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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

A Consistent AVHRR Visible Calibration Record Based on Multiple Methods Applicable for the NOAA Degrading Orbits: Validation - Part 2

Consistent cross-sensor Advanced Very High Resolution Radiometer (AVHRR) calibration coefficients are determined using desert, polar ice, and deep convective cloud (DCC) invariant Earth targets. The greatest AVHRR calibration challenge is the slow orbit degradation of the host satellite, which precesses toward a terminator orbit. This issue is solved by characterizing the invariant targets with NOAA-16 AVHRR observed radiances that have been referenced to the Aqua Moderate Resolution Imaging Spectrometer (MODIS) calibration using simultaneous nadir overpass (SNO) observations. Another benefit of the NOAA-16 invariant target-modeled reflectance method is that, because of the similarities among the AVHRR spectral response functions, a smaller spectral band adjustment factor is required than when establishing calibrations relative to a non-AVHRR reference instrument. The sensor- and band-specific calibration uncertainties, with respect to the calibration reference, are, on average, 2 percent and 3 percent for channels 1 and 2, respectively. The uncertainties are smaller for sensors that are in afternoon orbits, have longer records, and spend less time in terminator conditions. The multiple invariant targets referenced to Aqua MODIS (MITRAM) AVHRR calibration coefficients are evaluated for individual target consistency, compared against Aqua MODIS/AVHRR SNOs, and selected published calibration gains. The MITRAM and SNO relative calibration biases mostly agree to within 1 percent for channels 1 and 2, respectively. The individual invariant target and MITRAM sensor relative calibration biases are mostly consistent to within 1 percent and 2 percent for channels 1 and 2, respectively. The differences between the MITRAM and other published calibrations are mostly attributed to the reference instrument calibration differences.

Doelling, David R.↗
DOE OSTI2024

Dynamic Wind Loading on CSP Collectors Caused by Turbulent Wind Fluctuations: Insights from a 2-Year Field Campaign

Concentrating Solar Power (CSP) is a promising solar technology for electricity generation with thermal energy storage and with the additional benefit of industrial heat production. Wind loading on CSP collector structures, such as parabolic troughs or heliostats, is one of the primary drivers of their structural design costs. In particular, dynamic wind loading is a major source of uncertainty in the collector design process, which heavily relies on wind tunnel testing. In the field, the turbulent nature of the incoming wind creates fluctuating loads (support structure loads and resulting mirror deflections) on the collectors, with impacts on fatigue lifetime and optical performance. As is well known, wind tunnel tests cannot entirely reproduce the complex turbulent wind conditions typically observed at full-scale plants. To shed light on this topic, NREL initiated a field campaign at the operational Nevada Solar One (NSO) powerplant that uses parabolic troughs as solar collectors. The aim of the project is a detailed characterization of prevailing wind and turbulence conditions and resulting operational loads on parabolic troughs. We use the published 2-year dataset of high-resolution combined wind and structural loads measurements [1] to characterize the dynamic structural wind response. For quantifying dynamic wind loading, we apply the concept of admittance functions, which are spectral transfer functions that couple the turbulent wind to resulting structural loads (aerodynamic admittance), and to the structural response (mechanical admittance). In practice, aerodynamic admittance describes which turbulent eddy sizes are effective in creating structural loads. The mechanical admittance describes in which frequency ranges these loads are reinforced or dampened by the structure. While these functions are an established concept in civil engineering, their recent application to a single full-scale heliostat [2] proved their broader applicability to CSP collectors. Here, we present a characterization of admittance functions for full-scale parabolic trough collectors and show how wind characteristics (mean wind speed and direction, turbulent kinetic energy, turbulent length scales), the sun-tracking trough angle, and row position alter the admittance functions. Further, we study to which extent the admittance functions are universal for a specific trough geometry and how our findings compare to reported heliostat results. References [1] https://data.openei.org/submissions/5938. [2] Blume, K., Roger, M., and Pitz-Paal, R. 2023b. "Simplified analytical model to describe wind loads and wind-induced tracking deviations of heliostats." Solar Energy, 256, 96-109. https://doi.org/10.1016/j.solener.2023.03.055.

admittance functions↗
NASA NTRS1995

An improved spectral calibration requirement for AVIRIS

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures spectra from 400 to 2500 nm through 224 contiguous spectral channels. These spectra are used to identify and determine the abundances of constituents of the earth's surface and atmosphere through the analysis of spectral molecular absorptions and scattering properties of materials. Spectral calibration of the AVIRIS is required to pursue these determinations, which are based on these fundamental spectral characteristics. The spectral calibration of AVIRIS consists of a description of the spectral response function for each of the 224 spectral channels. The spectral response function of AVIRIS channels was measured in the laboratory and shown to be Gaussian in shape. A subset of nine AVIRIS spectral channels is shown with channel centers at 10 nm intervals and channel shapes of Gaussian form with 10 nm full width and half maximum (FWHM). For AVIRIS the spectral calibration is described by the spectral center and FWHM of a Gaussian function for each channel. Uncertainty in the determination of the spectral center and FWHM for each channel are also reported. This paper presents results from an investigation of the sensitivity of AVIRIS-measured upwelling radiance to errors in spectral calibration. Based on this sensitivity analysis in conjunction with earlier work, an improved spectral calibration requirement for AVIRIS is proposed.

Green, Robert O.↗
NASA NTRS2018

Spectral Response and Effective Area Functions of the Hitomi Imaging Instruments

We describe the tools and the underlying methods and principles for generating the spectral response functions for the four imaging instruments that were flown on the Hitomi x-ray astronomy satellite [Soft X-ray Spectrometer, or SXS; Soft X-ray Imager, or SXI, and two Hard X-ray Imagers, or HXI]. In essence, the spectral response function is a temporally and spatially averaged effective area and line-spread-function. For model-fittingx-ray spectra from an instrument, the spectral response function encapsulates the end-to-end physics of the entire system from telescope to detector, and also includes satellite attitude drift, exposure corrections, and in the case of the HXIs, drift in the telescope/detector alignment system. Accuracy in the construction of the spectral response functions is, therefore, critical to maximize the science return from the data.

Yaqoob, Tahir↗
NASA NTRS1978

Simplified model of statistically stationary spacecraft rotation and associated induced gravity environments

A stochastic model of spacecraft motion was developed based on the assumption that the net torque vector due to crew activity and rocket thruster firings is a statistically stationary Gaussian vector process. The process had zero ensemble mean value, and the components of the torque vector were mutually stochastically independent. The linearized rigid-body equations of motion were used to derive the autospectral density functions of the components of the spacecraft rotation vector. The cross-spectral density functions of the components of the rotation vector vanish for all frequencies so that the components of rotation were mutually stochastically independent. The autospectral and cross-spectral density functions of the induced gravity environment imparted to scientific apparatus rigidly attached to the spacecraft were calculated from the rotation rate spectral density functions via linearized inertial frame to body-fixed principal axis frame transformation formulae. The induced gravity process was a Gaussian one with zero mean value. Transformation formulae were used to rotate the principal axis body-fixed frame to which the rotation rate and induced gravity vector were referred to a body-fixed frame in which the components of the induced gravity vector were stochastically independent. Rice's theory of exceedances was used to calculate expected exceedance rates of the components of the rotation and induced gravity vector processes.

Fichtl, G. H.↗
NASA NTRS2021

Deconvolution of SNPP VIIRS Solar Diffuser Bidirectional Reflectance Distribution Function On-orbit Change Factor

The Earth-observing Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite regularly calibrates its reflective solar bands (RSBs), primarily through observing an onboard sunlit solar diffuser (SD). The on-orbit change of the value of the SD bidirectional reflectance distribution function (BRDF) is quantified by a numerical factor, called the H-factor, and is determined by the onboard SD stability monitor (SDSM). Because the spectral response function of an SDSM detector spreads in wavelength, the directly measured H-factor is the true H-factor convolved with the spectral response function. To find the true H-factor, we use the traditional direct method and an innovative iterative approach to separately deconvolve the measured H-factor. Our iterative approach relies on two properties of the SDSM detector spectral response function: the central peak width is narrow enough so that the H-factor does not change much over the peak width, and the dominance of the spectral response function’s integral with respect to the wavelength over the width. The iterative approach is more accurate, of a smaller noise impact, much more flexible in terms of interpolation and extrapolation of function values, and faster. We have used deconvolved H-factors to calibrate the NASA SNPP VIIRS RSB Collections 1 and 2 Level-1B products.

SNPP VIIRS↗
NASA NTRS1987

A model for fully developed turbulence

A model for stationary, fully developed turbulence is presented in which the turbulent spectral energy function is completely determined once the time scale for the energy fed into the eddy interaction is known. The form of the eddy correlation time scale determining the turbulent viscosity is suggested by the basic equation of the model itself, up to a dimensionless constant that is fixed by demanding that the coefficient of the spectrum in the Heisenberg-Kolmogoroff inertial range of wavenunmbers be the experimental value. The model makes quantitative predictions that are compared with data on turbulent convection; the k-epsilon and Smagorinsky relations; the spectral function, transfer term, and dissipation term; the skewness factor; the Kolmogoroff and Batchelor constants; and the inertial-conductive and inertial-convective ranges.

Canuto, V. M.↗
NASA NTRS1993

On the use of the noncentral chi-square density function for the distribution of helicopter spectral estimates

A probability density function for the variability of ensemble averaged spectral estimates from helicopter acoustic signals in Gaussian background noise was evaluated. Numerical methods for calculating the density function and for determining confidence limits were explored. Density functions were predicted for both synthesized and experimental data and compared with observed spectral estimate variability.

Garber, Donald P.↗
NASA NTRS2012

GX 3+1: The Stability of Spectral Index as a Function of Mass Accretion Rate

We present an analysis of the spectral and timing properties observed in X-rays from neutron star (NS) binary GX 3+1 (4U 1744-26) during long-term transitions between the faint and bright phases superimposed on short-term transitions between lower banana (LB) and upper banana (UB) branches in terms of its color-color diagram, We analyze all observations of this source obtained with the Rossi X-ray Timing Explorer and BeppoSAX satellites, We find that the X-ray broadband energy spectra during these spectral transitions can be adequately reproduced by a composition of a low-temperature blackbody component, a Comptonized component (COMPTB), and Gaussian component We argue that the electron temperature kTe of the Compton cloud monotonically increases from 2.3 keY to 4.5 keY, when GX 3+1 makes a transition from UB to LB. We also detect an evolution of noise components (a very low frequency noise and a high-frequency noise) during these LB-UB transitions. Using a disk seed photon normalization of COMPTB, which is proportional to the mass accretion rate, we find that the photon power-law index Gamma is almost constant (Gamma = 2.00 +/- 0.02) when mass accretion rate changes by factor four. In addition, we find that the emergent spectrum is dominated by the strong Comptonized component We interpret this quasi-stability of the index Gamma and a particular form of the spectrum in the framework of a model in which the energy release in the transition layer located between the accretion disk and NS surface dominates that in the disk. Moreover, this index stability effect now established for GX 3+ I was previously found in the atoll source 4U 1728-34 and suggested for a number of other low-mass X-ray NS binaries. This intrinsic behavior of NSs, in particular for atoll sources, is fundamentally different from that seen in black hole binary sources where the index monotonically increases during spectral transition from the low state to the high state and then finally saturates at high values of mass accretion rate.

Seifana, Elena↗
NASA NTRS1988

Variation of surface water spectral response as a function of in situ sampling technique

Tests were carried out to determine the spectral variation contributed by a particular sampling technique. A portable radiometer was used to measure the surface water spectral response. Variation due to the reflectance of objects near the radiometer (i.e., the boat side) during data acquisition was studied. Consideration was also given to the variation due to the temporal nature of the phenomena (i.e., wave activity).

Davis, Bruce A.↗
NASA NTRS1982

IUE data reduction - The parameterization of the motion of the IUE reseau grids and spectral formats as a function of time and temperature

Improvements are made on IUE data reduction using corrected reseau positions and dispersion constants for temperature variations and secular effects. Models describing the motion of the high dispersion spectral format as a function of THDA alone reduce the scatter in the predicted position of a given wavelength, and scatter is further reduced when a linear dependence on time is also allowed. A correction technique is presented for early data which reduces errors in wavelength assignments from over 30 km/s to less than 3 km/s in high dispersion. The reseau temperature correction helps locate the minimum background signal, centered between the echelle orders. The residual uncertainty of 2 km/s for SWP and 2.7 km/s for LWR makes the wavelength accuracy of time and temperature corrected IUE spectra comparable to that of temperature corrected data from the Copernicus satellite.

Thompson, R. W.↗
DOE OSTI2021

SDSS-IV MaNGA: Modeling the Spectral Line-spread Function to Subpercent Accuracy

The Sloan Digital Sky Survey IV Mapping Nearby Galaxies at APO (MaNGA) program has been operating from 2014 to 2020, and has now observed a sample of 9269 galaxies in the low redshift universe (z ∼ 0.05) with integral-field spectroscopy. With rest-optical (λλ0.36–1.0 μm) spectral resolution R ∼ 2000 the instrumental spectral line-spread function (LSF) typically has 1σ width of about 70 km s{sup −1}, which poses a challenge for the study of the typically 20–30 km s{sup −1} velocity dispersion of the ionized gas in present-day disk galaxies. In this contribution, we present a major revision of the MaNGA data pipeline architecture, focusing particularly on a variety of factors impacting the effective LSF (e.g., under-sampling, spectral rectification, and data cube construction). Through comparison with external assessments of the MaNGA data provided by substantially higher-resolution R ∼ 10,000 instruments, we demonstrate that the revised MPL-10 pipeline measures the instrumental LSF sufficiently accurately (≤0.6% systematic, 2% random around the wavelength of Hα) that it enables reliable measurements of astrophysical velocity dispersions σ {sub Hα} ∼ 20 km s{sup −1} for spaxels with emission lines detected at signal-to-noise ratio > 50. Velocity dispersions derived from [O II], Hβ, [O III], [N II], and [S II] are consistent with those derived from Hα to within about 2% at σ {sub Hα} > 30 km s{sup −1}. Although the impact of these changes to the estimated LSF will be minimal at velocity dispersions greater than about 100 km s{sup −1}, scientific results from previous data releases that are based on dispersions far below the instrumental resolution should be reevaluated.

47 OTHER INSTRUMENTATION↗
NASA NTRS2015

Measured Polarized Spectral Responsivity of JPSS J1 VIIRS Using the NIST T-SIRCUS

Recent pre-launch measurements performed on the Joint Polar Satellite System (JPSS) J1 Visible Infrared Imaging Radiometer Suite (VIIRS) using the National Institute of Standards and Technology (NIST) Traveling Spectral Irradiance and Radiance Responsivity Calibrations Using Uniform Sources (T-SIRCUS) monochromatic source have provided wavelength dependent polarization sensitivity for select spectral bands and viewing conditions. Measurements were made at a number of input linear polarization states (twelve in total) and initially at thirteen wavelengths across the bandpass (later expanded to seventeen for some cases). Using the source radiance information collected by an external monitor, a spectral responsivity function was constructed for each input linear polarization state. Additionally, an unpolarized spectral responsivity function was derived from these polarized measurements. An investigation of how the centroid, bandwidth, and detector responsivity vary with polarization state was weighted by two model input spectra to simulate both ground measurements as well as expected on-orbit conditions. These measurements will enhance our understanding of VIIRS polarization sensitivity, improve the design for future flight models, and provide valuable data to enhance product quality in the post-launch phase.

JPSS↗