The Experts below are selected from a list of 201 Experts worldwide ranked by ideXlab platform
Paul Berdahl - One of the best experts on this subject based on the ideXlab platform.
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measuring Solar reflectance part ii review of practical methods
Solar Energy, 2010Co-Authors: Ronnen Levinson, Hashem Akbari, Paul BerdahlAbstract:Abstract A companion article explored how Solar reflectance varies with surface orientation and Solar Position, and found that clear sky air mass 1 global horizontal (AM1GH) Solar reflectance is a preferred quantity for estimating Solar heat gain. In this study we show that AM1GH Solar reflectance Rg,0 can be accurately measured with a pyranometer, a Solar spectrophotometer, or an updated edition of the Solar Spectrum Reflectometer (version 6). Of primary concern are errors that result from variations in the spectral and angular distributions of incident sunlight. Neglecting shadow, background and instrument errors, the conventional pyranometer technique can measure Rg,0 to within 0.01 for surface slopes up to 5:12 [23°], and to within 0.02 for surface slopes up to 12:12 [45°]. An alternative pyranometer method minimizes shadow errors and can be used to measure Rg,0 of a surface as small as 1 m in diameter. The accuracy with which it can measure Rg,0 is otherwise comparable to that of the conventional pyranometer technique. A Solar spectrophotometer can be used to determine R g,0 ∗ , a Solar reflectance computed by averaging Solar spectral reflectance weighted with AM1GH Solar spectral irradiance. Neglecting instrument errors, R g,0 ∗ matches Rg,0 to within 0.006. The air mass 1.5 Solar reflectance measured with version 5 of the Solar Spectrum Reflectometer can differ from R g,0 ∗ by as much as 0.08, but the AM1GH output of version 6 of this instrument matches R g,0 ∗ to within about 0.01.
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measuring Solar reflectance part i defining a metric that accurately predicts Solar heat gain
Solar Energy, 2010Co-Authors: Ronnen Levinson, Hashem Akbari, Paul BerdahlAbstract:Abstract Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, Solar Position and atmospheric conditions. A widely used Solar reflectance metric based on the ASTM Standard E891 beam-normal Solar spectral irradiance underestimates the Solar heat gain of a spectrally selective “cool colored” surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland US latitudes, this metric RE891BN can underestimate the annual peak Solar heat gain of a typical roof or pavement (slope ⩽ 5:12 [23°]) by as much as 89 W m−2, and underestimate its peak surface temperature by up to 5 K. Using RE891BN to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool roof net energy savings by as much as 23%. We define clear sky air mass one global horizontal (“AM1GH”) Solar reflectance Rg,0, a simple and easily measured property that more accurately predicts Solar heat gain. Rg,0 predicts the annual peak Solar heat gain of a roof or pavement to within 2 W m−2, and overestimates N by no more than 3%. Rg,0 is well suited to rating the Solar reflectances of roofs, pavements and walls. We show in Part II that Rg,0 can be easily and accurately measured with a pyranometer, a Solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer.
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measuring Solar reflectance part i defining a metric that accurately predicts Solar heat gain
Solar Energy, 2010Co-Authors: Ronnen Levinson, Hashem Akbari, Paul BerdahlAbstract:Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, Solar Position and atmospheric conditions. A widely used Solar reflectance metric based on the ASTM Standard E891 beam-normal Solar spectral irradiance underestimates the Solar heat gain of a spectrally selective ''cool colored'' surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland US latitudes, this metric R{sub E891BN} can underestimate the annual peak Solar heat gain of a typical roof or pavement (slope {<=} 5:12 [23 ]) by as much as 89 W m{sup -2}, and underestimate its peak surface temperature by up to 5 K. Using R{sub E891BN} to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool roof net energy savings by as much as 23%. We define clear sky air mass one global horizontal (''AM1GH'') Solar reflectance R{sub g,0}, a simple and easily measured property that more accurately predicts Solar heat gain. R{sub g,0} predicts the annual peak Solar heat gain of a roof or pavement to within 2 W m{sup -2}, and overestimates N by no more thanmore » 3%. R{sub g,0} is well suited to rating the Solar reflectances of roofs, pavements and walls. We show in Part II that R{sub g,0} can be easily and accurately measured with a pyranometer, a Solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer. (author)« less
Ronnen Levinson - One of the best experts on this subject based on the ideXlab platform.
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measuring Solar reflectance part ii review of practical methods
Solar Energy, 2010Co-Authors: Ronnen Levinson, Hashem Akbari, Paul BerdahlAbstract:Abstract A companion article explored how Solar reflectance varies with surface orientation and Solar Position, and found that clear sky air mass 1 global horizontal (AM1GH) Solar reflectance is a preferred quantity for estimating Solar heat gain. In this study we show that AM1GH Solar reflectance Rg,0 can be accurately measured with a pyranometer, a Solar spectrophotometer, or an updated edition of the Solar Spectrum Reflectometer (version 6). Of primary concern are errors that result from variations in the spectral and angular distributions of incident sunlight. Neglecting shadow, background and instrument errors, the conventional pyranometer technique can measure Rg,0 to within 0.01 for surface slopes up to 5:12 [23°], and to within 0.02 for surface slopes up to 12:12 [45°]. An alternative pyranometer method minimizes shadow errors and can be used to measure Rg,0 of a surface as small as 1 m in diameter. The accuracy with which it can measure Rg,0 is otherwise comparable to that of the conventional pyranometer technique. A Solar spectrophotometer can be used to determine R g,0 ∗ , a Solar reflectance computed by averaging Solar spectral reflectance weighted with AM1GH Solar spectral irradiance. Neglecting instrument errors, R g,0 ∗ matches Rg,0 to within 0.006. The air mass 1.5 Solar reflectance measured with version 5 of the Solar Spectrum Reflectometer can differ from R g,0 ∗ by as much as 0.08, but the AM1GH output of version 6 of this instrument matches R g,0 ∗ to within about 0.01.
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measuring Solar reflectance part i defining a metric that accurately predicts Solar heat gain
Solar Energy, 2010Co-Authors: Ronnen Levinson, Hashem Akbari, Paul BerdahlAbstract:Abstract Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, Solar Position and atmospheric conditions. A widely used Solar reflectance metric based on the ASTM Standard E891 beam-normal Solar spectral irradiance underestimates the Solar heat gain of a spectrally selective “cool colored” surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland US latitudes, this metric RE891BN can underestimate the annual peak Solar heat gain of a typical roof or pavement (slope ⩽ 5:12 [23°]) by as much as 89 W m−2, and underestimate its peak surface temperature by up to 5 K. Using RE891BN to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool roof net energy savings by as much as 23%. We define clear sky air mass one global horizontal (“AM1GH”) Solar reflectance Rg,0, a simple and easily measured property that more accurately predicts Solar heat gain. Rg,0 predicts the annual peak Solar heat gain of a roof or pavement to within 2 W m−2, and overestimates N by no more than 3%. Rg,0 is well suited to rating the Solar reflectances of roofs, pavements and walls. We show in Part II that Rg,0 can be easily and accurately measured with a pyranometer, a Solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer.
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measuring Solar reflectance part i defining a metric that accurately predicts Solar heat gain
Solar Energy, 2010Co-Authors: Ronnen Levinson, Hashem Akbari, Paul BerdahlAbstract:Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, Solar Position and atmospheric conditions. A widely used Solar reflectance metric based on the ASTM Standard E891 beam-normal Solar spectral irradiance underestimates the Solar heat gain of a spectrally selective ''cool colored'' surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland US latitudes, this metric R{sub E891BN} can underestimate the annual peak Solar heat gain of a typical roof or pavement (slope {<=} 5:12 [23 ]) by as much as 89 W m{sup -2}, and underestimate its peak surface temperature by up to 5 K. Using R{sub E891BN} to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool roof net energy savings by as much as 23%. We define clear sky air mass one global horizontal (''AM1GH'') Solar reflectance R{sub g,0}, a simple and easily measured property that more accurately predicts Solar heat gain. R{sub g,0} predicts the annual peak Solar heat gain of a roof or pavement to within 2 W m{sup -2}, and overestimates N by no more thanmore » 3%. R{sub g,0} is well suited to rating the Solar reflectances of roofs, pavements and walls. We show in Part II that R{sub g,0} can be easily and accurately measured with a pyranometer, a Solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer. (author)« less
Hashem Akbari - One of the best experts on this subject based on the ideXlab platform.
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measuring Solar reflectance part ii review of practical methods
Solar Energy, 2010Co-Authors: Ronnen Levinson, Hashem Akbari, Paul BerdahlAbstract:Abstract A companion article explored how Solar reflectance varies with surface orientation and Solar Position, and found that clear sky air mass 1 global horizontal (AM1GH) Solar reflectance is a preferred quantity for estimating Solar heat gain. In this study we show that AM1GH Solar reflectance Rg,0 can be accurately measured with a pyranometer, a Solar spectrophotometer, or an updated edition of the Solar Spectrum Reflectometer (version 6). Of primary concern are errors that result from variations in the spectral and angular distributions of incident sunlight. Neglecting shadow, background and instrument errors, the conventional pyranometer technique can measure Rg,0 to within 0.01 for surface slopes up to 5:12 [23°], and to within 0.02 for surface slopes up to 12:12 [45°]. An alternative pyranometer method minimizes shadow errors and can be used to measure Rg,0 of a surface as small as 1 m in diameter. The accuracy with which it can measure Rg,0 is otherwise comparable to that of the conventional pyranometer technique. A Solar spectrophotometer can be used to determine R g,0 ∗ , a Solar reflectance computed by averaging Solar spectral reflectance weighted with AM1GH Solar spectral irradiance. Neglecting instrument errors, R g,0 ∗ matches Rg,0 to within 0.006. The air mass 1.5 Solar reflectance measured with version 5 of the Solar Spectrum Reflectometer can differ from R g,0 ∗ by as much as 0.08, but the AM1GH output of version 6 of this instrument matches R g,0 ∗ to within about 0.01.
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measuring Solar reflectance part i defining a metric that accurately predicts Solar heat gain
Solar Energy, 2010Co-Authors: Ronnen Levinson, Hashem Akbari, Paul BerdahlAbstract:Abstract Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, Solar Position and atmospheric conditions. A widely used Solar reflectance metric based on the ASTM Standard E891 beam-normal Solar spectral irradiance underestimates the Solar heat gain of a spectrally selective “cool colored” surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland US latitudes, this metric RE891BN can underestimate the annual peak Solar heat gain of a typical roof or pavement (slope ⩽ 5:12 [23°]) by as much as 89 W m−2, and underestimate its peak surface temperature by up to 5 K. Using RE891BN to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool roof net energy savings by as much as 23%. We define clear sky air mass one global horizontal (“AM1GH”) Solar reflectance Rg,0, a simple and easily measured property that more accurately predicts Solar heat gain. Rg,0 predicts the annual peak Solar heat gain of a roof or pavement to within 2 W m−2, and overestimates N by no more than 3%. Rg,0 is well suited to rating the Solar reflectances of roofs, pavements and walls. We show in Part II that Rg,0 can be easily and accurately measured with a pyranometer, a Solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer.
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measuring Solar reflectance part i defining a metric that accurately predicts Solar heat gain
Solar Energy, 2010Co-Authors: Ronnen Levinson, Hashem Akbari, Paul BerdahlAbstract:Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, Solar Position and atmospheric conditions. A widely used Solar reflectance metric based on the ASTM Standard E891 beam-normal Solar spectral irradiance underestimates the Solar heat gain of a spectrally selective ''cool colored'' surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland US latitudes, this metric R{sub E891BN} can underestimate the annual peak Solar heat gain of a typical roof or pavement (slope {<=} 5:12 [23 ]) by as much as 89 W m{sup -2}, and underestimate its peak surface temperature by up to 5 K. Using R{sub E891BN} to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool roof net energy savings by as much as 23%. We define clear sky air mass one global horizontal (''AM1GH'') Solar reflectance R{sub g,0}, a simple and easily measured property that more accurately predicts Solar heat gain. R{sub g,0} predicts the annual peak Solar heat gain of a roof or pavement to within 2 W m{sup -2}, and overestimates N by no more thanmore » 3%. R{sub g,0} is well suited to rating the Solar reflectances of roofs, pavements and walls. We show in Part II that R{sub g,0} can be easily and accurately measured with a pyranometer, a Solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer. (author)« less
Maria Selina Nitschai - One of the best experts on this subject based on the ideXlab platform.
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first gaia dynamical model of the milky way disc with six phase space coordinates a test for galaxy dynamics
Monthly Notices of the Royal Astronomical Society, 2020Co-Authors: Maria Selina Nitschai, Michele Cappellari, N NeumayerAbstract:We construct the first comprehensive dynamical model for the high-quality subset of stellar kinematics of the Milky Way disc, with full 6D phase-space coordinates, provided by the Gaia Data Release 2. We adopt an axisymmetric approximation and use an updated Jeans Anisotropic Modelling (JAM) method, which allows for a generic shape and radial orientation of the velocity ellipsoid, as indicated by the Gaia data, to fit the mean velocities and all three components of the intrinsic velocity dispersion tensor. The Milky Way is the first galaxy for which all intrinsic phase space coordinates are available, and the kinematics are superior to the best integral-field kinematics of external galaxies. This situation removes the long-standing dynamical degeneracies and makes this the first dynamical model highly over-constrained by the kinematics. For these reasons, our ability to fit the data provides a fundamental test for both galaxy dynamics and the mass distribution in the Milky Way disc. We tightly constrain the volume average total density logarithmic slope, in the radial range 3.6--12 kpc, to be $\alpha_{\rm tot}=-2.149\pm 0.055$ and find that the dark halo slope must be significantly steeper than $\alpha_{\rm DM}=-1$ (NFW). The dark halo shape is close to spherical and its density is $\rho_{\rm DM}(R_\odot)=0.0115\pm0.0020$ M$_\odot$ pc$^{-3}$ ($0.437\pm0.076$ GeV cm$^{-3}$), in agreement with previous estimates. The circular velocity at the Solar Position $v_{\rm circ}(R_{\odot}) = 236.5\pm 3.1$ km s$^{-1}$ (including systematics) and its gently declining radial trends are also consistent with recent determinations.
Afshin Andreas - One of the best experts on this subject based on the ideXlab platform.
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Solar Position algorithm for Solar radiation applications revised
Related Information: Supercedes November 2005 version, 2008Co-Authors: Ibrahim Reda, Afshin AndreasAbstract:This report is a step-by-step procedure for implementing an algorithm to calculate the Solar zenith and azimuth angles in the period from the year -2000 to 6000, with uncertainties of ?0.0003/. It is written in a step-by-step format to simplify otherwise complicated steps, with a focus on the sun instead of the planets and stars in general. The algorithm is written in such a way to accommodate Solar radiation applications.
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Solar Position algorithm for Solar radiation applications
Solar Energy, 2004Co-Authors: Ibrahim Reda, Afshin AndreasAbstract:Abstract There have been many published articles describing Solar Position algorithms for Solar radiation applications. The best uncertainty achieved in most of these articles is greater than ±0.01° in calculating the Solar zenith and azimuth angles. For some, the algorithm is valid for a limited number of years varying from 15 years to a hundred years. This report is a step by step procedure for implementing an algorithm to calculate the Solar zenith and azimuth angles in the period from the year −2000 to 6000, with uncertainties of ±0.0003°. The algorithm is described in a book written by Jean Meeus in 1998. This report is written in a step by step format to simplify the complicated steps described in the book, with a focus on the sun instead of the planets and stars in general. It also introduces some changes to accommodate for Solar radiation applications. The changes include changing the direction of measuring azimuth angles to be measured from north and eastward instead of being measured from south and eastward, and the direction of measuring the observer’s geographical longitude to be measured as positive eastward from Greenwich meridian instead of negative. This report also includes the calculation of incidence angle for a surface that is tilted to any horizontal and vertical angle, as described by Iqbals in 1983.