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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

New developments of a knowledge based system (VEG) for inferring vegetation characteristics

An extraction technique for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input has been developed. A knowledge-based system (VEG) accepts spectral data of an unknown target as input, determines the best strategy for inferring the desired vegetation characteristic, applies the strategy to the target data, and provides a rigorous estimate of the accuracy of the inference. Progress in developing the system is presented. VEG combines methods from remote sensing and artificial intelligence, and integrates input spectral measurements with diverse knowledge bases. VEG has been developed to (1) infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; (2) test and develop new extraction techniques on an internal spectral database; (3) browse, plot, or analyze directional reflectance data in the system's spectral database; (4) discriminate between user-defined vegetation classes using spectral and directional reflectance relationships; and (5) infer unknown view angles from known view angles (known as view angle extension).

Kimes, D. S.↗
NASA NTRS1994

Application of AI techniques to infer vegetation characteristics from directional reflectance(s)

Traditionally, the remote sensing community has relied totally on spectral knowledge to extract vegetation characteristics. However, there are other knowledge bases (KB's) that can be used to significantly improve the accuracy and robustness of inference techniques. Using AI (artificial intelligence) techniques a KB system (VEG) was developed that integrates input spectral measurements with diverse KB's. These KB's consist of data sets of directional reflectance measurements, knowledge from literature, and knowledge from experts which are combined into an intelligent and efficient system for making vegetation inferences. VEG accepts spectral data of an unknown target as input, determines the best techniques for inferring the desired vegetation characteristic(s), applies the techniques to the target data, and provides a rigorous estimate of the accuracy of the inference. VEG was developed to: infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; infer percent ground cover from any combination of nadir and/or off-nadir view angles; infer unknown view angle(s) from known view angle(s) (known as view angle extension); and discriminate between user defined vegetation classes using spectral and directional reflectance relationships developed from an automated learning algorithm. The errors for these techniques were generally very good ranging between 2 to 15% (proportional root mean square). The system is designed to aid scientists in developing, testing, and applying new inference techniques using directional reflectance data.

Kimes, D. S.↗
NASA NTRS2016

Degree of Ice Particle Surface Roughness Inferred from Polarimetric Observations

The degree of surface roughness of ice particles within thick, cold ice clouds is inferred from multidirectional, multi-spectral satellite polarimetric observations over oceans, assuming a column-aggregate particle habit. An improved roughness inference scheme is employed that provides a more noise-resilient roughness estimate than the conventional best-fit approach. The improvements include the introduction of a quantitative roughness parameter based on empirical orthogonal function analysis and proper treatment of polarization due to atmospheric scattering above clouds. A global 1-month data sample supports the use of a severely roughened ice habit to simulate the polarized reflectivity associated with ice clouds over ocean. The density distribution of the roughness parameter inferred from the global 1- month data sample and further analyses of a few case studies demonstrate the significant variability of ice cloud single-scattering properties. However, the present theoretical results do not agree with observations in the tropics. In the extra-tropics, the roughness parameter is inferred but 74% of the sample is out of the expected parameter range. Potential improvements are discussed to enhance the depiction of the natural variability on a global scale.

surface↗
DOE OSTI2020

The Terahertz Dynamics of an Aqueous Nanoparticle Suspension: An Inelastic X-ray Scattering Study

We used the high-resolution Inelastic X-ray Scattering beamline of the Advanced Photon Source at Argonne National Laboratory to measure the terahertz spectrum of pure water and a dilute aqueous suspension of 15 nm diameter spherical Au nanoparticles (Au-NPs). We observe that, despite their sparse volume concentration of about 0.5%, the immersed NPs strongly influence the collective molecular dynamics of the hosting liquid. We investigate this effect through a Bayesian inference analysis of the spectral lineshape, which elucidates how terahertz transport properties of water change upon Au-NP immersion. In particular, we observe a nearly complete disappearance of the longitudinal acoustic mode and a mildly decreased ability to support shear wave propagation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2022

Optimal Estimation Framework for Ocean Color Atmospheric Correction and Pixel-level Uncertainty Quantification

Ocean color remote sensing requires compensation for atmospheric scattering and absorption (aerosol, Rayleigh, and trace gases), referred to as atmospheric correction (AC). AC allows inference of parameters such as spectrally resolved remote sensing reflectance ( R rs )(λ) ; sr 1 ) at the ocean surface from the top-of-atmosphere reflectance. Often, the uncertainty of this process is not fully explored. Bayesian inference techniques provide a simultaneous AC and uncertainty assessment via a full posterior distribution of the relevant variables, given the prior distribution of those variables and the radiative transfer (RT) likelihood function. Given uncertainties in the algorithm inputs, the Bayesian framework enables better constraints on the AC process by using the complete spectral information compared to traditional approaches that use only a subset of bands for AC. This paper investigates a Bayesian inference research method (Optimal Estimation, OE) for ocean color AC by simultaneously retrieving atmospheric and ocean properties using all visible and near-infrared spectral bands. The OE algorithm analytically approximates the posterior distribution of parameters based on normality assumptions and provides a potentially viable operational algorithm with a reduced computational expense. We developed a Neural Network (NN) RT forward model look-up-table-based emulator to increase algorithm efficiency further and thus speed up the likelihood computations. We then applied the OE algorithm to synthetic data and observations from the MODerate resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua spacecraft. We compared the R rs )(λ) retrieval and its uncertainty estimates from the OE method with in-situ validation data from the SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and Aerosol Robotic Network Ocean Color (AERONET-OC) datasets. The OE algorithm improved R rs )(λ) estimates relative to the NASA standard operational algorithm by improving all statistical metrics at 443, 555, and 667 nm. Unphysical negative R rs )(λ) , which often appear in complex water conditions, was reduced by a factor of 3. The OE-derived pixel-level R rs )(λ) uncertainty estimates were also assessed relative to in-situ data and were shown to have skill.

Atmospheric correction↗
DOE OSTI2020

Machine-Learning X-Ray Absorption Spectra to Quantitative Accuracy

Simulations of excited state properties, such as spectral functions, are often computationally expensive and therefore not suitable for high-throughput modeling. As a proof of principle, here we demonstrate that graph-based neural networks can be used to predict the x-ray absorption near-edge structure spectra of molecules to quantitative accuracy. Specifically, the predicted spectra reproduce nearly all prominent peaks, with 90% of the predicted peak locations within 1 eV of the ground truth. Besides its own utility in spectral analysis and structure inference, our method can be combined with structure search algorithms to enable high-throughput spectrum sampling of the vast material configuration space, which opens up new pathways to material design and discovery.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1974

The chemical composition and distribution of interstellar grains

The chemical composition of interstellar grains is derived here on the basis of (1) the cosmic abundance of the elements; (2) the wavelength dependence of extinction and polarization; (3) the average total extinction; (4) the ratio of polarization to extinction; (5) the predominantly dielectric character of grains in the visible spectral region; and (6) infrared spectral characteristics of grains. Inferences of the core-mantle model with respect to spatial distribution are consistent with the proposition that growth of the mantles occurs in the galactic shock region predicted by the density-wave theory. Estimates of the total visual extinction toward the galactic center and the consequent estimates of the total amount of far infrared radiation are shown to depend critically on the grain model. Variations of the ratio of far ultraviolet to visual extinction are correlated with the conditions for growth of mantles on the bare small particles which are generally prevented from accreting mantles primarily because of their extreme temperature fluctuations produced by the ultraviolet photons in the radiation field.

Greenberg, J. M.↗
NASA NTRS1985

The inference of vector magnetic fields from polarization measurements with limited spectral resolution

A method is presented for recovery of the vector magnetic field and thermodynamic parameters from polarization measurement of photospheric line profiles measured with filtergraphs. The method includes magneto-optic effects and may be utilized on data sampled at arbitrary wavelengths within the line profile. The accuracy of this method is explored through inversion of synthetic Stokes profiles subjected to varying levels of random noise, instrumental wave-length resolution, and line profile sampling. The level of error introduced by the systematic effect of profile sampling over a finite fraction of the 5 minute oscillation cycle is also investigated. The results presented here are intended to guide instrumental design and observational procedure.

Lites, B. W.↗
NASA NTRS1991

Spectroscopy of an unusual emission line M star

Moderate-resolution spectroscopy of an unusual late-type faint emission-line star, PC 0025 + 0047, is reported. A very strong (greater than 250 A equivalent width) an H-alpha emission line was detected by the present automated line search algorithm. The spectrum was found to have two unresolved emission lines (H-alpha and H-beta) near zero velocity, superposed on the absorption spectrum of a very red M dwarf which has strong K I, and relatively weak bands of TiO. From the weakness of the subordinate lines of Na I (8192 A) and other spectral features, it is inferred that it is definitely a cooler, and probably fainter, analog of LHS 2924. The strength of the emission lines indicates that PC 0025 + 0447 is very young and may be a fading predecessor brown drawf at an estimated M(bol) approaching 14m at a distance of about 60 pc.

Schneider, Donald P.↗
NASA NTRS1991

What are the gigahertz peaked-spectrum radio sources?

The astrophysical implications of recent radio and optical observations of the powerful compact gigahertz peaked-spectrum (GPS) radio sources are discussed. Some tentative conclusions are presented and a scenario based on the existing data is suggested. It is argued that the spectrum is due to synchrotron self-absorption, which is assumed as the basis for the present inferences from the radio spectral shape. The finding that some GPS sources have a very narrow spectral shape is consistent with the hypothesis that there is a narrow range of size scales which dominate the radio luminosity. The highly inverted LF radio spectrum is consistent with the hypothesis that the radio source is tightly confined. The conclusion that the radio polarization of these sources is systematically low is consistent either with a very tangled magnetic field or very large Faraday rotation measures. It is suggested that GPS radio sources are formed when the radio plasma is confined on the scale of the narrow-line region by an unusually dense and clumpy ISM. The existing optical spectroscopic results are also consistent with the existence of a dense and dusty nuclear ISM.

O'Dea, C. P.↗
NASA NTRS2001

Exploration of Solar Wind Acceleration Region Using Interplanetary Scintillation of Water Vapor Maser Source and Quasars

Single-station observations of interplanetary scintillation UPS) at three microwave frequencies 2, 8, and 22GHz, were carried out between 1989 and 1998 using a large (34-micro farad) radio telescope at the Kashima Space Research Center of the Communications Research Laboratory. The aim of these observations was to explore the near-sun solar wind, which is the key region for the study of the solar wind acceleration mechanism. Strong quasars, 3C279 and 3C273B, were used for the Kashima IPS observations at 2 and 8GHz, and a water-vapor maser source, IRC20431, was used for the IPS observations at 22GHz. Solar wind speeds derived from Kashima IPS data suggest that the solar wind acceleration takes place at radial distances between 10 and 30 solar radii (Rs) from the sun. The properties of the turbulence spectrum (e.g. anisotropy, spectral index, inner scale) inferred from the Kashima data were found to change systematically in the solar wind acceleration region. While the solar wind in the maximum phase appears to be dominated by the slow wind, fast and rarefied winds associated with the coronal holes were found to develop significantly at high latitudes as the solar activity declined. Nevertheless, the Kashima data suggests that the location of the acceleration region is stable throughout the solar cycle.

Tokumaru, Munetoshi↗
NASA NTRS2001

Exploration of Solar Wind Acceleration Region Using Interplanetary Scintillation of Water Vapor Maser Source and Quasars

Single-station observations of interplanetary scintillation (IPS) at three microwave frequencies; 2 GHz, 8 GHz and 22 GHz have been carried out between 1989 and 1998 using a large (34 m farad) radio telescope at the Kashima Space Research Center of the Communications Research Laboratory. The aim of these observations is to explore the near-sun solar wind, which is the key region for the study of the solar wind acceleration mechanism. Strong quasars; 3C279 and 3C273B were used for Kashima IPS observations at 2 GHz and 8 GHz, and a water vapor maser source, IRC20431 was used for the IPS observations at 22 GHz. Solar wind velocities derived from Kashima IPS data suggest that the solar wind acceleration takes place at radial distances between 10 and 30 solar radii (R(sub s)) from the sun. Properties of the turbulence spectrum (e.g. anisotropy, spectral index, inner scale) inferred from Kashima data are found to change systematically in the solar wind acceleration region. While the solar wind in the maximum phase appears to be dominated by the slow wind, fast and rarefied winds associated with coronal holes are found to develop significantly at high latitudes as the solar activity declines. Nevertheless, Kashima data suggests that the location of the acceleration region is stable throughout the solar cycle.

Tokumaru, Munetoshi↗
NASA NTRS2020

A Composite Analysis of Snowfall Modes from Four Winter Seasons in Marquette, Michigan

Presented are four winter seasons of data from an enhanced precipitation instrument suite based at the National Weather Service (NWS) Office in Marquette (MQT), Michigan (250–500 cm of annual snow accumulation). In 2014 the site was augmented with a Micro Rain Radar (MRR) and a Precipitation Imaging Package (PIP). MRR observations are utilized to partition large-scale synoptically driven (deep)and surface-forced (shallow) snow events. Coincident PIP and NWS MQT meteorological surface observations illustrate different characteristics with respect to snow event category. Shallow snow events are often extremely shallow, with MRR-indicated precipitation heights of less than 1500 m above ground level. Large vertical reflectivity gradients indicate efficient particle growth, and increased boundary layer turbulence inferred from observations of spectral width implies increased aggregation in shallow snow events. Shallow snow events occur 2 times as often as deep events; however, both categories contribute approximately equally to estimated annual accumulation. PIP measurements reveal distinct regime-dependent snow microphysical differences, with shallow snow events having broader particle size distributions and comparatively fewer small particles and deep snow events having narrower particle size distributions and comparatively more small particles. In addition, coincident surface meteorological measurements indicate that most shallow snow events are associated with surface winds originating from the northwest (over Lake Superior), cold temperatures, and relatively high surface pressures, which are characteristics that are consistent with cold-air outbreaks. Deep snow events have meteorologically distinct conditions that are accordant with midlatitude cyclones and frontal structures, with mostly southwest surface winds, warmer temperatures approaching freezing, and lower surface pressures.

Claire Pettersen↗
NASA NTRS1997

From Top to Bottom - the Multiwavelength Campaign of V824 Ara (HD 155555)

A great deal of progress has been made in recent years in decomposing the 2-D structure in the atmospheres of late-type stars. Doppler images of many photospheres single stars, T Tauri stars, Algols, RS CV(sub n) binaries to name a few - are regularly published (Strassmeier 1996; Richards and Albright 1996; Rice and Strassmeier 1996; Kuerster et al. 1994). Ultraviolet spectral images of chromospheres appear in the literature (e.g., Walter et al. 1987; Neff et al. 1989) but are less common owing to the difficult nature of obtaining complete phase coverage. Zeeman doppler images of magnetic fields are now feasible (e.g., Donati et al. 1992). Performing Doppler imaging of the same targets over many seasons has also been accomplished (e.g, Vogt et al. 1997). Even when a true image reconstruction is not possible due to poor spectral resolution, we can still infer a great deal about spatial structure if enough phases are observed. However, it is increasingly apparent that to make sense of recent results, many different spectral features spanning a range of formation temperature and density must be observed simultaneously for a coherent picture to emerge. Here we report on one such campaign. In 1996, we observed the southern hemisphere RS CV(sub n) binary V824 Ara (P=1(sup d).68, G5IV+K0V-IV-IV) over one complete stellar rotation with the Hubble Space Telescope and EUVE. In conjunction, radio and optical photometry and spectroscopy were obtained from the ground. Unique to this campaign is the complete phase coverage of a number of activity proxy indicators that cover source temperatures ranging from the photosphere to the corona.

Dempsey, Robert↗
DOE OSTI2025

Fermi-LAT Captures a Late-2024 Gamma-Ray Outburst near Two Newly Identified Gamma-Ray-emitting Galactic Supernova Remnants, without Evidence of Physical Association

We report the gamma-ray study of two neighboring in the sky Galactic supernova remnants (SNRs), namely, 3C 434.1 (or G094.0+01.0) and G093.7–00.2. In the vicinity of the two SNRs, a late-2024 gamma-ray outburst—not physically connected to the SNRs—was detected with the Fermi Large Area Telescope (LAT). Employing 16.5 yr of Fermi-LAT data, we report the first firm detection of the gamma-ray counterpart of 3C 434.1 at a 7.2σ significance and a likely detection of an enhanced gamma-ray emission signal at a 4.5σ level from G093.7–00.2. The late-2024 gamma-ray outburst is detected at a ∼12σ significance level over a duration of 3 days. For all three objects, a comprehensive morphological and spectral analysis of the corresponding gamma-ray data was conducted. The prevalent scenario for the nature of the gamma-ray emission of both SNRs is attributed to their surrounding environment. Both are likely interacting with nearby dense material, resulting in hadronically induced gamma-ray emission. We deduce that the outburst source is most likely a blazar in flare, linked to the compact, flat-spectrum radio source TXS 2138+527 (also known as NVSS J213953+530016). Further, the spectral analysis of the gamma-ray source conducted within the 100 MeV–800 GeV energy range using the complete LAT data sets, which yielded a soft averaged spectral shape, supports the hypothesis of a flat spectrum radio quasar (FSRQ) origin for the source; with a most likely leptonically induced scenario for the observed gamma-ray outburst as inferred from the obtained hard spectral shape when utilizing short time intervals focusing on the outburst.

Michailidis, Miltiadis [Stanford Univ., CA (United↗
NASA NTRS1987

Solar active region physical parameters inferred from a thermal cyclotron line and soft X-ray spectral lines

Simultaneous high-resolution observations of coronal loops were made at the 20-cm wavelength with the VLA and at soft X-ray wavelengths with the SMM FCS. The images obtained at both wavelengths have nearly identical sizes and ellipsoidal shapes, with the emission stretching between and across regions of opposite magnetic polarity in the underlying photosphere. The results indicate that the radiation at 20 cm and soft X-ray wavelengths originates from the same region, and that 20 cm maps can image X-ray coronal loops. The X-ray spectral lines were used to obtain values of electron temperature, T(e), of about 2.6 x 10 to the 6th K and electron density, N(e), of about 3.1 x 10 to the 9th/cu cm. These parameters were used to show that the layers emitting 20-cm radiation can be optically thick to either thermal bremsstrahlung or thermal gyroresonance radiation, depending upon unknown but plausible values of loop thickness, magnetic scale height, and magnetic field strength.

Lang, Kenneth R.↗
NASA NTRS1991

Infrared (2.08-14 micron) spectra of powered stony meteorites

Infrared biconical reflectance spectra of 60 powdered meteorite samples, representing 50 different stony meteorites, were measured as analogues of asteroidal regolith. Representative samples were measured in directional hemispherical reflectance to assure that Kirchhoff's Law can be used to predict relative emissivity from the reflectance spectra. These spectral data confirm that the O-H fundamental absorption band near 2.9 microns is an extremely sensitive indicator of incipient alteration, which often has taken place in powdered meteorite samples exposed only to water vapor in the air. Such non-carbonaceous samples typically contain less than 1 percent water by weight. Likewise, the C-H fundamental absorption bands near 3.4 and 3.5 microns are equally sensitive indicators of contamination with volatile hydrocarbons, which can also be absorbed from the air. The heavy, macromolecular hydrocarbons native to chondrites do not display such heavy bands, making detection of these bands in remote sensing of asteroids unlikely. Despite the spectral artifacts introduced by alteration and hydrocarbon contamination, powdered stony meteorites display a wide variety of real spectral features that can be used for their identification, including residual reststrahlen bands, absorption bands, and the Christiansen feature. Researchers found that the wavelengths of the peaks or troughs of each of these spectral features can be used independently to infer meteorite composition, but the best results are obtained when the entire spectral curve is used, or at least the portion of it encompassed by the 8 to 14 micron atmospheric window, in a digital search library.

Salisbury, J. W.↗
DOE OSTI2022

KilonovaNet : Surrogate models of kilonova spectra with conditional variational autoencoders

ABSTRACT Detailed radiative transfer simulations of kilonova spectra play an essential role in multimessenger astrophysics. Using the simulation results in parameter inference studies requires building a surrogate model from the simulation outputs to use in algorithms requiring sampling. In this work, we present kilonovanet, an implementation of conditional variational autoencoders (cVAEs) for the construction of surrogate models of kilonova spectra. This method can be trained on spectra directly, removing overhead time of pre-processing spectra, and greatly speeds up parameter inference time. We build surrogate models of three state-of-the-art kilonova simulation data sets and present in-depth surrogate error evaluation methods, which can in general be applied to any surrogate construction method. By creating synthetic photometric observations from the spectral surrogate, we perform parameter inference for the observed light-curve data of GW170817 and compare the results with previous analyses. Given the speed with which kilonovanet performs during parameter inference, it will serve as a useful tool in future gravitational wave observing runs to quickly analyse potential kilonova candidates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗