFORNIA RIVERSIDE Wide Blue Sky A Thesis submitted in

  17. An Efficient Algorithm for Compressed MR Imaging using Total Variation and Wavelets

    E-Print Network [OSTI]

    Yin, Wotao

    Integrated Data Systems, Siemens Corporate Research Princeton, NJ 08540, USA amit.chakraborty@siemens and Fourier transforms enabling our code to process MR images from actual real life applications. We show of the Inverse Dis- crete Fourier Transform to arrive at the required image of the anatomy under consideration

  18. Total Dose Evaluation of Deep Submicron CMOS Imaging Technology Through Elementary Device and

    E-Print Network [OSTI]

    Mailhes, Corinne

    layer. Current-voltage character- istics were carried out at 23 using a low-current ( 10 fA) test bench. Bernard, and G. Rolland Abstract--Ionizing radiation effects on CMOS image sensors (CIS) manufactured to understand ionizing dose effects on devices and then on image sensors. The main degra- dations observed

  19. Combined iterative reconstruction and image-domain decomposition for dual energy CT using total-variation regularization

    SciTech Connect (OSTI)

    Dong, Xue; Niu, Tianye; Zhu, Lei, E-mail: leizhu@gatech.edu [Nuclear and Radiological Engineering and Medical Physics Programs, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 (United States)] [Nuclear and Radiological Engineering and Medical Physics Programs, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 (United States)

    2014-05-15T23:59:59.000Z

    Purpose: Dual-energy CT (DECT) is being increasingly used for its capability of material decomposition and energy-selective imaging. A generic problem of DECT, however, is that the decomposition process is unstable in the sense that the relative magnitude of decomposed signals is reduced due to signal cancellation while the image noise is accumulating from the two CT images of independent scans. Direct image decomposition, therefore, leads to severe degradation of signal-to-noise ratio on the resultant images. Existing noise suppression techniques are typically implemented in DECT with the procedures of reconstruction and decomposition performed independently, which do not explore the statistical properties of decomposed images during the reconstruction for noise reduction. In this work, the authors propose an iterative approach that combines the reconstruction and the signal decomposition procedures to minimize the DECT image noise without noticeable loss of resolution. Methods: The proposed algorithm is formulated as an optimization problem, which balances the data fidelity and total variation of decomposed images in one framework, and the decomposition step is carried out iteratively together with reconstruction. The noise in the CT images from the proposed algorithm becomes well correlated even though the noise of the raw projections is independent on the two CT scans. Due to this feature, the proposed algorithm avoids noise accumulation during the decomposition process. The authors evaluate the method performance on noise suppression and spatial resolution using phantom studies and compare the algorithm with conventional denoising approaches as well as combined iterative reconstruction methods with different forms of regularization. Results: On the Catphan©600 phantom, the proposed method outperforms the existing denoising methods on preserving spatial resolution at the same level of noise suppression, i.e., a reduction of noise standard deviation by one order of magnitude. This improvement is mainly attributed to the high noise correlation in the CT images reconstructed by the proposed algorithm. Iterative reconstruction using different regularization, including quadratic orq-generalized Gaussian Markov random field regularization, achieves similar noise suppression from high noise correlation. However, the proposed TV regularization obtains a better edge preserving performance. Studies of electron density measurement also show that our method reduces the average estimation error from 9.5% to 7.1%. On the anthropomorphic head phantom, the proposed method suppresses the noise standard deviation of the decomposed images by a factor of ?14 without blurring the fine structures in the sinus area. Conclusions: The authors propose a practical method for DECT imaging reconstruction, which combines the image reconstruction and material decomposition into one optimization framework. Compared to the existing approaches, our method achieves a superior performance on DECT imaging with respect to decomposition accuracy, noise reduction, and spatial resolution.

  20. OPTIMAL CONSTRUCTIONS OF WAVELET COEFFICIENTS USING TOTAL VARIATION REGULARIZATION IN IMAGE COMPRESSION

    E-Print Network [OSTI]

    Chan, Tony F.

    (TV), to select and modify the retained stan- dard wavelet coeÆcients so that the reconstructed images. Along this direction, Claypoole, Davis, Sweldens and Baraniuk [13] proposed an adaptive lifting scheme

  1. The Sloan Digital Sky Survey

    E-Print Network [OSTI]

    Bruce Margon

    1998-08-19T23:59:59.000Z

    The Sloan Digital Sky Survey is an ambitious, multi-institutional project to create a huge digital imaging and spectroscopic data bank of 25% of the celestial sphere, approximately 10,000 deg^2 centred on the north galactic polar cap. The photometric atlas will be in 5 specially-chosen colours, covering the pi ster of the Survey area to a limiting magnitude of r~23.1, on 0.4" pixels, resulting in a 1 Tpixel map. This data base will be automatically analysed to catalog the photometric and astrometric properties of 10^8 stellar images, 10^8 galaxies, and 10^6 colour-selected QSO candidates; the galaxy data will in addition include detailed morphological data. The photometric data are used to autonomously and homogeneously select objects for the spectroscopic survey, which will include spectra of 10^6 galaxies, 10^5 QSOs, and 10^5 unusual stars. Although the project was originally motivated by the desire to study Large Scale Structure, we anticipate that these data will impact virtually every field of astronomy, from Earth-crossing asteroids to QSOs at z>6. In particular, the ~12 TByte multi-colour, precision calibrated imaging archive should be a world resource for many decades of the next century.

  2. Mining the Blazar Sky

    E-Print Network [OSTI]

    Paolo Padovani; Paolo Giommi

    2000-12-15T23:59:59.000Z

    We present the results of our methods to "mine" the blazar sky, i.e., select blazar candidates with very high efficiency. These are based on the cross-correlation between public radio and X-ray catalogs and have resulted in two surveys, the Deep X-ray Radio Blazar Survey (DXRBS) and the "Sedentary" BL Lac survey. We show that data mining is vital to select sizeable, deep samples of these rare active galactic nuclei and we touch upon the identification problems which deeper surveys will face.

  3. Global horizontal irradiance clear sky models : implementation and analysis.

    SciTech Connect (OSTI)

    Stein, Joshua S.; Hansen, Clifford W.; Reno, Matthew J.

    2012-03-01T23:59:59.000Z

    Clear sky models estimate the terrestrial solar radiation under a cloudless sky as a function of the solar elevation angle, site altitude, aerosol concentration, water vapor, and various atmospheric conditions. This report provides an overview of a number of global horizontal irradiance (GHI) clear sky models from very simple to complex. Validation of clear-sky models requires comparison of model results to measured irradiance during clear-sky periods. To facilitate validation, we present a new algorithm for automatically identifying clear-sky periods in a time series of GHI measurements. We evaluate the performance of selected clear-sky models using measured data from 30 different sites, totaling about 300 site-years of data. We analyze the variation of these errors across time and location. In terms of error averaged over all locations and times, we found that complex models that correctly account for all the atmospheric parameters are slightly more accurate than other models, but, primarily at low elevations, comparable accuracy can be obtained from some simpler models. However, simpler models often exhibit errors that vary with time of day and season, whereas the errors for complex models vary less over time.

  4. The Eighth Data Release of the Sloan Digital Sky Survey: First Data from SDSS-III

    SciTech Connect (OSTI)

    Aihara, Hiroaki; /Tokyo U.; Prieto, Carlos Allende; /Laguna U., Tenerife; An, Deokkeun; /Ewha Women's U., Seoul; Anderson, Scott F.; /Washington U., Seattle, Astron. Dept.; Aubourg, Eric; /APC, Paris /DAPNIA, Saclay; Balbinot, Eduardo; /Rio Grande do Sul U. /Rio de Janeiro Observ.; Beers, Timothy C.; /Michigan State U.; Berlind, Andreas A.; /Vanderbilt U.; Bickerton, Steven J.; /Princeton U.; Bizyaev, Dmitry; /Apache Point Observ.; Blanton, Michael R.; /New York U., CCPP /Penn State U.

    2011-01-01T23:59:59.000Z

    The Sloan Digital Sky Survey (SDSS) started a new phase in August 2008, with new instrumentation and new surveys focused on Galactic structure and chemical evolution, measurements of the baryon oscillation feature in the clustering of galaxies and the quasar Ly{alpha} forest, and a radial velocity search for planets around {approx}8000 stars. This paper describes the first data release of SDSS-III (and the eighth counting from the beginning of the SDSS). The release includes 5-band imaging of roughly 5200 deg{sup 2} in the Southern Galactic Cap, bringing the total footprint of the SDSS imaging to 14,555 deg{sup 2}, or over a third of the Celestial Sphere. All the imaging data have been reprocessed with an improved sky-subtraction algorithm and a final, self-consistent recalibration and flat-field determination. This release also includes all data from the second phase of the Sloan Extension for Galactic Understanding and Evolution (SEGUE-2), consisting of spectroscopy of approximately 118,000 stars at both high and low Galactic latitudes. All the more than half a million stellar spectra obtained with the SDSS spectrograph have been reprocessed through an improved stellar parameters pipeline, which has better determination of metallicity for high metallicity stars.

  5. The Real Message in the Sky

    E-Print Network [OSTI]

    Douglas Scott; J. P. Zibin

    2005-11-15T23:59:59.000Z

    A recent paper by Hsu & Zee (physics/0510102) suggests that if a Creator wanted to leave a message for us, and she wanted it to be decipherable to all sentient beings, then she would place it on the most cosmic of all billboards, the Cosmic Microwave Background (CMB) sky. Here we point out that the spherical harmonic coefficients of the observed CMB anisotropies (or their squared amplitudes at each multipole) depend on the location of the observer, in both space and time. The amount of observer-independent information available in the CMB is a small fraction of the total that any observer can measure. Hence a lengthy message on the CMB sky is fundamentally no less observer-specific than a communication hidden in this morning's tea-leaves. Nevertheless, the CMB sky does encode a wealth of information about the structure of the cosmos and possibly about the nature of physics at the highest energy levels. The Universe has left us a message all on its own.

  6. Big Sky Trust Fund (Montana)

    Broader source: Energy.gov [DOE]

    The Big Sky Trust Fund reimburses expenses incurred in the purchase, leasing, or relocation of real assets for direct use of the assisted business or employee training costs. A local or tribal...

  7. The Dancing Sky: 6 years of night sky observations at Cerro Paranal

    E-Print Network [OSTI]

    F. Patat

    2008-01-15T23:59:59.000Z

    The present work provides the results of the first six years of operation of the systematic night-sky monitoring at ESO-Paranal (Chile). The UBVRI night-sky brightness was estimated on about 10,000 VLT-FORS1 archival images, obtained on more than 650 separate nights, distributed over 6 years and covering the descent from maximum to minimum of sunspot cycle n.23. Additionally, a set of about 1,000 low resolution, optical night-sky spectra have been extracted and analyzed. The unprecedented database discussed in this paper has led to the detection of a clear seasonal variation of the broad band night sky brightness in the VRI passbands, similar to the well known semi-annual oscillation of the NaI D doublet. The spectroscopic data demonstrate that this seasonality is common to all spectral features, with the remarkable exception of the OH rotational-vibrational bands. A clear dependency on the solar activity is detected in all passbands and it is particularly pronounced in the U band, where the sky brightness decreased by about 0.6 mag arcsec-2 from maximum to minimum of solar cycle n.23. No correlation is found between solar activity and the intensity of the NaI D doublet and the OH bands. A strong correlation between the intensity of NI 5200A and [OI]6300,6364A is reported here for the first time. The paper addresses also the determination of the correlation timescales with solar activity and the possible connection with the flux of charged particles emitted by the Sun.

  8. Gamma-ray Sky Observed with Fermi Large Area Telescope

    E-Print Network [OSTI]

    Yamamoto, Hirosuke

    detection reported Flare activity reported via ATel Gamma Ray Bursts reported via GCN Giant MC imageGamma-ray Sky Observed with Fermi Large Area Telescope RESCEU Symposium on Astroparticle Physics) Measure the photon direction Identification of the gamma-ray shower 36 planes of Si strip detectors (228 m

  9. average clear-sky broadband: Topics by E-print Network

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

    brightness, clear-sky radiance, digital image analysis, atmospheric optics from solar energy engineering2 ,3 to atmospheric optics4'5 have repeatedly measured and modeled Lee Jr.,...

  10. Color and luminance asymmetries in the clear sky Javier Herna ndez-Andre s, Raymond L. Lee, Jr., and Javier Romero

    E-Print Network [OSTI]

    Lee Jr., Raymond L.

    Color and luminance asymmetries in the clear sky Javier Herna´ ndez-Andre´ s, Raymond L. Lee, Jr., and Javier Romero A long-standing assumption about the clear sky is that its colors and luminances-image analyses show that clear-sky color and luminance routinely depart perceptibly from exact symmetry

  11. SPACE: the SPectroscopic All-sky Cosmic Explorer

    E-Print Network [OSTI]

    A. Cimatti; M. Robberto; C. M. Baugh; S. V. W. Beckwith; R. Content; E. Daddi; G. De Lucia; B. Garilli; L. Guzzo; G. Kauffmann; M. Lehnert; D. Maccagni; A. Martinez-Sansigre; F. Pasian; I. N. Reid; P. Rosati; R. Salvaterra; M. Stiavelli; Y. Wang; M. Zapatero Osorio; the SPACE team

    2008-04-28T23:59:59.000Z

    We describe the scientific motivations, the mission concept and the instrumentation of SPACE, a class-M mission proposed for concept study at the first call of the ESA Cosmic-Vision 2015-2025 planning cycle. SPACE aims to produce the largest three-dimensional evolutionary map of the Universe over the past 10 billion years by taking near-IR spectra and measuring redshifts for more than half a billion galaxies at 0SPACE will also target a smaller sky field, performing a deep spectroscopic survey of millions of galaxies to AB~26 and at 2SPACE will use a 1.5m diameter Ritchey-Chretien telescope equipped with a set of arrays of Digital Micro-mirror Devices (DMDs) covering a total field of view of 0.4 deg2, and will perform large-multiplexing multi-object spectroscopy (e.g. ~6000 targets per pointing) at a spectral resolution of R~400 as well as diffraction-limited imaging with continuous coverage from 0.8mum to 1.8mum.

  12. Sloan Digital Sky Survey II (SDSS-II), Data Release 7, including the Legacy Survey

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

    The Sloan Digital Sky Survey (SDSS) is a series of three interlocking imaging and spectroscopic surveys, carried out over an eight-year period with a dedicated 2.5m telescope located at Apache Point Observatory in Southern New Mexico. The seventh data release (DR7) from the SDSS represents a completion of the overall, original project, though SDSS-III began in 2008 and will build upon the knowledge gained already. The SDSS Legacy Survey provided a uniform, well-calibrated map of more than 7,500 square degrees of the North Galactic Cap, and three stripes in the South Galactic Cap totaling 740 square degrees. The central stripe in the South Galactic Gap, Stripe 82, was scanned multiple times to enable a deep co-addition of the data and to enable discovery of variable objects. Legacy data supported studies ranging from asteroids and nearby stars to the large-scale structure of the universe. All of the imaging data have been processed to yield calibrated astrometric and photometric parameters and classifications. These parameters are available in one or more tables in a database accessible via the Catalog Archive Server (CAS) at http://cas.sdss.org/astro. [taken and edited from the Legacy page at http://www.sdss.org/legacy/index.html] All three surveys summarized are: 1) Legacy: an imaging survey in five bands over a contiguous 7646 deg2 high-latitude elliptical region in the Northern Galactic Cap, plus an additional 750 deg2 in the Southern Galactic Cap, together with spectroscopy of complete samples of galaxies and quasars covering about 8200 square degrees. The total imaging area in the Legacy survey is 8423 square degrees; 2) SEGUE: (Sloan Extension for Galactic Understanding and Exploration): additional imaging of 3240 deg2 of sky at lower Galactic latitudes, together with spectroscopy of 240,000 stars towards 200 sight lines covering 1400 square degrees (spread throughout the Legacy and SEGUE imaging footprints), to study the structure of the Milky Way; 3) Supernova: the equivalent of about 80 repeated imaging scans of the Southern Equatorial Stripe (ra > 310 or ra < 59; -1.25 > dec < 1.25) obtained in variable weather conditions (some clouds) to search for supernovae in the redshift range 0.1 < z < 0.4. The catalog derived from the images includes more than 350 million celestial objects, and spectra of 930,000 galaxies, 120,000 quasars, and 460,000 stars. The data are fully calibrated and reduced, carefully checked for quality, and publicly accessible through efficient databases. The data have been publicly released in a series of annual data releases, culminating in the final data release, DR7.

  13. Red Sky with Red Mesa

    ScienceCinema (OSTI)

    None

    2014-06-23T23:59:59.000Z

    The Red Sky/Red Mesa supercomputing platform dramatically reduces the time required to simulate complex fuel models, from 4-6 months to just 4 weeks, allowing researchers to accelerate the pace at which they can address these complex problems. Its speed also reduces the need for laboratory and field testing, allowing for energy reduction far beyond data center walls.

  14. Is the Sky? Bob Rutledge

    E-Print Network [OSTI]

    Ronis, David M.

    Revolution (cont.) · Tycho Brahe (1546-1601) made careful observations of the positions of the planets as they moved through the sky. · Brahe's student Johannes Kepler, following Brahe's death, analyzed) with the sun at one of the two focii. Brahe #12;Kepler's Three Laws (1609 and 1619) 1. The planets move about

  15. Technique and application of a non-invasive three dimensional image matching method for the study of total shoulder arthroplasty

    E-Print Network [OSTI]

    Massimini, Daniel Frank

    2009-01-01T23:59:59.000Z

    Knowledge of in-vivo glenohumeral joint biomechanics after total shoulder arthroplasty are important for the improvement of patient function, implant longevity and surgical technique. No data has been published on the ...

  16. The First Data Release of the Sloan Digital Sky Survey

    E-Print Network [OSTI]

    Abazajian, Kevork N; Agüeros, Marcel A; Allam, Sahar S; Anderson, Scott F; Annis, James; Bahcall, Neta A; Baldry, Ivan K; Bastian, Steven; Berlind, Andreas A; Bernardi, Mariangela; Blanton, Michael R; Blythe, Norman; Bochanski, John J; Boroski, William N; Brewington, Howard; Briggs, John W; Brinkmann, J; Brunner, Robert J; Budavari, Tamas; Carey, Larry N; Carr, Michael A; Castander, F J; Chiu, Kuenley; Collinge, Matthew J; Connolly, A J; Covey, Kevin R; Csabai, Istvan; Dodelson, Scott; Doi, Mamoru; Dong, Feng; Eisenstein, Daniel J; Evans, Michael L; Fan, Xiaohui; Feldman, Paul D; Finkbeiner, Douglas P; Friedman, Scott D; Frieman, Joshua A; Fukugita, Masataka; Gal, Roy R; Gillespie, Bruce; Glazebrook, Karl; Gonzalez, Carlos F; Gray, Jim; Grebel, Eva K; Grodnicki, Lauren; Gunn, James E; Gurbani, Vijay K; Hall, Patrick B; Hao, Lei; Harbeck, Daniel; Harris, Frederick H; Harris, Hugh C; Harvanek, Michael J; Hawley, Suzanne L; Heckman, Timothy M; Helmboldt, J F; Hendry, John S; Hennessy, Gregory S; Hindsley, Robert B; Hogg, David W; Holmgren, Donald; Holtzman, Jon A; Homer, Lee; Hui, Lam; Ichikawa, Shin-ichi; Ichikawa, Takashi; Inkmann, John P; Ivezic, Z; Jester, Sebastian; Johnston, David E; Jordan, Beatrice; Jordan, Wendell P; Jorgensen, Anders M; Juric, Mario; Kauffmann, Guinevere; Kent, Stephen M; Kleinman, S J; Knapp, G R; Kniazev, Alexei Yu; Kron, Richard G; Krzesinski, Jurek; Kunszt, Peter Z; Kuropatkin, Nickolai; Lamb, Donald Q; Lampeitl, Hubert; Laubscher, Bryan E; Lee, Brian C; Leger, R French; Li No Lan; Lidz, Adam; Lin, Huan; Loh Yeong Shang; Long, Daniel C; Loveday, Jon; Lupton, Robert H; Malik, Tanu; Margon, Bruce; McGehee, Peregrine M; McKay, Timothy A; Meiksin, Avery; Miknaitis, Gajus A; Moorthy, Bhasker K; Munn, Jeffrey A; Murphy, Tara; Nakajima, Reiko; Narayanan, Vijay K; Nash, Thomas; Neilsen, Erich; Newberg, Heidi Jo; Newman, Peter R; Nichol, Robert C; Nicinski, Tom; Nieto-Santisteban, Maria; Nitta, Atsuko; Odenkirchen, Michael; Okamura, Sadanori; Ostriker, Jeremiah P; Owen, Russell; Padmanabhan, Nikhil; Peoples, John; Pier, Jeffrey R; Pindor, Bartosz; Pope, Adrian C; Quinn, Thomas R; Rafikov, R R; Raymond, Sean N; Richards, Gordon T; Richmond, Michael W; Rix, Hans-Walter; Rockosi, Constance M; Schaye, Joop; Schlegel, David J; Schneider, D P; Schroeder, Joshua; Scranton, Ryan; Sekiguchi, Maki; Seljak, Uros; Sergey, Gary; Sesar, Branimir; Sheldon, E S; Shimasaku, Kazu; Siegmund, Walter A; Silvestri, Nicole M; Sinisgalli, Allan J; Sirko, Edwin; Smith, Allyn J; Smolcic, Vernesa; Snedden, Stephanie A; Stebbins, Albert; Steinhardt, Charles; Stinson, Gregory M; Stoughton, Chris; Strateva, Iskra V; Strauss, Michael A; SubbaRao, Mark; Szalay, Alexander S; Istvan Szapudi; Szkody, Paula; Tasca, Lidia; Tegmark, Max; Thakar, Aniruddha R; Tremonti, Christy A; Tucker, Douglas L; Uomoto, Alan; Vanden Berk, Daniel E; Vandenberg, Jan; Vogeley, Michael S; Voges, Wolfgang; Vogt, Nicole P; Walkowicz, Lucianne M; Weinberg, David H; West, Andrew A; White, Simon D M; Wilhite, Brian C; Willman, Beth; Xu Yong Hong; Yanny, Brian; Yarger, Jean; Yasuda, Naoki; Yip, Ching-Wa; Yocum, D R; York, Donald G; Zakamska, Nadia L; Zheng, Wei; Zibetti, Stefano; Zucker, Daniel B

    2003-01-01T23:59:59.000Z

    The Sloan Digital Sky Survey has validated and made publicly available its First Data Release. This consists of 2099 square degrees of five-band (u, g, r, i, z) imaging data, 186,240 spectra of galaxies, quasars, stars and calibrating blank sky patches selected over 1360 square degrees of this area, and tables of measured parameters from these data. The imaging data go to a depth of r ~ 22.6 and are photometrically and astrometrically calibrated to 2% rms and 100 milli-arcsec rms per coordinate, respectively. The spectra cover the range 3800--9200 A, with a resolution of 1800--2100. Further characteristics of the data are described, as are the data products themselves.

  17. ARM: Fractional cloud cover, clear-sky and all-sky shortwave flux for each of 25 individual SGP facilities.

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

    Gaustad, Krista; Gaustad, Krista; McFarlane, Sally; McFarlane, Sally

    Fractional cloud cover, clear-sky and all-sky shortwave flux for each of 25 individual SGP facilities.

  18. Sky Vegetables | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro Industries Pvt LtdShawangunk, New York:SiG Solar GmbHKentucky:SinosolSitalceaSkokie,Lake,Sky

  19. Sky Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit with form HistoryRistmaSinosteel Corporation Jump to: navigation,SiriSky

  20. BIGGER AND BETTER BANGS IN THE SKY

    E-Print Network [OSTI]

    TRIMBLE, V

    1982-01-01T23:59:59.000Z

    better hangs in the sky Supernovae are massive stars thatthe traditional prototype of supernovae; and its‘ remains,applicable to other supernovae and remnants. What do we know

  1. A SIMPLIFIED PROCEDURE FOR CALCULATING THE EFFECTS OF DAYLIGHT FROM CLEAR SKIES

    E-Print Network [OSTI]

    Bryan, Harvey J.

    2012-01-01T23:59:59.000Z

    obstructed sky. The clear sky luminance distribution thatformula: where Le "' Luminance of sky position beingof Luminance Distribution on Clear Skies,~r CIE PUBLICATION

  2. BIG SKY CARBON SEQUESTRATION PARTNERSHIP

    SciTech Connect (OSTI)

    Susan M. Capalbo

    2004-06-01T23:59:59.000Z

    The Big Sky Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts during the second performance period fall into four areas: evaluation of sources and carbon sequestration sinks; development of GIS-based reporting framework; designing an integrated suite of monitoring, measuring, and verification technologies; and initiating a comprehensive education and outreach program. At the first two Partnership meetings the groundwork was put in place to provide an assessment of capture and storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that would complement the ongoing DOE research. The region has a diverse array of geological formations that could provide storage options for carbon in one or more of its three states. Likewise, initial estimates of terrestrial sinks indicate a vast potential for increasing and maintaining soil C on forested, agricultural, and reclaimed lands. Both options include the potential for offsetting economic benefits to industry and society. Steps have been taken to assure that the GIS-based framework is consistent among types of sinks within the Big Sky Partnership area and with the efforts of other western DOE partnerships. Efforts are also being made to find funding to include Wyoming in the coverage areas for both geological and terrestrial sinks and sources. The Partnership recognizes the critical importance of measurement, monitoring, and verification technologies to support not only carbon trading but all policies and programs that DOE and other agencies may want to pursue in support of GHG mitigation. The efforts begun in developing and implementing MMV technologies for geological sequestration reflect this concern. Research is also underway to identify and validate best management practices for soil C in the partnership region, and to design a risk/cost effectiveness framework to make comparative assessments of each viable sink, taking into account economic costs, offsetting benefits, scale of sequestration opportunities, spatial and time dimensions, environmental risks, and long term viability. Scientifically sound information on MMV is critical for public acceptance of these technologies. Two key deliverables were completed this quarter--a literature review/database to assess the soil carbon on rangelands, and the draft protocols, contracting options for soil carbon trading. To date, there has been little research on soil carbon on rangelands, and since rangeland constitutes a major land use in the Big Sky region, this is important in achieving a better understanding of terrestrial sinks. The protocols developed for soil carbon trading are unique and provide a key component of the mechanisms that might be used to efficiently sequester GHG and reduce CO{sub 2} concentrations. Progress on other deliverables is noted in the PowerPoint presentations. A series of meetings held during the second quarter have laid the foundations for assessing the issues surrounding the implementation of a market-based setting for soil C credits. These meetings provide a connection to stakeholders in the region and a basis on which to draw for the DOE PEIS hearings. Finally, the education and outreach efforts have resulted in a comprehensive plan and process which serves as a guide for implementing the outreach activities under Phase I. While we are still working on the public website, we have made many presentations to stakeholders and policy makers, connections to other federal and state agencies concerned with GHG emissions, climate change, and efficient and environmentally-friendly energy production. In addition, we have laid plans for integration of our outreach efforts with the students, especially at the tribal colleges and at the universities involved in our partnership. This includes collaboration with the film and media arts departments at MSU, with outreach effort

  3. BIG SKY CARBON SEQUESTRATION PARTNERSHIP

    SciTech Connect (OSTI)

    Susan M. Capalbo

    2004-01-04T23:59:59.000Z

    The Big Sky Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts during the first performance period fall into four areas: evaluation of sources and carbon sequestration sinks; development of GIS-based reporting framework; designing an integrated suite of monitoring, measuring, and verification technologies; and initiating a comprehensive education and outreach program. At the first Partnership meeting the groundwork was put in place to provide an assessment of capture and storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that would complement the ongoing DOE research. The region has a diverse array of geological formations that could provide storage options for carbon in one or more of its three states. Likewise, initial estimates of terrestrial sinks indicate a vast potential for increasing and maintaining soil C on forested, agricultural, and reclaimed lands. Both options include the potential for offsetting economic benefits to industry and society. Complementary to the efforts on evaluation of sources and sinks is the development of the Big Sky Partnership Carbon Cyberinfrastructure (BSP-CC) and a GIS Road Map for the Partnership. These efforts will put in place a map-based integrated information management system for our Partnership, with transferability to the national carbon sequestration effort. The Partnership recognizes the critical importance of measurement, monitoring, and verification technologies to support not only carbon trading but other policies and programs that DOE and other agencies may want to pursue in support of GHG mitigation. The efforts begun in developing and implementing MMV technologies for geological sequestration reflect this concern. Research is also underway to identify and validate best management practices for soil C in the partnership region, and to design a risk/cost effectiveness framework to make comparative assessments of each viable sink, taking into account economic costs, offsetting benefits, scale of sequestration opportunities, spatial and time dimensions, environmental risks, and long term viability. A series of meetings held in November and December, 2003, have laid the foundations for assessing the issues surrounding the implementation of a market-based setting for soil C credits. These include the impact of existing local, state, and federal permitting issues for terrestrial based carbon sequestration projects, consistency of final protocols and planning standards with national requirements, and alignments of carbon sequestration projects with existing federal and state cost-share programs. Finally, the education and outreach efforts during this performance period have resulted in a comprehensive plan which serves as a guide for implementing the outreach activities under Phase I. The primary goal of this plan is to increase awareness, understanding, and public acceptance of sequestration efforts and build support for a constituent based network which includes the initial Big Sky Partnership and other local and regional businesses and entities.

  4. BIG SKY CARBON SEQUESTRATION PARTNERSHIP

    SciTech Connect (OSTI)

    Susan M. Capalbo

    2005-01-31T23:59:59.000Z

    The Big Sky Carbon Sequestration Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts under this Partnership in Phase I fall into four areas: evaluation of sources and carbon sequestration sinks that will be used to determine the location of pilot demonstrations in Phase II; development of GIS-based reporting framework that links with national networks; designing an integrated suite of monitoring, measuring, and verification technologies and assessment frameworks; and initiating a comprehensive education and outreach program. The groundwork is in place to provide an assessment of storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that would complement the ongoing DOE research. Efforts are underway to showcase the architecture of the GIS framework and initial results for sources and sinks. The region has a diverse array of geological formations that could provide storage options for carbon in one or more of its three states. Likewise, initial estimates of terrestrial sinks indicate a vast potential for increasing and maintaining soil C on forested, agricultural, and reclaimed lands. Both options include the potential for offsetting economic benefits to industry and society. Steps have been taken to assure that the GIS-based framework is consistent among types of sinks within the Big Sky Partnership area and with the efforts of other western DOE partnerships. The Partnership recognizes the critical importance of measurement, monitoring, and verification technologies to support not only carbon trading but all policies and programs that DOE and other agencies may want to pursue in support of GHG mitigation. The efforts in developing and implementing MMV technologies for geological sequestration reflect this concern. Research is also underway to identify and validate best management practices for soil C in the Partnership region, and to design a risk/cost effectiveness framework to make comparative assessments of each viable sink, taking into account economic costs, offsetting benefits, scale of sequestration opportunities, spatial and time dimensions, environmental risks, and long-term viability. Scientifically sound information on MMV is critical for public acceptance of these technologies.

  5. Sloan Digital Sky Survey (SDSS): Data Release 3

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

    The Sloan Digital Sky Survey (SDSS) is one of the most ambitious and influential surveys in the history of astronomy.Over eight years of operations (SDSS-I, 2000-2005; SDSS-II, 2005-2008), it obtained deep, multi-color images covering more than a quarter of the sky and created 3-dimensional maps containing more than 930,000 galaxies and more than 120,000 quasars. The SDSS used a dedicated 2.5-meter telescope at Apache Point Observatory, New Mexico, equipped with two powerful special-purpose instruments. SDSS data have supported fundamental work across an extraordinary range of astronomical disciplines, including the properties of galaxies, the evolution of quasars, the structure and stellar populations of the Milky Way, the dwarf galaxy companions of the Milky Way and M31, asteroids and other small bodies in the solar system, and the large scale structure and matter and energy contents of the universe. (Taken from home page of www.sdss.org). DR3 provides provides images, imaging catalogs, spectra, and redshifts for download.

  6. Sloan Digital Sky Survey (SDSS): Data Release 1

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

    The Sloan Digital Sky Survey (SDSS) is one of the most ambitious and influential surveys in the history of astronomy.Over eight years of operations (SDSS-I, 2000-2005; SDSS-II, 2005-2008), it obtained deep, multi-color images covering more than a quarter of the sky and created 3-dimensional maps containing more than 930,000 galaxies and more than 120,000 quasars. The SDSS used a dedicated 2.5-meter telescope at Apache Point Observatory, New Mexico, equipped with two powerful special-purpose instruments. SDSS data have supported fundamental work across an extraordinary range of astronomical disciplines, including the properties of galaxies, the evolution of quasars, the structure and stellar populations of the Milky Way, the dwarf galaxy companions of the Milky Way and M31, asteroids and other small bodies in the solar system, and the large scale structure and matter and energy contents of the universe. (Taken from home page of www.sdss.org). DR1 was the first major data release, providing images, imaging catalogs, spectra, and redshifts for download.

  7. Sloan Digital Sky Survey (SDSS): Data Release 4

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

    The Sloan Digital Sky Survey (SDSS) is one of the most ambitious and influential surveys in the history of astronomy.Over eight years of operations (SDSS-I, 2000-2005; SDSS-II, 2005-2008), it obtained deep, multi-color images covering more than a quarter of the sky and created 3-dimensional maps containing more than 930,000 galaxies and more than 120,000 quasars. The SDSS used a dedicated 2.5-meter telescope at Apache Point Observatory, New Mexico, equipped with two powerful special-purpose instruments. SDSS data have supported fundamental work across an extraordinary range of astronomical disciplines, including the properties of galaxies, the evolution of quasars, the structure and stellar populations of the Milky Way, the dwarf galaxy companions of the Milky Way and M31, asteroids and other small bodies in the solar system, and the large scale structure and matter and energy contents of the universe. (Taken from home page of www.sdss.org). DR4 provides provides images, imaging catalogs, spectra, and redshifts for download.

  8. Sloan Digital Sky Survey (SDSS): Data Release 2

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

    The Sloan Digital Sky Survey (SDSS) is one of the most ambitious and influential surveys in the history of astronomy.Over eight years of operations (SDSS-I, 2000-2005; SDSS-II, 2005-2008), it obtained deep, multi-color images covering more than a quarter of the sky and created 3-dimensional maps containing more than 930,000 galaxies and more than 120,000 quasars. The SDSS used a dedicated 2.5-meter telescope at Apache Point Observatory, New Mexico, equipped with two powerful special-purpose instruments. SDSS data have supported fundamental work across an extraordinary range of astronomical disciplines, including the properties of galaxies, the evolution of quasars, the structure and stellar populations of the Milky Way, the dwarf galaxy companions of the Milky Way and M31, asteroids and other small bodies in the solar system, and the large scale structure and matter and energy contents of the universe. (Taken from home page of www.sdss.org). DR2 provides provides images, imaging catalogs, spectra, and redshifts for download.

  9. Sloan Digital Sky Survey (SDSS): Data Release 5

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

    The Sloan Digital Sky Survey (SDSS) is one of the most ambitious and influential surveys in the history of astronomy.Over eight years of operations (SDSS-I, 2000-2005; SDSS-II, 2005-2008), it obtained deep, multi-color images covering more than a quarter of the sky and created 3-dimensional maps containing more than 930,000 galaxies and more than 120,000 quasars. The SDSS used a dedicated 2.5-meter telescope at Apache Point Observatory, New Mexico, equipped with two powerful special-purpose instruments. SDSS data have supported fundamental work across an extraordinary range of astronomical disciplines, including the properties of galaxies, the evolution of quasars, the structure and stellar populations of the Milky Way, the dwarf galaxy companions of the Milky Way and M31, asteroids and other small bodies in the solar system, and the large scale structure and matter and energy contents of the universe. (Taken from home page of www.sdss.org). DR5 provides provides images, imaging catalogs, spectra, and redshifts for download.

  10. Sensitivity improvements for Shack-Hartmann wavefront sensors using total variation minimisation

    E-Print Network [OSTI]

    Basden, Alastair

    2015-01-01T23:59:59.000Z

    We investigate the improvements in Shack-Hartmann wavefront sensor image processing that can be realised using total variation minimisation techniques to remove noise from these images. We perform Monte-Carlo simulation to demonstrate that at certain signal-to-noise levels, sensitivity improvements of up to one astronomical magnitude can be realised. We also present on-sky measurements taken with the CANARY adaptive optics system that demonstrate an improvement in performance when this technique is employed, and show that this algorithm can be implemented in a real-time control system. We conclude that total variation minimisation can lead to improvements in sensitivity of up to one astronomical magnitude when used with adaptive optics systems.

  11. Discovery of Eight z ~ 6 Quasars in the Sloan Digital Sky Survey Overlap Regions

    E-Print Network [OSTI]

    Jiang, Linhua; Fan, Xiaohui; Bian, Fuyan; Cai, Zheng; Clement, Benjamin; Wang, Ran; Fan, Zhou

    2015-01-01T23:59:59.000Z

    We present the discovery of eight quasars at z~6 identified in the Sloan Digital Sky Survey (SDSS) overlap regions. Individual SDSS imaging runs have some overlap with each other, leading to repeat observations over an area spanning >4000 deg^2 (more than 1/4 of the total footprint). These overlap regions provide a unique dataset that allows us to select high-redshift quasars more than 0.5 mag fainter in the z band than those found with the SDSS single-epoch data. Our quasar candidates were first selected as i-band dropout objects in the SDSS imaging database. We then carried out a series of follow-up observations in the optical and near-IR to improve photometry, remove contaminants, and identify quasars. The eight quasars reported here were discovered in a pilot study utilizing the overlap regions at high galactic latitude (|b|>30 deg). These quasars span a redshift range of 5.86

  12. Optimization Online - Total variation superiorization schemes in ...

    E-Print Network [OSTI]

    S.N. Penfold

    2010-10-08T23:59:59.000Z

    Oct 8, 2010 ... Total variation superiorization schemes in proton computed tomography ... check improved the image quality, in particular image noise, in the ...

  13. A Robotic Wide-Angle H-Alpha Survey of the Southern Sky

    E-Print Network [OSTI]

    J. E. Gaustad; P. R. McCullough; W. Rosing; D. Van Buren

    2001-08-31T23:59:59.000Z

    We have completed a robotic wide-angle imaging survey of the southern sky (declination less than +15 degrees) at 656.3 nm wavelength, the H-alpha emission line of hydrogen. Each image of the resulting Southern H-Alpha Sky Survey Atlas (SHASSA) covers an area of the sky 13 degrees square at an angular resolution of approximately 0.8 arcminute, and reaches a sensitivity level of 2 rayleigh (1.2 x 10^-17 erg cm^-2 s^-1 arcsec^-2) per pixel, corresponding to an emission measure of 4 cm^-6 pc, and to a brightness temperature for microwave free-free emission of 12 microkelvins at 30 GHz. Smoothing over several pixels allows features as faint as 0.5 rayleigh to be detected.

  14. Sky coverage of orbital detectors. Analytical approach

    E-Print Network [OSTI]

    Diego Casadei

    2005-12-28T23:59:59.000Z

    Orbital detectors without pointing capability have to keep their field of view axis laying on their orbital plane, to observe the largest sky fraction. A general approach to estimate the exposure of each sky element for such detectors is a valuable tool in the R&D phase of a project, when the detector characteristics are still to be fixed. An analytical method to estimate the sky exposure is developed, which makes only few very reasonable approximations. The formulae obtained with this method are used to compute the histogram of the sky exposure of a hypothetical gamma-ray detector installed on the ISS. The C++ code used in this example is freely available on the http://cern.ch/casadei/software.html web page.

  15. Big Sky Carbon Sequestration Partnership

    SciTech Connect (OSTI)

    Susan M. Capalbo

    2005-11-01T23:59:59.000Z

    The Big Sky Carbon Sequestration Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts under this Partnership in Phase I fall into four areas: evaluation of sources and carbon sequestration sinks that will be used to determine the location of pilot demonstrations in Phase II; development of GIS-based reporting framework that links with national networks; designing an integrated suite of monitoring, measuring, and verification technologies and assessment frameworks; and initiating a comprehensive education and outreach program. The groundwork is in place to provide an assessment of storage capabilities for CO2 utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that would complement the ongoing DOE research agenda in Carbon Sequestration. The region has a diverse array of geological formations that could provide storage options for carbon in one or more of its three states. Likewise, initial estimates of terrestrial sinks indicate a vast potential for increasing and maintaining soil C on forested, agricultural, and reclaimed lands. Both options include the potential for offsetting economic benefits to industry and society. Steps have been taken to assure that the GIS-based framework is consistent among types of sinks within the Big Sky Partnership area and with the efforts of other DOE regional partnerships. The Partnership recognizes the critical importance of measurement, monitoring, and verification technologies to support not only carbon trading but all policies and programs that DOE and other agencies may want to pursue in support of GHG mitigation. The efforts in developing and implementing MMV technologies for geological sequestration reflect this concern. Research is also underway to identify and validate best management practices for soil C in the Partnership region, and to design a risk/cost effectiveness framework to make comparative assessments of each viable sink, taking into account economic costs, offsetting benefits, scale of sequestration opportunities, spatial and time dimensions, environmental risks, and long-term viability. Scientifically sound MMV is critical for public acceptance of these technologies. Deliverables for the 7th Quarter reporting period include (1) for the geological efforts: Reports on Technology Needs and Action Plan on the Evaluation of Geological Sinks and Pilot Project Deployment (Deliverables 2 and 3), and Report on the Feasibility of Mineralization Trapping in the Snake River Plain Basin (Deliverable 14); (2) for the terrestrial efforts: Report on the Evaluation of Terrestrial Sinks and a Report of the Best Production Practices for Soil C Sequestration (Deliverables 8 and 15). In addition, the 7th Quarter activities for the Partnership included further development of the proposed activities for the deployment and demonstration phase of the carbon sequestration pilots including geological and terrestrial pilots, expansion of the Partnership to encompass regions and institutions that are complimentary to the steps we have identified, building greater collaborations with industry and stakeholders in the region, contributed to outreach efforts that spanned all partnerships, co-authorship on the Carbon Capture and Separation report, and developed a regional basis to address future energy opportunities in the region. The deliverables and activities are discussed in the following sections and appended to this report. The education and outreach efforts have resulted in a comprehensive plan which serves as a guide for implementing the outreach activities under Phase I. The public website has been expanded and integrated with the GIS carbon atlas. We have made presentations to stakeholders and policy makers including two tribal sequestration workshops, and made connections to other federal and state agencies concerned with GHG emissions, climate change, and efficient and environmental

  16. BIG SKY CARBON SEQUESTRATION PARTNERSHIP

    SciTech Connect (OSTI)

    Susan M. Capalbo

    2004-10-31T23:59:59.000Z

    The Big Sky Carbon Sequestration Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts under this Partnership fall into four areas: evaluation of sources and carbon sequestration sinks; development of GIS-based reporting framework; designing an integrated suite of monitoring, measuring, and verification technologies; and initiating a comprehensive education and outreach program. At the first two Partnership meetings the groundwork was put in place to provide an assessment of capture and storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that would complement the ongoing DOE research. During the third quarter, planning efforts are underway for the next Partnership meeting which will showcase the architecture of the GIS framework and initial results for sources and sinks, discuss the methods and analysis underway for assessing geological and terrestrial sequestration potentials. The meeting will conclude with an ASME workshop. The region has a diverse array of geological formations that could provide storage options for carbon in one or more of its three states. Likewise, initial estimates of terrestrial sinks indicate a vast potential for increasing and maintaining soil C on forested, agricultural, and reclaimed lands. Both options include the potential for offsetting economic benefits to industry and society. Steps have been taken to assure that the GIS-based framework is consistent among types of sinks within the Big Sky Partnership area and with the efforts of other western DOE partnerships. Efforts are also being made to find funding to include Wyoming in the coverage areas for both geological and terrestrial sinks and sources. The Partnership recognizes the critical importance of measurement, monitoring, and verification technologies to support not only carbon trading but all policies and programs that DOE and other agencies may want to pursue in support of GHG mitigation. The efforts begun in developing and implementing MMV technologies for geological sequestration reflect this concern. Research is also underway to identify and validate best management practices for soil C in the Partnership region, and to design a risk/cost effectiveness framework to make comparative assessments of each viable sink, taking into account economic costs, offsetting benefits, scale of sequestration opportunities, spatial and time dimensions, environmental risks, and long-term viability. Scientifically sound information on MMV is critical for public acceptance of these technologies. Two key deliverables were completed in the second quarter--a literature review/database to assess the soil carbon on rangelands, and the draft protocols, contracting options for soil carbon trading. The protocols developed for soil carbon trading are unique and provide a key component of the mechanisms that might be used to efficiently sequester GHG and reduce CO{sub 2} concentrations. While no key deliverables were due during the third quarter, progress on other deliverables is noted in the PowerPoint presentations and in this report. A series of meetings held during the second and third quarters have laid the foundations for assessing the issues surrounding carbon sequestration in this region, the need for a holistic approach to meeting energy demands and economic development potential, and the implementation of government programs or a market-based setting for soil C credits. These meetings provide a connection to stakeholders in the region and a basis on which to draw for the DOE PEIS hearings. In the fourth quarter, three deliverables have been completed, some in draft form to be revised and updated to include Wyoming. This is due primarily to some delays in funding to LANL and INEEL and the approval of a supplemental proposal to include Wyoming in much of the GIS data sets, analysis, and related materials. The de

  17. BIG SKY CARBON SEQUESTRATION PARTNERSHIP

    SciTech Connect (OSTI)

    Susan M. Capalbo

    2004-06-30T23:59:59.000Z

    The Big Sky Carbon Sequestration Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts under this Partnership fall into four areas: evaluation of sources and carbon sequestration sinks; development of GIS-based reporting framework; designing an integrated suite of monitoring, measuring, and verification technologies; and initiating a comprehensive education and outreach program. At the first two Partnership meetings the groundwork was put in place to provide an assessment of capture and storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that would complement the ongoing DOE research. During the third quarter, planning efforts are underway for the next Partnership meeting which will showcase the architecture of the GIS framework and initial results for sources and sinks, discuss the methods and analysis underway for assessing geological and terrestrial sequestration potentials. The meeting will conclude with an ASME workshop (see attached agenda). The region has a diverse array of geological formations that could provide storage options for carbon in one or more of its three states. Likewise, initial estimates of terrestrial sinks indicate a vast potential for increasing and maintaining soil C on forested, agricultural, and reclaimed lands. Both options include the potential for offsetting economic benefits to industry and society. Steps have been taken to assure that the GIS-based framework is consistent among types of sinks within the Big Sky Partnership area and with the efforts of other western DOE partnerships. Efforts are also being made to find funding to include Wyoming in the coverage areas for both geological and terrestrial sinks and sources. The Partnership recognizes the critical importance of measurement, monitoring, and verification technologies to support not only carbon trading but all policies and programs that DOE and other agencies may want to pursue in support of GHG mitigation. The efforts begun in developing and implementing MMV technologies for geological sequestration reflect this concern. Research is also underway to identify and validate best management practices for soil C in the Partnership region, and to design a risk/cost effectiveness framework to make comparative assessments of each viable sink, taking into account economic costs, offsetting benefits, scale of sequestration opportunities, spatial and time dimensions, environmental risks, and long-term viability. Scientifically sound information on MMV is critical for public acceptance of these technologies. Two key deliverables were completed in the second quarter--a literature review/database to assess the soil carbon on rangelands, and the draft protocols, contracting options for soil carbon trading. The protocols developed for soil carbon trading are unique and provide a key component of the mechanisms that might be used to efficiently sequester GHG and reduce CO2 concentrations. While no key deliverables were due during the third quarter, progress on other deliverables is noted in the PowerPoint presentations and in this report. A series of meetings held during the second and third quarters have laid the foundations for assessing the issues surrounding carbon sequestration in this region, the need for a holistic approach to meeting energy demands and economic development potential, and the implementation of government programs or a market-based setting for soil C credits. These meetings provide a connection to stakeholders in the region and a basis on which to draw for the DOE PEIS hearings. A third Partnership meeting has been planned for August 04 in Idaho Falls; a preliminary agenda is attached.

  18. What Do the Sun and the Sky Tell Us About the Camera? Jean-Francois Lalonde, Srinivasa G. Narasimhan, and Alexei A. Efros

    E-Print Network [OSTI]

    Treuille, Adrien

    What Do the Sun and the Sky Tell Us About the Camera? Jean-Fran¸cois Lalonde, Srinivasa G in computer vision because its appearance in an image depends on the sun position, weather conditions sources of information available within the visible portion of the sky region: the sun position

  19. Big Sky Carbon Sequestration Partnership

    SciTech Connect (OSTI)

    Susan Capalbo

    2005-12-31T23:59:59.000Z

    The Big Sky Carbon Sequestration Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts under this Partnership in Phase I are organized into four areas: (1) Evaluation of sources and carbon sequestration sinks that will be used to determine the location of pilot demonstrations in Phase II; (2) Development of GIS-based reporting framework that links with national networks; (3) Design of an integrated suite of monitoring, measuring, and verification technologies, market-based opportunities for carbon management, and an economic/risk assessment framework; (referred to below as the Advanced Concepts component of the Phase I efforts) and (4) Initiation of a comprehensive education and outreach program. As a result of the Phase I activities, the groundwork is in place to provide an assessment of storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that complements the ongoing DOE research agenda in Carbon Sequestration. The geology of the Big Sky Carbon Sequestration Partnership Region is favorable for the potential sequestration of enormous volume of CO{sub 2}. The United States Geological Survey (USGS 1995) identified 10 geologic provinces and 111 plays in the region. These provinces and plays include both sedimentary rock types characteristic of oil, gas, and coal productions as well as large areas of mafic volcanic rocks. Of the 10 provinces and 111 plays, 1 province and 4 plays are located within Idaho. The remaining 9 provinces and 107 plays are dominated by sedimentary rocks and located in the states of Montana and Wyoming. The potential sequestration capacity of the 9 sedimentary provinces within the region ranges from 25,000 to almost 900,000 million metric tons of CO{sub 2}. Overall every sedimentary formation investigated has significant potential to sequester large amounts of CO{sub 2}. Simulations conducted to evaluate mineral trapping potential of mafic volcanic rock formations located in the Idaho province suggest that supercritical CO{sub 2} is converted to solid carbonate mineral within a few hundred years and permanently entombs the carbon. Although MMV for this rock type may be challenging, a carefully chosen combination of geophysical and geochemical techniques should allow assessment of the fate of CO{sub 2} in deep basalt hosted aquifers. Terrestrial carbon sequestration relies on land management practices and technologies to remove atmospheric CO{sub 2} where it is stored in trees, plants, and soil. This indirect sequestration can be implemented today and is on the front line of voluntary, market-based approaches to reduce CO{sub 2} emissions. Initial estimates of terrestrial sinks indicate a vast potential for increasing and maintaining soil Carbon (C) on rangelands, and forested, agricultural, and reclaimed lands. Rangelands can store up to an additional 0.05 mt C/ha/yr, while the croplands are on average four times that amount. Estimates of technical potential for soil sequestration within the region in cropland are in the range of 2.0 M mt C/yr over 20 year time horizon. This is equivalent to approximately 7.0 M mt CO{sub 2}e/yr. The forestry sinks are well documented, and the potential in the Big Sky region ranges from 9-15 M mt CO{sub 2} equivalent per year. Value-added benefits include enhanced yields, reduced erosion, and increased wildlife habitat. Thus the terrestrial sinks provide a viable, environmentally beneficial, and relatively low cost sink that is available to sequester C in the current time frame. The Partnership recognizes the critical importance of measurement, monitoring, and verification technologies to support not only carbon trading but all policies and programs that DOE and other agencies may want to pursue in support of GHG mitigation. The efforts in developing and implementing MMV technologies for geological and terrestrial sequestration re

  20. AN ALL-SKY CATALOG OF BRIGHT M DWARFS

    SciTech Connect (OSTI)

    Lepine, Sebastien [Department of Astrophysics, Division of Physical Sciences, American Museum of Natural History, Central Park West at 79th Street, New York, NY 10024 (United States); Gaidos, Eric [Department of Geology and Geophysics, University of Hawaii, 1680 East-West Road, Honolulu, HI 96822 (United States)

    2011-10-15T23:59:59.000Z

    We present an all-sky catalog of M dwarf stars with apparent infrared magnitude J < 10. The 8889 stars are selected from the ongoing SUPERBLINK survey of stars with proper motion {mu} > 40 mas yr{sup -1}, supplemented on the bright end with the Tycho-2 catalog. Completeness tests which account for kinematic (proper motion) bias suggest that our catalog represents {approx}75% of the estimated {approx}11, 900 M dwarfs with J < 10 expected to populate the entire sky. Our catalog is, however, significantly more complete for the northern sky ({approx}90%) than it is for the south ({approx}60%). Stars are identified as cool, red M dwarfs from a combination of optical and infrared color cuts, and are distinguished from background M giants and highly reddened stars using either existing parallax measurements or, if such measurements are lacking, using their location in an optical-to-infrared reduced proper motion diagram. These bright M dwarfs are all prime targets for exoplanet surveys using the Doppler radial velocity or transit methods; the combination of low-mass and bright apparent magnitude should make possible the detection of Earth-size planets on short-period orbits using currently available techniques. Parallax measurements, when available, and photometric distance estimates are provided for all stars, and these place most systems within 60 pc of the Sun. Spectral type estimated from V - J color shows that most of the stars range from K7 to M4, with only a few late M dwarfs, all within 20 pc. Proximity to the Sun also makes these stars good targets for high-resolution exoplanet imaging searches, especially if younger objects can be identified on the basis of X-ray or UV excess. For that purpose, we include X-ray flux from ROSAT and FUV/NUV ultraviolet magnitudes from GALEX for all stars for which a counterpart can be identified in those catalogs. Additional photometric data include optical magnitudes from Digitized Sky Survey plates and infrared magnitudes from the Two Micron All Sky Survey.

  1. Sloan Digital Sky Survey II (SDSS-II) Supernova Data

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

    The Sloan Digital Sky Survey (SDSS) is a series of three interlocking imaging and spectroscopic surveys, carried out over an eight-year period with a dedicated 2.5m telescope located at Apache Point Observatory in Southern New Mexico. The SDSS Supernova Survey was one of those three components of SDSS and SDSS-II, a 3-year extension of the original SDSS that operated from July 2005 to July 2008. The Supernova Survey was a time-domain survey, involving repeat imaging of the same region of sky every other night, weather permitting. The primary scientific motivation was to detect and measure light curves for several hundred supernovae through repeat scans of the SDSS Southern equatorial stripe 82 (about 2.5? wide by ~120? long). Over the course of three 3-month campaigns SDSS-II SN discovered and measured multi-band lightcurves for ~500 spectroscopically confirmed Type Ia supernovae in the redshift range z=0.05-0.4. In addition, the project harvested a few hundred light curves for SNe Ia and discovered about 80 spectroscopically confirmed core-collapse supernovae (supernova types Ib/c and II).

  2. TASS Mark IV Photometric Survey of the Northern Sky

    E-Print Network [OSTI]

    Thomas F. Droege; Michael W. Richmond; Michael P. Sallman; Robert P. Creager

    2006-10-17T23:59:59.000Z

    The Amateur Sky Survey (TASS) is a loose confederation of amateur and professional astronomers. We describe the design and construction of our Mark IV systems, a set of wide-field telescopes with CCD cameras which take simultaneous images in the $V$ and $I_C$ passbands. We explain our observational procedures and the pipeline which processes and reduces the images into lists of stellar positions and magnitudes. We have compiled a large database of measurements for stars in the northern celestial hemisphere with $V$-band magnitudes in the range 7 < V < 13. This paper describes data taken over the four-year period starting November, 2001. One of our results is a catalog of repeated measurements on the Johnson-Cousins system for over 4.3 million stars.

  3. Cloudy Sky Version of Bird's Broadband Hourly Clear Sky Model (Presentation)

    SciTech Connect (OSTI)

    Myers, D.

    2006-08-01T23:59:59.000Z

    Presentation on Bird's Broadband Hourly Clear Sky Model given by NREL's Daryl Myers at SOLAR 2006. The objective of this report is to produce ''all sky'' modeled hourly solar radiation. This is based on observed cloud cover data using a SIMPLE model.

  4. Sloan Digital Sky Survey III (SDSS-III), Data Release 8

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

    Building on the legacy of the Sloan Digital Sky Survey (SDSS) and SDSS-II, the SDSS-III Collaboration is working to map the Milky Way, search for extrasolar planets, and solve the mystery of dark energy. SDSS-III's first release, Data Release 8 (DR8), became available in the first half of 2012. DR8 contains all the images ever taken by the SDSS telescope. Together, these images make up the largest color image of the sky ever made. A version of the DR8 image is shown to the right. DR8 also includes measurements for nearly 500 million stars, galaxies, and quasars, and spectra for nearly two million. All of DR8's images, spectra, and measurements are available to anyone online. You can browse through sky images, look up data for individual objects, or search for objects anywhere using any criteria. SDSS-III will collect data from 2008 to 2014, using the 2.5-meter telescope at Apache Point Observatory. SDSS-III consists of four surveys, each focused on a different scientific theme. These four surveys are: 1) Baryon Oscillation Spectroscopic Survey (BOSS); 2) SEGUE-2 (Sloan Extension for Galactic Understanding and Exploration); 3) The APO Galactic Evolution Experiment (APOGEE); and 4) The Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). [Copied with edits from http://www.sdss3.org/index.php

  5. Multi-Wavelength Image Space: Another Grid-Enabled Science Roy Williams1

    E-Print Network [OSTI]

    Williams, Roy

    paradigm for mining knowledge from the images of the sky surveys: by federating the images directly We describe a new Grid-enabled branch of astronomy: multi-wavelength images. To see sky images-wavelength image. We will describe both scientific goals, and also how grid computing can open this new field

  6. Remote sensing of total integrated water vapor, wind speed, and cloud liquid water over the ocean using the Special Sensor Microwave/Imager (SSM/I)

    E-Print Network [OSTI]

    Manning, Norman Willis William

    1997-01-01T23:59:59.000Z

    A modified D-matrix retrieval method is the basis of the refined total integrated water vapor (TIWV), total integrated cloud liquid water (CLW), and surface wind speed (WS) retrieval methods that are developed. The 85 GHZ polarization difference...

  7. Sky Solar Global SA | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit with form HistoryRistmaSinosteel Corporation Jump to: navigation,SiriSkySky Solar

  8. SkyFuel Inc | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit with form HistoryRistmaSinosteel Corporation Jump to: navigation,SiriSkySky

  9. Accounting for Circumsolar and Horizon Cloud Determination Errors in Sky Image Inferral of Sky Cover

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP7-0973 1 Introduction In theACMEAccountable Property

  10. Dusty WDs in the WISE all sky survey ? SDSS

    SciTech Connect (OSTI)

    Barber, Sara D.; Kilic, Mukremin; Gianninas, A. [Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, 440 W. Brooks St., Norman, OK 73019 (United States); Brown, Warren R., E-mail: barber@nhn.ou.edu [Smithsonian Astrophysical Observatory, 60 Garden Street, Cambridge, MA 02138 (United States)

    2014-05-10T23:59:59.000Z

    A recent cross-correlation between the Sloan Digital Sky Survey (SDSS) Data Release 7 White Dwarf Catalog with the Wide-Field Infrared Survey Explorer (WISE) all-sky photometry at 3.4, 4.6, 12, and 22 ?m performed by Debes et al. resulted in the discovery of 52 candidate dusty white dwarfs (WDs). However, the 6'' WISE beam allows for the possibility that many of the excesses exhibited by these WDs may be due to contamination from a nearby source. We present MMT+SAO Wide-Field InfraRed Camera J- and H-band imaging observations (0.''5-1.''5 point spread function) of 16 of these candidate dusty WDs and confirm that four have spectral energy distributions (SEDs) consistent with a dusty disk and are not accompanied by a nearby source contaminant. The remaining 12 WDs have contaminated WISE photometry and SEDs inconsistent with a dusty disk when the contaminating sources are not included in the photometry measurements. We find the frequency of disks around single WDs in the WISE ? SDSS sample to be 2.6%-4.1%. One of the four new dusty WDs has a mass of 1.04 M {sub ?} (progenitor mass 5.4 M {sub ?}) and its discovery offers the first confirmation that massive WDs (and their massive progenitor stars) host planetary systems.

  11. SURVEYING THE TEV SKY WITH SABRINA CASANOVA

    E-Print Network [OSTI]

    California at Santa Cruz, University of

    survey of the Northern Hemisphere sky at TeV energies. In addition to detecting the Crab Nebula and Mrk. Recently the Milagro Collaboration has reported the detection of very high energy (VHE) gamma rays from the Cygnus Region. In this region evidence for diffuse emission and for a new TeV source, coincident

  12. Influence of sky conditions on carbon dioxide uptake by forests 

    E-Print Network [OSTI]

    Dengel, Sigrid

    2009-01-01T23:59:59.000Z

    Sky conditions play an important role in the Earth’s climate system, altering the solar radiation reaching the Earth’s surface and determining the fraction of incoming direct and diffuse radiation. Sky conditions dictate ...

  13. Satellite measurements of the clear-sky greenhouse effect from

    E-Print Network [OSTI]

    Waliser, Duane E.

    LETTERS Satellite measurements of the clear-sky greenhouse effect from tropospheric ozone HELEN M of 0.48±0.14 W m-2 between 45 S and 45 N. This estimate of the clear-sky greenhouse effect from

  14. Sloan Digital Sky Survey II (SDSS-II), Data Release 6, including Extension for Galactic Understanding and Exploration (SEGUE)

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

    Yanny, Brian; Rockosi, Constance; Newberg, Heidi Jo; Knapp, Gillian R.

    The Sloan Digital Sky Survey (see www.sdss.org for general information) will map one-quarter of the entire sky and perform a redshift survey of galaxies, quasars and stars. The DR6 is the sixth major data release and provides images, imaging catalogs, spectra, and redshifts for download. It is the first data release of SDSS-II, an extension of the original SDSS consisting of three subprojects: Legacy, SEGUE and a Supernova survey. Be sure to check out the separate page for SEGUE also at http://classic.sdss.org/dr6/start/aboutsegue.html.

  15. TOTAL M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total M F Total Spring 2010

    E-Print Network [OSTI]

    Hayes, Jane E.

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

  16. Total Energy Monitor

    SciTech Connect (OSTI)

    Friedrich, S

    2008-08-11T23:59:59.000Z

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

  17. ARM - Field Campaign - Whole Sky Imager Cloud Fraction Data

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

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

  18. Deep Sky Astronomical Image Database Project at NERSC

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management FermiDavid Turner David3 | National Nuclear6DecodingDeep

  19. The Animated Gamma-ray Sky Revealed by the Fermi Gamma-ray Space Telescope

    ScienceCinema (OSTI)

    Isabelle Grenier

    2010-01-08T23:59:59.000Z

    The Fermi Gamma-ray Space Telescope has been observing the sky in gamma-rays since August 2008.  In addition to breakthrough capabilities in energy coverage (20 MeV-300 GeV) and angular resolution, the wide field of view of the Large Area Telescope enables observations of 20% of the sky at any instant, and of the whole sky every three hours. It has revealed a very animated sky with bright gamma-ray bursts flashing and vanishing in minutes, powerful active galactic nuclei flaring over hours and days, many pulsars twinkling in the Milky Way, and X-ray binaries shimmering along their orbit. Most of these variable sources had not been seen by the Fermi predecessor, EGRET, and the wealth of new data already brings important clues to the origin of the high-energy emission and particles powered by the compact objects. The telescope also brings crisp images of the bright gamma-ray emission produced by cosmic-ray interactions in the interstellar medium, thus allowing to measure the cosmic nuclei and electron spectra across the Galaxy, to weigh interstellar clouds, in particular in the dark-gas phase. The telescope sensitivity at high energy will soon provide useful constraints on dark-matter annihilations in a variety of environments. I will review the current results and future prospects of the Fermi mission.

  20. Sloan Digital Sky Survey Photometric Calibration Revisited

    SciTech Connect (OSTI)

    Marriner, John; /Fermilab

    2012-06-29T23:59:59.000Z

    The Sloan Digital Sky Survey calibration is revisited to obtain the most accurate photometric calibration. A small but significant error is found in the flat-fielding of the Photometric telescope used for calibration. Two SDSS star catalogs are compared and the average difference in magnitude as a function of right ascension and declination exhibits small systematic errors in relative calibration. The photometric transformation from the SDSS Photometric Telescope to the 2.5 m telescope is recomputed and compared to synthetic magnitudes computed from measured filter bandpasses.

  1. SkyBuilt Power | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDITCalifornia Sector:Shrenik Industries Jump to:SimranSkyBuilt Power

  2. North Sky River | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRoseConcerns Jumpsource History View New PagesRiver Shores,North ShoreSky

  3. One Sky Homes | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRoseConcernsCompany Oil and GasOff the Grid 1BOG Jump to: navigation,Sky

  4. Big Sky Wind Facility | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia: EnergyAvignon,Belcher Homes JumpMaintenance |Big CreekBig SandySky

  5. Blue Sky Bio Fuels | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia: EnergyAvignon,Belcher HomesLyonsBirchBlockVI JumpBlueBlueBlue Sky

  6. Desert Sky Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489 No revision hasda62829c05bGabbs Valley AreaEnergyDerbyIIQueenSky

  7. ARM: Gridded (0.25 x 0.25 lat/lon) fractional cloud cover, clear-sky and all-sky shortwave flux over the SGP site.

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

    Gaustad, Krista; Gaustad, Krista; McFarlane, Sally; McFarlane, Sally

    Gridded (0.25 x 0.25 lat/lon) fractional cloud cover, clear-sky and all-sky shortwave flux over the SGP site.

  8. Multi-Wavelength Image Space: Another Grid-Enabled Science Roy Williams 1

    E-Print Network [OSTI]

    Deelman, Ewa

    the wavelengths. In this paper, we consider a new paradigm for mining knowledge from the images of the sky surveys multi- wavelength images. To see sky images in the same pixel space, they must be projected will describe both scientific goals, and also how grid computing can open this new field. The term multi

  9. SkyMine Carbon Mineralization Pilot Project

    SciTech Connect (OSTI)

    Christenson, Norm; Walters, Jerel

    2014-12-31T23:59:59.000Z

    This Topical Report addresses accomplishments achieved during Phase 2b of the SkyMine® Carbon Mineralization Pilot Project. The primary objectives of this project are to design, construct, and operate a system to capture CO2 from a slipstream of flue gas from a commercial coal-fired cement kiln, convert that CO2 to products having commercial value (i.e., beneficial use), show the economic viability of the CO2 capture and conversion process, and thereby advance the technology to the point of readiness for commercial scale demonstration and deployment. The overall process is carbon negative, resulting in mineralization of CO2 that would otherwise be released into the atmosphere. The project will also substantiate market opportunities for the technology by sales of chemicals into existing markets, and identify opportunities to improve technology performance and reduce costs at the commercial scale. The project is being conducted in two phases. The primary objectives of Phase 1 were to evaluate proven SkyMine® process chemistry for commercial pilot-scale operation and complete the preliminary design for the pilot plant to be built and operated in Phase 2, complete a NEPA evaluation, and develop a comprehensive carbon life cycle analysis. The objective of Phase 2b was to build the pilot plant to be operated and tested in Phase 2c.

  10. The sun's position in the sky

    E-Print Network [OSTI]

    Jenkins, Alejandro

    2012-01-01T23:59:59.000Z

    We express the position of the sun in the sky as a function of time and the observer's geographic coordinates. Our method is based on applying rotation matrices to vectors describing points on the celestial sphere. We also derive direct expressions, as functions of date of the year and geographic latitude, for the duration of daylight, the maximum and minimum altitudes of the sun, and the cardinal directions of sunrise and sunset. We discuss how to account for the eccentricity of the earth's orbit, the precessions of the equinoxes and the perihelion, the size of the solar disk, and atmospheric refraction. We illustrate these results by computing the dates of "Manhattanhenge" (when sunset aligns with the east-west streets on the man traffic grid for Manhattan, in New York City), by plotting the altitude of the sun over representative cities as a function of time, and by showing plots ("analemmas") for the position of the sun in the sky at a given hour of the day.

  11. SkyMine Carbon Mineralization Pilot Project

    SciTech Connect (OSTI)

    Joe Jones; Clive Barton; Mark Clayton; Al Yablonsky; David Legere

    2010-09-30T23:59:59.000Z

    This Topical Report addresses accomplishments achieved during Phase 1 of the SkyMine{reg_sign} Carbon Mineralization Pilot Project. The primary objectives of this project are to design, construct, and operate a system to capture CO{sub 2} from a slipstream of flue gas from a commercial coal-fired cement kiln, convert that CO{sub 2} to products having commercial value (i.e., beneficial use), show the economic viability of the CO{sub 2} capture and conversion process, and thereby advance the technology to a point of readiness for commercial scale demonstration and proliferation. The project will also substantiate market opportunities for the technology by sales of chemicals into existing markets, and identify opportunities to improve technology performance and reduce costs at commercial scale. The primary objectives of Phase 1 of the project were to elaborate proven SkyMine{reg_sign} process chemistry to commercial pilot-scale operation and complete the preliminary design ('Reference Plant Design') for the pilot plant to be built and operated in Phase 2. Additionally, during Phase 1, information necessary to inform a DOE determination regarding NEPA requirements for the project was developed, and a comprehensive carbon lifecycle analysis was completed. These items were included in the formal application for funding under Phase 2. All Phase 1 objectives were successfully met on schedule and within budget.

  12. NREL Success Stories - SkyFuel Partnership Reflects Bright Future

    ScienceCinema (OSTI)

    Jorgensen, Gary; Gee, Randy

    2013-05-29T23:59:59.000Z

    NREL Scientists and SkyFuel share a story about how their partnership has resulted in a revolutionary concentrating solar power technology ReflecTech Mirror Film.

  13. Imaging

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

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

  14. Imaging

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC) EnvironmentalGyroSolé(tm)Hydrogen StorageITERITERBuilding EnergyImaging Print The

  15. Imaging

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC) EnvironmentalGyroSolé(tm)Hydrogen StorageITERITERBuilding EnergyImaging Print

  16. Climatology of Mid-latitude Ionospheric Disturbances from the Very Large Array Low-frequency Sky Survey

    E-Print Network [OSTI]

    Helmboldt, J F; Cotton, W D

    2012-01-01T23:59:59.000Z

    The results of a climatological study of ionospheric disturbances derived from observations of cosmic sources from the Very Large Array (VLA) Low-frequency Sky Survey (VLSS) are presented. We have used the ionospheric corrections applied to the 74 MHz interferometric data within the VLSS imaging process to obtain fluctuation spectra for the total electron content (TEC) gradient on spatial scales from a few to hundreds of kilometers and temporal scales from less than one minute to nearly an hour. The observations sample nearly all times of day and all seasons. They also span latitudes and longitudes from 28 deg. N to 40 deg. N and 95 deg. W to 114 deg. W, respectively. We have binned and averaged the fluctuation spectra according to time of day, season, and geomagnetic (Kp index) and solar (F10.7) activity. These spectra provide a detailed, multi-scale account of seasonal and intraday variations in ionospheric activity with wavelike structures detected at wavelengths between about 35 and 250 km. In some cases,...

  17. The Sloan Digital Sky Survey Monitor Telescope Pipeline

    E-Print Network [OSTI]

    D. L. Tucker; S. Kent; M. W. Richmond; J. Annis; J. A. Smith; S. S. Allam; C. T. Rodgers; J. L. Stute; J. K. Adelman-McCarthy; J. Brinkmann; M. Doi; D. Finkbeiner; M. Fukugita; J. Goldston; B. Greenway; J. E. Gunn; J. S. Hendry; D. W. Hogg; S. -I. Ichikawa; Z. Ivezic; G. R. Knapp; H. Lampeitl; B. C. Lee; H. Lin; T. A. McKay; A. Merrelli; J. A. Munn; E. H. Neilsen, Jr.; H. J. Newberg; G. T. Richards; D. J. Schlegel; C. Stoughton; A. Uomoto; B. Yanny

    2006-08-26T23:59:59.000Z

    The photometric calibration of the Sloan Digital Sky Survey (SDSS) is a multi-step process which involves data from three different telescopes: the 1.0-m telescope at the US Naval Observatory (USNO), Flagstaff Station, Arizona (which was used to establish the SDSS standard star network); the SDSS 0.5-m Photometric Telescope (PT) at the Apache Point Observatory (APO), New Mexico (which calculates nightly extinctions and calibrates secondary patch transfer fields); and the SDSS 2.5-m telescope at APO (which obtains the imaging data for the SDSS proper). In this paper, we describe the Monitor Telescope Pipeline, MTPIPE, the software pipeline used in processing the data from the single-CCD telescopes used in the photometric calibration of the SDSS (i.e., the USNO 1.0-m and the PT). We also describe transformation equations that convert photometry on the USNO-1.0m u'g'r'i'z' system to photometry the SDSS 2.5m ugriz system and the results of various validation tests of the MTPIPE software. Further, we discuss the semi-automated PT factory, which runs MTPIPE in the day-to-day standard SDSS operations at Fermilab. Finally, we discuss the use of MTPIPE in current SDSS-related projects, including the Southern u'g'r'i'z' Standard Star project, the u'g'r'i'z' Open Star Clusters project, and the SDSS extension (SDSS-II).

  18. Atmospheric optical measurements during high altitude balloon flight, Part II: Sky luminances

    E-Print Network [OSTI]

    Boileau, Almerian R

    1961-01-01T23:59:59.000Z

    BALLOON FLIGHT, PART II, SKY LUMINANCES Almerian R. Boileaufor Luminance Plots', Fig. 6 Sky Luminance vs Altitude, Fig.7, et seq. Sky Luminance vs Altitude, Fig. 25, et seq.

  19. Atmospheric optical measurements in western Florida, Flight 112, Part II: Sky luminances

    E-Print Network [OSTI]

    Boileau, Almerian R

    1960-01-01T23:59:59.000Z

    by which the sky luminance and radiance distributions wereRecording schedule. Sky luminance distribution data wereof Data Lines used for Sky Luminance P l o t s , Figure 4

  20. HIGH-VELOCITY CLOUDS IN THE GALACTIC ALL SKY SURVEY. I. CATALOG

    SciTech Connect (OSTI)

    Moss, V. A.; Kummerfeld, J. K. [Sydney Institute for Astronomy, School of Physics A29, University of Sydney, Sydney, NSW 2006 (Australia); McClure-Griffiths, N. M.; Murphy, T. [CSIRO Astronomy and Space Science, ATNF, P.O. Box 76, Epping, NSW 1710 (Australia); Pisano, D. J. [Department of Physics, West Virginia University, P.O. Box 6315, Morgantown, WV 26506 (United States); Curran, J. R., E-mail: vmoss@physics.usyd.edu.au [School of Information Technologies, University of Sydney, Sydney, NSW 2006 (Australia)

    2013-11-01T23:59:59.000Z

    We present a catalog of high-velocity clouds (HVCs) from the Galactic All Sky Survey (GASS) of southern sky neutral hydrogen, which has 57 mK sensitivity and 1 km s{sup –1} velocity resolution and was obtained with the Parkes Telescope. Our catalog has been derived from the stray-radiation-corrected second release of GASS. We describe the data and our method of identifying HVCs and analyze the overall properties of the GASS population. We catalog a total of 1693 HVCs at declinations <0°, including 1111 positive velocity HVCs and 582 negative velocity HVCs. Our catalog also includes 295 anomalous velocity clouds (AVCs). The cloud line-widths of our HVC population have a median FWHM of ?19 km s{sup –1}, which is lower than that found in previous surveys. The completeness of our catalog is above 95% based on comparison with the HIPASS catalog of HVCs upon which we improve by an order of magnitude in spectral resolution. We find 758 new HVCs and AVCs with no HIPASS counterpart. The GASS catalog will shed unprecedented light on the distribution and kinematic structure of southern sky HVCs, as well as delve further into the cloud populations that make up the anomalous velocity gas of the Milky Way.

  1. Mining the Sky with Redshift Surveys

    E-Print Network [OSTI]

    Marc Davis; Jeffrey Newman

    2001-04-25T23:59:59.000Z

    Since the late 1970's, redshift surveys have been vital for progress in understanding large-scale structure in the Universe. The original CfA redshift survey collected spectra of 20-30 galaxies per clear night on a 1.5 meter telescope; over a two year period the project added ~2000 new redshifts to the literature. Subsequent low-z redshift surveys have been up to an order of magnitude larger, and ongoing surveys will yield a similar improvement over the generation preceding them. Full sky redshift surveys have a special role to play as predictors of cosmological flows, and deep pencil beam surveys have provided fundamental constraints on the evolution of properties of galaxies. With the 2DF redshift survey and the SDSS survey, our knowledge of the statistical clustering of low-redshift galaxies will achieve unprecedented precision. Measurements of clustering in the distant Universe are more limited at present, but will become much better in this decade as the VLT/VIRMOS and Keck/DEIMOS projects produce results. As in so many other fields, progress in large scale structure studies, both observational and theoretical, has been made possible by improvements in technologies, especially computing. This review briefly highlights twenty years of progress in this evolving discipline and describes a few novel cosmological tests that will be attempted with the Keck/DEIMOS survey.

  2. artificial night sky: Topics by E-print Network

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

    the Canadian High Arctic. Law, Nicholas M; Wulfken, Philip; Ratzloff, Jeffrey; Kavanaugh, Dustin 2014-01-01 110 The i-band Sky brightness and Transparency at Dome A, Antarctica...

  3. Evaluation of Clear Sky Models for Satellite-Based Irradiance Estimates

    SciTech Connect (OSTI)

    Sengupta, M.; Gotseff, P.

    2013-12-01T23:59:59.000Z

    This report describes an intercomparison of three popular broadband clear sky solar irradiance model results with measured data, as well as satellite-based model clear sky results compared to measured clear sky data. The authors conclude that one of the popular clear sky models (the Bird clear sky model developed by Richard Bird and Roland Hulstrom) could serve as a more accurate replacement for current satellite-model clear sky estimations. Additionally, the analysis of the model results with respect to model input parameters indicates that rather than climatological, annual, or monthly mean input data, higher-time-resolution input parameters improve the general clear sky model performance.

  4. LOW-FREQUENCY IMAGING OF FIELDS AT HIGH GALACTIC LATITUDE WITH THE MURCHISON WIDEFIELD ARRAY 32 ELEMENT PROTOTYPE

    SciTech Connect (OSTI)

    Williams, Christopher L.; Hewitt, Jacqueline N.; Levine, Alan M. [MIT Kavli Institute for Astrophysics and Space Research, Cambridge, MA (United States); De Oliveira-Costa, Angelica; Hernquist, Lars L.; Bernardi, Gianni [Harvard-Smithsonian Center for Astrophysics, Cambridge, MA (United States); Bowman, Judd D. [School of Earth and Space Exploration, Arizona State University, Tempe, AZ (United States); Briggs, Frank H. [Research School of Astronomy and Astrophysics, The Australian National University, Canberra (Australia); Gaensler, B. M.; Mitchell, Daniel A.; Subrahmanyan, Ravi; Sadler, Elaine M. [ARC Centre of Excellence for All-sky Astrophysics (CAASTRO) (Australia); Morales, Miguel F. [Department of Physics, University of Washington, Seattle, WA (United States); Sethi, Shiv K. [Raman Research Institute, Bangalore (India); Arcus, Wayne; Crosse, Brian W. [International Centre for Radio Astronomy Research, Curtin University, Perth (Australia); Barnes, David G. [Center for Astrophysics and Supercomputing, Swinburne University of Technology, Melbourne (Australia); Bunton, John D. [CSIRO Astronomy and Space Science, Epping (Australia); Cappallo, Roger C.; Corey, Brian E., E-mail: clmw@mit.edu [MIT Haystack Observatory, Westford, MA (United States); and others

    2012-08-10T23:59:59.000Z

    The Murchison Widefield Array (MWA) is a new low-frequency, wide-field-of-view radio interferometer under development at the Murchison Radio-astronomy Observatory in Western Australia. We have used a 32 element MWA prototype interferometer (MWA-32T) to observe two 50 Degree-Sign diameter fields in the southern sky, covering a total of {approx}2700 deg{sup 2}, in order to evaluate the performance of the MWA-32T, to develop techniques for epoch of reionization experiments, and to make measurements of astronomical foregrounds. We developed a calibration and imaging pipeline for the MWA-32T, and used it to produce {approx}15' angular resolution maps of the two fields in the 110-200 MHz band. We perform a blind source extraction using these confusion-limited images, and detect 655 sources at high significance with an additional 871 lower significance source candidates. We compare these sources with existing low-frequency radio surveys in order to assess the MWA-32T system performance, wide-field analysis algorithms, and catalog quality. Our source catalog is found to agree well with existing low-frequency surveys in these regions of the sky and with statistical distributions of point sources derived from Northern Hemisphere surveys; it represents one of the deepest surveys to date of this sky field in the 110-200 MHz band.

  5. The $AKARI$ Far-Infrared All-Sky Survey Maps

    E-Print Network [OSTI]

    Doi, Yasuo; Ootsubo, Takafumi; Arimatsu, Ko; Tanaka, Masahiro; Kitamura, Yoshimi; Kawada, Mitsunobu; Matsuura, Shuji; Nakagawa, Takao; Morishima, Takahiro; Hattori, Makoto; Komugi, Shinya; White, Glenn J; Ikeda, Norio; Kato, Daisuke; Chinone, Yuji; Etxaluze, Mireya; Figueredo, Elysandra

    2015-01-01T23:59:59.000Z

    We present a far-infrared all-sky atlas from a sensitive all-sky survey using the Japanese $AKARI$ satellite. The survey covers $> 99$% of the sky in four photometric bands centred at 65 $\\mu$m, 90 $\\mu$m, 140 $\\mu$m, and 160 $\\mu$m with spatial resolutions ranging from 1 to 1.5 arcmin. These data provide crucial information for the investigation and characterisation of the properties of dusty material in the Interstellar Medium (ISM), since significant portion of its energy is emitted between $\\sim$50 and 200 $\\mu$m. The large-scale distribution of interstellar clouds, their thermal dust temperatures and column densities, can be investigated with the improved spatial resolution compared to earlier all-sky survey observations. In addition to the point source distribution, the large-scale distribution of ISM cirrus emission, and its filamentary structure, are well traced. We have made the first public release of the full-sky data to provide a legacy data set for use by the astronomical community.

  6. Color constancy in natural scenes explained by global image statistics

    E-Print Network [OSTI]

    Foster, David H.

    -frequency analysis of the images showed that the gradient of the luminance amplitude spectrum accounted for only 5-vegetated scenes under different illumi- nants characteristic of the sun and sky at different times of the day

  7. The Sloan Digital Sky Survey-II Supernova Survey: Technical Summary

    SciTech Connect (OSTI)

    Frieman, Joshua A.; /Fermilab /KICP, Chicago /Chicago U., Astron. Astrophys. Ctr.; Bassett, Bruce; /Cape Town U. /South African Astron. Observ.; Becker, Andrew; /Washington; Choi, Changsu; /Seoul Natl. U.; Cinabro, David; /Wayne State U.; DeJongh, Don Frederic; /Fermilab; Depoy, Darren L.; /Ohio State U.; Doi, Mamoru; /Tokyo U.; Garnavich, Peter M.; /Notre Dame U.; Hogan, Craig J.; /Washington U., Seattle, Astron. Dept.; Holtzman, Jon; /New Mexico State U.; Im, Myungshin; /Seoul Natl. U.; Jha, Saurabh; /Stanford U., Phys. Dept.; Konishi, Kohki; /Tokyo U.; Lampeitl, Hubert; /Baltimore, Space Telescope Sci.; Marriner, John; /Fermilab; Marshall, Jennifer L.; /Ohio State U.; McGinnis,; /Fermilab; Miknaitis, Gajus; /Fermilab; Nichol, Robert C.; /Portsmouth U.; Prieto, Jose Luis; /Ohio State U. /Rochester Inst. Tech. /Stanford U., Phys. Dept. /Pennsylvania U.

    2007-09-14T23:59:59.000Z

    The Sloan Digital Sky Survey-II (SDSS-II) has embarked on a multi-year project to identify and measure light curves for intermediate-redshift (0.05 < z < 0.35) Type Ia supernovae (SNe Ia) using repeated five-band (ugriz) imaging over an area of 300 sq. deg. The survey region is a stripe 2.5 degrees wide centered on the celestial equator in the Southern Galactic Cap that has been imaged numerous times in earlier years, enabling construction of a deep reference image for discovery of new objects. Supernova imaging observations are being acquired between 1 September and 30 November of 2005-7. During the first two seasons, each region was imaged on average every five nights. Spectroscopic follow-up observations to determine supernova type and redshift are carried out on a large number of telescopes. In its first two three-month seasons, the survey has discovered and measured light curves for 327 spectroscopically confirmed SNe Ia, 30 probable SNe Ia, 14 confirmed SNe Ib/c, 32 confirmed SNe II, plus a large number of photometrically identified SNe Ia, 94 of which have host-galaxy spectra taken so far. This paper provides an overview of the project and briefly describes the observations completed during the first two seasons of operation.

  8. Mapping the nano-Hertz gravitational wave sky

    E-Print Network [OSTI]

    Neil J. Cornish; Rutger van Haasteren

    2014-06-19T23:59:59.000Z

    We describe a new method for extracting gravitational wave signals from pulsar timing data. We show that any gravitational wave signal can be decomposed into an orthogonal set of sky maps, with the number of maps equal to the number of pulsars in the timing array. These maps may be used as a basis to construct gravitational wave templates for any type of source, including collections of point sources. A variant of the standard Hellings-Downs correlation analysis is recovered for statistically isotropic signals. The template based approach allows us to probe potential anisotropies in the signal and produce maps of the gravitational wave sky.

  9. A blue sky catastrophe in double-diffusive convection

    E-Print Network [OSTI]

    Esteban Meca; Isabel Mercader; Oriol Batiste; Laureano Ramirez-Piscina

    2004-05-27T23:59:59.000Z

    A global bifurcation of the blue sky catastrophe type has been found in a small Prandtl number binary mixture contained in a laterally heated cavity. The system has been studied numerically applying the tools of bifurcation theory. The catastrophe corresponds to the destruction of an orbit which, for a large range of Rayleigh numbers, is the only stable solution. This orbit is born in a global saddle-loop bifurcation and becomes chaotic in a period doubling cascade just before its disappearance at the blue sky catastrophe.

  10. Comparative Study of summer, Winter and Quinox Sky Type of India Using Daylight Coefficient Method and Cie Standard General Sky Model

    E-Print Network [OSTI]

    Sutapa Mukherjee M. Tech

    Abstract:- Energy efficiency provided by daylight requires an accurate estimation of the amount of daylight entering a building. The actual daylight illuminance of a room is mainly influenced by the luminance levels and patterns of the sky in the direction of view of the window at that time. The daylight coefficient concept, which considers the changes in the luminance of the sky elements, offers a more effective way of computing indoor daylight illuminances. Recently, Kittler et al. have proposed a new range of 15 standard sky luminance distributions including the CIE (International Commission onIllumination) standard clear sky. Lately, these 15 sky luminance models have been adopted as the CIE Standard General Skies.This paper aims to find out representative CIE (International Commission on Illumination) Standard Clear Sky model(s) for three different seasons-winter solstice, equinox, and summer solstice applicable for prevailing clear sky climatic conditions in India [Roorkee]. Indian measured sky luminance distribution database is available only for Roorkee[29 0 51 ' N; 77 0 53 ' E]. To find out the best match between Indian measured sky luminance distribution and each of five CIE Standard Clear sky models, only sky component of spatial illuminance distribution over the working plane of a room was simulated by MATLABfor three different seasons. Daylight Coefficient method has been applied for the simulation using Indian sky luminance database.The simulation has been done for the room with eight different window orientations ranging from 0 0 to 315 0 with an interval of 45 0 to generate data for the entire sky vault. To find out the

  11. THE SLOAN DIGITAL SKY SURVEY REVERBERATION MAPPING PROJECT: TECHNICAL OVERVIEW

    SciTech Connect (OSTI)

    Shen, Yue [Carnegie Observatories, 813 Santa Barbara Street, Pasadena, CA 91101 (United States); Brandt, W. N. [Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802 (United States); Dawson, Kyle S. [Department of Physics and Astronomy, University of Utah, 115 South 1400 East, Salt Lake City, UT 84112 (United States); Hall, Patrick B. [Department of Physics and Astronomy, York University, Toronto, ON M3J 1P3 (Canada); McGreer, Ian D.; Fan, Xiaohui [Steward Observatory, The University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721-0065 (United States); Anderson, Scott F. [Astronomy Department, University of Washington, Box 351580, Seattle, WA 98195 (United States); Chen, Yuguang [Department of Astronomy, School of Physics, Peking University, Beijing 100871 (China); Denney, Kelly D. [Department of Astronomy, The Ohio State University, 140 West 18th Avenue, Columbus, OH 43210 (United States); Eftekharzadeh, Sarah [Department of Physics and Astronomy, University of Wyoming, 1000 East University Avenue, Laramie, WY 82071 (United States); Gao, Yang [Department of Engineering Physics and Center for Astrophysics, Tsinghua University, Beijing 100084 (China); Green, Paul J. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Greene, Jenny E. [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States); Ho, Luis C. [Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871 (China); Horne, Keith [SUPA Physics/Astronomy, University of St. Andrews, St. Andrews KY16 9SS (United Kingdom); Jiang, Linhua [School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287-1504 (United States); Kelly, Brandon C. [Department of Physics, Broida Hall, University of California, Santa Barbara, CA 93107 (United States); and others

    2015-01-01T23:59:59.000Z

    The Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) project is a dedicated multi-object RM experiment that has spectroscopically monitored a sample of 849 broad-line quasars in a single 7 deg{sup 2} field with the SDSS-III Baryon Oscillation Spectroscopic Survey spectrograph. The RM quasar sample is flux-limited to i {sub psf} = 21.7 mag, and covers a redshift range of 0.1 < z < 4.5 without any other cuts on quasar properties. Optical spectroscopy was performed during 2014 January-July dark/gray time, with an average cadence of ?4 days, totaling more than 30 epochs. Supporting photometric monitoring in the g and i bands was conducted at multiple facilities including the Canada-France-Hawaii Telescope (CFHT) and the Steward Observatory Bok telescope in 2014, with a cadence of ?2 days and covering all lunar phases. The RM field (R.A., decl. = 14:14:49.00, +53:05:00.0) lies within the CFHT-LS W3 field, and coincides with the Pan-STARRS 1 (PS1) Medium Deep Field MD07, with three prior years of multi-band PS1 light curves. The SDSS-RM six month baseline program aims to detect time lags between the quasar continuum and broad line region (BLR) variability on timescales of up to several months (in the observed frame) for ?10% of the sample, and to anchor the time baseline for continued monitoring in the future to detect lags on longer timescales and at higher redshift. SDSS-RM is the first major program to systematically explore the potential of RM for broad-line quasars at z > 0.3, and will investigate the prospects of RM with all major broad lines covered in optical spectroscopy. SDSS-RM will provide guidance on future multi-object RM campaigns on larger scales, and is aiming to deliver more than tens of BLR lag detections for a homogeneous sample of quasars. We describe the motivation, design, and implementation of this program, and outline the science impact expected from the resulting data for RM and general quasar science.

  12. Atmospheric ozone and colors of the Antarctic twilight sky

    E-Print Network [OSTI]

    Lee Jr., Raymond L.

    Atmospheric ozone and colors of the Antarctic twilight sky Raymond L. Lee, Jr.,1, * Wolfgang Meyer absorption at longer wavelengths by ozone's Chappuis bands. Because stratospheric ozone is greatly depleted correlations between ozone concentration and twilight colors. We also used a spectroradiometer at a midlatitude

  13. Bluer Skies and Brighter Days: The U.S. and India Collaborate...

    Energy Savers [EERE]

    Bluer Skies and Brighter Days: The U.S. and India Collaborate in First Long-Term Climate Experiment Bluer Skies and Brighter Days: The U.S. and India Collaborate in First Long-Term...

  14. all-sky hard x-ray: Topics by E-print Network

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

    sky coverage each orbit, and full sky coverage each 50 days, hard x-ray studies of gamma-ray bursts, AGN, galactic transients, x-ray binaries and accretion-powered pulsars can be...

  15. all-sky survey agn: Topics by E-print Network

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

    sky coverage each orbit, and full sky coverage each 50 days, hard x-ray studies of gamma-ray bursts, AGN, galactic transients, x-ray binaries and accretion-powered pulsars can be...

  16. all-sky survey mission: Topics by E-print Network

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

    sky coverage each orbit, and full sky coverage each 50 days, hard x-ray studies of gamma-ray bursts, AGN, galactic transients, x-ray binaries and accretion-powered pulsars can be...

  17. Assessment of clear and cloudy sky parameterizations for daily downwelling longwave radiation over different land surfaces in

    E-Print Network [OSTI]

    meteorological data, resulting in reliable quantification of net radiation and evapotranspiration in FloridaAssessment of clear and cloudy sky parameterizations for daily downwelling longwave radiation over sky downwelling longwave radiation (Rldc) and cloudy sky downwelling longwave radiation (Rld) formulas

  18. A Flight Through the Universe, by the Sloan Digital Sky Survey

    SciTech Connect (OSTI)

    Miguel Aragon; Mark Subbarao

    2012-08-08T23:59:59.000Z

    This animated flight through the universe was made by Miguel Aragon of Johns Hopkins University with Mark Subbarao of the Adler Planetarium and Alex Szalay of Johns Hopkins. There are close to 400,000 galaxies in the animation, with images of the actual galaxies in these positions (or in some cases their near cousins in type) derived from the Sloan Digital Sky Survey (SDSS) Data Release 7. Vast as this slice of the universe seems, its most distant reach is to redshift 0.1, corresponding to roughly 1.3 billion light years from Earth. SDSS Data Release 9 from the Baryon Oscillation Spectroscopic Survey (BOSS), led by Berkeley Lab scientists, includes spectroscopic data for well over half a million galaxies at redshifts up to 0.8 -- roughly 7 billion light years distant -- and over a hundred thousand quasars to redshift 3.0 and beyond.

  19. Total Light Management

    Broader source: Energy.gov [DOE]

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

  20. Total Space Heat-

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

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

  1. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

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

  2. Surveying the TeV Sky with Milagro C.P. Lansdell for the Milagro Collaboration

    E-Print Network [OSTI]

    California at Santa Cruz, University of

    .9°, the Cygnus region of the galaxy becomes the most luminous source of TeV gamma rays in the Northern skySurveying the TeV Sky with Milagro C.P. Lansdell for the Milagro Collaboration University sky. In addition to detecting the known TeV sources of the Crab Nebula and Markarian 421, Milagro has

  3. Incorporating Cloud Distribution in Sky Representation Kuan-Chuan Peng, Tsuhan Chen

    E-Print Network [OSTI]

    Chen, Tsuhan

    science and related fields have proposed different sky models to fit the measured luminance or radiance parameters with the luminance of the sky by normalized cross correlation. However, the above works useIncorporating Cloud Distribution in Sky Representation Kuan-Chuan Peng, Tsuhan Chen Cornell

  4. Towards radio astronomical imaging using an arbitrary basis

    E-Print Network [OSTI]

    Petschow, Matthias

    2015-01-01T23:59:59.000Z

    The new generation of radio telescopes, such as the Square Kilometer Array (SKA), requires dramatic advances in computer hardware and software, in order to process the large amounts of produced data efficiently. In this document, we explore a new approach to wide-field imaging. By generalizing the image reconstruction, which is performed by an inverse Fourier transform, to arbitrary transformations, we gain enormous new possibilities. In particular, we outline an approach that might allow to obtain a sky image of size P times Q in (optimal) O(PQ) time. This could be a step in the direction of real-time, wide-field sky imaging for future telescopes.

  5. Ground-based All-sky Mid-infrared and Visible Imagery for Purposes of Characterizing Cloud Properties

    SciTech Connect (OSTI)

    Klebe, Dimitri; Blatherwick, R. D.; Morris, Victor R.

    2014-02-24T23:59:59.000Z

    This paper describes the All Sky Infrared Visible Analyzer (ASIVA), a multi-purpose visible and infrared sky imaging and analysis instrument whose primary functionality is to provide radiometrically calibrated imagery in the mid-infrared (mid-IR) atmospheric window. This functionality enables the determination of diurnal hemispherical cloud fraction (HCF) and estimates of sky/cloud temperature from which one can derive estimates of cloud emissivity and cloud height. This paper describes the calibration methods and performance of the ASIVA instrument with particular emphasis on data products being developed for the meteorological community. Data presented here were collected during a field campaign conducted at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Climate Research Facility from May 21 to July 27, 2009. The purpose of this campaign was to determine the efficacy of IR technology in providing reliable nighttime HCF data. Significant progress has been made in the analysis of the campaign data over the past several years and the ASIVA has proven to be an excellent instrument for determining HCF as well as several other important cloud properties.

  6. Cosmology using the Parkes Multibeam Southern-Sky HI Survey

    E-Print Network [OSTI]

    P. A. Thomas

    1996-07-02T23:59:59.000Z

    I discuss the implications of the Parkes HI Multibeam Southern Sky Survey for cosmology. It will determine the local mass function of HI clouds, detecting several hundred per decade of mass. Each of these will come with a redshift and, for the more massive clouds, an estimate of the velocity width. This will provide an ideal database for peculiar motion studies and for measurements of biasing of galaxies relative to the underlying matter distribution.

  7. Total Synthesis of (?)-Himandrine

    E-Print Network [OSTI]

    Movassaghi, Mohammad

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

  8. Jade Sky Technologies Partners with CLTC on LED Replacement Lamp Upgrade Project UC Davis' California Lighting Technology Center will utilize Jade Sky Technologies' driver ICs to help spur

    E-Print Network [OSTI]

    California at Davis, University of

    Jade Sky Technologies Partners with CLTC on LED Replacement Lamp Upgrade Project UC Davis and power factor. "JST shares our goal of making the transition to LED lamps a satisfying experience of cost-effective, easy-to-use LED lighting solutions Milpitas, Calif. ­ October 15, 2013 ­ Jade Sky

  9. Bright Lyman Break Galaxies in the Sloan Digital Sky Survey First Data Release

    E-Print Network [OSTI]

    Bentz, M C; Weinberg, D H; Bentz, Misty C.; Osmer, Patrick S.; Weinberg, David H.

    2003-01-01T23:59:59.000Z

    We report the discovery of six compact, starburst galaxies with redshifts 2.3 < z < 2.8 and r-band magnitudes 19.8-20.5 in the Quasar Catalog of the Sloan Digital Sky Survey First Data Release (SDSS DR1). The SDSS spectra of these objects resemble the composite spectrum of Lyman Break Galaxies (LBGs) at z \\approx 3, but the galaxies are 4-5 magnitudes brighter than an ``L*'' LBG and 2-3 magnitudes brighter than the most luminous objects in typical LBG spectroscopic surveys. Star formation rates inferred from the UV continuum luminosities are about 300-1000 M_sun yr^-1 with no correction for dust extinction. Such rates are similar to those inferred for ultraluminous infrared galaxies, but in these UV-bright objects the star formation is evidently not obscured by high dust column densities. The SDSS images show no evidence of multiple imaging or foreground lensing structures, but amplification by gravitational lensing (as in the case of MS 1512-cB58) cannot be ruled out with the present data. Assuming tha...

  10. Total Precipitable Water

    SciTech Connect (OSTI)

    None

    2012-01-01T23:59:59.000Z

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

  11. Confusion of Diffuse Objects in the X-ray Sky

    E-Print Network [OSTI]

    G. Mark Voit; August E. Evrard; Greg L. Bryan

    2000-12-08T23:59:59.000Z

    Most of the baryons in the present-day universe are thought to reside in intergalactic space at temperatures of 10^5-10^7 K. X-ray emission from these baryons contributes a modest (~10%) fraction of the ~ 1 keV background whose prominence within the large-scale cosmic web depends on the amount of non-gravitational energy injected into intergalactic space by supernovae and AGNs. Here we show that the virialized regions of groups and clusters cover over a third of the sky, creating a source-confusion problem that may hinder X-ray searches for individual intercluster filaments and contaminate observations of distant groups.

  12. Definitions of Clear-sky Fluxes and Implications

    E-Print Network [OSTI]

    Verma, Abhishek

    2012-02-14T23:59:59.000Z

    in radiances at various wavelengths to- wards or away from the earth system. Various studies have estimated the distribu- tion of these uxes at top-of-atmosphere (TOA), over land, ocean and ice-covered surfaces, in both upwelling and downwelling direction... (shortwave and longwave) are constructed using radiances that aren?t attenuated by cloud hydrometeors and are used in determining CRFs. By far, clear-sky uxes are derived using two approaches based on (i) satellite measurements and (ii) model generated...

  13. Lessons Learned from Sloan Digital Sky Survey Operations

    E-Print Network [OSTI]

    S. J. Kleinman; J. E. Gunn; B. Boroski; D. Long; S. Snedden; A. Nitta; J. Krzesi?ski; M. Harvanek; E. Neilsen; B. Gillespie; J. C. Barentine; A. Uomoto; D. Tucker; D. York; S. Jester

    2008-10-15T23:59:59.000Z

    Astronomy is changing. Large projects, large collaborations, and large budgets are becoming the norm. The Sloan Digital Sky Survey (SDSS) is one example of this new astronomy, and in operating the original survey, we put in place and learned many valuable operating principles. Scientists sometimes have the tendency to invent everything themselves but when budgets are large, deadlines are many, and both are tight, learning from others and applying it appropriately can make the difference between success and failure. We offer here our experiences well as our thoughts, opinions, and beliefs on what we learned in operating the SDSS.

  14. Zhenjiang Sky Solar Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapersWindey Wind Generating Engineering JumpDachengZhenjiang Sky

  15. SkyPower Pekon Electronics JV | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDITCalifornia Sector:Shrenik Industries Jump to:SimranSkyBuilt

  16. SkySails GmbH | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-f < RAPID‎ |Rippey JumpAirPowerSilcioEthanol LLCSitkaOregonSkySails

  17. Blue Sky Green Field Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia: EnergyAvignon,Belcher HomesLyonsBirchBlockVI JumpBlueBlueBlue SkyGreen

  18. Sky Energy Luoyang Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit with form HistoryRistmaSinosteel Corporation Jump to: navigation,SiriSky Energy

  19. Clear Skies Group Inc Holdings Inc | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model, clickInformation SmyrnaNewClay ElectricCleangoogleSolutionsClearSkies Group

  20. American Clean Skies Foundation | OpenEI Community

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDITCaliforniaWeifangwikiAgouraAlbatechFuelsdiesel LLCClean Skies

  1. BRIGHTNESS AND FLUCTUATION OF THE MID-INFRARED SKY FROM AKARI OBSERVATIONS TOWARD THE NORTH ECLIPTIC POLE

    SciTech Connect (OSTI)

    Pyo, Jeonghyun; Jeong, Woong-Seob [Korea Astronomy and Space Science Institute (KASI), Daejeon 305-348 (Korea, Republic of); Matsumoto, Toshio [Department of Physics and Astronomy, Seoul National University, Seoul 151-742 (Korea, Republic of); Matsuura, Shuji, E-mail: jhpyo@kasi.re.kr [Institute of Space and Astronautical Science (ISAS), Japan Aerospace Exploration Agency (JAXA), Kanagawa 252-5210 (Japan)

    2012-12-01T23:59:59.000Z

    We present the smoothness of the mid-infrared sky from observations by the Japanese infrared astronomical satellite AKARI. AKARI monitored the north ecliptic pole (NEP) during its cold phase with nine wave bands covering from 2.4 to 24 {mu}m, out of which six mid-infrared bands were used in this study. We applied power-spectrum analysis to the images in order to search for the fluctuation of the sky brightness. Observed fluctuation is explained by fluctuation of photon noise, shot noise of faint sources, and Galactic cirrus. The fluctuations at a few arcminutes scales at short mid-infrared wavelengths (7, 9, and 11 {mu}m) are largely caused by the diffuse Galactic light of the interstellar dust cirrus. At long mid-infrared wavelengths (15, 18, and 24 {mu}m), photon noise is the dominant source of fluctuation over the scale from arcseconds to a few arcminutes. The residual fluctuation amplitude at 200'' after removing these contributions is at most 1.04 {+-} 0.23 nW m{sup -2} sr{sup -1} or 0.05% of the brightness at 24 {mu}m and at least 0.47 {+-} 0.14 nW m{sup -2} sr{sup -1} or 0.02% at 18 {mu}m. We conclude that the upper limit of the fluctuation in the zodiacal light toward the NEP is 0.03% of the sky brightness, taking 2{sigma} error into account.

  2. TotalView Training

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

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

  3. Cool covered sky-splitting spectrum-splitting FK

    SciTech Connect (OSTI)

    Mohedano, Rubén; Chaves, Julio; Falicoff, Waqidi; Hernandez, Maikel; Sorgato, Simone [LPI, Altadena, CA, USA and Madrid (Spain); Miñano, Juan C.; Benitez, Pablo [LPI, Altadena, CA, USA and Madrid, Spain and Universidad Politécnica de Madrid (UPM), Madrid (Spain); Buljan, Marina [Universidad Politécnica de Madrid (UPM), Madrid (Spain)

    2014-09-26T23:59:59.000Z

    Placing a plane mirror between the primary lens and the receiver in a Fresnel Köhler (FK) concentrator gives birth to a quite different CPV system where all the high-tech components sit on a common plane, that of the primary lens panels. The idea enables not only a thinner device (a half of the original) but also a low cost 1-step manufacturing process for the optics, automatic alignment of primary and secondary lenses, and cell/wiring protection. The concept is also compatible with two different techniques to increase the module efficiency: spectrum splitting between a 3J and a BPC Silicon cell for better usage of Direct Normal Irradiance DNI, and sky splitting to harvest the energy of the diffuse radiation and higher energy production throughout the year. Simple calculations forecast the module would convert 45% of the DNI into electricity.

  4. Running the Sloan Digital Sky Survey data archive server

    SciTech Connect (OSTI)

    Neilsen, Eric H., Jr.; Stoughton, Chris; /Fermilab

    2006-11-01T23:59:59.000Z

    The Sloan Digital Sky Survey (SDSS) Data Archive Server (DAS) provides public access to over 12Tb of data in 17 million files produced by the SDSS data reduction pipeline. Many tasks which seem trivial when serving smaller, less complex data sets present challenges when serving data of this volume and technical complexity. The included output files should be chosen to support as much science as possible from publicly released data, and only publicly released data. Users must have the resources needed to read and interpret the data correctly. Server administrators must generate new data releases at regular intervals, monitor usage, quickly recover from hardware failures, and monitor the data served by the DAS both for contents and corruption. We discuss these challenges, describe tools we use to administer and support the DAS, and discuss future development plans.

  5. all-sky infrared sasir: Topics by E-print Network

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

    all-sky infrared sasir First Page Previous Page 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Next Page Last Page Topic Index 1 The Synoptic All-Sky Infrared...

  6. GOALS: The Great Observatories All-Sky LIRG Survey J. M. MAZZARELLA,2

    E-Print Network [OSTI]

    Spoon, Henrik

    GOALS: The Great Observatories All-Sky LIRG Survey L. ARMUS,1 J. M. MAZZARELLA,2 A. S. EVANS,3,4 J. The Great Observatories All-Sky LIRG Survey (GOALS20 ) combines data from NASA's Spitzer Space Telescope 200 low-redshift (z Luminous Infrared Galaxies (LIRGs). The LIRGs are a complete subset

  7. WHAT IS THEMIS? If you look up into the sky on a clear, dark night

    E-Print Network [OSTI]

    Waliser, Duane E.

    WHAT IS THEMIS? If you look up into the sky on a clear, dark night while in Alaska, Canada, or the Northern United States, you may see a bright greenish-white band of light that stretches across the sky Carrington but it is related to distant Solar eruptions. 1866 Anders Angström Auroral displays are self-luminous

  8. The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III

    E-Print Network [OSTI]

    Alam, Shadab; Prieto, Carlos Allende; Anders, F; Anderson, Scott F; Andrews, Brett H; Armengaud, Eric; Aubourg, Éric; Bailey, Stephen; Bautista, Julian E; Beaton, Rachael L; Bender, Chad F; Berlind, Andreas A; Beutler, Florian; Bhardwaj, Vaishali; Bird, Jonathan C; Bizyaev, Dmitry; Blanton, Michael R; Blomqvist, Michael; Bochanski, John J; Bolton, Adam S; Bovy, Jo; Bradley, A Shelden; Brandt, W N; Brauer, D E; Brinkmann, J; Brown, Peter J; Brownstein, Joel R; Burden, Angela; Burtin, Etienne; Busca, Nicolás G; Cai, Zheng; Capozzi, Diego; Rosell, Aurelio Carnero; Carrera, Ricardo; Chen, Yen-Chi; Chiappini, Cristina; Chojnowski, S Drew; Chuang, Chia-Hsun; Clerc, Nicolas; Comparat, Johan; Covey, Kevin; Croft, Rupert A C; Cuesta, Antonio J; Cunha, Katia; da Costa, Luiz N; Da Rio, Nicola; Davenport, James R A; Dawson, Kyle S; De Lee, Nathan; Delubac, Timothée; Deshpande, Rohit; Dutra-Ferreira, Letícia; Dwelly, Tom; Ealet, Anne; Ebelke, Garrett L; Edmondson, Edward M; Eisenstein, Daniel J; Escoffier, Stephanie; Esposito, Massimiliano; Fan, Xiaohui; Fernández-Alvar, Emma; Feuillet, Diane; Ak, Nurten Filiz; Finley, Hayley; Flaherty, Kevin; Fleming, Scott W; Font-Ribera, Andreu; Foster, Jonathan; Frinchaboy, Peter M; Galbraith-Frew, J G; García-Hernández, D A; Pérez, Ana E García; Gaulme, Patrick; Ge, Jian; Génova-Santos, R; Ghezzi, Luan; Gillespie, Bruce A; Girardi, Léo; Goddard, Daniel; Gontcho, Satya Gontcho A; Hernández, Jonay I González; Grebel, Eva K; Grieb, Jan Niklas; Grieves, Nolan; Gunn, James E; Guo, Hong; Harding, Paul; Hasselquist, Sten; Hawley, Suzanne L; Hayden, Michael; Hearty, Fred R; Ho, Shirley; Hogg, David W; Holley-Bockelmann, Kelly; Holtzman, Jon A; Honscheid, Klaus; Huehnerhoff, Joseph; Jiang, Linhua; Johnson, Jennifer A; Kinemuchi, Karen; Kirkby, David; Kitaura, Francisco; Klaene, Mark A; Kneib, Jean-Paul; Koenig, Xavier P; Lam, Charles R; Lan, Ting-Wen; Lang, Dustin; Laurent, Pierre; Goff, Jean-Marc Le; Lee, Khee-Gan; Lee, Young Sun; Licquia, Timothy C; Liu, Jian; Long, Daniel C; López-Corredoira, Martín; Lorenzo-Oliveira, Diego; Lucatello, Sara; Lundgren, Britt; Lupton, Robert H; Mack, Claude E; Mahadevan, Suvrath; Maia, Marcio A G; Majewski, Steven R; Malanushenko, Elena; Malanushenko, Viktor; Manchado, A; Manera, Marc; Mao, Qingqing; Maraston, Claudia; Marchwinski, Robert C; Margala, Daniel; Martell, Sarah L; Martig, Marie; Masters, Karen L; McBride, Cameron K; McGehee, Peregrine M; McGreer, Ian D; McMahon, Richard G; Ménard, Brice; Menzel, Marie-Luise; Merloni, Andrea; Mészáros, Szabolcs; Miralda-Escudé, Jordi; Miyatake, Hironao; Montero-Dorta, Antonio D; Morice-Atkinson, Xan; Morrison, Heather L; Muna, Demitri; Myers, Adam D; Newman, Jeffrey A; Neyrinck, Mark; Nguyen, Duy Cuong; Nichol, Robert C; Nidever, David L; Noterdaeme, Pasquier; Nuza, Sebastián E; O'Connell, Julia E; O'Connell, Robert W; O'Connell, Ross; Ogando, Ricardo L C; Olmstead, Matthew D; Oravetz, Audrey E; Oravetz, Daniel J; Osumi, Keisuke; Owen, Russell; Padgett, Deborah L; Padmanabhan, Nikhil; Paegert, Martin; Palanque-Delabrouille, Nathalie; Pan, Kaike; Parejko, John K; Park, Changbom; Pâris, Isabelle; Pattarakijwanich, Petchara; Pellejero-Ibanez, M; Pepper, Joshua; Percival, Will J; Pérez-Fournon, Ismael; Pérez-Ràfols, Ignasi; Petitjean, Patrick; Pieri, Matthew M; Pinsonneault, Marc H; de Mello, Gustavo F Porto; Prada, Francisco; Prakash, Abhishek; Price-Whelan, Adrian M; Raddick, M Jordan; Rahman, Mubdi; Reid, Beth A; Rich, James; Rix, Hans-Walter; Robin, Annie C; Rockosi, Constance M; Rodrigues, Thaíse S; Rodríguez-Rottes, Sergio; Roe, Natalie A; Ross, Ashley J; Ross, Nicholas P; Rossi, Graziano; Ruan, John J; Rubiño-Martín, J A; Salazar-Albornoz, Salvador; Salvato, Mara; Samushia, Lado; Sánchez, Ariel G; Santiago, Basílio; Sayres, Conor; Schiavon, Ricardo P; Schlegel, David J; Schmidt, Sarah J; Schneider, Donald P; Schultheis, Mathias; Schwope, Axel D; Scóccola, C G; Sellgren, Kris; Seo, Hee-Jong; Shane, Neville; Shen, Yue; Shetrone, Matthew; Shu, Yiping; Skrutskie, M F; Slosar, Anže; Smith, Verne V; Sobreira, Flávia; Stassun, Keivan G; Steinmetz, Matthias; Strauss, Michael A; Streblyanska, Alina; Swanson, Molly E C; Tan, Jonathan C; Tayar, Jamie; Terrien, Ryan C; Thakar, Aniruddha R; Thomas, Daniel; Thompson, Benjamin A; Tinker, Jeremy L; Tojeiro, Rita; Troup, Nicholas W; Vargas-Magaña, Mariana; Verde, Licia; Viel, Matteo; Vogt, Nicole P; Wake, David A; Wang, Ji; Weaver, Benjamin A; Weinberg, David H; Weiner, Benjamin J; White, Martin; Wilson, John C; Wisniewski, John P; Wood-Vasey, W M

    2015-01-01T23:59:59.000Z

    The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 sq. deg of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 s...

  9. Imaging with Scattered Neutrons

    E-Print Network [OSTI]

    H. Ballhausen; H. Abele; R. Gaehler; M. Trapp; A. Van Overberghe

    2006-10-30T23:59:59.000Z

    We describe a novel experimental technique for neutron imaging with scattered neutrons. These scattered neutrons are of interest for condensed matter physics, because they permit to reveal the local distribution of incoherent and coherent scattering within a sample. In contrast to standard attenuation based imaging, scattered neutron imaging distinguishes between the scattering cross section and the total attenuation cross section including absorption. First successful low-noise millimeter-resolution images by scattered neutron radiography and tomography are presented.

  10. Tunable Imaging Filters in Astronomy

    E-Print Network [OSTI]

    J. Bland-Hawthorn

    2000-06-05T23:59:59.000Z

    While tunable filters are a recent development in night time astronomy, they have long been used in other physical sciences, e.g. solar physics, remote sensing and underwater communications. With their ability to tune precisely to a given wavelength using a bandpass optimized for the experiment, tunable filters are already producing some of the deepest narrowband images to date of astrophysical sources. Furthermore, some classes of tunable filters can be used in fast telescope beams and therefore allow for narrowband imaging over angular fields of more than a degree over the sky.

  11. A Comparison of Three Total Variation Based Texture Extraction Models

    E-Print Network [OSTI]

    Soatto, Stefano

    Goldfarb b , Stanley Osher c aRice University, Department of Computational and Applied Mathematics, 6100 models for signal/image texture extraction based on total variation minimization: the Meyer [2], the Vese using 1D oscillating signals and 2D images reveal their differences: the Meyer model tends to extract

  12. Spectroscopic Target Selection for the Sloan Digital Sky Survey: The Luminous Red Galaxy Sample

    E-Print Network [OSTI]

    D. J. Eisenstein; J. Annis; J. E. Gunn; A. S. Szalay; A. J. Connolly; R. C. Nichol; N. A. Bahcall; M. Bernardi; S. Burles; F. J. Castander; M. Fukugita; D. W. Hogg; Z. Ivezic; G. R. Knapp; R. H. Lupton; V. Narayanan; M. Postman; D. E. Riechart; M. Richmond; D. P. Schneider; D. J. Schlegel; M. A. Strauss; M. SubbaRao; D. L. Tucker; D. Vanden Berk; M. S. Vogeley; D. H. Weinberg; B. Yanny

    2001-08-09T23:59:59.000Z

    We describe the target selection and resulting properties of a spectroscopic sample of luminous, red galaxies (LRG) from the imaging data of the Sloan Digital Sky Survey (SDSS). These galaxies are selected on the basis of color and magnitude to yield a sample of luminous, intrinsically red galaxies that extends fainter and further than the main flux-limited portion of the SDSS galaxy spectroscopic sample. The sample is designed to impose a passively-evolving luminosity and rest-frame color cut to a redshift of 0.38. Additional, yet more luminous, red galaxies are included to a redshift of 0.5. Approximately 12 of these galaxies per square degree are targeted for spectroscopy, so the sample will number over 100,000 with the full survey. SDSS commissioning data indicate that the algorithm efficiently selects luminous (M_g=-21.4), red galaxies, that the spectroscopic success rate is very high, and that the resulting set of galaxies is approximately volume-limited out to z=0.38. When the SDSS is complete, the LRG spectroscopic sample will fill over 1h^-3 Gpc^3 with an approximately homogeneous population of galaxies and will therefore be well suited to studies of large-scale structure and clusters out to z=0.5.

  13. A deep proper motion catalog within the Sloan digital sky survey footprint

    SciTech Connect (OSTI)

    Munn, Jeffrey A.; Harris, Hugh C.; Tilleman, Trudy M. [US Naval Observatory, Flagstaff Station, 10391 West Naval Observatory Road, Flagstaff, AZ 86005-8521 (United States); Hippel, Ted von [Embry-Riddle Aeronautical University, Physical Sciences, 600 South Clyde Morris Boulevard Daytona Beach, FL 32114-3900 (United States); Kilic, Mukremin [University of Oklahoma, Homer L. Dodge Department of Physics and Astronomy, 440 West Brooks Street, Norman, OK 73019 (United States); Liebert, James W. [University of Arizona, Steward Observatory, Tucson, AZ 85721 (United States); Williams, Kurtis A. [Department of Physics and Astronomy, Texas A and M University-Commerce, P.O. Box 3011, Commerce, TX 75429 (United States); DeGenarro, Steven [Department of Astronomy, University of Texas at Austin, 1 University Station C1400, Austin, TX 78712-0259 (United States); Jeffery, Elizabeth, E-mail: jam@nofs.navy.mil, E-mail: hch@nofs.navy.mil, E-mail: trudy@nofs.navy.mil, E-mail: ted.vonhippel@erau.edu, E-mail: kilic@ou.edu, E-mail: jamesliebert@gmail.com, E-mail: kurtis.williams@tamuc.edu, E-mail: studiofortytwo@yahoo.com, E-mail: ejeffery@byu.edu [BYU Department of Physics and Astronomy, N283 ESC, Provo, UT 84602 (United States)

    2014-12-01T23:59:59.000Z

    A new proper motion catalog is presented, combining the Sloan Digital Sky Survey (SDSS) with second epoch observations in the r band within a portion of the SDSS imaging footprint. The new observations were obtained with the 90prime camera on the Steward Observatory Bok 90 inch telescope, and the Array Camera on the U.S. Naval Observatory, Flagstaff Station, 1.3 m telescope. The catalog covers 1098 square degrees to r = 22.0, an additional 1521 square degrees to r = 20.9, plus a further 488 square degrees of lesser quality data. Statistical errors in the proper motions range from 5 mas year{sup ?1} at the bright end to 15 mas year{sup ?1} at the faint end, for a typical epoch difference of six years. Systematic errors are estimated to be roughly 1 mas year{sup ?1} for the Array Camera data, and as much as 2–4 mas year{sup ?1} for the 90prime data (though typically less). The catalog also includes a second epoch of r band photometry.

  14. A simple evaluation of global and diffuse Luminous Efficacy for all sky conditions in tropical and humid climate

    E-Print Network [OSTI]

    Boyer, Edmond

    1 A simple evaluation of global and diffuse Luminous Efficacy for all sky conditions in tropical to determine luminous efficacy under different sky conditions. A comparison between these empirical constants. Keywords Global and diffuse luminous efficacy, different sky conditions, solar irradiance, solar

  15. Ensemble Properties of Comets in the Sloan Digital Sky Survey

    SciTech Connect (OSTI)

    Solontoi, Michael; /Adler Planetarium, Chicago; Ivezic, Zeljko; /Washington U., Seattle, Astron. Dept.; Juric, Mario; /Harvard Coll. Observ.; Becker, Andrew C.; /Washington U., Seattle, Astron. Dept.; Jones, Lynne; /Washington U., Seattle, Astron. Dept.; West, Andrew A.; /Boston U.; Kent, Steve; /Fermilab; Lupton, Robert H.; /Princeton U. Observ.; Claire, Mark; /Washington U., Seattle, Astron. Dept.; Knapp, Gillian R.; /Princeton U. Observ.; Quinn, Tom; /Washington U., Seattle, Astron. Dept. /Princeton U. Observ.

    2012-02-01T23:59:59.000Z

    We present the ensemble properties of 31 comets (27 resolved and 4 unresolved) observed by the Sloan Digital Sky Survey (SDSS). This sample of comets represents about 1 comet per 10 million SDSS photometric objects. Five-band (u, g, r, i, z) photometry is used to determine the comets colors, sizes, surface brightness profiles, and rates of dust production in terms of the Afp formalism. We find that the cumulative luminosity function for the Jupiter Family Comets in our sample is well fit by a power law of the form N(

  16. Oxygen abundance in the Sloan Digital Sky Survey

    E-Print Network [OSTI]

    F. Shi; X. Kong; F. Z. Cheng

    2006-03-10T23:59:59.000Z

    We present two samples of $\\hii$ galaxies from the Sloan Digital Sky Survey (SDSS) spectroscopic observations data release 3. The electron temperatures($T_e$) of 225 galaxies are calculated with the photoionized $\\hii$ model and $T_e$ of 3997 galaxies are calculated with an empirical method. The oxygen abundances from the $T_e$ methods of the two samples are determined reliably. The oxygen abundances from a strong line metallicity indicator, such as $R_{23}$, $P$, $N2$, and $O3N2$, are also calculated. We compared oxygen abundances of $\\hii$ galaxies obtained with the $T_e$ method, $R_{23}$ method, $P$ method, $N2$ method, and $O3N2$method. The oxygen abundances derived with the $T_e$ method are systematically lower by $\\sim$0.2 dex than those derived with the $R_{23}$ method, consistent with previous studies based on $\\hii$ region samples. No clear offset for oxygen abundance was found between $T_e$ metallicity and $P$, $N2$ and $O3N2$ metallicity. When we studied the relation between N/O and O/H, we found that in the metallicity regime of $\\zoh > 7.95$, the large scatter of the relation can be explained by the contribution of small mass stars to the production of nitrogen. In the high metallicity regime, $\\zoh > 8.2$, nitrogen is primarily a secondary element produced by stars of all masses.

  17. Mapping the Cosmic Web with the Sloan Digital Sky Survey

    E-Print Network [OSTI]

    Michael S. Vogeley; Fiona Hoyle; Randall R. Rojas; David M. Goldberg

    2004-08-31T23:59:59.000Z

    Wide-angle, moderately deep redshift surveys such as that conducted as part of the Sloan Digital Sky Survey (SDSS) allow study of the relationship between the structural elements of the large-scale distribution of galaxies -- including groups, cluster, superclusters, and voids -- and the dependence of galaxy formation and evolution on these enviroments. We present a progress report on mapping efforts with the SDSS and discuss recently constructed catalogs of clusters, voids, and void galaxies, and evidence for a 420Mpc/h supercluster or ``Great Wall.'' Analysis of multi-band photometry and moderate-resolution spectroscopy from the SDSS reveals environmental dependence of the star formation history of galaxies that extends over more than a factor of 100 in density, from clusters all the way to the deep interiors of voids. On average, galaxies in the rarified environments of voids exhibit bluer colors, higher specific star formation rates, lower dust content, and more disk-like morphology than objects in denser regions. This trend persists in comparisons of samples in low vs. high-density regions with similar luminosity and morphology, thus this dependence is not simply an extension of the morphology-density relation. Large-scale modulation of the halo mass function and the temperature of the intergalactic medium might explain this dependence of galaxy evolution on the large-scale environment.

  18. The UKIRT Infrared Deep Sky Survey Early Data Release

    E-Print Network [OSTI]

    Dye, S; Almaini, O; Cross, N J G; Edge, A C; Hambly, N C; Hirst, P; Hodgkin, S T; Irwin, M J; Jameson, R F; Lawrence, A; Warren, S J

    2006-01-01T23:59:59.000Z

    This paper defines the UKIRT Infrared Deep Sky Survey (UKIDSS) Early Data Release (EDR). UKIDSS is a set of five large near-infra-red surveys defined by Lawrence et al. (2006), being undertaken with the UK Infra-red Telescope (UKIRT) Wide Field Camera (WFCAM). The programme began in May 2005 and has an expected duration of seven years. Each survey uses some or all of the broadband filter complement ZYJHK. The EDR is the first public release of data to the European Southern Observatory (ESO) community. All worldwide releases occur after a delay of 18 months from the ESO release. The EDR provides a small sample dataset, ~60 sq.deg (about 1% of the whole of UKIDSS), that is a lower limit to the expected quality of future survey data releases. In addition, an EDR+ dataset contains all EDR data plus extra data of similar quality, but for areas not observed in all of the required filters (amounting to ~220 sq.deg). The first large data release, DR1, will occur in mid-2006. We provide details of the observational im...

  19. The Sloan Digital Sky Survey-II Supernova Survey:Search Algorithm and Follow-up Observations

    SciTech Connect (OSTI)

    Sako, Masao; /Pennsylvania U. /KIPAC, Menlo Park; Bassett, Bruce; /Cape Town U. /South African Astron. Observ.; Becker, Andrew; /Washington U., Seattle, Astron. Dept.; Cinabro, David; /Wayne State U.; DeJongh, Don Frederic; /Fermilab; Depoy, D.L.; /Ohio State U.; Doi, Mamoru; /Tokyo U.; Garnavich, Peter M.; /Notre Dame U.; Craig, Hogan, J.; /Washington U., Seattle, Astron. Dept.; Holtzman, Jon; /New Mexico State U.; Jha, Saurabh; /Stanford U., Phys. Dept.; Konishi, Kohki; /Tokyo U.; Lampeitl, Hubert; /Baltimore, Space; Marriner, John; /Fermilab; Miknaitis, Gajus; /Fermilab; Nichol, Robert C.; /Portsmouth U.; Prieto, Jose Luis; /Ohio State U.; Richmond, Michael W.; /Rochester Inst.; Schneider, Donald P.; /Penn State U., Astron. Astrophys.; Smith, Mathew; /Portsmouth U.; SubbaRao, Mark; /Chicago U. /Tokyo U. /Tokyo U. /South African Astron. Observ. /Tokyo

    2007-09-14T23:59:59.000Z

    The Sloan Digital Sky Survey-II Supernova Survey has identified a large number of new transient sources in a 300 deg2 region along the celestial equator during its first two seasons of a three-season campaign. Multi-band (ugriz) light curves were measured for most of the sources, which include solar system objects, Galactic variable stars, active galactic nuclei, supernovae (SNe), and other astronomical transients. The imaging survey is augmented by an extensive spectroscopic follow-up program to identify SNe, measure their redshifts, and study the physical conditions of the explosions and their environment through spectroscopic diagnostics. During the survey, light curves are rapidly evaluated to provide an initial photometric type of the SNe, and a selected sample of sources are targeted for spectroscopic observations. In the first two seasons, 476 sources were selected for spectroscopic observations, of which 403 were identified as SNe. For the Type Ia SNe, the main driver for the Survey, our photometric typing and targeting efficiency is 90%. Only 6% of the photometric SN Ia candidates were spectroscopically classified as non-SN Ia instead, and the remaining 4% resulted in low signal-to-noise, unclassified spectra. This paper describes the search algorithm and the software, and the real-time processing of the SDSS imaging data. We also present the details of the supernova candidate selection procedures and strategies for follow-up spectroscopic and imaging observations of the discovered sources.

  20. MUJERES TOTAL BIOLOGIA 16 27

    E-Print Network [OSTI]

    Autonoma de Madrid, Universidad

    , PLASTICA Y VISUAL 2 2 EDUCACION FISICA, DEPORTE Y MOTRICIDAD HUMANA 1 1 6 11 TOTAL CIENCIAS Nº DE TESIS

  1. MUJERES ( * ) TOTAL BIOLOGA 16 22

    E-Print Network [OSTI]

    Autonoma de Madrid, Universidad

    , DEPORTE Y MOTRICIDAD HUMANA 0 4 TOTAL FORMACIÓN DE PROFESORADO Y EDUCACIÓN 0 6 ANATOMÍA PATOLÓGICA 2 5

  2. The Total RNA Story Introduction

    E-Print Network [OSTI]

    Goldman, Steven A.

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

  3. Deep radio imaging of the UKIDSS Ultra Deep Survey field : the nature of the faint radio population, and the star-formation history of the Universe 

    E-Print Network [OSTI]

    Arumugam, Vinodiran

    2013-07-01T23:59:59.000Z

    The centrepiece of this thesis is a deep, new, high-resolution 1.4-GHz image covering the United Kingdom Infrared (IR) Telescope IR Deep Sky Survey (UKIDSS) Ultra Deep Survey (UDS) legacy field. Deep pseudo-continuum ...

  4. all-sky survey 2mass: Topics by E-print Network

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

    found at http:sirius.astrouw.edu.plgpasasasas.html . G. Pojmanski 1997-12-11 2 Infrared Properties of Cataclysmic Variables in the 2MASS All Sky Data Release Astrophysics...

  5. all-sky earth occultation: Topics by E-print Network

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

    and can serve well as a cost-effective science capability for monitoring the high energy sky. Here we describe the Earth occultation technique for locating new sources and for...

  6. The artificial night sky brightness mapped from DMSP Operational Linescan System measurements

    E-Print Network [OSTI]

    P. Cinzano; F. Falchi; C. D. Elvidge; K. E. Baugh

    2000-03-28T23:59:59.000Z

    We present a method to map the artificial sky brightness across large territories in astronomical photometric bands with a resolution of approximately 1 km. This is useful to quantify the situation of night sky pollution, to recognize potential astronomical sites and to allow future monitoring of trends. The artificial sky brightness present in the chosen direction at a given position on the Earth's surface is obtained by the integration of the contributions produced by every surface area in the surrounding. Each contribution is computed based on detailed models for the propagation in the atmosphere of the upward light flux emitted by the area. The light flux is measured with top of atmosphere radiometric observations made by the Defense Meteorological Satellite Program (DMSP) Operational Linescan System. We applied the described method to Europe obtaining the maps of artificial sky brightness in V and B bands.

  7. angle x-ray sky: Topics by E-print Network

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

    Astrophysics (arXiv) Summary: We describe a search for X-ray afterglows from gamma-ray bursts using the ROSAT all-sky survey (RASS) data. If the emission in the soft X-ray...

  8. Spectrometer for Sky-Scanning Sun-Tracking Atmospheric Research (4STAR): Instrument Technology

    SciTech Connect (OSTI)

    Dunagan, Stephen; Johnson, Roy; Zavaleta, Jhony; Russell, P. B.; Schmid, Beat; Flynn, Connor J.; Redemann, Jens; Shinozuka, Yohei; Livingston, J.; Segal Rozenhaimer, Michal

    2013-08-06T23:59:59.000Z

    The Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) combines airborne sun tracking and sky scanning with diffraction spectroscopy, to improve knowledge of atmospheric constituents and their links to air-pollution/climate. Direct beam hyper-spectral measurement of optical depth improves retrievals of gas constituents and determination of aerosol properties. Sky scanning enhances retrievals of aerosol type and size distribution. 4STAR measurements will tighten the closure between satellite and ground-based measurements. 4STAR incorporates a modular sun-tracking/ sky-scanning optical head with fiber optic signal transmission to rack mounted spectrometers, permitting miniaturization of the external optical head, and future detector evolution. Technical challenges include compact optical collector design, radiometric dynamic range and stability, and broad spectral coverage. Test results establishing the performance of the instrument against the full range of operational requirements are presented, along with calibration, engineering flight test, and scientific field campaign data and results.

  9. Dkar yol nang Paean 8, The High Blue Sky and the Low White Clouds

    E-Print Network [OSTI]

    Rdo rje rgyal

    ??????? Tape No. / Track / Item No. Dkar yol nang Paean 8.WAV Length of track 00:03:05 Related tracks (include description/relationship if appropriate) Title of track The High Blue Sky and the Low White Clouds ??????? ?...

  10. OT 060420: A Seemingly Optical Transient Recorded by All-Sky Cameras

    E-Print Network [OSTI]

    Lior Shamir; Robert J. Nemiroff

    2006-07-03T23:59:59.000Z

    We report on a ~5th magnitude flash detected for approximately 10 minutes by two CONCAM all-sky cameras located in Cerro Pachon - Chile and La Palma - Spain. A third all-sky camera, located in Cerro Paranal - Chile did not detect the flash, and therefore the authors of this paper suggest that the flash was a series of cosmic-ray hits, meteors, or satellite glints. Another proposed hypothesis is that the flash was an astronomical transient with variable luminosity. In this paper we discuss bright optical transient detection using fish-eye all-sky monitors, analyze the apparently false-positive optical transient, and propose possible causes to false optical transient detection in all-sky cameras.

  11. A Radiometric All-Sky Infrared Camera (RASICAM) for DES/CTIO

    SciTech Connect (OSTI)

    Lewis, Peter M.; Rogers, Howard; Schindler, Rafe H.; /SLAC

    2010-08-25T23:59:59.000Z

    A novel radiometric all-sky infrared camera [RASICAM] has been constructed to allow automated real-time quantitative assessment of night sky conditions for the Dark Energy Camera [DECam] located on the Blanco Telescope at the Cerro Tololo Inter-American Observatory in Chile. The camera is optimized to detect the position, motion and optical depth of thin, high (8-10km) cirrus clouds and contrails by measuring their apparent temperature above the night sky background. The camera system utilizes a novel wide-field equiresolution catadioptic mirror system that provides sky coverage of 2{pi} azimuth and 14-90{sup o} from zenith. Several new technological and design innovations allow the RASICAM system to provide unprecedented cloud detection and IR-based photometricity quantification. The design of the RASICAM system is presented.

  12. AN EMPIRICAL METHOD FOR ESTIMATING THE THERMAL RADIANCE OF CLEAR SKIES

    E-Print Network [OSTI]

    Berdahl, Paul

    2012-01-01T23:59:59.000Z

    Cloud cover has a strong effect on the atmos- pheric radiationeffect of clouds upon the spectrum of atmospheric radiationclouds will not be detected, but their effect on the sky radiation

  13. UPRE method for total variation parameter selection

    SciTech Connect (OSTI)

    Wohlberg, Brendt [Los Alamos National Laboratory; Lin, Youzuo [Los Alamos National Laboratory

    2008-01-01T23:59:59.000Z

    Total Variation (TV) Regularization is an important method for solving a wide variety of inverse problems in image processing. In order to optimize the reconstructed image, it is important to choose the optimal regularization parameter. The Unbiased Predictive Risk Estimator (UPRE) has been shown to give a very good estimate of this parameter for Tikhonov Regularization. In this paper we propose an approach to extend UPRE method to the TV problem. However, applying the extended UPRE is impractical in the case of inverse problems such as de blurring, due to the large scale of the associated linear problem. We also propose an approach to reducing the large scale problem to a small problem, significantly reducing computational requirements while providing a good approximation to the original problem.

  14. Milagro: A TeV Gamma-Ray Monitor of the Northern Hemisphere Sky

    E-Print Network [OSTI]

    California at Santa Cruz, University of

    transients, such as gamma-ray bursts, and all sky surveys are diÆcult. A new type of TeV -ray observatoryMilagro: A TeV Gamma-Ray Monitor of the Northern Hemisphere Sky B.L. Dingus 1 , R. Atkins 1 , W type of very high energy (> a few 100 GeV) gamma-ray observatory, Milagro, has been built with a large

  15. Ice-induced enhancement of solar radiation beneath overcast skies near Antarctica

    E-Print Network [OSTI]

    Horvath, Nicholas Charles

    1981-01-01T23:59:59.000Z

    ICE-INDUCED ENHANCEMENT OF SOLAR RADIATION BENEATH OVERCAST SKIES NEAR ANTARCTICA A Thesis by NICHOLAS CHARLES HORVATH Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirement for the degree... of MASTER OF SCIFNCE May 1981 Major Subject: Meteorology ICE-INDUCED ENHANCEMENT OF SOLAR RADIATION BENEATH OVERCAST SKIES NEAR ANTARCTICA A Thesis by NICHOLAS CHARLES HORVATH Approsed as to style and content by: (Ch irman of Committee) (Member...

  16. CORRELATIONS AMONG GALAXY PROPERTIES FROM THE SLOAN DIGITAL SKY SURVEY

    SciTech Connect (OSTI)

    Li Zhongmu; Mao Caiyan, E-mail: zhongmu.li@gmail.com [Institute for Astronomy and History of Science and Technology, Dali University, Dali 671003 (China)

    2013-07-01T23:59:59.000Z

    Galaxies are complex systems with many properties. Correlations among galaxy properties can supply important clues for studying the formation and evolution of galaxies. Using principal component analysis and least-squares fitting, this paper investigates the correlations among galactic parameters involving more properties (color, morphology, stellar population, and absolute magnitude) than previous studies. We use a volume-limited sample (whole sample) of 75,423 galaxies that was selected from the Sloan Digital Sky Survey Data Release 2 and divided into two subsamples (blue and red samples) using a critical color of (g - r) = 0.70 mag. In addition to recovering some previous results, we also obtain some new results. First, all separators for dividing galaxies into two groups can be related via good parameter-first principal component (PC1) correlations. A critical PC1 that indicates whether or not stellar age (or the evolution of a stellar population over time) is important can be used to separate galaxies. This suggests that a statistical parameter, PC1, is helpful in understanding the physical separators of galaxies. In addition, stellar age is shown to be unimportant for red galaxies, while both stellar age and mass are dominating parameters of blue galaxies. This suggests that the various numbers of dominating parameters of galaxies may result from the use of different samples. Finally, some parameters are shown to be correlated, and quantitative fits for a few correlations are obtained, e.g., log(t) = 8.57 + 1.65 (g - r) for the age (log t) and color (g - r) of blue galaxies and log (M{sub *}) = 4.31 - 0.30 M{sub r} for the stellar mass (log M{sub *}) and absolute magnitude (M{sub r}) of red galaxies. The median relationships between various parameter pairs are also presented for comparison.

  17. Signal and Image Processing, SIP-2000, Las Vegas, USA, (c) IASTED SEARCHING FOR AURORA

    E-Print Network [OSTI]

    Syrjäsuo, Mikko

    Signal and Image Processing, SIP-2000, Las Vegas, USA, (c) IASTED SEARCHING FOR AURORA MIKKO T. We demonstrate an automatical algorithm for searching aurora in auroral all-sky images. The algorithm that contain aurora and require further examination in the detection phase. The detection is based on shape

  18. Status of an Atmospheric Cherenkov Imaging Camera for the CANGAROOIII Experiment

    E-Print Network [OSTI]

    Enomoto, Ryoji

    Gamma Ray Observa- tory (CGRO) was launched in 1991. The EGRET detector [7] on board CGRO detected gamma]. The detection of gamma rays from an Active Galactic Nuclei(AGN), Markarian 421 [10], established the imaging of very high energy gamma rays from celestial objects in the southern sky. We use an array of 4 imaging

  19. Star-Formation in Low Radio Luminosity AGN from the Sloan Digital Sky Survey

    SciTech Connect (OSTI)

    de Vries, W H; Hodge, J A; Becker, R H; White, R L; Helfand, D J

    2007-04-18T23:59:59.000Z

    We investigate faint radio emission from low- to high-luminosity Active Galactic Nuclei (AGN) selected from the Sloan Digital Sky Survey (SDSS). Their radio properties are inferred by coadding large ensembles of radio image cut-outs from the FIRST survey, as almost all of the sources are individually undetected. We correlate the median radio flux densities against a range of other sample properties, including median values for redshift, [O III] luminosity, emission line ratios, and the strength of the 4000{angstrom} break. We detect a strong trend for sources that are actively undergoing star-formation to have excess radio emission beyond the {approx} 10{sup 28} ergs s{sup -1} Hz{sup -1} level found for sources without any discernible star-formation. Furthermore, this additional radio emission correlates well with the strength of the 4000{angstrom} break in the optical spectrum, and may be used to assess the age of the star-forming component. We examine two subsamples, one containing the systems with emission line ratios most like star-forming systems, and one with the sources that have characteristic AGN ratios. This division also separates the mechanism responsible for the radio emission (star-formation vs. AGN). For both cases we find a strong, almost identical, correlation between [O III] and radio luminosity, with the AGN sample extending toward lower, and the star-formation sample toward higher luminosities. A clearer separation between the two subsamples is seen as function of the central velocity dispersion {sigma} of the host galaxy. For systems at similar redshifts and values of {sigma}, the star-formation subsample is brighter than the AGN in the radio by an order of magnitude. This underlines the notion that the radio emission in star-forming systems can dominate the emission associated with the AGN.

  20. The Sloan Digital Sky Survey Quasar Catalog. 3. Third data release

    SciTech Connect (OSTI)

    Schneider, Donald P.; Hall, Patrick B.; Richards, Gordon T.; Vanden Berk, Daniel E.; Anderson, Scott F.; Fan, Xiao-Hui; Jester, Sebastian; Stoughton, Chris; Strauss,; SubbaRao, Mark; Brandt, W.N.; Gunn, James E.; Yanny, Brian; Bahcall, Neta A.; Barentine, J.C.; Blanton, Michael R.; Boroski, William N.; Brewington, Howard J.; Brinkmann, J.; Brunner, Robert; Csabai, Istvan; /Penn State U., Astron. Astrophys. /York U., Canada /Princeton U. Observ. /Washington U., Seattle, Astron. Dept. /Arizona U.,

    2005-03-01T23:59:59.000Z

    We present the third edition of the Sloan Digital Sky Survey (SDSS) Quasar Catalog. The catalog consists of the 46,420 objects in the SDSS Third Data Release that have luminosities larger than M{sub i} = -22 (in a cosmology with H{sub 0} = 70 km s{sup -1} Mpc{sup -1}, {Omega}{sub M} = 0.3, and {Omega}{sub {Lambda}} = 0.7), have at least one emission line with FWHM larger than 1000 km s{sup -1} or are unambiguously broad absorption line quasars, are fainter than i = 15.0, and have highly reliable redshifts. The area covered by the catalog is {approx} 4188 deg{sup 2}. The quasar redshifts range from 0.08 to 5.41, with a median value of 1.47; the high-redshift sample includes 520 quasars at redshifts greater than four, of which 17 are at redshifts greater than five. For each object the catalog presents positions accurate to better than 0.2'' rms per coordinate, five-band (ugriz) CCD-based photometry with typical accuracy of 0.03 mag, and information on the morphology and selection method. The catalog also contains radio, near-infrared, and X-ray emission properties of the quasars, when available, from other large-area surveys. The calibrated digital spectra cover the wavelength region 3800-9200 at a spectral resolution of {approx} 2000; the spectra can be retrieved from the public database using the information provided in the catalog. A total of 44,221 objects in the catalog were discovered by the SDSS; 28,400 of the SDSS discoveries are reported here for the first time.

  1. Properties of Luminous Red Galaxies in the Sloan Digital Sky Survey

    E-Print Network [OSTI]

    T. Barber; A. Meiksin; T. Murphy

    2006-11-02T23:59:59.000Z

    We perform population synthesis modelling of a magnitude-limited sample of 4391 Luminous Red Galaxies selected from the Sloan Digital Sky Survey Data Release 4 (SDSS DR4). We fit measured spectral indices using a large library of high resolution spectra, covering a wide range of metallicities and assuming an exponentially decaying star-formation rate punctuated by bursts, to obtain median-likelihood estimates for the light-weighted age, metallicity, stellar mass and extinction for the galaxies. The ages lie in the range 4-10 Gyr, peaking near 6 Gyr, with metallicities in the range -0.4<[Z/H]<0.4, peaking at [Z/H] ~ 0.2. Only a few per cent of the spectra are better fit allowing for a burst in addition to continuous star-formation. The total stellar masses of all the galaxies are confined to a very narrow range. Our results broadly agree with those of previous groups using an independent population synthesis code. We find, however, that our choice in priors results in ages 1-2 Gyr smaller, decreasing the peak star formation epoch from z=2.3 to z=1.3. We develop a metal evolution model incorporating stochastic star-formation quenching motivated by recent attempts to solve the `anti-hierarchical' formation problem of ellipticals. Two scenarios emerge, a closed box with an effective stellar yield of 0.26, and an accreting box with an effective stellar yield of 0.10. Both scenarios require an IMF weighted towards massive stars and characteristic star-formation quenching times of about 100 Myr, the expected lifetime of luminous QSOs. The models predict an anti-correlation between the age and mean metallicity similar to that observed.

  2. Sixty-seven Additional L Dwarfs Discovered by the Two Micron All Sky Survey (2MASS)

    E-Print Network [OSTI]

    J. Davy Kirkpatrick; I. Neill Reid; James Liebert; John E. Gizis; Adam J. Burgasser; David G. Monet; Conard C. Dahn; Brant Nelson; Rik J. Williams

    2000-03-22T23:59:59.000Z

    We present JHKs photometry, far red spectra, and spectral classifications for an additional 67 L dwarfs discovered by the Two Micron All Sky Survey. One of the goals of this new search was to locate more examples of the latest L dwarfs. Of the 67 new discoveries, 17 have types of L6 or later. Analysis of these new discoveries shows that H-alpha emission has yet to be convincingly detected in any L dwarf later than type L4.5, indicating a decline or absence of chromospheric activity in the latest L dwarfs. Further analysis shows that 16 (and possibly 4 more) of the new L dwarfs are lithium brown dwarfs and that the average line strength for those L dwarfs showing lithium increases until roughly type L6.5 V then declines for later types. This disappearance may be the first sign of depletion of atomic lithium as it begins to form into lithium-bearing molecules. Another goal of the search was to locate nearer, brighter L dwarfs of all subtypes. Using absolute magnitudes for 17 L dwarf systems with trigonometric parallax measurements, we develop spectrophotometric relations to estimate distances to the other L dwarfs. Of the 67 new discoveries, 21 have photometric distances placing them within 25 parsecs of the Sun. A table of all known L and T dwarfs believed to lie within 25 parsecs - 53 in total - is also presented. Using the distance measurement of the coolest L dwarf known, we calculate that the gap in temperature between L8 and the warmest known T dwarfs is less than 350K and probably much less. If the transition region between the two classes spans a very small temperature interval, this would explain why no transition objects have yet been uncovered. This evidence, combined with model fits to low-resolution spectra of late-M and early-L dwarfs, indicates that L dwarfs span the range 1300K < Teff < 2000K.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    Gasoline and Diesel Fuel Update (EIA)

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

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

    Gasoline and Diesel Fuel Update (EIA)

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

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

    Gasoline and Diesel Fuel Update (EIA)

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

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

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

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

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

    Gasoline and Diesel Fuel Update (EIA)

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

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

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

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

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

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

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

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

    Gasoline and Diesel Fuel Update (EIA)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo7.1 19.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo7.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1Do NotDo7.1...

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

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

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

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

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

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

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1DoCooking25.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.0 12.1DoCooking25.65.6

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

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

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

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.04.2 7.6 16.6 Personal

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.04.2 7.6 16.6 Personal

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2, 2003Tool ofTopo II:7.1 7.0 8.04.2 7.6 16.6

  1. Total

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear JanYear Jan Feb Mar Apr May(MillionFeet)July 23,

  2. Total

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear JanYear Jan Feb Mar Apr May(MillionFeet)July 23,Product:

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720 1,970

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720 111.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720Q Table

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720Q

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6 2,720Q14.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1 86.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.8 20.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.8 20.6,171

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.8

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.820.6 25.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.820.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7 28.820.626.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1 19.0 22.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1 19.0 22.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1 19.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1 19.014.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.178.1 64.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.178.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770 111.126.747.178.1.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,770

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.2 3.3 1.9

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.2 3.3

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.2 3.3Type

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.214.7 7.4

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.214.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0 1.214.75.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.6 40.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.65.6 17.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.65.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8 1.025.65.64.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.8

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.0 22.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.025.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.025.6.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1 19.025.6.5.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2 7.6 16.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2 7.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2 7.67.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2 7.67.10.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.24.2 7.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.24.2 7.6Do

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.24.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2 7.87.14.24.2Cooking

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not Have Cooling

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not Have

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo Not

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo NotDo

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo0.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo0.7

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not HaveDo0.77.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1 7.0 8.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1 7.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1 7.05.6

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1Personal

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do Not7.1Personal4.2

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do 111.1 47.1 19.0

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33 111 1,613 122 40 Buildingto17questionnairesU.S. Weekly70516,2,730,77015.2Do 111.1 47.1

  17. A Catalog of Spectroscopically Identified White Dwarf Stars in the First Data Release of the Sloan Digital Sky Survey

    E-Print Network [OSTI]

    S. J. Kleinman; Hugh C. Harris; Daniel J. Eisenstein; James Liebert; Atsuko Nitta; Jurek Krzesi?ski; Jeffrey A. Munn; Conard C. Dahn; Suzanne L. Hawley; Jeffrey R. Pier; Gary Schmidt; Nicole M. Silvestri; J. Allyn Smith; Paula Szkody; Michael A. Strauss; G. R. Knapp; Matthew J. Collinge; A. S. Mukadam; D. Koester; Alan Uomoto; D. J. Schlegel; Scott F. Anderson; J. Brinkmann; D. Q. Lamb; Donald P. Schneider; Donald G. York

    2004-02-12T23:59:59.000Z

    We present the full spectroscopic white dwarf and hot subdwarf sample from the SDSS first data release, DR1. We find 2551 white dwarf stars of various types, 240 hot subdwarf stars, and an additional 144 objects we have identified as uncertain white dwarf stars. Of the white dwarf stars, 1888 are non-magnetic DA types and 171, non-magnetic DBs. The remaining (492) objects consist of all different types of white dwarf stars: DO, DQ, DC, DH, DZ, hybrid stars like DAB, etc., and those with non-degenerate companions. We fit the DA and DB spectra with a grid of models to determine the Teff and log(g) for each object. For all objects, we provide coordinates, proper motions, SDSS photometric magnitudes, and enough information to retrieve the spectrum/image from the SDSS public database. This catalog nearly doubles the known sample of spectroscopically-identified white dwarf stars. In the DR1 imaged area of the sky, we increase the known sample of white dwarf stars by a factor of 8.5. We also comment on several particularly interesting objects in this sample.

  18. CLEAR SKY MODELS ASSESSMENT FOR AN OPERATIONAL PV PRODUCTION FORECASTING Sylvain Cros, Olivier Liandrat, Nicolas Sbastien, Nicolas Schmutz

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    reanalysis instead of punctual measurements significantly reduces errors in clear sky models. 1 INTRODUCTION the concentration of atmospheric components absorbing and diffusing solar radiation in the shortwave. Concerned

  19. Bistatic SAR: Signal Processing and Image Formation.

    SciTech Connect (OSTI)

    Wahl, Daniel E.; Yocky, David A.

    2014-10-01T23:59:59.000Z

    This report describes the significant processing steps that were used to take the raw recorded digitized signals from the bistatic synthetic aperture RADAR (SAR) hardware built for the NCNS Bistatic SAR project to a final bistatic SAR image. In general, the process steps herein are applicable to bistatic SAR signals that include the direct-path signal and the reflected signal. The steps include preprocessing steps, data extraction to for a phase history, and finally, image format. Various plots and values will be shown at most steps to illustrate the processing for a bistatic COSMO SkyMed collection gathered on June 10, 2013 on Kirtland Air Force Base, New Mexico.

  20. CMB Maps at 0.5 degree Resolution I: Full-Sky Simulations and Basic Results

    E-Print Network [OSTI]

    G. Hinshaw; C. L. Bennett; A. Kogut

    1994-08-12T23:59:59.000Z

    We have simulated full-sky maps of the Cosmic Microwave Background (CMB) anisotropy expected from Cold Dark Matter (CDM) models at 0.5 and 1.0 degree angular resolution. Statistical properties of the maps are presented as a function of sky coverage, angular resolution, and instrument noise, and the implications of these results for observability of the Doppler peak are discussed. The rms fluctuations in a map are not a particularly robust probe of the existence of a Doppler peak, however, a full correlation analysis can provide reasonable sensitivity. We find that sensitivity to the Doppler peak depends primarily on the fraction of sky covered, and only secondarily on the angular resolution and noise level. Color plates and one-dimensional scans of the maps are presented to visually illustrate the anisotropies.

  1. Neural networks and separation of background and foregrounds in astrophysical sky maps

    E-Print Network [OSTI]

    Baccigalupi, C; Burigana, C; De Zotti, G; Farusi, A; Maino, D; Maris, M; Perrotta, F; Salerno, E; Toffolatti, L; Tonazzini, A

    2000-01-01T23:59:59.000Z

    The Independent Component Analysis (ICA) algorithm is implemented as a neuralnetwork for separating signals of different origin in astrophysical sky maps.Due to its self-organizing capability, it works without prior assumptions onthe signals, neither on their frequency scaling, nor on the signal mapsthemselves; instead, it learns directly from the input data how to separate thephysical components, making use of their statistical independence. To test thecapabilities of this approach, we apply the ICA algorithm on sky patches, takenfrom simulations and observations, at the microwave frequencies, that are goingto be deeply explored in a few years on the whole sky, by the MicrowaveAnisotropy Probe (MAP) and by the {\\sc Planck} Surveyor Satellite. The maps areat the frequencies of the Low Frequency Instrument (LFI) aboard the {\\scPlanck} satellite (30, 44, 70 and 100 GHz), and contain simulated astrophysicalradio sources, Cosmic Microwave Background (CMB) radiation, and Galacticdiffuse emissions from thermal dust...

  2. The Cosmic Lens All-Sky Survey:II. Gravitational lens candidate selection and follow-up

    E-Print Network [OSTI]

    I. W. A. Browne; P. N. Wilkinson; N. J. F. Jackson; S. T. Myers; C. D. Fassnacht; L. V. E. Koopmans; D. R. Marlow; M. Norbury; D. Rusin; C. M. Sykes; A. D. Biggs; R. D. Blandford; A. G. de Bruyn; K-H. Chae; P. Helbig; L. J. King; J. P. McKean; T. J. Pearson; P. M. Phillips; A. C. S. Readhead; E. Xanthopoulos; T. York

    2002-11-11T23:59:59.000Z

    We report the final results of the search for gravitationally lensed flat-spectrum radio sources found in the combination of CLASS (Cosmic Lens All Sky Survey) and JVAS (Jodrell-Bank VLA Astrometric Survey). VLA observations of 16,503 sources have been made, resulting in the largest sample of arcsec-scale lens systems available. Contained within the 16,503 sources is a complete sample of 11,685 sources having two-point spectral indices between 1.4 and 5 GHz flatter than -0.5 and 5 GHz flux densities $\\geq$30 mJy. A subset of 8,958 sources form a well-defined statistical sample suitable for analysis of the lens statistics. We describe the systematic process by which 149 candidate lensed sources were picked from the statistical sample on the basis of possessing multiple compact components in the 0.2 arcsec-resolution VLA maps. Candidates were followed up with 0.05 arcsec resolution MERLIN and 0.003 arcsec VLBA observations at 5 GHz and rejected as lens systems if they failed well-defined surface brightness and/or morphological tests. Maps for all the candidates can be found on the World Wide Web at http://www.jb.man.ac.uk/research/gravlens/index.html We summarize the properties of each of the 22 gravitational lens systems in JVAS/CLASS. Twelve are double-image systems, nine are four-image systems and one is a six-image system. Thirteen constitute a statistically well-defined sample giving a point-source lensing rate of 1:690$\\pm$190. The interpretation of the results in terms of the properties of the lensing galaxy population and cosmological parameters will be published elsewhere. (Abridged)

  3. Mass Media Minor Requirements (total 20 credits) Prerequisites

    E-Print Network [OSTI]

    Bates, Rebecca A.

    in Mass Media · MASS 334 (04) Writing and Speaking For Broadcast · MASS 351 (04) Digital Imaging For Mass Media · MASS 360 (04) Digital Design For Mass Media · MASS 412 (04) Mass Media History · MASS 431 (04Mass Media Minor Requirements (total 20 credits) Prerequisites: · MASS 110 Introduction to Mass

  4. Correction factors for the sun shield used with the Eppley pyranometer for the measurement of sky radiation under clear and partly cloudy skies

    E-Print Network [OSTI]

    Albro, William Arthur

    1967-01-01T23:59:59.000Z

    times. This process is termed multiple scattering. In a qualitative sense, however, Ray- leigh's theory leads us to the conclusion that sky radiation is anisotropic and that its maximum intensity should be concentrated in the vicinity of the solar... of solar radiation are discussed. The method in which a metal. band is utilized to screen the direct rays of Sun from the pyrano- metric sensor is examined in detail. Based on the assumption that the distribution of skI ~adiation is isotropic...

  5. Galaxy Evolution Insights from Spectral Modeling of Large Data Sets from the Sloan Digital Sky Survey

    SciTech Connect (OSTI)

    Hoversten, Erik A.; /Johns Hopkins U.

    2007-10-01T23:59:59.000Z

    This thesis centers on the use of spectral modeling techniques on data from the Sloan Digital Sky Survey (SDSS) to gain new insights into current questions in galaxy evolution. The SDSS provides a large, uniform, high quality data set which can be exploited in a number of ways. One avenue pursued here is to use the large sample size to measure precisely the mean properties of galaxies of increasingly narrow parameter ranges. The other route taken is to look for rare objects which open up for exploration new areas in galaxy parameter space. The crux of this thesis is revisiting the classical Kennicutt method for inferring the stellar initial mass function (IMF) from the integrated light properties of galaxies. A large data set ({approx} 10{sup 5} galaxies) from the SDSS DR4 is combined with more in-depth modeling and quantitative statistical analysis to search for systematic IMF variations as a function of galaxy luminosity. Galaxy H{alpha} equivalent widths are compared to a broadband color index to constrain the IMF. It is found that for the sample as a whole the best fitting IMF power law slope above 0.5 M{sub {circle_dot}} is {Lambda} = 1.5 {+-} 0.1 with the error dominated by systematics. Galaxies brighter than around M{sub r,0.1} = -20 (including galaxies like the Milky Way which has M{sub r,0.1} {approx} -21) are well fit by a universal {Lambda} {approx} 1.4 IMF, similar to the classical Salpeter slope, and smooth, exponential star formation histories (SFH). Fainter galaxies prefer steeper IMFs and the quality of the fits reveal that for these galaxies a universal IMF with smooth SFHs is actually a poor assumption. Related projects are also pursued. A targeted photometric search is conducted for strongly lensed Lyman break galaxies (LBG) similar to MS1512-cB58. The evolution of the photometric selection technique is described as are the results of spectroscopic follow-up of the best targets. The serendipitous discovery of two interesting blue compact dwarf galaxies is reported. These galaxies were identified by their extremely weak (< 150) [N {pi}] {lambda}6584 to H{alpha} emission line ratios. Abundance analysis from emission line fluxes reveals that these galaxies have gas phase oxygen abundances 12 + log(O/H) {approx} 7.7 to 7.9, not remarkably low, and near infrared imaging detects an old stellar population. However, the measured nitrogen to oxygen ratios log(N/O) < 1.7 are anomalously low for blue compact dwarf galaxies. These objects may be useful for understanding the chemical evolution of nitrogen.

  6. Advances in total scattering analysis

    SciTech Connect (OSTI)

    Proffen, Thomas E [Los Alamos National Laboratory; Kim, Hyunjeong [Los Alamos National Laboratory

    2008-01-01T23:59:59.000Z

    In recent years the analysis of the total scattering pattern has become an invaluable tool to study disordered crystalline and nanocrystalline materials. Traditional crystallographic structure determination is based on Bragg intensities and yields the long range average atomic structure. By including diffuse scattering into the analysis, the local and medium range atomic structure can be unravelled. Here we give an overview of recent experimental advances, using X-rays as well as neutron scattering as well as current trends in modelling of total scattering data.

  7. Total Imports of Residual Fuel

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality", 2013,Iowa"Dakota"YearProductionShaleInput Product: TotalCountry:

  8. THE GREAT OBSERVATORIES ALL-SKY LIRG SURVEY: COMPARISON OF ULTRAVIOLET AND FAR-INFRARED PROPERTIES

    SciTech Connect (OSTI)

    Howell, Justin H.; Armus, Lee; Surace, Jason A.; Petric, Andreea; Bridge, Carrie; Haan, Sebastian; Inami, Hanae [Spitzer Science Center, MS 220-6, California Institute of Technology, Pasadena, CA 91125 (United States); Mazzarella, Joseph M.; Chan, Ben H. P.; Madore, Barry F. [Infrared Processing and Analysis Center, MS 100-22, California Institute of Technology, Pasadena, CA 91125 (United States); Evans, Aaron S.; Kim, Dong-Chan [Department of Astronomy, University of Virginia, P.O. Box 400325, Charlottesville, VA 22904 (United States); Sanders, David B. [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States); Appleton, Phil; Frayer, David T.; Lord, Steven; Schulz, Bernhard [NASA Herschel Science Center, IPAC, MS 100-22, California Institute of Technology, Pasadena, CA 91125 (United States); Bothun, Greg [Department of Physics, University of Oregon, Eugene, OR 97403 (United States); Charmandaris, Vassilis [University of Crete, Department of Physics, Heraklion 71003 (Greece); Melbourne, Jason, E-mail: jhhowell@ipac.caltech.ed [Caltech Optical Observatories, Division of Physics, Mathematics and Astronomy, Mail Stop 320-47, California Institute of Technology, Pasadena, CA 91125 (United States)

    2010-05-20T23:59:59.000Z

    The Great Observatories All-sky LIRG Survey (GOALS) consists of a complete sample of 202 luminous infrared galaxies (LIRGs) selected from the IRAS Revised Bright Galaxy Sample (RBGS). The galaxies span the full range of interaction stages, from isolated galaxies to interacting pairs to late stage mergers. We present a comparison of the UV and infrared properties of 135 galaxies in GOALS observed by GALEX and Spitzer. For interacting galaxies with separations greater than the resolution of GALEX and Spitzer ({approx}2''-6''), we assess the UV and IR properties of each galaxy individually. The contribution of the FUV to the measured star formation rate (SFR) ranges from 0.2% to 17.9%, with a median of 2.8% and a mean of 4.0% {+-} 0.4%. The specific star formation rate (SSFR) of the GOALS sample is extremely high, with a median value (3.9 x 10{sup -10} yr{sup -1}) that is comparable to the highest SSFRs seen in the Spitzer Infrared Nearby Galaxies Survey sample. We examine the position of each galaxy on the IR excess-UV slope (IRX-{beta}) diagram as a function of galaxy properties, including IR luminosity and interaction stage. The LIRGs on average have greater IR excesses than would be expected based on their UV colors if they obeyed the same relations as starbursts with L{sub IR} < 10{sup 11} L{sub sun} or normal late-type galaxies. The ratio of L{sub IR} to the value one would estimate from the IRX-{beta} relation published for lower luminosity starburst galaxies ranges from 0.2 to 68, with a median value of 2.7. A minimum of 19% of the total IR luminosity in the RBGS is produced in LIRGs and ultraluminous infrared galaxies with red UV colors ({beta}>0). Among resolved interacting systems, 32% contain one galaxy which dominates the IR emission while the companion dominates the UV emission. Only 21% of the resolved systems contain a single galaxy which dominates both wavelengths.

  9. Page (Total 3) Philadelphia University

    E-Print Network [OSTI]

    Page (Total 3) Philadelphia University Faculty of Science Department of Biotechnology and Genetic be used in animals or plants. It can be also used in environmental monitoring, food processing ...etc are developed and marketed in kit format by biotechnology companies. The main source of information is web sites

  10. SkyHunter: A Multi-Surface Environment for Supporting Oil and Gas Exploration

    E-Print Network [OSTI]

    Maurer, Frank

    SkyHunter: A Multi-Surface Environment for Supporting Oil and Gas Exploration Teddy Seyed, Mario}@ucalgary.ca ABSTRACT The process of oil and gas exploration and its result, the decision to drill for oil in a specific show in this paper, many of the existing technologies and practices that support the oil and gas

  11. Multipole vector anomalies in the first-year WMAP data: a cut-sky analysis

    E-Print Network [OSTI]

    P. Bielewicz; H. K. Eriksen; A. J. Banday; K. M. Gorski; P. B. Lilje

    2005-08-15T23:59:59.000Z

    We apply the recently defined multipole vector framework to the frequency-specific first-year WMAP sky maps, estimating the low-l multipole coefficients from the high-latitude sky by means of a power equalization filter. While most previous analyses of this type have considered only heavily processed (and foreground-contaminated) full-sky maps, the present approach allows for greater control of residual foregrounds, and therefore potentially also for cosmologically important conclusions. The low-l spherical harmonics coefficients and corresponding multipole vectors are tabulated for easy reference. Using this formalism, we re-assess a set of earlier claims of both cosmological and non-cosmological low-l correlations based on multipole vectors. First, we show that the apparent l=3 and 8 correlation claimed by Copi et al. (2004) is present only in the heavily processed map produced by Tegmark et al. (2003), and must therefore be considered an artifact of that map. Second, the well-known quadrupole-octopole correlation is confirmed at the 99% significance level, and shown to be robust with respect to frequency and sky cut. Previous claims are thus supported by our analysis. Finally, the low-l alignment with respect to the ecliptic claimed by Schwarz et al. (2004) is nominally confirmed in this analysis, but also shown to be very dependent on severe a-posteriori choices. Indeed, we show that given the peculiar quadrupole-octopole arrangement, finding such a strong alignment with the ecliptic is not unusual.

  12. Horizon brightness revisited: measurements and a model of clear-sky radiances

    E-Print Network [OSTI]

    Lee Jr., Raymond L.

    from solar energy engineering2 ,3 to atmospheric optics4'5 have repeatedly measured and modeled. Second, before the advent of narrow field-of-view (FOV) radiometers8 and photographic analysis tech explanation of the phenomenon. High-Resolution Measurements of Clear-Sky Radiances We beginby electronically

  13. Investigation of astrophysical phenomena in short time scales with "Pi of the Sky" apparatus

    E-Print Network [OSTI]

    Marcin Sokolowski

    2008-10-07T23:59:59.000Z

    In this thesis the data analysis designed by author for the "Pi of the Sky" experiment is presented. The data analysis consists of data reduction and specific algorithms for identification of short time scale astrophysical processes. The algorithms have been tested and their efficiency has been determined and described. The "Pi of the Sky" prototype is collecting data since June 2004 and algorithms could be intensively studied and improved during over 700 nights. A few events of confirmed astrophysical origin and above 100 events in 10s time scale of unknown nature have been discovered. During the data collection period 3 Gamma Ray Bursts (out of 231) occurred in the field of view of the telescope, but no optical counterpart has been found. The upper limits for brightness of the optical counterpart have been determined. The continuous monitoring of the sky and own trigger for optical flashes allowed to determine limits on the number of GRBs without corresponding gamma-ray detection. This allowed determining limits on the ratio of emission collimation in optical and gamma bands, which is R >= 4.4. The perspectives of the full "Pi of the Sky" system has been studied and number of positive detections has been estimated on the level of ~ 2.5 events per year.

  14. The Artificial Sky Luminance And The Emission Angles Of The Upward Light Flux

    E-Print Network [OSTI]

    P. Cinzano; F. J. Diaz Castro

    1998-11-19T23:59:59.000Z

    The direction of the upward light emission has different polluting effects on the sky depending on the distance of the observation site. We studied with detailed models for light pollution propagation the ratio $(b_{H})/(b_{L})$, at given distances from a city, between the artificial sky luminance $b_{H}$ produced by its upward light emission between a given threshold angle $\\theta_{0}$ and the vertical and the artificial sky luminance $b_{L}$ produced by its upward light emission between the horizontal and the threshold angle $\\theta_{0}$. Our results show that as the distance from the city increases the effects of the emission at high angles above the horizontal decrease relative to the effects of emission at lower angles above the horizontal. Outside some kilometers from cities or towns the light emitted between the horizontal and 10\\deg ~is as important as the light emitted at all the other angles in producing the artificial sky luminance. Therefore the protection of a site requires also a careful control of this emission which needs to be reduced to at most 1/10 of the remaining emission. The emission between the horizontal and 10\\deg ~is mostly produced by spill light from luminaires, so fully shielded fixtures (e.g. flat glass luminaires or asymmetric spot-lights installed without any tilt) are needed for this purpose.

  15. Tracing luminous and dark matter with the Sloan Digital Sky Survey

    E-Print Network [OSTI]

    Jon Loveday; for the SDSS collaboration

    2001-08-30T23:59:59.000Z

    I summarize the scientific goals and current status of the Sloan Digital Sky Survey, briefly describe the Early Data Release, and discuss some recent scientific results obtained from commissioning data which are apposite to the distribution of luminous and dark matter in the Universe.

  16. Go forth, under the To Nature's t open sky, and list

    E-Print Network [OSTI]

    Mojzsis, Stephen J.

    #12;Go forth, under the To Nature's t open sky, and list eachlngs. -William Cullen Bryant / #12;A. Summertime possibilities range from hiking and biking to exploring old mining towns and sailing on mountain's Division of Continuing Education. These outreach programs are open to students, to members of the com

  17. All-sky search for periodic gravitational waves in the full S5 LIGO data

    E-Print Network [OSTI]

    Barsotti, Lisa

    We report on an all-sky search for periodic gravitational waves in the frequency band 50–800 Hz and with the frequency time derivative in the range of 0 through -6×10[superscript -9]??Hz/s. Such a signal could be produced ...

  18. Searching for axion-like-particles in the sky C. Burragea

    E-Print Network [OSTI]

    1 Searching for axion-like-particles in the sky C. Burragea a Theory Group, Deutsches Elektronen it behaves as an Axion-Like-Particle (ALP). ALPs mix with photons in the presence of magnetic fields of a coupling between the scalar field and photons. Fields with such couplings are generically known as Axion

  19. Blue sky in SOI: new opportunities for quantum and hot-electron devices

    E-Print Network [OSTI]

    Luryi, Serge

    Blue sky in SOI: new opportunities for quantum and hot-electron devices S. Luryi a , A. Zaslavsky b to quantum effect and hot-electron devices. A number of such devices, based on quantum tunneling, hot-electron) substrates with ultrathin Si and insulator layers opens new oppor- tunities for quantum effect and hot-electron

  20. Einstein@Home all-sky search for periodic gravitational waves in LIGO S5 data

    E-Print Network [OSTI]

    Barsotti, Lisa

    This paper presents results of an all-sky search for periodic gravitational waves in the frequency range [50,1?190]??Hz and with frequency derivative range of ?[-20,1.1]×10[superscript -10]??Hz?s[superscript -1] for the ...

  1. Designing and Mining Multi-Terabyte Astronomy Archives: The Sloan Digital Sky Survey

    E-Print Network [OSTI]

    Narasayya, Vivek

    will operate a data pump to support sweep searches touching most of the data. The anticipated queries will re management challenges. Keywords Database, archive, data analysis, data mining, astronomy, scaleable, InternetDesigning and Mining Multi-Terabyte Astronomy Archives: The Sloan Digital Sky Survey Alexander S

  2. The Nature of Faint Blue Stars in the PHL and Ton Catalogues based on Digital Sky Surveys

    E-Print Network [OSTI]

    Andernach, H; W., W Copo Cordova; Santiago-Bautista, I del C

    2015-01-01T23:59:59.000Z

    We determined accurate positions for 3000 of the "faint blue stars" in the PHL (Palomar-Haro-Luyten) and Ton/TonS catalogues. These were published from 1957 to 1962, and, aimed at finding new white dwarfs, provide approximate positions for about 10750 blue stellar objects. Some of these "stars" had become known as quasars, a type of objects unheard-of before 1963. We derived subarcsec positions from a comparison of published finding charts with images from the first-epoch Digitized Sky Survey. Numerous objects are now well known, but unfortunately neither their PHL or Ton numbers, nor their discoverers, are recognized in current databases. A comparison with modern radio, IR, UV and X-ray surveys leads us to suggest that the fraction of extragalactic objects in the PHL and Ton catalogues is at least 15 per cent. However, because we failed to locate the original PHL plates or finding charts, it may be impossible to correctly identify the remaining 7726 PHL objects.

  3. The Spatial Clustering of ROSAT All-Sky Survey AGN: I. The cross-correlation function with SDSS Luminous Red Galaxies

    E-Print Network [OSTI]

    Krumpe, Mirko; Coil, Alison L

    2010-01-01T23:59:59.000Z

    We investigate the clustering properties of ~1550 broad-line AGNs at =0.25 detected in the ROSAT All-Sky Survey (RASS) through their measured cross-correlation function (CCF) with ~46000 Luminous Red Galaxies (LRGs) in the Sloan Digital Sky Survey. By measuring the cross-correlation of our AGN sample with a larger tracer set of LRGs, we both minimize shot noise errors due to the relatively small AGN sample size and avoid systematic errors due to the spatially-varying Galactic absorption that would affect direct measurements of the auto-correlation function (ACF) of the AGN sample. The measured ACF correlation length for the total RASS-AGN sample (=1.5 x 10^(44) erg/s) is r_0=4.3^{+0.4}_{-0.5} h^(-1) Mpc and the slope \\gamma=1.7^{+0.1}_{-0.1}. Splitting the sample into low and high L_X samples at L_(0.5-10 keV)=10^(44) erg/s, we detect an X-ray luminosity-dependence of the clustering amplitude at the ~2.5 \\sigma level. The low L_X sample has r_0=3.3^{+0.6}_{-0.8} h^(-1) Mpc (\\gamma=1.7^{+0.4}_{-0.3}), which is...

  4. Co-evolution of Extreme Star Formation and Quasar: hints from {\\it Herschel} and the Sloan Digital Sky Survey

    E-Print Network [OSTI]

    Ma, Zhiyuan

    2015-01-01T23:59:59.000Z

    Using the public data from the Herschel very wide field surveys, we study the far-infrared properties of optical-selected quasars from the Sloan Digital Sky Survey. Within the common area of $\\sim 172~deg^2$, we have identified the far-infrared counterparts for 372 quasars, among which 134 are highly secure detections in the Herschel 250$\\mu$m band (signal-to-noise ratios $\\geq 5$). This sample is the largest far-infrared quasar sample of its kind, and spans a wide redshift range of $0.14\\leq z \\leq 4.7$. Their far-infrared spectral energy distributions are consistent with heated dust emission due to active star formation, and the vast majority of them ($\\gtrsim 80$\\%) have total infrared luminosities $L_{IR}>10^{12}L_{\\odot}$ and thus qualify as ultra-luminous infrared galaxies. Their infrared luminosities are not correlated with the absolute magnitudes or the black hole masses of the quasars, which further support the interpretation that their far-infrared emissions are not due to their active galactic nucl...

  5. All-sky search for gravitational-wave bursts in the second joint LIGO-Virgo run

    E-Print Network [OSTI]

    the LIGO Scientific Collaboration; the Virgo Collaboration; J. Abadie; B. P. Abbott; R. Abbott; T. D. Abbott; M. Abernathy; T. Accadia; F. Acernese; C. Adams; R. Adhikari; C. Affeldt; M. Agathos; K. Agatsuma; P. Ajith; B. Allen; E. Amador Ceron; D. Amariutei; S. B. Anderson; W. G. Anderson; K. Arai; M. A. Arain; M. C. Araya; S. M. Aston; P. Astone; D. Atkinson; P. Aufmuth; C. Aulbert; B. E. Aylott; S. Babak; P. Baker; G. Ballardin; S. Ballmer; J. C. B. Barayoga; D. Barker; F. Barone; B. Barr; L. Barsotti; M. Barsuglia; M. A. Barton; I. Bartos; R. Bassiri; M. Bastarrika; A. Basti; J. Batch; J. Bauchrowitz; Th. S. Bauer; M. Bebronne; D. Beck; B. Behnke; M. Bejger; M. G. Beker; A. S. Bell; A. Belletoile; I. Belopolski; M. Benacquista; J. M. Berliner; A. Bertolini; J. Betzwieser; N. Beveridge; P. T. Beyersdorf; I. A. Bilenko; G. Billingsley; J. Birch; R. Biswas; M. Bitossi; M. A. Bizouard; E. Black; J. K. Blackburn; L. Blackburn; D. Blair; B. Bland; M. Blom; O. Bock; T. P. Bodiya; C. Bogan; R. Bondarescu; F. Bondu; L. Bonelli; R. Bonnand; R. Bork; M. Born; V. Boschi; S. Bose; L. Bosi; B. Bouhou; S. Braccini; C. Bradaschia; P. R. Brady; V. B. Braginsky; M. Branchesi; J. E. Brau; J. Breyer; T. Briant; D. O. Bridges; A. Brillet; M. Brinkmann; V. Brisson; M. Britzger; A. F. Brooks; D. A. Brown; T. Bulik; H. J. Bulten; A. Buonanno; J. Burguet-Castell; D. Buskulic; C. Buy; R. L. Byer; L. Cadonati; G. Cagnoli; E. Calloni; J. B. Camp; P. Campsie; J. Cannizzo; K. Cannon; B. Canuel; J. Cao; C. D. Capano; F. Carbognani; L. Carbone; S. Caride; S. Caudill; M. Cavaglia; F. Cavalier; R. Cavalieri; G. Cella; C. Cepeda; E. Cesarini; O. Chaibi; T. Chalermsongsak; P. Charlton; E. Chassande-Mottin; S. Chelkowski; W. Chen; X. Chen; Y. Chen; A. Chincarini; A. Chiummo; H. Cho; J. Chow; N. Christensen; S. S. Y. Chua; C. T. Y. Chung; S. Chung; G. Ciani; D. E. Clark; J. Clark; J. H. Clayton; F. Cleva; E. Coccia; P. -F. Cohadon; C. N. Colacino; J. Colas; A. Colla; M. Colombini; A. Conte; R. Conte; D. Cook; T. R. Corbitt; M. Cordier; N. Cornish; A. Corsi; C. A. Costa; M. Coughlin; J. -P. Coulon; P. Couvares; D. M. Coward; M. Cowart; D. C. Coyne; J. D. E. Creighton; T. D. Creighton; A. M. Cruise; A. Cumming; L. Cunningham; E. Cuoco; R. M. Cutler; K. Dahl; S. L. Danilishin; R. Dannenberg; S. D'Antonio; K. Danzmann; V. Dattilo; B. Daudert; H. Daveloza; M. Davier; E. J. Daw; R. Day; T. Dayanga; R. De Rosa; D. DeBra; G. Debreczeni; W. Del Pozzo; M. del Prete; T. Dent; V. Dergachev; R. DeRosa; R. DeSalvo; S. Dhurandhar; L. Di Fiore; A. Di Lieto; I. Di Palma; M. Di Paolo Emilio; A. Di Virgilio; M. Diaz; A. Dietz; F. Donovan; K. L. Dooley; M. Drago; R. W. P. Drever; J. C. Driggers; Z. Du; J. -C. Dumas; T. Eberle; M. Edgar; M. Edwards; A. Effler; P. Ehrens; G. Endroczi; R. Engel; T. Etzel; K. Evans; M. Evans; T. Evans; M. Factourovich; V. Fafone; S. Fairhurst; Y. Fan; B. F. Farr; D. Fazi; H. Fehrmann; D. Feldbaum; F. Feroz; I. Ferrante; F. Fidecaro; L. S. Finn; I. Fiori; R. P. Fisher; R. Flaminio; M. Flanigan; S. Foley; E. Forsi; L. A. Forte; N. Fotopoulos; J. -D. Fournier; J. Franc; S. Frasca; F. Frasconi; M. Frede; M. Frei; Z. Frei; A. Freise; R. Frey; T. T. Fricke; D. Friedrich; P. Fritschel; V. V. Frolov; M. -K. Fujimoto; P. J. Fulda; M. Fyffe; J. Gair; M. Galimberti; L. Gammaitoni; J. Garcia; F. Garufi; M. E. Gaspar; G. Gemme; R. Geng; E. Genin; A. Gennai; L. A. Gergely; S. Ghosh; J. A. Giaime; S. Giampanis; K. D. Giardina; A. Giazotto; S. Gil; C. Gill; J. Gleason; E. Goetz; L. M. Goggin; G. Gonzalez; M. L. Gorodetsky; S. Gossler; R. Gouaty; C. Graef; P. B. Graff; M. Granata; A. Grant; S. Gras; C. Gray; N. Gray; R. J. S. Greenhalgh; A. M. Gretarsson; C. Greverie; R. Grosso; H. Grote; S. Grunewald; G. M. Guidi; R. Gupta; E. K. Gustafson; R. Gustafson; T. Ha; J. M. Hallam; D. Hammer; G. Hammond; J. Hanks; C. Hanna; J. Hanson; A. Hardt; J. Harms; G. M. Harry; I. W. Harry; E. D. Harstad; M. T. Hartman; K. Haughian; K. Hayama; J. -F. Hayau; J. Heefner; A. Heidmann; M. C. Heintze; H. Heitmann; P. Hello; M. A. Hendry; I. S. Heng; A. W. Heptonstall; V. Herrera; M. Hewitson; S. Hild; D. Hoak; K. A. Hodge; K. Holt; M. Holtrop; T. Hong; S. Hooper; D. J. Hosken; J. Hough; E. J. Howell; B. Hughey; S. Husa; S. H. Huttner; R. Inta; T. Isogai; A. Ivanov; K. Izumi; M. Jacobson; E. James; Y. J. Jang; P. Jaranowski; E. Jesse; W. W. Johnson; D. I. Jones; G. Jones; R. Jones; L. Ju; P. Kalmus; V. Kalogera; S. Kandhasamy; G. Kang; J. B. Kanner; R. Kasturi; E. Katsavounidis; W. Katzman; H. Kaufer; K. Kawabe; S. Kawamura; F. Kawazoe; D. Kelley; W. Kells; D. G. Keppel; Z. Keresztes; A. Khalaidovski; F. Y. Khalili; E. A. Khazanov; B. Kim; C. Kim; H. Kim; K. Kim; N. Kim; Y. -M. Kim; P. J. King; D. L. Kinzel; J. S. Kissel; S. Klimenko; K. Kokeyama; V. Kondrashov; S. Koranda; W. Z. Korth; I. Kowalska; D. Kozak; O. Kranz; V. Kringel; S. Krishnamurthy

    2012-04-20T23:59:59.000Z

    We present results from a search for gravitational-wave bursts in the data collected by the LIGO and Virgo detectors between July 7, 2009 and October 20, 2010: data are analyzed when at least two of the three LIGO-Virgo detectors are in coincident operation, with a total observation time of 207 days. The analysis searches for transients of duration < 1 s over the frequency band 64-5000 Hz, without other assumptions on the signal waveform, polarization, direction or occurrence time. All identified events are consistent with the expected accidental background. We set frequentist upper limits on the rate of gravitational-wave bursts by combining this search with the previous LIGO-Virgo search on the data collected between November 2005 and October 2007. The upper limit on the rate of strong gravitational-wave bursts at the Earth is 1.3 events per year at 90% confidence. We also present upper limits on source rate density per year and Mpc^3 for sample populations of standard-candle sources. As in the previous joint run, typical sensitivities of the search in terms of the root-sum-squared strain amplitude for these waveforms lie in the range 5 10^-22 Hz^-1/2 to 1 10^-20 Hz^-1/2. The combination of the two joint runs entails the most sensitive all-sky search for generic gravitational-wave bursts and synthesizes the results achieved by the initial generation of interferometric detectors.

  6. GALACTIC ALL-SKY SURVEY HIGH-VELOCITY CLOUDS IN THE REGION OF THE MAGELLANIC LEADING ARM

    SciTech Connect (OSTI)

    For, Bi-Qing; Staveley-Smith, Lister [International Centre for Radio Astronomy Research, University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009 (Australia)] [International Centre for Radio Astronomy Research, University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009 (Australia); McClure-Griffiths, N. M., E-mail: biqing.for@uwa.edu.au [Australia Telescope National Facility, CSIRO Astronomy and Space Science, PO Box 76, Epping, NSW 1710 (Australia)

    2013-02-10T23:59:59.000Z

    We present a catalog of high-velocity clouds in the region of the Magellanic Leading Arm. The catalog is based on neutral hydrogen (H I) observations from the Parkes Galactic All-Sky Survey. Excellent spectral resolution allows clouds with narrow-line components to be resolved. The total number of detected clouds is 419. We describe the method of cataloging and present the basic parameters of the clouds. We discuss the general distribution of the high-velocity clouds and classify the clouds based on their morphological type. The presence of a significant number of head-tail clouds and their distribution in the region is discussed in the context of Magellanic System simulations. We suggest that ram-pressure stripping is a more important factor than tidal forces for the morphology and formation of the Magellanic Leading Arm and that different environmental conditions might explain the morphological difference between the Magellanic Leading Arm and Magellanic Stream. We also discuss a newly identified population of clouds that forms the LA IV and a new diffuse bridge-like feature connecting the LA II and III complexes.

  7. WHAM South Sky Survey The Wisconsin H-Alpha Mapper (WHAM) was first located at Ki: Peak Na>onal Observatory in

    E-Print Network [OSTI]

    Wisconsin at Madison, University of

    WHAM South Sky Survey The Wisconsin H-Alpha Mapper (WHAM) was first-thirds of the sky in the WHAM Northern Sky Survey. Then, to gather data on the remaining, and fiYng an atmospheric template for subtrac>on. Once everything is fit

  8. Total Adjusted Sales of Kerosene

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5 Tables July 1996 Energy Information Administration Office ofthroughYear JanYear Jan Feb Mar Apr May(MillionFeet)JulyEnd Use: Total

  9. U.S. Total Exports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality",Area: U.S. East Coast (PADD 1) New120,814 136,9322009 2010(Billion

  10. U.S. Total Exports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality",Area: U.S. East Coast (PADD 1) New120,814 136,9322009 2010(Billion120,814 136,932

  11. U.S. Total Imports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality",Area: U.S. East Coast (PADD 1) New120,814 136,9322009 2010(Billion120,814

  12. U.S. Total Imports

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality",Area: U.S. East Coast (PADD 1) New120,814 136,9322009 2010(Billion120,814Pipeline

  13. U.S. Total Stocks

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are nowTotal" (Percent) Type: Sulfur Content API GravityDakota" "Fuel, quality",Area: U.S. East Coast (PADD 1) New120,814 136,9322009Feet)

  14. Candidate isolated neutron stars and other optically blank x-ray fields identified from the rosat all-sky and sloan digital sky surveys

    SciTech Connect (OSTI)

    Agueros, Marcel A.; Anderson, Scott F.; /Washington U., Seattle, Astron. Dept.; Margon, Bruce; /Baltimore, Space Telescope Sci.; Haberl, Frank; Voges, Wolfgang; /Garching,; Annis, James; /Fermilab; Schneider, Donald P.; /Penn State U., Astron. Astrophys.; Brinkmann, Jonathan; /Apache Point Observ.

    2005-11-01T23:59:59.000Z

    Only seven radio-quiet isolated neutron stars (INSs) emitting thermal X rays are known, a sample that has yet to definitively address such fundamental issues as the equation of state of degenerate neutron matter. We describe a selection algorithm based on a cross-correlation of the ROSAT All-Sky Survey (RASS) and the Sloan Digital Sky Survey (SDSS) that identifies X-ray error circles devoid of plausible optical counterparts to the SDSS g {approx} 22 magnitudes limit. We quantitatively characterize these error circles as optically blank; they may host INSs or other similarly exotic X-ray sources such as radio-quiet BL Lacs, obscured AGN, etc. Our search is an order of magnitude more selective than previous searches for optically blank RASS error circles, and excludes the 99.9% of error circles that contain more common X-ray-emitting subclasses. We find 11 candidates, nine of which are new. While our search is designed to find the best INS candidates and not to produce a complete list of INSs in the RASS, it is reassuring that our number of candidates is consistent with predictions from INS population models. Further X-ray observations will obtain pinpoint positions and determine whether these sources are entirely optically blank at g {approx} 22, supporting the presence of likely isolated neutron stars and perhaps enabling detailed follow-up studies of neutron star physics.

  15. Markov Random Field Model for Single Image Defogging Laurent Caraffa and Jean-Philippe Tarel

    E-Print Network [OSTI]

    Boyer, Edmond

    is the so-called Koschmieder law, where D is the object depth, and Is is the intensity of the sky. From (1 the intrinsic luminance I0 and the depth D at every pixel, only knowing I. The first method for single image

  16. Test Images

    E-Print Network [OSTI]

    Test Images. I hope to have a set of test images for the course soon. Some images are available now; some will have to wait until I can find another 100-200

  17. unWISE: Unblurred coadds of the WISE imaging

    SciTech Connect (OSTI)

    Lang, Dustin, E-mail: dstn@cmu.edu [McWilliams Center for Cosmology, Department of Physics, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213 (United States)

    2014-05-01T23:59:59.000Z

    The Wide-field Infrared Survey Explorer (WISE) satellite observed the full sky in four mid-infrared bands in the 2.8-28 ?m range. The primary mission was completed in 2010. The WISE team has done a superb job of producing a series of high-quality, well-documented, complete data releases in a timely manner. However, the 'Atlas Image' coadds that are part of the recent AllWISE and previous data releases were intentionally blurred. Convolving the images by the point-spread function while coadding results in 'matched-filtered' images that are close to optimal for detecting isolated point sources. But these matched-filtered images are sub-optimal or inappropriate for other purposes. For example, we are photometering the WISE images at the locations of sources detected in the Sloan Digital Sky Survey through forward modeling, and this blurring decreases the available signal-to-noise by effectively broadening the point-spread function. This paper presents a new set of coadds of the WISE images that have not been blurred. These images retain the intrinsic resolution of the data and are appropriate for photometry preserving the available signal-to-noise. Users should be cautioned, however, that the W3- and W4-band coadds contain artifacts around large, bright structures (large galaxies, dusty nebulae, etc.); eliminating these artifacts is the subject of ongoing work. These new coadds, and the code used to produce them, are publicly available at http://unwise.me.

  18. Homogeneity of bright radio sources at 15 GHz on the sky and in the space

    E-Print Network [OSTI]

    Arshakian, T G; Zensus, J A; Lister, M L

    2003-01-01T23:59:59.000Z

    A revised sample of the 2 cm Very Long Baseline Array (VLBA) survey is studied to test the isotropic distribution of radio sources on the sky and their uniform distribution in space. The revised sample is complete to flux-density limits of 1.5 Jy for positive declinations and 2 Jy for declinations between 0 and -20 degrees. At present the active galactic nuclei sample comprises 122 members. Application of the two-dimensional Kolmogorov-Smirnov (K-S) test shows that there is no significant deviation from the homogenous distribution in the sky, while the V/Vmax test shows that the space distribution of active nuclei is not uniform at high confidence level (99.9%). This is indicative of a strong luminosity and/or density evolution implying that active nuclei (or jet activity phenomena) were more populous at high redshifts, z~2.

  19. A novel approach to reconstructing signals of isotropy violation from a masked CMB sky

    E-Print Network [OSTI]

    Aluri, Pavan K; Rotti, Aditya; Souradeep, Tarun

    2015-01-01T23:59:59.000Z

    Statistical isotropy (SI) is one of the fundamental assumptions made in cosmological model building. This assumption is now being rigorously tested using the almost full sky measurements of the CMB anisotropies. A major hurdle in any such analysis is to handle the large biases induced due to the process of masking. We have developed a new method of analysis, using the bipolar spherical harmonic basis functions, in which we semi-analytically evaluate the modifications to SI violation induced by the mask. The method developed here is generic and can be potentially used to search for any arbitrary form of SI violation. We specifically demonstrate the working of this method by recovering the Doppler boost signal from a set of simulated, masked CMB skies.

  20. All-sky astrophysical component separation with Fast Independent Component Analysis (FastICA)

    E-Print Network [OSTI]

    Maino, D; Baccigalupi, C; Perrotta, F; Banday, A J; Bedini, L; Burigana, C; Zotti, G D; Górski, K M; Salerno, E

    2001-01-01T23:59:59.000Z

    We present a new, fast, algorithm for the separation of astrophysical components superposed in maps of the sky, based on the fast Independent Component Analysis technique (FastICA). It allows to recover both the spatial pattern and the frequency scalings of the emissions from statistically independent astrophysical processes, present along the line-of-sight, from multi-frequency observations. We apply FastICA to simulated observations of the microwave sky with angular resolution and instrumental noise at the mean nominal levels for the Planck satellite, containing the most important known diffuse signals: the Cosmic Microwave Background (CMB), Galactic synchrotron, dust and free-free emissions. A method for calibrating the reconstructed maps of each component at each frequency has been devised. The spatial pattern of all the components have been recovered on all scales probed by the instrument. In particular, the CMB angular power spectra is recovered at the percent level up to $\\ell_{max}\\simeq 2000$. Freque...

  1. Low-Mass Dwarf Template Spectra from the Sloan Digital Sky Survey

    E-Print Network [OSTI]

    John J. Bochanski; Andrew A. West; Suzanne L. Hawley; Kevin R. Covey

    2006-10-20T23:59:59.000Z

    We present template spectra of low-mass (M0-L0) dwarfs derived from over 4,000 Sloan Digital Sky Survey (SDSS) spectra. These composite spectra are suitable for use as medium-resolution (R ~ 1,800) radial velocity standards. We report mean spectral properties (molecular bandhead strengths,equivalent widths) and use the templates to investigate the effects of magnetic activity and metallicity on the spectroscopic and photometric properties of low-mass stars.

  2. All-sky astrophysical component separation with Fast Independent Component Analysis (FastICA)

    E-Print Network [OSTI]

    D. Maino; A. Farusi; C. Baccigalupi; F. Perrotta; A. J. Banday; L. Bedini; C. Burigana; G. De Zotti; K. M. Gorski; E. Salerno

    2001-08-22T23:59:59.000Z

    We present a new, fast, algorithm for the separation of astrophysical components superposed in maps of the sky, based on the fast Independent Component Analysis technique (FastICA). It allows to recover both the spatial pattern and the frequency scalings of the emissions from statistically independent astrophysical processes, present along the line-of-sight, from multi-frequency observations. We apply FastICA to simulated observations of the microwave sky with angular resolution and instrumental noise at the mean nominal levels for the Planck satellite, containing the most important known diffuse signals: the Cosmic Microwave Background (CMB), Galactic synchrotron, dust and free-free emissions. A method for calibrating the reconstructed maps of each component at each frequency has been devised. The spatial pattern of all the components have been recovered on all scales probed by the instrument. In particular, the CMB angular power spectra is recovered at the percent level up to $\\ell_{max}\\simeq 2000$. Frequency scalings and normalization have been recovered with better than percent precision for all the components at frequencies and in sky regions where their signal-to-noise ratio exceeds 1.5; the error increases at ten percent level for signal-to-noise ratios about 1. Runs have been performed on a Pentium III 600 MHz computer; FastICA typically took a time of the order of 10 minutes for all-sky simulations with 3.5 arcminutes pixel size. We conclude that FastICA is an extremly promising technique for analyzing the maps that will be obtained by the forthcoming high resolution CMB experiments.

  3. An All-Sky Search for Steady VHE Gamma-Ray Sources

    E-Print Network [OSTI]

    Atkins, R; Berley, D; Chen, M L; Coyne, D G; Delay, R S; Dingus, B L; Dorfan, D E; Ellsworth, R W; Evans, D; Falcone, A D; Fleysher, L; Fleysher, R; Gisler, G; Goodman, J A; Haines, T J; Hoffman, C M; Hugenberger, S; Kelley, L A; Leonor, I; Macri, J R; McConnell, M; McCullough, J F; McEnery, J E; Miller, R S; Mincer, A I; Morales, M F; Némethy, P; Ryan, J M; Schneider, M; Shen, B; Shoup, A L; Sinnis, G; Smith, A J; Sullivan, G W; Thompson, T N; Tümer, T O; Wang, K; Wascko, M O; Westerhoff, S; Williams, D A; Yang, T; Yodh, G B

    1999-01-01T23:59:59.000Z

    The Milagrito water Cherenkov detector in the Jemez Mountains near Los Alamos, New Mexico took data from February 1997 to April 1998. Milagrito served as a prototype for the larger Milagro detector, which has just begun operations. Milagrito was the first large-aperture gamma-ray detector with sensitivity to gamma rays below 1 TeV. We report here on a search for steady emission from point sources over most of the northern sky using data from Milagrito.

  4. An All-Sky Search for Steady VHE Gamma-Ray Sources

    E-Print Network [OSTI]

    R. Atkins; W. Benbow; D. Berley; M. -L. Chen; D. G. Coyne; R. S. Delay; B. L. Dingus; D. E. Dorfan; R. W. Ellsworth; D. Evans; A. Falcone; L. Fleysher; R. Fleysher; G. Gisler; J. A. Goodman; T. J. Haines; C. M. Hoffman; S. Hugenberger; L. A. Kelley; I. Leonor; J. Macri; M. McConnell; J. F. McCullough; J. E. McEnery; R. S. Miller; A. I. Mincer; M. F. Morales; P. Nemethy; J. M. Ryan; M. Schneider; B. Shen; A. Shoup; G. Sinnis; A. J. Smith; G. W. Sullivan; T. N. Thompson; O. T. Tumer; K. Wang; M. O. Wascko; S. Westerhoff; D. A. Williams; T. Yang; G. B. Yodh

    1999-06-23T23:59:59.000Z

    The Milagrito water Cherenkov detector in the Jemez Mountains near Los Alamos, New Mexico took data from February 1997 to April 1998. Milagrito served as a prototype for the larger Milagro detector, which has just begun operations. Milagrito was the first large-aperture gamma-ray detector with sensitivity to gamma rays below 1 TeV. We report here on a search for steady emission from point sources over most of the northern sky using data from Milagrito.

  5. Image Analysis

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

    Recognition Image Analysis and Recognition Snapshot1498121slicesqResedison Fibers permeating imaged material (Courtesy: Bale, Loring, Perciano and Ushizima) Imagery coming from...

  6. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 1,602 1,397...

  7. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All...

  8. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 1,870 1,276...

  9. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings ... 2,037...

  10. THE 70 MONTH SWIFT-BAT ALL-SKY HARD X-RAY SURVEY

    SciTech Connect (OSTI)

    Baumgartner, W. H.; Tueller, J.; Markwardt, C. B.; Skinner, G. K.; Barthelmy, S.; Gehrels, N. [NASA/Goddard Space Flight Center, Astrophysics Science Division, Greenbelt, MD 20771 (United States); Mushotzky, R. F. [Department of Astronomy, University of Maryland, College Park, MD 20742 (United States); Evans, P. A., E-mail: whbaumga@alum.mit.edu [X-Ray and Observational Astronomy Group/Department of Physics and Astronomy, University of Leicester, Leicester, LE1 7RH (United Kingdom)

    2013-08-15T23:59:59.000Z

    We present the catalog of sources detected in 70 months of observations with the Burst Alert Telescope (BAT) hard X-ray detector on the Swift gamma-ray burst observatory. The Swift-BAT 70 month survey has detected 1171 hard X-ray sources (more than twice as many sources as the previous 22 month survey) in the 14-195 keV band down to a significance level of 4.8{sigma}, associated with 1210 counterparts. The 70 month Swift-BAT survey is the most sensitive and uniform hard X-ray all-sky survey and reaches a flux level of 1.03 Multiplication-Sign 10{sup -11} erg s{sup -1} cm{sup -2} over 50% of the sky and 1.34 Multiplication-Sign 10{sup -11} erg s{sup -1} cm{sup -2} over 90% of the sky. The majority of new sources in the 70 month survey continue to be active galactic nuclei, with over 700 in the catalog. As part of this new edition of the Swift-BAT catalog, we also make available eight-channel spectra and monthly sampled light curves for each object detected in the survey in the online journal and at the Swift-BAT 70 month Web site.

  11. All-sky Search for Periodic Gravitational Waves in the Full S5 LIGO Data

    E-Print Network [OSTI]

    J. Abadie; B. P. Abbott; R. Abbott; T. D. Abbott; M. Abernathy; T. Accadia; F. Acernese; C. Adams; R. Adhikari; C. Affeldt; P. Ajith; B. Allen; G. S. Allen; E. Amador Ceron; D. Amariutei; R. S. Amin; S. B. Anderson; W. G. Anderson; K. Arai; M. A. Arain; M. C. Araya; S. M. Aston; P. Astone; D. Atkinson; P. Aufmuth; C. Aulbert; B. E. Aylott; S. Babak; P. Baker; G. Ballardin; S. Ballmer; D. Barker; F. Barone; B. Barr; P. Barriga; L. Barsotti; M. Barsuglia; M. A. Barton; I. Bartos; R. Bassiri; M. Bastarrika; A. Basti; J. Batch; J. Bauchrowitz; Th. S. Bauer; M. Bebronne; B. Behnke; M. G. Beker; A. S. Bell; A. Belletoile; I. Belopolski; M. Benacquista; J. M. Berliner; A. Bertolini; J. Betzwieser; N. Beveridge; P. T. Beyersdorf; I. A. Bilenko; G. Billingsley; J. Birch; R. Biswas; M. Bitossi; M. A. Bizouard; E. Black; J. K. Blackburn; L. Blackburn; D. Blair; B. Bland; M. Blom; O. Bock; T. P. Bodiya; C. Bogan; R. Bondarescu; F. Bondu; L. Bonelli; R. Bonnand; R. Bork; M. Born; V. Boschi; S. Bose; L. Bosi; B. Bouhou; S. Braccini; C. Bradaschia; P. R. Brady; V. B. Braginsky; M. Branchesi; J. E. Brau; J. Breyer; T. Briant; D. O. Bridges; A. Brillet; M. Brinkmann; V. Brisson; M. Britzger; A. F. Brooks; D. A. Brown; A. Brummit; T. Bulik; H. J. Bulten; A. Buonanno; J. Burguet--Castell; O. Burmeister; D. Buskulic; C. Buy; R. L. Byer; L. Cadonati; G. Cagnoli; J. Cain; E. Calloni; J. B. Camp; P. Campsie; J. Cannizzo; K. Cannon; B. Canuel; J. Cao; C. D. Capano; F. Carbognani; S. Caride; S. Caudill; M. Cavaglià; F. Cavalier; R. Cavalieri; G. Cella; C. Cepeda; E. Cesarini; O. Chaibi; T. Chalermsongsak; E. Chalkley; P. Charlton; E. Chassande-Mottin; S. Chelkowski; Y. Chen; A. Chincarini; A. Chiummo; H. Cho; N. Christensen; S. S. Y. Chua; C. T. Y. Chung; S. Chung; G. Ciani; F. Clara; D. E. Clark; J. Clark; J. H. Clayton; F. Cleva; E. Coccia; P. -F. Cohadon; C. N. Colacino; J. Colas; A. Colla; M. Colombini; A. Conte; R. Conte; D. Cook; T. R. Corbitt; M. Cordier; N. Cornish; A. Corsi; C. A. Costa; M. Coughlin; J. -P. Coulon; P. Couvares; D. M. Coward; D. C. Coyne; J. D. E. Creighton; T. D. Creighton; A. M. Cruise; A. Cumming; L. Cunningham; E. Cuoco; R. M. Cutler; K. Dahl; S. L. Danilishin; R. Dannenberg; S. D'Antonio; K. Danzmann; V. Dattilo; B. Daudert; H. Daveloza; M. Davier; G. Davies; E. J. Daw; R. Day; T. Dayanga; R. De Rosa; D. DeBra; G. Debreczeni; J. Degallaix; W. Del Pozzo; M. del Prete; T. Dent; V. Dergachev; R. DeRosa; R. DeSalvo; S. Dhurandhar; L. Di Fiore; A. Di Lieto; I. Di Palma; M. Di Paolo Emilio; A. Di Virgilio; M. Díaz; A. Dietz; F. Donovan; K. L. Dooley; S. Dorsher; M. Drago; R. W. P. Drever; J. C. Driggers; Z. Du; J. -C. Dumas; S. Dwyer; T. Eberle; M. Edgar; M. Edwards; A. Effler; P. Ehrens; G. Endr?czi; R. Engel; T. Etzel; K. Evans; M. Evans; T. Evans; M. Factourovich; V. Fafone; S. Fairhurst; Y. Fan; B. F. Farr; W. Farr; D. Fazi; H. Fehrmann; D. Feldbaum; I. Ferrante; F. Fidecaro; L. S. Finn; I. Fiori; R. P. Fisher; R. Flaminio; M. Flanigan; S. Foley; E. Forsi; L. A. Forte; N. Fotopoulos; J. -D. Fournier; J. Franc; S. Frasca; F. Frasconi; M. Frede; M. Frei; Z. Frei; A. Freise; R. Frey; T. T. Fricke; D. Friedrich; P. Fritschel; V. V. Frolov; P. J. Fulda; M. Fyffe; M. Galimberti; L. Gammaitoni; M. R. Ganija; J. Garcia; J. A. Garofoli; F. Garufi; M. E. Gáspár; G. Gemme; R. Geng; E. Genin; A. Gennai; L. Á. Gergely; S. Ghosh; J. A. Giaime; S. Giampanis; K. D. Giardina; A. Giazotto; C. Gill; E. Goetz; L. M. Goggin; G. González; M. L. Gorodetsky; S. Goßler; R. Gouaty; C. Graef; M. Granata; A. Grant; S. Gras; C. Gray; N. Gray; R. J. S. Greenhalgh; A. M. Gretarsson; C. Greverie; R. Grosso; H. Grote; S. Grunewald; G. M. Guidi; C. Guido; R. Gupta; E. K. Gustafson; R. Gustafson; T. Ha; B. Hage; J. M. Hallam; D. Hammer; G. Hammond; J. Hanks; C. Hanna; J. Hanson; J. Harms; G. M. Harry; I. W. Harry; E. D. Harstad; M. T. Hartman; K. Haughian; K. Hayama; J. -F. Hayau; T. Hayler; J. Heefner; A. Heidmann; M. C. Heintze; H. Heitmann; P. Hello; M. A. Hendry; I. S. Heng; A. W. Heptonstall; V. Herrera; M. Hewitson; S. Hild; D. Hoak; K. A. Hodge; K. Holt; T. Hong; S. Hooper; D. J. Hosken; J. Hough; E. J. Howell; B. Hughey; S. Husa; S. H. Huttner; T. Huynh-Dinh; D. R. Ingram; R. Inta; T. Isogai; A. Ivanov; K. Izumi; M. Jacobson; H. Jang; P. Jaranowski; W. W. Johnson; D. I. Jones; G. Jones; R. Jones; L. Ju; P. Kalmus; V. Kalogera; I. Kamaretsos; S. Kandhasamy; G. Kang; J. B. Kanner; E. Katsavounidis; W. Katzman; H. Kaufer; K. Kawabe; S. Kawamura; F. Kawazoe; W. Kells; D. G. Keppel; Z. Keresztes; A. Khalaidovski; F. Y. Khalili; E. A. Khazanov; B. Kim; C. Kim; D. Kim; H. Kim; K. Kim; N. Kim; Y. -M. Kim; P. J. King; M. Kinsey; D. L. Kinzel; J. S. Kissel; S. Klimenko; K. Kokeyama; V. Kondrashov; R. Kopparapu; S. Koranda; W. Z. Korth; I. Kowalska; D. Kozak; V. Kringel; S. Krishnamurthy; B. Krishnan; A. Królak

    2011-10-02T23:59:59.000Z

    We report on an all-sky search for periodic gravitational waves in the frequency band 50-800 Hz and with the frequency time derivative in the range of 0 through -6e-9 Hz/s. Such a signal could be produced by a nearby spinning and slightly non-axisymmetric isolated neutron star in our galaxy. After recent improvements in the search program that yielded a 10x increase in computational efficiency, we have searched in two years of data collected during LIGO's fifth science run and have obtained the most sensitive all-sky upper limits on gravitational wave strain to date. Near 150 Hz our upper limit on worst-case linearly polarized strain amplitude $h_0$ is 1e-24, while at the high end of our frequency range we achieve a worst-case upper limit of 3.8e-24 for all polarizations and sky locations. These results constitute a factor of two improvement upon previously published data. A new detection pipeline utilizing a Loosely Coherent algorithm was able to follow up weaker outliers, increasing the volume of space where signals can be detected by a factor of 10, but has not revealed any gravitational wave signals. The pipeline has been tested for robustness with respect to deviations from the model of an isolated neutron star, such as caused by a low-mass or long-period binary companion.

  12. Spectral selectivity of electrochromic windows with color state for all-sky conditions

    SciTech Connect (OSTI)

    Soule, D.E. [Western Illinois Univ., Macomb, IL (United States)] [Western Illinois Univ., Macomb, IL (United States); Zhang, J.G.; Benson, D.K. [National Renewable Energy Lab., Golden, CO (United States)] [National Renewable Energy Lab., Golden, CO (United States)

    1995-07-01T23:59:59.000Z

    The optical performance of an electrochromic window is studied for the visible, ultraviolet, and near infrared spectral regions. The performance is found to deviate strongly with window color state and for clear or cloudy skies. A new spectral cloud model is applied to an electrochromic window recently developed at NREL. A spectral comparison is made between the electrochromic window and spectrally selective standard windows. Two series of double-glazed window sections, including the electrochromic window with color state and a series of low-E windows, were measured for transmittance and reflectance (300-2500nm), With these spectral data, a new near-infrared blocking (reflection + absorption) factor is developed for window application in warm climates for cooling load reduction. A chromaticity analysis is presented for both the daylight spectra and the transmitted electrochromic window spectra with color state, Computed daylight correlated color temperatures show a wide range, with values of 5660K for clear global irradiation, 6210K for clouds, and 13,250K for a zenith blue sky. Chromatic trajectories with color state for transmitted radiation extend further toward the blue to 8180K for the global and 28,990K for zenith sky irradiation.

  13. SkyMouse: A smart interface for astronomical on-line resources and services

    E-Print Network [OSTI]

    Chen-Zhou CUI; Hua-Ping SUN; Yong-Heng ZHAO; Yu LUO; Da-Zhi QI

    2007-11-27T23:59:59.000Z

    With the development of network and the World Wide Web (WWW), the Internet has been growing and changing dramatically. More and more on-line database systems and different kinds of services are available for astronomy research. How to help users find their way through the jungle of information services becomes an important challenge. Although astronomers have been aware of the importance of interoperability and introduced the concept of Virtual Observatory as a uniform environment for future astronomical on-line resources and services, transparent access to heterogeneous on-line information is still difficult. SkyMouse is a lightweight interface for distributed astronomical on-line resources and services, which is designed and developed by us, i.e., Chinese Virtual Observatory Project. Taking advantage of screen word-capturing technology, different kinds of information systems can be queried through simple mouse actions, and results are returned in a uniform web page. SkyMouse is an easy to use application, aiming to show basic information or to create a comprehensive overview of a specific astronomical object. In this paper current status of on-line resources and services access is reviewed; system architecture, features and functions of SkyMouse are described; challenges for intelligent interface for on-line astronomical resources and services are discussed.

  14. Exploring the variable sky with Linear. II. Halo structure and substructure traced by RR Lyrae stars to 30 kpc

    E-Print Network [OSTI]

    Sesar, Branimir

    We present a sample of ~5000 RR Lyrae stars selected from the recalibrated LINEAR data set and detected at heliocentric distances between 5 kpc and 30 kpc over ~8000 deg[superscript 2] of sky. The coordinates and light ...

  15. Investigation of a cloud-cover modification to SPCTRAL2, SERI's simple model for cloudless-sky, spectral solar irradiance

    SciTech Connect (OSTI)

    Bird, R.E.; Riordan, C.J.; Myers, D.R.

    1987-06-01T23:59:59.000Z

    This report summarizes the investigation of a cloud-cover modification to SPCTRAL2, SERI's simple model for cloudless-sky, spectral solar irradiance. Our approach was to develop a modifier that relies on commonly acquired meteorological and broadband-irradiance data rather than detailed cloud properties that are generally not available. The method was to normalize modeled, cloudless-sky spectral irradiance to a measured broadband-irradiance value under cloudy skies, and then to compare the normalized, modeled data with measured spectral-irradiance data to empirically derive spectral modifiers that improve the agreement between modeled and measured data. Results indicate the possible form of the spectral corrections; however, we must analyze additional data to develop a spectral transmission function for cloudy-sky conditions.

  16. Total termination of term rewriting is undecidable

    E-Print Network [OSTI]

    Utrecht, Universiteit

    Total termination of term rewriting is undecidable Hans Zantema Utrecht University, Department Usually termination of term rewriting systems (TRS's) is proved by means of a monotonic well­founded order. If this order is total on ground terms, the TRS is called totally terminating. In this paper we prove that total

  17. Total Petroleum Systems and Assessment Units (AU)

    E-Print Network [OSTI]

    Torgersen, Christian

    Total Petroleum Systems (TPS) and Assessment Units (AU) Field type Surface water Groundwater X X X X X X X X AU 00000003 Oil/ Gas X X X X X X X X Total X X X X X X X Total Petroleum Systems (TPS) and Assessment Units (AU) Field type Total undiscovered petroleum (MMBO or BCFG) Water per oil

  18. BRIGHT 22 ?m EXCESS CANDIDATES FROM THE WISE ALL-SKY CATALOG AND THE HIPPARCOS MAIN CATALOG

    SciTech Connect (OSTI)

    Wu, Chao-Jian; Wu, Hong; Lam, Man-I; Yang, Ming; Gao, Liang [National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 (China); Wen, Xiao-Qing [Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 (China); Li, Shuo [Department of Astronomy, Peking University, Beijing 100871 (China); Zhang, Tong-Jie [Department of Astronomy, Beijing Normal University, Beijing 100875 (China)

    2013-10-01T23:59:59.000Z

    In this paper, we present a catalog that includes 141 bright candidates (?10.27 mag, V band) showing an excess of infrared (IR) at 22 ?m. Of these 141 candidates, 38 stars are known IR-excess stars or disks, 23 stars are double or multiple stars, and 4 are Be stars while the remaining more than 70 stars are identified as 22 ?m excess candidates in our work. The criterion for selecting candidates is K{sub s} – [22]{sub ?m}. All these candidates are selected from the Wide-field Infrared Survey Explorer all-sky data cross-correlated with the Hipparcos main catalog and the likelihood-ratio technique is employed. Considering the effect of background, we introduce the IRAS 100 ?m level to exclude the high background. We also estimate the coincidence probability of these sources. In addition, we present the optical to mid-IR spectral energy distributions and optical images for all the candidates, and give the observed optical spectra of six stars with the National Astronomical Observatories, Chinese Academy of Sciences' 2.16 m telescope. To measure for the amount of dust around each star, the fractional luminosity is also provided. We also test whether our method of selecting IR-excess stars can be used to search for extra-solar planets; we cross-match our catalog with known IR-excess stars with planets but found no matches. Finally, we give the fraction of stars showing excess IR for different spectral types of main-sequence stars.

  19. Clear Skies

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041clothAdvanced Materials Advanced. C o w l i t zManufacturing: U.S. Competitiveness2 PA. A. lacis

  20. Cloudy Skies

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041clothAdvanced Materials Advanced. C o w l i t zManufacturing:DOE NationalCommitteeof3 the Marine

  1. Cloudy Skies

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041clothAdvanced Materials Advanced. C o w l i t zManufacturing:DOE NationalCommitteeof3 the MarineJ.

  2. Spectroscopic Needs for Imaging Dark Energy Experiments

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

    Newman, Jeffrey A. [Univ. of Pittsburgh and PITT PACC, PA (United States). Dept of Physics and Astronomy; Slosar, Anze [Brookhaven National Laboratory (BNL), Upton, NY (United States); Abate, Alexandra [Univ. of Arizona, Tucson, AZ (United States); Abdalla, Filipe B. [Univ. College London (United Kingdom); Allam, Sahar [Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Allen, Steven W. [SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Ansari, Reza [LAL Univ. Paris-Sud, Orsay (France); Bailey, Stephen [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Barkhouse, Wayne A. [Univ. of North Dakota, Grand Forks, ND (United States); Beers, Timothy C. [National Optical Astronomy Observations, Tucson, AZ (United States); Blanton, Michael R. [New York Univ., NY (United States); Brodwin, Mark [Univ. of Missouri at Kansas City, Kansas City, MO (United States); Brownstein, Joel R. [Univ. of Utah, Salt Lake City, UT (United States); Brunner, Robert J. [Illinois Univ., Urbana, IL (United States); Carrasco-Kind, Matias [Illinois Univ., Urbana, IL (United States); Cervantes-Cota, Jorge [Inst. Nacional de Investigaciones Nucleares (ININ), Escandon (Mexico); Chisari, Nora Elisa [Princeton Univ., Princeton, NJ (United States); Colless, Matthew [Australian National Univ., Canberra (Australia). Research School of Astronomy and Astrophysics; Comparat, Johan [Campus of International Excellence UAM and CSIC, Madrid (Spain); Coupon, Jean [Univ. of Geneva (Switzerland). Astronomical Observatory; Cheu, Elliott [Univ. of Arizona, Tucson, AZ (United States); Cunha, Carlos E. [Stanford Univ., Stanford, CA (United States). Kavli Inst. for Particle Astrophysics and Cosmology; de la Macorra, Alex [UNAM, Mexico City (Mexico). Dept. de Fisica Teorica and Inst. Avanzado de Cosmologia; Dell’Antonio, Ian P. [Brown Univ., Providence, RI (United States); Frye, Brenda L. [Univ. of Arizona, Tucson, AZ (United States); Gawiser, Eric J. [State Univ. of New Jersey, Piscataway, NJ (United States); Gehrels, Neil [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Grady, Kevin [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Hagen, Alex [Penn State Univ., University Park, PA (United States); Hall, Patrick B. [York Univ., Toronto, ON (Canada); Hearin, Andrew P. [Yale Univ., New Haven, CT (United States); Hildebrandt, Hendrik [Argelander-Inst. fuer Astronomie, Bonn (Germany); Hirata, Christopher M. [Ohio State Univ., Columbus, OH (United States); Ho, Shirley [Carnegie Mellon Univ., Pittsburgh, PA (United States). McWilliams Center for Cosmology; Honscheid, Klaus [Ohio State Univ., Columbus, OH (United States); Huterer, Dragan [Univ. of Michigan, Ann Arbor, MI (United States); Ivezic, Zeljko [Univ. of Washington, Seattle, WA (United States); Kneib, Jean -Paul [Laboratoire d'Astrophysique, Ecole Polytechnique Federale de Lausanne (EPFL) (Swizerland); Laboratoire d'Astrophysique de Marseille (France); Kruk, Jeffrey W. [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Lahav, Ofer [Univ. College London, Bloomsbury (United Kingdom); Mandelbaum, Rachel [Carnegie Mellon Univ., Pittsburgh, PA (United States). McWilliams Center for Cosmology; Marshall, Jennifer L. [Texas A and M Univ., College Station, TX (United States); Matthews, Daniel J. [Univ. of Pittsburgh and PITT PACC, PA (United States). Dept of Physics and Astronomy; Menard, Brice [Johns Hopkins Univ., Baltimore, MD (United States); Miquel, Ramon [Univ. Autonoma de Barcelona (Spain). Inst. de Fisica d'Altes Energies (IFAE); Moniez, Marc [Univ. Paris-Sud, Orsay (France); Moos, H. W. [Johns Hopkins Univ., Baltimore, MD (United States); Moustakas, John [Siena College, Loudonville, NY (United States); Papovich, Casey [Texas A and M Univ., College Station, TX (United States); Peacock, John A. [Univ. of Edinburgh (United Kingdom). Inst. for Astronomy, Royal Observatory; Park, Changbom [Korea Inst. for Advanced Study, Seoul (Korea, Republic of); Rhodes, Jason [Jet Propulsion Lab./Caltech, Pasadena, CA (United States)

    2015-03-01T23:59:59.000Z

    Ongoing and near-future imaging-based dark energy experiments are critically dependent upon photometric redshifts (a.k.a. photo-z’s): i.e., estimates of the redshifts of objects based only on flux information obtained through broad filters. Higher-quality, lower-scatter photo-z’s will result in smaller random errors on cosmological parameters; while systematic errors in photometric redshift estimates, if not constrained, may dominate all other uncertainties from these experiments. The desired optimization and calibration is dependent upon spectroscopic measurements for secure redshift information; this is the key application of galaxy spectroscopy for imaging-based dark energy experiments. Hence, to achieve their full potential, imaging-based experiments will require large sets of objects with spectroscopically-determined redshifts, for two purposes: Training: Objects with known redshift are needed to map out the relationship between object color and z (or, equivalently, to determine empirically-calibrated templates describing the rest-frame spectra of the full range of galaxies, which may be used to predict the color-z relation). The ultimate goal of training is to minimize each moment of the distribution of differences between photometric redshift estimates and the true redshifts of objects, making the relationship between them as tight as possible. The larger and more complete our “training set” of spectroscopic redshifts is, the smaller the RMS photo-z errors should be, increasing the constraining power of imaging experiments; Requirements: Spectroscopic redshift measurements for ~30,000 objects over >~15 widely-separated regions, each at least ~20 arcmin in diameter, and reaching the faintest objects used in a given experiment, will likely be necessary if photometric redshifts are to be trained and calibrated with conventional techniques. Larger, more complete samples (i.e., with longer exposure times) can improve photo-z algorithms and reduce scatter further, enhancing the science return from planned experiments greatly (increasing the Dark Energy Task Force figure of merit by up to ~50%); Options: This spectroscopy will most efficiently be done by covering as much of the optical and near-infrared spectrum as possible at modestly high spectral resolution (?/?? > ~3000), while maximizing the telescope collecting area, field of view on the sky, and multiplexing of simultaneous spectra. The most efficient instrument for this would likely be either the proposed GMACS/MANIFEST spectrograph for the Giant Magellan Telescope or the OPTIMOS spectrograph for the European Extremely Large Telescope, depending on actual properties when built. The PFS spectrograph at Subaru would be next best and available considerably earlier, c. 2018; the proposed ngCFHT and SSST telescopes would have similar capabilities but start later. Other key options, in order of increasing total time required, are the WFOS spectrograph at TMT, MOONS at the VLT, and DESI at the Mayall 4 m telescope (or the similar 4MOST and WEAVE projects); of these, only DESI, MOONS, and PFS are expected to be available before 2020. Table 2-3 of this white paper summarizes the observation time required at each facility for strawman training samples. To attain secure redshift measurements for a high fraction of targeted objects and cover the full redshift span of future experiments, additional near-infrared spectroscopy will also be required; this is best done from space, particularly with WFIRST-2.4 and JWST; Calibration: The first several moments of redshift distributions (the mean, RMS redshift dispersion, etc.), must be known to high accuracy for cosmological constraints not to be systematics-dominated (equivalently, the moments of the distribution of differences between photometric and true redshifts could be determined instead). The ultimate goal of calibration is to characterize these moments for every subsample used in analyses - i.e., to minimize the uncertainty in their mean redshift, RMS dispersion, etc. – rather than to make the moments themselve

  3. Spectroscopic Needs for Imaging Dark Energy Experiments

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

    Newman, Jeffrey A.; Slosar, Anze; Abate, Alexandra; Abdalla, Filipe B.; Allam, Sahar; Allen, Steven W.; Ansari, Reza; Bailey, Stephen; Barkhouse, Wayne A.; Beers, Timothy C.; et al

    2015-03-01T23:59:59.000Z

    Ongoing and near-future imaging-based dark energy experiments are critically dependent upon photometric redshifts (a.k.a. photo-z’s): i.e., estimates of the redshifts of objects based only on flux information obtained through broad filters. Higher-quality, lower-scatter photo-z’s will result in smaller random errors on cosmological parameters; while systematic errors in photometric redshift estimates, if not constrained, may dominate all other uncertainties from these experiments. The desired optimization and calibration is dependent upon spectroscopic measurements for secure redshift information; this is the key application of galaxy spectroscopy for imaging-based dark energy experiments. Hence, to achieve their full potential, imaging-based experiments will require large setsmore »of objects with spectroscopically-determined redshifts, for two purposes: Training: Objects with known redshift are needed to map out the relationship between object color and z (or, equivalently, to determine empirically-calibrated templates describing the rest-frame spectra of the full range of galaxies, which may be used to predict the color-z relation). The ultimate goal of training is to minimize each moment of the distribution of differences between photometric redshift estimates and the true redshifts of objects, making the relationship between them as tight as possible. The larger and more complete our “training set” of spectroscopic redshifts is, the smaller the RMS photo-z errors should be, increasing the constraining power of imaging experiments; Requirements: Spectroscopic redshift measurements for ~30,000 objects over >~15 widely-separated regions, each at least ~20 arcmin in diameter, and reaching the faintest objects used in a given experiment, will likely be necessary if photometric redshifts are to be trained and calibrated with conventional techniques. Larger, more complete samples (i.e., with longer exposure times) can improve photo-z algorithms and reduce scatter further, enhancing the science return from planned experiments greatly (increasing the Dark Energy Task Force figure of merit by up to ~50%); Options: This spectroscopy will most efficiently be done by covering as much of the optical and near-infrared spectrum as possible at modestly high spectral resolution (?/?? > ~3000), while maximizing the telescope collecting area, field of view on the sky, and multiplexing of simultaneous spectra. The most efficient instrument for this would likely be either the proposed GMACS/MANIFEST spectrograph for the Giant Magellan Telescope or the OPTIMOS spectrograph for the European Extremely Large Telescope, depending on actual properties when built. The PFS spectrograph at Subaru would be next best and available considerably earlier, c. 2018; the proposed ngCFHT and SSST telescopes would have similar capabilities but start later. Other key options, in order of increasing total time required, are the WFOS spectrograph at TMT, MOONS at the VLT, and DESI at the Mayall 4 m telescope (or the similar 4MOST and WEAVE projects); of these, only DESI, MOONS, and PFS are expected to be available before 2020. Table 2-3 of this white paper summarizes the observation time required at each facility for strawman training samples. To attain secure redshift measurements for a high fraction of targeted objects and cover the full redshift span of future experiments, additional near-infrared spectroscopy will also be required; this is best done from space, particularly with WFIRST-2.4 and JWST; Calibration: The first several moments of redshift distributions (the mean, RMS redshift dispersion, etc.), must be known to high accuracy for cosmological constraints not to be systematics-dominated (equivalently, the moments of the distribution of differences between photometric and true redshifts could be determined instead). The ultimate goal of calibration is to characterize these moments for every subsample used in analyses - i.e., to minimize the uncertainty in their mean redshift, RMS dispersion, etc. – rather than to make the m

  4. HAWC: A Next Generation All-Sky VHE Gamma-Ray Telescope

    E-Print Network [OSTI]

    G. Sinnis; A. Smith; J. E. McEnery

    2004-03-03T23:59:59.000Z

    The study of the universe at energies above 100 GeV is a relatively new and exciting field. The current generation of pointed instruments have detected TeV gamma rays from at least 10 sources and the next generation of detectors promises a large increase in sensitivity. We have also seen the development of a new type of all-sky monitor in this energy regime based on water Cherenkov technology (Milagro). To fully understand the universe at these extreme energies requires a highly sensitive detector capable of continuously monitoring the entire overhead sky. Such an instrument could observe prompt emission from gamma-ray bursts and probe the limits of Lorentz invariance at high energies. With sufficient sensitivity it could detect short transients ($\\sim$15 minutes) from active galaxies and study the time structure of flares at energies unattainable to space-based instruments. Unlike pointed instruments a wide-field instrument can make an unbiased study of all active galaxies and enable many multi-wavelength campaigns to study these objects. This paper describes the design and performance of a next generation water Cherenkov detector. To attain a low energy threshold and have high sensitivity the detector should be located at high altitude ($>$ 4km) and have a large area ($\\sim$40,000 m$^2$). Such an instrument could detect gamma ray bursts out to a redshift of 1, observe flares from active galaxies as short as 15 minutes in duration, and survey the overhead sky at a level of 50 mCrab in one year.

  5. Neural networks and separation of Cosmic Microwave Background and astrophysical signals in sky maps

    E-Print Network [OSTI]

    C. Baccigalupi; L. Bedini; C. Burigana; G. De Zotti; A. Farusi; D. Maino; M. Maris; F. Perrotta; E. Salerno; L. Toffolatti; A. Tonazzini

    2000-06-21T23:59:59.000Z

    The Independent Component Analysis (ICA) algorithm is implemented as a neural network for separating signals of different origin in astrophysical sky maps. Due to its self-organizing capability, it works without prior assumptions on the signals, neither on their frequency scaling, nor on the signal maps themselves; instead, it learns directly from the input data how to separate the physical components, making use of their statistical independence. To test the capabilities of this approach, we apply the ICA algorithm on sky patches, taken from simulations and observations, at the microwave frequencies, that are going to be deeply explored in a few years on the whole sky, by the Microwave Anisotropy Probe (MAP) and by the {\\sc Planck} Surveyor Satellite. The maps are at the frequencies of the Low Frequency Instrument (LFI) aboard the {\\sc Planck} satellite (30, 44, 70 and 100 GHz), and contain simulated astrophysical radio sources, Cosmic Microwave Background (CMB) radiation, and Galactic diffuse emissions from thermal dust and synchrotron. We show that the ICA algorithm is able to recover each signal, with precision going from 10% for the Galactic components to percent for CMB; radio sources are almost completely recovered down to a flux limit corresponding to $0.7\\sigma_{CMB}$, where $\\sigma_{CMB}$ is the rms level of CMB fluctuations. The signal recovering possesses equal quality on all the scales larger then the pixel size. In addition, we show that the frequency scalings of the input signals can be partially inferred from the ICA outputs, at the percent precision for the dominant components, radio sources and CMB.

  6. HAWC: a next generation all-sky VHE gamma-ray telescope

    SciTech Connect (OSTI)

    Sinnis, G. (Gus); Smith, A.; McEnery, J. E.

    2004-01-01T23:59:59.000Z

    The study of the universe at energies above 100 GeV is a relatively new and exciting field. The current generation of pointed instruments have detected TeV gamma rays from at least 10 sources and the next generation of detectors promises a large increase in sensitivity. We have also seen the development of a new type of all-sky monitor in this energy regime based on water Cherenkov technology (Milagro). To fully understand the universe at these extreme energies requires a highly sensitive detector capable of continuously monitoring the entire overhead sky. Such an instrument could observe prompt emission from gamma-ray bursts and probe the limits of Lorentz invariance at high energies. With sufficient sensitivity it could detect shorthransients ({approx}15 minutes) from active galaxies and study the time structure of flares at energies unattainable to space-based instruments. Unlike pointed instruments a wide-field instrument can make an unbiased study of all active galaxies and enable many multi-wavelength campaigns to study these objects. This paper describes the design and performance of a next generation water Cherenkov detector. To attain a low energy threshold and have high sensitivity the detector should be located at high altitude (> 4km) and have a large area ({approx}40,000 m{sup 2}). Such an instrument could detect gamma ray bursts out to a redshift of 1, observe flares from active galaxies as short as 15 minutes in duration, and survey the overhead sky at a level of 50 mCrab in one year.

  7. Ultraviolet imaging of hydrogen flames

    SciTech Connect (OSTI)

    Yates, G.J.; Wilke, M.; King, N.

    1988-01-01T23:59:59.000Z

    We have assembled an ultraviolet-sensitive intensified camera for observing hydrogen combustion by imaging the OH, A/sup 2/..sigma.. - X/sup 2//Pi/ bandhead emissions near 309 nm. The camera consists of a quartz and CaF achromat lense-coupled to an ultraviolet image intensifier which is in turn fiber-coupled to a focus projection scan (FPS) vidicon. The emission band is selected with interference filters which serve to discriminate against background. The camera provides optical gain of 100 to 1000 and is capable of being shuttered at nanosecond speeds and of being framed at over 600 frames per second. We present data from observations of test flames in air at standard RS-170 video rates with varying background conditions. Enhanced images using background subtraction are presented. Finally, we discuss the use of polarizaton effects to further discrimination against sky background. This work began as a feasibility study to investigate ultraviolet technology to detect hydrogen fires for the NASA space program. 6 refs., 7 figs, 2 tabs.

  8. Magnetic white dwarfs in the Early Data Release of the Sloan Digital Sky Survey

    E-Print Network [OSTI]

    B. T. Gaensicke; F. Euchner; S. Jordan

    2002-08-26T23:59:59.000Z

    We have identified 7 new magnetic DA white dwarfs in the Early Data Release of the Sloan Digital Sky Survey. Our selection strategy has also recovered all the previously known magnetic white dwarfs contained in the SDSS EDR, KUV03292+0035 and HE0330-0002. Analysing the SDSS fibre spectroscopy of the magnetic DA white dwarfs with our state-of-the-art model spectra, we find dipole field strengths 1.5<=B_d<=63MG and effective temperatures 8500<=Teff<=39000K. As a conservative estimate, we expect that the complete SDSS will increase the number of known magnetic white dwarfs by a factor 3.

  9. Automated Classification of Sloan Digital Sky Survey (SDSS) Stellar Spectra using Artificial Neural Networks

    E-Print Network [OSTI]

    Mahdi Bazarghan; Ranjan Gupta

    2008-04-26T23:59:59.000Z

    Automated techniques have been developed to automate the process of classification of objects or their analysis. The large datasets provided by upcoming spectroscopic surveys with dedicated telescopes urges scientists to use these automated techniques for analysis of such large datasets which are now available to the community. Sloan Digital Sky Survey (SDSS) is one of such surveys releasing massive datasets. We use Probabilistic Neural Network (PNN) for automatic classification of about 5000 SDSS spectra into 158 spectral type of a reference library ranging from O type to M type stars.

  10. Galaxy Types in the Sloan Digital Sky Survey Using Supervised Artificial Neural Networks

    E-Print Network [OSTI]

    Nicholas M Ball; Jon Loveday; Masataka Fukugita; Osamu Nakamura; Sadanori Okamura; Jon Brinkmann; Robert J Brunner

    2003-06-19T23:59:59.000Z

    Supervised artificial neural networks are used to predict useful properties of galaxies in the Sloan Digital Sky Survey, in this instance morphological classifications, spectral types and redshifts. By giving the trained networks unseen data, it is found that correlations between predicted and actual properties are around 0.9 with rms errors of order ten per cent. Thus, given a representative training set, these properties may be reliably estimated for galaxies in the survey for which there are no spectra and without human intervention.

  11. Flattening Scientific CCD Imaging Data with a Dome Flat Field System

    E-Print Network [OSTI]

    J. L. Marshall; D. L. DePoy

    2005-10-07T23:59:59.000Z

    We describe the flattening of scientific CCD imaging data using a dome flat field system. The system uses light emitting diodes (LEDs) to illuminate a carefully constructed dome flat field screen. LEDs have several advantages over more traditional illumination sources: they are available in a wide range of output wavelengths, are inexpensive, have a very long source lifetime, and are straightforward to control digitally. The circular dome screen is made of a material with Lambertian scattering properties that efficiently reflects light of a wide range of wavelengths and incident angles. We compare flat fields obtained using this new system with two types of traditionally-constructed flat fields: twilight sky flats and nighttime sky flats. Using photometric standard stars as illumination sources, we test the quality of each flat field by applying it to a set of standard star observations. We find that the dome flat field system produces flat fields that are superior to twilight or nighttime sky flats, particularly for photometric calibration. We note that a ratio of the twilight sky flat to the nighttime sky flat is flat to within the expected uncertainty; but since both of these flat fields are inferior to the dome flat, this common test is not an appropriate metric for testing a flat field. Rather, the only feasible and correct method for determining the appropriateness of a flat field is to use standard stars to measure the reproducibility of known magnitudes across the detector.

  12. Total System Performance Assessment Peer Review Panel

    Broader source: Energy.gov [DOE]

    Total System Performance Assessment (TSPA) Peer Review Panel for predicting the performance of a repository at Yucca Mountain.

  13. People Images

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

    People Images People Images Several hundred of the 1700 U.S. scientists contributing to the LHC accelerator and experiments gathered in June 2008 in CERN's building 40 CE0252 Joel...

  14. MAKO: a pathfinder instrument for on-sky demonstration of low-cost 350 micron imaging arrays

    E-Print Network [OSTI]

    Swenson, Loren J; Dowell, Charles D; Eom, Byeong H; Hollister, Matthew I; Jarnot, Robert; Kovãcs, Attila; Leduc, Henry G; McKenney, Christopher M; Monroe, Ryan; Mroczkowski, Tony; Nguyen, Hien T; Zmuidzinas, Jonas; 10.1117/12.926223

    2012-01-01T23:59:59.000Z

    Submillimeter cameras now have up to $10^4$ pixels (SCUBA 2). The proposed CCAT 25-meter submillimeter telescope will feature a 1 degree field-of-view. Populating the focal plane at 350 microns would require more than $10^6$ photon-noise limited pixels. To ultimately achieve this scaling, simple detectors and high-density multiplexing are essential. We are addressing this long-term challenge through the development of frequency-multiplexed superconducting microresonator detector arrays. These arrays use lumped-element, direct-absorption resonators patterned from titanium nitride films. We will discuss our progress toward constructing a scalable 350 micron pathfinder instrument focusing on fabrication simplicity, multiplexing density, and ultimately a low per-pixel cost.

  15. Validation of MODIS-Retrieved Cloud Fractions Using Whole Sky Imager Measurements at the Three ARM Sites

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

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

  16. 8, 31433162, 2008 Total ozone over

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    ACPD 8, 3143­3162, 2008 Total ozone over oceanic regions M. C. R. Kalapureddy et al. Title Page Chemistry and Physics Discussions Total column ozone variations over oceanic region around Indian sub­3162, 2008 Total ozone over oceanic regions M. C. R. Kalapureddy et al. Title Page Abstract Introduction

  17. 5, 1133111375, 2005 NH total ozone

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    ACPD 5, 11331­11375, 2005 NH total ozone increase S. Dhomse et al. Title Page Abstract Introduction On the possible causes of recent increases in NH total ozone from a statistical analysis of satellite data from License. 11331 #12;ACPD 5, 11331­11375, 2005 NH total ozone increase S. Dhomse et al. Title Page Abstract

  18. 6, 39133943, 2006 Svalbard total ozone

    E-Print Network [OSTI]

    Boyer, Edmond

    ACPD 6, 3913­3943, 2006 Svalbard total ozone C. Vogler et al. Title Page Abstract Introduction Discussions Re-evaluation of the 1950­1962 total ozone record from Longyearbyen, Svalbard C. Vogler 1 , S. Br total ozone C. Vogler et al. Title Page Abstract Introduction Conclusions References Tables Figures Back

  19. About Total Lubricants USA, Inc. Headquartered in Linden, New Jersey, Total Lubricants USA provides

    E-Print Network [OSTI]

    Fisher, Kathleen

    New Jersey, Total Lubricants USA provides advanced quality industrial lubrication productsAbout Total Lubricants USA, Inc. Headquartered in Linden, New Jersey, Total Lubricants USA provides. A subsidiary of Total, S.A., the world's fourth largest oil company, Total Lubricants USA still fosters its

  20. Image alignment

    DOE Patents [OSTI]

    Dowell, Larry Jonathan

    2014-04-22T23:59:59.000Z

    Disclosed is a method and device for aligning at least two digital images. An embodiment may use frequency-domain transforms of small tiles created from each image to identify substantially similar, "distinguishing" features within each of the images, and then align the images together based on the location of the distinguishing features. To accomplish this, an embodiment may create equal sized tile sub-images for each image. A "key" for each tile may be created by performing a frequency-domain transform calculation on each tile. A information-distance difference between each possible pair of tiles on each image may be calculated to identify distinguishing features. From analysis of the information-distance differences of the pairs of tiles, a subset of tiles with high discrimination metrics in relation to other tiles may be located for each image. The subset of distinguishing tiles for each image may then be compared to locate tiles with substantially similar keys and/or information-distance metrics to other tiles of other images. Once similar tiles are located for each image, the images may be aligned in relation to the identified similar tiles.

  1. Multi-wavelength study of 14000 star-forming galaxies from the Sloan Digital Sky Survey

    E-Print Network [OSTI]

    Izotov, Y I; Fricke, K J; Henkel, C

    2013-01-01T23:59:59.000Z

    (abridged) We studied a large sample of ~14000 dwarf star-forming galaxies with strong emission lines selected from the Sloan Digital Sky Survey (SDSS) and distributed in the redshift range of z~0-0.6. We modelled spectral energy distributions (SED) of all galaxies which were based on the SDSS spectra in the visible range of 0.38-0.92 micron and included both the stellar and ionised gas emission. These SEDs were extrapolated to the UV and mid-infrared ranges to cover the wavelength range of 0.1-22 micron. The SDSS spectroscopic data were supplemented by photometric data from the GALEX, SDSS, 2MASS, WISE, IRAS, and NVSS all-sky surveys. We derived global characteristics of the galaxies, such as their element abundances, luminosities, and stellar masses. The luminosities and stellar masses range within the sample over ~5 orders of magnitude, thereby linking low-mass and low-luminosity blue compact dwarf (BCD) galaxies to luminous galaxies, which are similar to high-redshift Lyman-break galaxies (LBGs). The lumi...

  2. THE SLOAN DIGITAL SKY SURVEY DATA RELEASE 7 SPECTROSCOPIC M DWARF CATALOG. I. DATA

    SciTech Connect (OSTI)

    West, Andrew A.; Morgan, Dylan P.; Andersen, Jan Marie; Covey, Kevin R.; Schluns, Kyle; Jones, David O. [Department of Astronomy, Boston University, 725 Commonwealth Avenue, Boston, MA 02215 (United States); Bochanski, John J.; Pineda, J. Sebastian [MIT Kavli Institute for Astrophysics and Space Research, 77 Massachusetts Avenue, Cambridge, MA 02139-4307 (United States); Bell, Keaton J.; Kowalski, Adam F.; Davenport, James R. A.; Hawley, Suzanne L.; Schmidt, Sarah J.; Hilton, Eric J. [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 (United States); Bernat, David; Muirhead, Philip; Rojas-Ayala, Barbara; Schlawin, Everett [Department of Astronomy, Cornell University, 610 Space Sciences Building, Ithaca, NY 14853 (United States); Gooding, Mary [Department of Mathematical and Physical Sciences, Wells College, 170 Main Street, Aurora, NY 13026 (United States); Dhital, Saurav, E-mail: aawest@bu.edu [Department of Physics and Astronomy, Vanderbilt University, 6301 Stevenson Center, Nashville, TN 37235 (United States)

    2011-03-15T23:59:59.000Z

    We present a spectroscopic catalog of 70,841 visually inspected M dwarfs from the seventh data release of the Sloan Digital Sky Survey. For each spectrum, we provide measurements of the spectral type, a number of molecular band heads, and the H{alpha}, H{beta}, H{gamma}, H{delta}, and Ca II K emission lines. In addition, we calculate the metallicity-sensitive parameter {zeta} and identify a relationship between {zeta} and the g - r and r - z colors of M dwarfs. We assess the precision of our spectral types (which were assigned by individual examination), review the bulk attributes of the sample, and examine the magnetic activity properties of M dwarfs, in particular those traced by the higher order Balmer transitions. Our catalog is cross-matched to Two Micron All Sky Survey infrared data, and contains photometric distances for each star. Finally, we identify eight new late-type M dwarfs that are possibly within 25 pc of the Sun. Future studies will use these data to thoroughly examine magnetic activity and kinematics in late-type M dwarfs and examine the chemical and dynamical history of the local Milky Way.

  3. Evidence of cross-correlation between the CMB lensing and the gamma-ray sky

    E-Print Network [OSTI]

    N. Fornengo; L. Perotto; M. Regis; S. Camera

    2015-03-02T23:59:59.000Z

    We report the measurement of the angular power spectrum of cross-correlation between the unresolved component of the Fermi-LAT gamma-ray sky-maps and the CMB lensing potential map reconstructed by the Planck satellite. The matter distribution in the Universe determines the bending of light coming from the last scattering surface. At the same time, the matter density drives the growth history of astrophysical objects, including their capability at generating non-thermal phenomena, which in turn give rise to gamma-ray emissions. The Planck lensing map provides information on the integrated distribution of matter, while the integrated history of gamma-ray emitters is imprinted in the Fermi-LAT sky maps. We report here the first evidence of their correlation. We find that the multipole dependence of the cross-correlation measurement is in agreement with current models of the gamma-ray luminosity function for AGN and star forming galaxies, with a statistical evidence of 3.0$\\sigma$. Moreover, its amplitude can in general be matched only assuming that these extra-galactic emitters are also the bulk contribution of the measured isotopic gamma-ray background (IGRB) intensity. This leaves little room for a big contribution from galactic sources to the IGRB measured by Fermi-LAT, pointing toward a direct evidence of the extragalactic origin of the IGRB.

  4. SkyMouse: A smart interface for astronomical on-line resources and services

    E-Print Network [OSTI]

    CUI, Chen-Zhou; ZHAO, Yong-Heng; LUO, Yu; QI, Da-Zhi

    2007-01-01T23:59:59.000Z

    With the development of network and the World Wide Web (WWW), the Internet has been growing and changing dramatically. More and more on-line database systems and different kinds of services are available for astronomy research. How to help users find their way through the jungle of information services becomes an important challenge. Although astronomers have been aware of the importance of interoperability and introduced the concept of Virtual Observatory as a uniform environment for future astronomical on-line resources and services, transparent access to heterogeneous on-line information is still difficult. SkyMouse is a lightweight interface for distributed astronomical on-line resources and services, which is designed and developed by us, i.e., Chinese Virtual Observatory Project. Taking advantage of screen word-capturing technology, different kinds of information systems can be queried through simple mouse actions, and results are returned in a uniform web page. SkyMouse is an easy to use application, a...

  5. HAWC (High Altitude Water Cherenkov) Observatory for Surveying the TeV Sky

    SciTech Connect (OSTI)

    Dingus, Brenda L. [Los Alamos National Lab, Los Alamos, NM 87545 (United States)

    2007-07-12T23:59:59.000Z

    The HAWC observatory is a proposed, large field of view ({approx}2 sr), high duty cycle (>95%) TeV gamma-ray detector which uses a large pond of water (150 m x 150 m) located at 4300 m elevation. The pond contains 900 photomultiplier tubes (PMTs) to observe the relativistic particles and secondary gamma lays in extensive air showers. This technique has been used successfully by the Milagro observatory to detect known, as well as new, TeV sources. The PMTs and much of the data acquisition system of Milagro will be reused for HAWC, resulting in a cost effective detector ({approx}6M$) that can be built quickly in 2-3 years. The improvements of HAWC will result in {approx}15 times the sensitivity of Milagro. HAWC will survey 2{pi} sr of the sky every day with a sensitivity of the Crab flux at a median energy of 1 TeV. After five years of operation half of the sky will be surveyed to 20 mCrab. This sensitivity will likely result in the discovery of new sources as well as allow the identification of which GLAST sources extend to higher energies.

  6. An Initial Survey of White Dwarfs in the Sloan Digital Sky Survey

    E-Print Network [OSTI]

    H. C. Harris; J. Liebert; S. J. Kleinman; A. Nitta; S. F. Anderson; G. R. Knapp; J. Krzesinski; G. Schmidt; M. A. Strauss; D. Vanden Berk; D. Eisenstein; S. Hawley; B. Margon; J. A. Munn; N. M. Silvestri; A. Smith; P. Szkody; M. J. Collinge; C. C. Dahn; X. Fan; P. B. Hall; D. P. Schneider; J. Brinkmann; S. Burles; J. E. Gunn; G. S. Hennessy; R. Hindsley; Z. Ivezic; S. Kent; D. Q. Lamb; R. H. Lupton; R. C. Nichol; J. R. Pier; D. J. Schlegel; M. SubbaRao; A. Uomoto; B. Yanny; D. G. York

    2003-05-19T23:59:59.000Z

    An initial assessment is made of white dwarf and hot subdwarf stars observed in the Sloan Digital Sky Survey. In a small area of sky (190 square degrees), observed much like the full survey will be, 269 white dwarfs and 56 hot subdwarfs are identified spectroscopically where only 44 white dwarfs and 5 hot subdwarfs were known previously. Most are ordinary DA (hydrogen atmosphere) and DB (helium) types. In addition, in the full survey to date, a number of WDs have been found with uncommon spectral types. Among these are blue DQ stars displaying lines of atomic carbon; red DQ stars showing molecular bands of C_2 with a wide variety of strengths; DZ stars where Ca and occasionally Mg, Na, and/or Fe lines are detected; and magnetic WDs with a wide range of magnetic field strengths in DA, DB, DQ, and (probably) DZ spectral types. Photometry alone allows identification of stars hotter than 12000 K, and the density of these stars for 15

  7. An Efficient Algorithm for Positioning Tiles in the Sloan Digital Sky Survey

    E-Print Network [OSTI]

    M. R. Blanton; R. H. Lupton; F. Miller Maley; N. Young; I. Zehavi; J. Loveday

    2001-05-30T23:59:59.000Z

    The Sloan Digital Sky Survey (SDSS) will observe around 10^6 spectra from targets distributed over an area of about 10,000 square degrees, using a multi-object fiber spectrograph which can simultaneously observe 640 objects in a circular field-of-view (referred to as a ``tile'') 1.49 degrees in radius. No two fibers can be placed closer than 55'' during the same observation; multiple targets closer than this distance are said to ``collide.'' We present here a method of allocating fibers to desired targets given a set of tile centers which includes the effects of collisions and which is nearly optimally efficient and uniform. Because of large-scale structure in the galaxy distribution (which form the bulk of the SDSS targets), a naive covering the sky with equally-spaced tiles does not yield uniform sampling. Thus, we present a heuristic for perturbing the centers of the tiles from the equally-spaced distribution which provides more uniform completeness. For the SDSS sample, we can attain a sampling rate greater than 92% for all targets, and greater than 99% for the set of targets which do not collide with each other, with an efficiency greater than 90% (defined as the fraction of available fibers assigned to targets).

  8. ARM: W-Band Scanning ARM Cloud Radar (W-SACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)

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

    Widener, Kevin; Nelson, Dan; Bharadwaj, Nitin; Lindenmaier, Iosif [Andrei; Johnson, Karen

    W-Band Scanning ARM Cloud Radar (W-SACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)

  9. ARM: X-Band Scanning ARM Cloud Radar (XSACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)

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

    Widener, Kevin; Nelson, Dan; Bharadwaj, Nitin; Lindenmaier, Iosif [Andrei; Johnson, Karen

    X-Band Scanning ARM Cloud Radar (XSACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)

  10. ARM: Ka-Band Scanning ARM Cloud Radar (KASACR) Hemispherical Sky RHI Scan (6 horizon-to-horizon scans at 30-degree azimuth intervals)

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

    Bharadwaj, Nitin; Widener, Kevin

    Ka-Band Scanning ARM Cloud Radar (KASACR) Hemispherical Sky RHI Scan (6 horizon-to-horizon scans at 30-degree azimuth intervals)

  11. VIMOS total transmission profiles for broad-band filters

    E-Print Network [OSTI]

    S. Mieske; M. Rejkuba; S. Bagnulo; C. Izzo; G. Marconi

    2007-04-13T23:59:59.000Z

    VIMOS is a wide-field imager and spectrograph mounted on UT3 at the VLT, whose FOV consists of four 7'x8' quadrants. Here we present the measurements of total transmission profiles -- i.e. the throughput of telescope + instrument -- for the broad band filters U, B, V, R, I, and z for each of its four quadrants. Those measurements can also be downloaded from the public VIMOS web-page. The transmission profiles are compared with previous estimates from the VIMOS consortium.

  12. SPIE Medical Imaging Medical Imaging

    E-Print Network [OSTI]

    Miga, Michael I.

    CT and SPECT (GE Hawkeye) SPIE Medical Imaging 2006 28 CT/PET System Combined CT and PET (Siemens Medical Imaging 2006 10 Computed Tomography (CT) 3D Tomography from multiple projections #12;6 SPIE: Scintillation Camera SPIE Medical Imaging 2006 26 PET and SPECT PET = Positron Emission Tomography SPECT

  13. EXTENDED HOT HALOS AROUND ISOLATED GALAXIES OBSERVED IN THE ROSAT ALL-SKY SURVEY

    SciTech Connect (OSTI)

    Anderson, Michael E.; Bregman, Joel N. [Department of Astronomy, University of Michigan, Ann Arbor, MI 48109 (United States)] [Department of Astronomy, University of Michigan, Ann Arbor, MI 48109 (United States); Dai, Xinyu, E-mail: michevan@umich.edu, E-mail: jbregman@umich.edu, E-mail: xdai@ou.edu [Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman, OK 73019 (United States)] [Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman, OK 73019 (United States)

    2013-01-10T23:59:59.000Z

    We place general constraints on the luminosity and mass of hot X-ray-emitting gas residing in extended 'hot halos' around nearby massive galaxies. We examine stacked images of 2165 galaxies from the 2MASS Isolated Galaxy Catalog as well as subsets of this sample based on galaxy morphology and K-band luminosity. We detect X-ray emission at high confidence (ranging up to nearly 10{sigma}) for each subsample of galaxies. The average L{sub X} within 50 kpc is 1.0 {+-} 0.1 (statistical) {+-}0.2 (systematic) Multiplication-Sign 10{sup 40} erg s{sup -1}, although the early-type galaxies are more than twice as luminous as the late-type galaxies. Using a spatial analysis, we also find evidence for extended emission around five out of seven subsamples (the full sample, the luminous galaxies, early-type galaxies, luminous late-type galaxies, and luminous early-type galaxies) at 92.7%, 99.3%, 89.3%, 98.7%, and 92.1% confidence, respectively. Several additional lines of evidence also support this conclusion and suggest that about 1/2 of the total emission is extended, and about 1/3 of the extended emission comes from hot gas. For the sample of luminous galaxies, which has the strongest evidence for extended emission, the average hot gas mass is 4 Multiplication-Sign 10{sup 9} M {sub Sun} within 50 kpc and the implied accretion rate is 0.4 M {sub Sun} yr{sup -1}.

  14. Climatological data for clouds over the globe from surface observations, 1982--1991: The total cloud edition

    SciTech Connect (OSTI)

    Hahn, C.J. [Colorado Univ., Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences] [Colorado Univ., Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences; Warren, S.G. [Washington Univ., Seattle, WA (United States). Dept. of Atmospheric Sciences] [Washington Univ., Seattle, WA (United States). Dept. of Atmospheric Sciences; London, J. [Colorado Univ., Boulder, CO (United States). Dept. of Astrophysical, Planetary, and Atmospheric Sciences] [Colorado Univ., Boulder, CO (United States). Dept. of Astrophysical, Planetary, and Atmospheric Sciences

    1994-10-01T23:59:59.000Z

    Routine, surface synoptic weather reports from ships and land stations over the entire globe, for the ten-year period December 1981 through November 1991, were processed for total cloud cover and the frequencies of occurrence of clear sky, precipitation, and sky-obscured due to fog. Archived data, consisting of various annual, seasonal and monthly averages, are provided in grid boxes that are typically 2.5{degrees} {times} 2.5{degrees} for land and 5{degrees} {times} 5{degrees} for ocean. Day and nighttime averages are also given separately for each season. Several derived quantities, such as interannual variations and annual and diurnal harmonics, are provided as well. This data set incorporates an improved representation of nighttime cloudiness by utilizing only those nighttime observations for which the illuminance due to moonlight exceeds a specified threshold. This reduction in the night-detection bias increases the computed global average total cloud cover by about 2%. The impact on computed diurnal cycles is even greater, particularly over the oceans where is found, in contrast to previous surface-based climatologies, that cloudiness is often greater at night than during the day.

  15. EXPLORING THE VARIABLE SKY WITH LINEAR. III. CLASSIFICATION OF PERIODIC LIGHT CURVES

    SciTech Connect (OSTI)

    Palaversa, Lovro; Eyer, Laurent; Rimoldini, Lorenzo [Observatoire Astronomique de l'Université de Genève, 51 chemin des Maillettes, CH-1290 Sauverny (Switzerland); Ivezi?, Željko; Loebman, Sarah; Hunt-Walker, Nicholas; VanderPlas, Jacob; Westman, David; Becker, Andrew C. [Department of Astronomy, University of Washington, P.O. Box 351580, Seattle, WA 98195-1580 (United States); Ruždjak, Domagoj; Sudar, Davor; Boži?, Hrvoje [Hvar Observatory, Faculty of Geodesy, Ka?i?eva 26, 10000 Zagreb (Croatia); Galin, Mario [Faculty of Geodesy, Ka?i?eva 26, 10000 Zagreb (Croatia); Kroflin, Andrea; Mesari?, Martina; Munk, Petra; Vrbanec, Dijana [Department of Physics, Faculty of Science, University of Zagreb, Bijeni?ka cesta 32, 10000 Zagreb (Croatia); Sesar, Branimir [Division of Physics, Mathematics, and Astronomy, Caltech, Pasadena, CA 91125 (United States); Stuart, J. Scott [Lincoln Laboratory, Massachusetts Institute of Technology, 244 Wood Street, Lexington, MA 02420-9108 (United States); Srdo?, Gregor, E-mail: lovro.palaversa@unige.ch [Saršoni 90, 51216 Viškovo (Croatia); and others

    2013-10-01T23:59:59.000Z

    We describe the construction of a highly reliable sample of ?7000 optically faint periodic variable stars with light curves obtained by the asteroid survey LINEAR across 10,000 deg{sup 2} of the northern sky. The majority of these variables have not been cataloged yet. The sample flux limit is several magnitudes fainter than most other wide-angle surveys; the photometric errors range from ?0.03 mag at r = 15 to ?0.20 mag at r = 18. Light curves include on average 250 data points, collected over about a decade. Using Sloan Digital Sky Survey (SDSS) based photometric recalibration of the LINEAR data for about 25 million objects, we selected ?200,000 most probable candidate variables with r < 17 and visually confirmed and classified ?7000 periodic variables using phased light curves. The reliability and uniformity of visual classification across eight human classifiers was calibrated and tested using a catalog of variable stars from the SDSS Stripe 82 region and verified using an unsupervised machine learning approach. The resulting sample of periodic LINEAR variables is dominated by 3900 RR Lyrae stars and 2700 eclipsing binary stars of all subtypes and includes small fractions of relatively rare populations such as asymptotic giant branch stars and SX Phoenicis stars. We discuss the distribution of these mostly uncataloged variables in various diagrams constructed with optical-to-infrared SDSS, Two Micron All Sky Survey, and Wide-field Infrared Survey Explorer photometry, and with LINEAR light-curve features. We find that the combination of light-curve features and colors enables classification schemes much more powerful than when colors or light curves are each used separately. An interesting side result is a robust and precise quantitative description of a strong correlation between the light-curve period and color/spectral type for close and contact eclipsing binary stars (? Lyrae and W UMa): as the color-based spectral type varies from K4 to F5, the median period increases from 5.9 hr to 8.8 hr. These large samples of robustly classified variable stars will enable detailed statistical studies of the Galactic structure and physics of binary and other stars and we make these samples publicly available.

  16. ,"New Mexico Natural Gas Total Consumption (MMcf)"

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

    ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Total Consumption (MMcf)",1,"Annual",2013 ,"Release Date:","331...

  17. ,"New York Natural Gas Total Consumption (MMcf)"

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

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New York Natural Gas Total Consumption (MMcf)",1,"Annual",2013 ,"Release Date:","2272015"...

  18. Two extremely metal-poor emission-line galaxies in the Sloan Digital Sky Survey

    E-Print Network [OSTI]

    Y. I. Izotov; P. Papaderos; N. G. Guseva; K. J. Fricke; T. X. Thuan

    2006-04-11T23:59:59.000Z

    We present spectroscopic observations with the 3.6m ESO telescope of two emission-line galaxies, J2104-0035 and J0113+0052, selected from the Data Release 4 (DR4) of the Sloan Digital Sky Survey (SDSS). From our data we determine the oxygen abundance of these systems to be respectively 12+logO/H = 7.26+/-0.03 and 7.17+/-0.09, making them the two most metal-deficient galaxies found thus far in the SDSS and placing them among the five most metal-deficient emission-line galaxies ever discovered. Their oxygen abundances are close to those of the two most metal-deficient emission-line galaxies known, SBS0335-052W with 12+logO/H = 7.12+/-0.03 and I Zw 18 with 12+logO/H = 7.17+/-0.01.

  19. Hierarchical Hough all-sky search for periodic gravitational waves in LIGO S5 data

    E-Print Network [OSTI]

    Llucia Sancho de la Jordana; for the LIGO Scientific Collaboration; the Virgo Collaboration

    2010-01-21T23:59:59.000Z

    We describe a new pipeline used to analyze the data from the fifth science run (S5) of the LIGO detectors to search for continuous gravitational waves from isolated spinning neutron stars. The method employed is based on the Hough transform, which is a semi-coherent, computationally efficient, and robust pattern recognition technique. The Hough transform is used to find signals in the time-frequency plane of the data whose frequency evolution fits the pattern produced by the Doppler shift imposed on the signal by the Earth's motion and the pulsar's spin-down during the observation period. The main differences with respect to previous Hough all-sky searches are described. These differences include the use of a two-step hierarchical Hough search, analysis of coincidences among the candidates produced in the first and second year of S5, and veto strategies based on a $\\chi^2$ test.

  20. Mapping the Heavens: Probing Cosmology with the Sloan Digital Sky Survey

    SciTech Connect (OSTI)

    Frieman, Josh (University of Chicago) [University of Chicago

    2006-12-04T23:59:59.000Z

    This talk will provide an overview of results from the on-going Sloan Digital Sky Survey (SDSS), the most ambitious mapping of the Universe yet undertaken, focusing on those with implications for cosmology. It will include a virtual fly-through of the survey that reveals the 3-dimensional large-scale structure of the galaxy distribution. Recent measurements of this large-scale structure, in combination with observations of the cosmic microwave background, have provided independent evidence for a Universe dominated by dark matter and dark energy as well as insights into how galaxies and larger-scale structures formed. I will also describe early results from the SDSS Supernova Survey, which aims to provide more precise constraints on the nature of dark energy. Future planned surveys from the ground and from space will build on these foundations to probe the history of the cosmic expansion--and thereby the dark energy--with even greater precision.

  1. Data-Mining a Large Digital Sky Survey: From the Challenges to the Scientific Results

    E-Print Network [OSTI]

    S. G. Djorgovski; R. R. de Carvalho; S. C. Odewahn; R. R. Gal; J. Roden; P. Stolorz; A. Gray

    1997-08-24T23:59:59.000Z

    The analysis and an efficient scientific exploration of the Digital Palomar Observatory Sky Survey (DPOSS) represents a major technical challenge. The input data set consists of 3 Terabytes of pixel information, and contains a few billion sources. We describe some of the specific scientific problems posed by the data, including searches for distant quasars and clusters of galaxies, and the data-mining techniques we are exploring in addressing them. Machine-assisted discovery methods may become essential for the analysis of such multi-Terabyte data sets. New and future approaches involve unsupervised classification and clustering analysis in the Giga-object data space, including various Bayesian techniques. In addition to the searches for known types of objects in this data base, these techniques may also offer the possibility of discovering previously unknown, rare types of astronomical objects.

  2. An all-sky study of compact, isolated high-velocity clouds

    E-Print Network [OSTI]

    V. de Heij; R. Braun; W. B. Burton

    2002-06-18T23:59:59.000Z

    We combine the catalogs of compact high-velocity HI clouds extracted from the LDS and HIPASS surveys and analyze the all-sky properties of the ensemble. Five principal observables are defined for the CHVC population: (1) the spatial deployment of the objects on the sky, (2) the kinematic distribution, (3) the number distribution of observed HI column densities, (4) the number distribution of angular sizes, and (5) the number distribution of HI linewidth. Two classes of models are considered to reproduce the observed properties. The agreement of models with the data is judged by extracting these same observables from simulations, in a manner consistent with the sensitivities of the observations and explicitly taking account of Galactic obscuration. We show that models in which the CHVCs are the HI counterparts of dark-matter halos evolving in the Local Group potential provide a good match to the observables. The best-fitting populations have a maximum HI mass of 10^7 M_Sun a power-law slope of the HI mass distribution in the range -1.7 to -1.8, and a Gaussian dispersion for their spatial distributions of between 150 and 200 kpc centered on both the Milky Way and M31. Given its greater mean distance, only a small fraction of the M31 sub-population is predicted to have been detected in present surveys. An empirical model for an extended Galactic halo distribution for the CHVCs is also considered. While reproducing some aspects of the population, this class of models does not account for some key systematic features of the population.

  3. The 60-month all-sky BAT Survey of AGN and the Anisotropy of Nearby AGN

    SciTech Connect (OSTI)

    Ajello, M.; /KIPAC, Menlo Park; Alexander, D.M.; /Durham U.; Greiner, J.; /Garching, Max Planck Inst., MPE; Madejski, G.M.; /KIPAC, Menlo Park; Gehrels, N.; /NASA, Goddard; Burlon, D.; /Garching, Max Planck Inst., MPE

    2012-04-02T23:59:59.000Z

    Surveys above 10 keV represent one of the the best resources to provide an unbiased census of the population of Active Galactic Nuclei (AGN). We present the results of 60 months of observation of the hard X-ray sky with Swift/BAT. In this timeframe, BAT detected (in the 15-55 keV band) 720 sources in an all-sky survey of which 428 are associated with AGN, most of which are nearby. Our sample has negligible incompleteness and statistics a factor of {approx}2 larger over similarly complete sets of AGN. Our sample contains (at least) 15 bona-fide Compton-thick AGN and 3 likely candidates. Compton-thick AGN represent a {approx}5% of AGN samples detected above 15 keV. We use the BAT dataset to refine the determination of the LogN-LogS of AGN which is extremely important, now that NuSTAR prepares for launch, towards assessing the AGN contribution to the cosmic X-ray background. We show that the LogN-LogS of AGN selected above 10 keV is now established to a {approx}10% precision. We derive the luminosity function of Compton-thick AGN and measure a space density of 7.9{sub -2.9}{sup +4.1} x 10{sup -5} Mpc{sup -3} for objects with a de-absorbed luminosity larger than 2 x 10{sup 42} erg s{sup -1}. As the BAT AGN are all mostly local, they allow us to investigate the spatial distribution of AGN in the nearby Universe regardless of absorption. We find concentrations of AGN that coincide spatially with the largest congregations of matter in the local ({le} 85 Mpc) Universe. There is some evidence that the fraction of Seyfert 2 objects is larger than average in the direction of these dense regions.

  4. Our Star, The Sun Looking up at the sky with the naked eye, the Sun seems static, constant. It provides the warmth and light that

    E-Print Network [OSTI]

    Christian, Eric

    #12;Our Star, The Sun Looking up at the sky with the naked eye, the Sun seems static, constant in the Sun are its location (as it ravels across the sky) and its color (will the atmosphere make it turn red or orange?) Scientists have learned a lot about the Sun in the past 400 years. We know that the Sun

  5. What causes the excessive response of clear-sky greenhouse effect to El Nin~o warming in Community Atmosphere Models?

    E-Print Network [OSTI]

    Sun, Dezheng

    What causes the excessive response of clear-sky greenhouse effect to El Nin~o warming in Community.-Z. Sun (2008), What causes the excessive response of clear-sky greenhouse effect to El Nin~o warming for global warming because the latter may have a different spatial pattern of warming [e.g., Sun and Held

  6. IMAGING DISK DISTORTION OF BE BINARY SYSTEM {delta} SCORPII NEAR PERIASTRON

    SciTech Connect (OSTI)

    Che, X.; Monnier, J. D.; Kraus, S.; Baron, F. [Astronomy Department, University of Michigan, 1034 Dennison Bldg, Ann Arbor, MI 48109-1090 (United States); Tycner, C. [Department of Physics, Central Michigan University, Mount Pleasant, MI 48859 (United States); Zavala, R. T. [US Naval Observatory, Flagstaff Station, 10391 West Naval Observatory Road, Flagstaff, AZ 86001 (United States); Pedretti, E. [European Southern Observatory, Karl-Schwarzschild-Str. 2, 85748 Garching bei Muenchen (Germany); Ten Brummelaar, T.; McAlister, H.; Sturmann, J.; Sturmann, L.; Turner, N. [CHARA Array of Georgia State University, Mount Wilson, CA 91023 (United States); Ridgway, S. T., E-mail: xche@umich.edu [National Optical Astronomy Observatory, NOAO, Tucson, AZ (United States)

    2012-09-20T23:59:59.000Z

    The highly eccentric Be binary system {delta} Sco reached periastron during early 2011 July, when the distance between the primary and secondary was a few times the size of the primary disk in the H band. This opened a window of opportunity to study how the gaseous disks around Be stars respond to gravitational disturbance. We first refine the binary parameters with the best orbital phase coverage data from the Navy Precision Optical Interferometer. Then we present the first imaging results of the disk after the periastron, based on seven nights of five telescope observations with the MIRC combiner at the CHARA array. We found that the disk was inclined 27.{sup 0}6 {+-} 6.{sup 0}0 from the plane of the sky, had a half-light radius of 0.49 mas (2.2 stellar radii), and consistently contributed 71.4% {+-} 2.7% of the total flux in the H band from night to night, suggesting no ongoing transfer of material into the disk during the periastron. The new estimation of the periastron passage is UT 2011 July 3 07:00 {+-} 4:30. Re-analysis of archival VLTI-AMBER interferometry data allowed us to determine the rotation direction of the primary disk, constraining it to be inclined either {approx}119 Degree-Sign or {approx}171 Degree-Sign relative to the orbital plane of the binary system. We also detect inner disk asymmetries that could be explained by spot-like emission with a few percent of the disk total flux moving in Keplerian orbits, although we lack sufficient angular resolution to be sure of this interpretation and cannot yet rule out spiral density waves or other more complicated geometries.

  7. TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION

    E-Print Network [OSTI]

    Skogestad, Sigurd

    TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION BERND WITTGENS, RAJAB LITTO, EVA S RENSEN a generalization of previously proposed batch distillation schemes. A simple feedback control strategy for total re verify the simulations. INTRODUCTION Although batch distillation generally is less energy e cient than

  8. Total correlations as fully additive entanglement monotones

    E-Print Network [OSTI]

    Gerardo A. Paz-Silva; John H. Reina

    2007-04-05T23:59:59.000Z

    We generalize the strategy presented in Refs. [1, 2], and propose general conditions for a measure of total correlations to be an entanglement monotone using its pure (and mixed) convex-roof extension. In so doing, we derive crucial theorems and propose a concrete candidate for a total correlations measure which is a fully additive entanglement monotone.

  9. CBER-DETR Nevada Coincident and Leading Employment Cloudy Skies Continue to Hang over the Nevada Employment Sector

    E-Print Network [OSTI]

    Ahmad, Sajjad

    CBER-DETR Nevada Coincident and Leading Employment Indexes1 Cloudy Skies Continue to Hang over the Nevada Employment Sector The Nevada Coincident Employment Index measures the ups and downs of the Nevada economy using an index of employment variables. The Nevada Leading Employment Index also measures the ups

  10. 1 JUNE 2000 1951A L L A N Evaluation of Simulated Clear-Sky Longwave Radiation Using

    E-Print Network [OSTI]

    Allan, Richard P.

    the clear-sky surface down- welling longwave irradiance (SDLc) to be an important amplifier of greenhouse). It is therefore important that SDLc is simulated adequately by climate models, particularly where the surface radiosonde profiles as input data. Model SDLc tended to be underestimated by about 5 W m 2 in comparison

  11. A SKY-HIGH CHALLENGE: THE CARBON FOOTPRINT OF AVIATION IN BRITISH COLUMBIA, CANADA, AND MEASURES TO MITIGATE IT

    E-Print Network [OSTI]

    Pedersen, Tom

    A SKY-HIGH CHALLENGE: THE CARBON FOOTPRINT OF AVIATION IN BRITISH COLUMBIA, CANADA, AND MEASURES but not subnational scale. In this thesis, I present what seems to be the first detailed analysis of the carbon footprint (CF) of civil aviation at a subnational level together with an assessment of what key stakeholders

  12. IEEE TRANSACTIONS ON CLOUD COMPUTING, VOL. XX, NO. X, XXXX 1 Cloud Federations in the Sky: Formation Game

    E-Print Network [OSTI]

    Grosu, Daniel

    IEEE TRANSACTIONS ON CLOUD COMPUTING, VOL. XX, NO. X, XXXX 1 Cloud Federations in the Sky federation, virtual machine, game theory. 1 INTRODUCTION CLOUDS are large-scale distributed computing sys (VM) instances. Cloud computing systems' ability to provide on de- mand access to always-on computing

  13. High-Resolution Spectroscopic Study of Extremely Metal-Poor Star Candidates from the SkyMapper Survey

    E-Print Network [OSTI]

    Jacobson, Heather R; Frebel, Anna; Casey, Andrew R; Asplund, Martin; Bessell, Michael S; Da Costa, Gary S; Lind, Karin; Marino, Anna F; Norris, John E; Pena, Jose M; Schmidt, Brian P; Tisserand, Patrick; Walsh, Jennifer M; Yong, David; Yu, Qinsi

    2015-01-01T23:59:59.000Z

    The SkyMapper Southern Sky Survey is carrying out a search for the most metal-poor stars in the Galaxy. It identifies candidates by way of its unique filter set that allows for estimation of stellar atmospheric parameters. The set includes a narrow filter centered on the Ca II K 3933A line, enabling a robust estimate of stellar metallicity. Promising candidates are then confirmed with spectroscopy. We present the analysis of Magellan-MIKE high-resolution spectroscopy of 122 metal-poor stars found by SkyMapper in the first two years of commissioning observations. 41 stars have [Fe/H] 2. Only one other star is known to have a comparable value. Seven stars are "CEMP-no" stars ([C/Fe] > 0.7, [Ba/Fe] = 1.0. These results demonstrate the ability to identify extremely metal-poor stars from SkyMapper photometry, pointing to increased sample sizes and a better characterization of the metal-poor tail of the halo metallicity distribution function in the future.

  14. A SIMULATION ASSESSMENT OF THE HEIGHT OF LIGHT SHELVES TO ENHANCE DAYLIGHTING QUALITY IN TROPICAL OFFICE BUILDINGS UNDER OVERCAST SKY CONDITIONS IN DHAKA, BANGLADESH

    E-Print Network [OSTI]

    Md. Ashikur; Rahman Joarder; Zebun Nasreen Ahmed; Andrew Price; Monjur Mourshed

    The objective of this paper is to highlight the effectiveness of light shelves in tropical office buildings to enhance interior daylighting quality. Daylight simulation was performed for custom light shelves for a typical office floor of Dhaka City in Bangladesh, to determine the best possible location under overcast sky conditions. Six alternative models of a 3m high study space were created with varying heights of light shelves. The 3D models were first generated in the Ecotect to study the distribution and uniformity of daylight in the interior space with splitflux method. These models were then exported to a physically-based backward raytracer, Radiance Synthetic Imaging software to generate realistic lighting levels for validating and crosschecking the Ecotect results. The results showed that for achieving light levels closest to specified standards, light shelves at a height of 2m above floor level perform better among the seven alternatives studied including the alternative where no light shelves are present. Finally, the decisions were verified with DAYSIM simulation program to ensure the compliance of the decisions with dynamic annual climate-based daylight performance metrics.

  15. all-sky lirg survey: Topics by E-print Network

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

    a comprehensive imaging and spectroscopic survey of over 200 low redshift Luminous Infrared Galaxies (LIRGs). The LIRGs are a complete subset of the IRAS Revised Bright Galaxy...

  16. Positron emission tomography and optical tissue imaging

    DOE Patents [OSTI]

    Falen, Steven W. (Carmichael, CA); Hoefer, Richard A. (Newport News, VA); Majewski, Stanislaw (Yorktown, VA); McKisson, John (Hampton, VA); Kross, Brian (Yorktown, VA); Proffitt, James (Newport News, VA); Stolin, Alexander (Newport News, VA); Weisenberger, Andrew G. (Yorktown, VA)

    2012-05-22T23:59:59.000Z

    A mobile compact imaging system that combines both PET imaging and optical imaging into a single system which can be located in the operating room (OR) and provides faster feedback to determine if a tumor has been fully resected and if there are adequate surgical margins. While final confirmation is obtained from the pathology lab, such a device can reduce the total time necessary for the procedure and the number of iterations required to achieve satisfactory resection of a tumor with good margins.

  17. The 8 O'Clock Arc: A Serendipitous Discovery of a Strongly Lensed Lyman Break Galaxy in the SDSS DR4 Imaging Data

    SciTech Connect (OSTI)

    Allam, Sahar S.; /Fermilab /Wyoming U.; Tucker, Douglas L.; Lin, Huan; Diehl, H.Thomas; Annis, James; Buckley-Geer, Elizabeth J.; /Fermilab; Frieman, Joshua A.; /Fermilab

    2006-11-01T23:59:59.000Z

    We report on the serendipitous discovery of the brightest Lyman Break Galaxy (LBG) currently known, a galaxy at z = 2.73 that is being strongly lensed by the z = 0.38 Luminous Red Galaxy (LRG) SDSS J002240.91+143110.4. The arc of this gravitational lens system, which we have dubbed the ''8 o'clock arc'' due to its time of discovery, was initially identified in the imaging data of the Sloan Digital Sky Survey Data Release 4 (SDSS DR4); followup observations on the Astrophysical Research Consortium (ARC) 3.5m telescope at Apache Point Observatory confirmed the lensing nature of this system and led to the identification of the arc's spectrum as that of an LBG. The arc has a spectrum and a redshift remarkably similar to those of the previous record-holder for brightest LBG (MS 1512-cB58, a.k.a ''cB58''), but, with an estimated total magnitude of (g,r,i) = (20.0,19.2,19.0) and surface brightness of ({mu}{sub g}, {mu}{sub r}, {mu}{sub i}) = (23.3, 22.5, 22.3) mag arcsec{sup -2}, the 8 o'clock arc is thrice as bright. The 8 o'clock arc, which consists of three lensed images of the LBG, is 162{sup o}(9.6'') long and has a length-to-width ratio of 6:1. A fourth image of the LBG--a counter-image--can also be identified in the ARC 3.5m g-band images. A simple lens model for the system assuming a singular isothermal ellipsoid potential yields an Einstein radius of {theta}{sub Ein} = 2.91'' {+-} 0.14'', a total mass for the lensing LRG (within the 10.6 {+-} 0.5 h{sup -1} kpc enclosed by the lensed images) of 1.04 x 10{sup 12} h{sup -1} M{sub {circle_dot}}, and a magnification factor for the LBG of 12.3{sub -3.6}{sup +15}. The LBG itself is intrinsically quite luminous ({approx} 6 x L{sub *}) and shows indications of massive recent star formation, perhaps as high as 160 h{sup -1} M{sub {circle_dot}} yr{sup -1}.

  18. A comparison of three total variation based texture extraction models q Wotao Yin a,*, Donald Goldfarb b

    E-Print Network [OSTI]

    Yin, Wotao

    Goldfarb b , Stanley Osher c a Rice University, Department of Computational and Applied Mathematics, 6100/image texture extraction based on total variation min- imization: the Meyer [27], Vese­Osher (VO) [35], and TV with these models on 1D oscillating signals and 2D images reveal their differences: the Meyer model tends to extract

  19. High Dynamic Range Imaging of Natural Scenes Feng Xiao, Jeffrey M. DiCarlo, Peter B. Catrysse and Brian A. Wandell

    E-Print Network [OSTI]

    Wandell, Brian A.

    of the sky seen in the window is on the order of 10,000 cd/m2; the luminance of a face within the room may scene. The scene luminance ranges span two to six orders of magnitude. Within any scene, both of luminance is an important issue in image acquisition, analysis, and display [1, 2]. Difficulties

  20. Total to withdraw from Qatar methanol - MTBE?

    SciTech Connect (OSTI)

    NONE

    1996-05-01T23:59:59.000Z

    Total is rumored to be withdrawing from the $700-million methanol and methyl tert-butyl ether (MTBE) Qatar Fuel Additives Co., (Qafac) project. The French company has a 12.5% stake in the project. Similar equity is held by three other foreign investors: Canada`s International Octane, Taiwan`s Chinese Petroleum Corp., and Lee Change Yung Chemical Industrial Corp. Total is said to want Qafac to concentrate on methanol only. The project involves plant unit sizes of 610,000 m.t./year of MTBE and 825,000 m.t./year of methanol. Total declines to comment.