Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “spectral modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

An initial model for estimating soybean development stages from spectral data

A model, utilizing a direct relationship between remotely sensed spectral data and soybean development stage, has been proposed. The model is based upon transforming the spectral data in Landsat bands to greenness values over time and relating the area of this curve to soybean development stage. Soybean development stages were estimated from data acquired in 1978 from research plots at the Purdue University Agronomy Farm as well as Landsat data acquired over sample areas of the U.S. Corn Belt in 1978 and 1979. Analysis of spectral data from research plots revealed that the model works well with reasonable variation in planting date, row spacing, and soil background. The R-squared of calculated U.S. observed development stage exceeded 0.91 for all treatment variables. Using Landsat data the calculated U.S. observed development stage gave an R-squared of 0.89 in 1978 and 0.87 in 1979. No difference in the models performance could be detected between early and late planted fields, small and large fields, or high and low yielding fields.

Henderson, K. E.↗
DOE OSTI2023

Applied Machine-Learning Models to Identify Spectral Sub-Types of M Dwarfs from Photometric Surveys

M dwarfs are the most abundant stars in the Solar Neighborhood and they are prime targets for searching for rocky planets in habitable zones. Consequently, a detailed characterization of these stars is in demand. The spectral sub-type is one of the parameters that is used for the characterization and it is traditionally derived from the observed spectra. However, obtaining the spectra of M dwarfs is expensive in terms of observation time and resources due to their intrinsic faintness. We study the performance of four machine-learning (ML) models—K-Nearest Neighbor (KNN), Random Forest (RF), Probabilistic Random Forest (PRF), and Multilayer Perceptron (MLP)—in identifying the spectral sub-types of M dwarfs at a grand scale by deploying broadband photometry in the optical and near-infrared. We trained the ML models by using the spectroscopically identified M dwarfs from the Sloan Digital Sky Survey (SDSS) Data Release (DR) 7, together with their photometric colors that were derived from the SDSS, Two-Micron All-Sky Survey, and Wide-field Infrared Survey Explorer. We found that the RF, PRF, and MLP give a comparable prediction accuracy, 74%, while the KNN provides slightly lower accuracy, 71%. We also found that these models can predict the spectral sub-type of M dwarfs with ~99% accuracy within ±1 sub-type. The five most useful features for the prediction are r - z, r - i, r - J, r - H , and g - z, and hence lacking data in all SDSS bands substantially reduces the prediction accuracy. However, we can achieve an accuracy of over 70% when the r and i magnitudes are available. Since the stars in this study are nearby (d ≲ 1300 pc for 95% of the stars), the dust extinction can reduce the prediction accuracy by only 3%. Finally, we used our optimized RF models to predict the spectral sub-types of M dwarfs from the Catalog of Cool Dwarf Targets for the Transiting Exoplanet Survey Satellite, and we provide the optimized RF models for public use.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2010

Thermal Infrared Emission Spectroscopy of Synthetic Allophane and its Potential Formation on Mars

Allophane is a poorly-crystalline, hydrous aluminosilicate with variable Si/Al ratios approx.0.5-1 and a metastable precursor of clay minerals. On Earth, it forms rapidly by aqueous alteration of volcanic glass under neutral to slightly acidic conditions [1]. Based on in situ chemical measurements and the identification of alteration phases [2-4], the Martian surface is interpreted to have been chemically weathered on local to regional scales. Chemical models of altered surfaces detected by the Mars Exploration Rover Spirit in Gusev crater suggest the presence of an allophane-like alteration product [3]. Thermal infrared (TIR) spectroscopy and spectral deconvolution models are primary tools for determining the mineralogy of the Martian surface [5]. Spectral models of data from the Thermal Emission Spectrometer (TES) indicate a global compositional dichotomy, where high latitudes tend to be enriched in a high-silica material [6,7], interpreted as high-silica, K-rich volcanic glass [6,8]. However, later interpretations proposed that the high-silica material may be an alteration product (such as amorphous silica, clay minerals, or allophane) and that high latitude surfaces are chemically weathered [9-11]. A TIR spectral library of pure minerals is available for the public [12], but it does not contain allophane spectra. The identification of allophane on the Martian surface would indicate high water activity at the time of its formation and would help constrain the aqueous alteration environment [13,14]. The addition of allophane to the spectral library is necessary to address the global compositional dichotomy. In this study, we characterize a synthetic allophane by IR spectroscopy, X-ray diffraction (XRD), and transmission electron microscopy (TEM) to create an IR emission spectrum of pure allophane for the Mars science community to use in Martian spectral models.

Rampe, E. B.↗
NASA NTRS1998

Using Ground Spectral Irradiance for Model Correction of AVIRIS Data

Over the last decade a series of techniques has been developed to correct hyperspectral imaging sensor data to apparent surface reflectance. The techniques range from the empirical line method that makes use of ground target measurements to model-based methods such as ATREM that derive parameters from the data themselves to convert radiance to reflectance, and combinations of the above. Here we describe a technique that combines ground measurements of spectral irradiance with existing radiative transfer models to derive the model equivalent of an empirical line method correction without the need for uniform ground targets of different reflectance.

Goetz, Alexander F. H.↗
DOE OSTI2026

Dataset describing two reference models for full-spectral lighting and daylight simulations together with implementations for two software systems

A dataset of two spectral lighting simulation reference models - one office and one factory hall - is presented. It aims to demonstrate and support full-spectral daylight and electric lighting simulations and facilitate evaluation of non-visual effects of light. The dataset includes Rhino CAD geometry, comprehensive spectral material and light source data and window system BSDF data. Example implementations in the two software tools, Radiance and OWL, enable reproducible workflows and support adoption in other software. The dataset is openly available on Zenodo. The office model reproduces Room 518 at the University of Innsbruck, including a west-facing façade and interior furnishings. The factory hall model follows the proposed geometry in the European standard 15193 for building energy performance. Interior reflectances in the office were measured in-situ using a handheld spectrometer. Exterior spectra and factory hall materials matching specified reflectances were obtained from an online spectral materials database. Glazing transmittance was derived from IGDB data using LBNL Optics/WINDOW. BSDFs for venetian blinds at various tilt angles, and for a diffusing pane adapted from the Complex Glazing Database, were generated in WINDOW. Luminaires in both models are specified with photometric files (Eulumdat/IES) and lamp spectra (Fluorescent 840, 4000 K LED). The provided example implementations (Radiance, OWL) include prepared input data and scripts to run first spectral simulations; example results are also included. The dataset is prepared to support reuse by researchers, designers and software developers for method validation, software engineering and comparison, and development of spectral metrics and controls.

Geisler-Moroder, David↗
NASA NTRS1990

Computational equations for radiating and ablating shock layers

The computational equations governing the shock-layer flowfield over a blunt body dominated by radiation and ablation are derived. The flowfield considered is that expected around the vehicles entering the atmosphere of the planet Mars or the earth on return from Mars on a sprint-type manned mission. To determine the appropriate method of approach, the radiative transfer calculations are made first using the existing computer code RASLE (Nicolet et al., 1978), which uses the assumption of equilibrium and a coarse spectral band model for radiative transfer, and the code NONEQ which accounts for thermochemical nonequilibrium and carries out line-by-line calculation of radiation. By comparing the results, it is concluded that a thermochemical nonequilibrium model and a line-by-line spectral model must be used.

Park, Chul↗
NASA NTRS1985

Solar radiance models for determination of ERBE scanner filter factor

Shortwave spectral radiance models for use in the spectral correction algorithms for the ERBE Scanner Instrument are provided. The required data base was delivered to the ERBe Data Reduction Group in October 1984. It consisted of two sets of data files: (1) the spectral bidirectional angular models and (2) the spectral flux modes. The bidirectional models employ the angular characteristics of reflection by the Earth-atmosphere system and were derived from detailed radiance calculations using a finite difference model of the radiative transfer process. The spectral flux models were created through the use of a delta-Eddington model to economically simulate the effects of atmospheric variability. By combining these data sets, a wide range of radiances may be approximated for a number of scene types.

Arduini, R. F.↗
NASA NTRS2016

Directional and Spectral Irradiance in Ocean Models: Effects on Simulated Global Phytoplankton, Nutrients, and Primary Production

The importance of including directional and spectral light in simulations of ocean radiative transfer was investigated using a coupled biogeochemical-circulation-radiative model of the global oceans. The effort focused on phytoplankton abundances, nutrient concentrations and vertically-integrated net primary production. The importance was approached by sequentially removing directional (i.e., direct vs. diffuse) and spectral irradiance and comparing results of the above variables to a fully directionally and spectrally-resolved model. In each case the total irradiance was kept constant; it was only the pathways and spectral nature that were changed. Assuming all irradiance was diffuse had negligible effect on global ocean primary production. Global nitrate and total chlorophyll concentrations declined by about 20% each. The largest changes occurred in the tropics and sub-tropics rather than the high latitudes, where most of the irradiance is already diffuse. Disregarding spectral irradiance had effects that depended upon the choice of attenuation wavelength. The wavelength closest to the spectrally-resolved model, 500 nm, produced lower nitrate (19%) and chlorophyll (8%) and higher primary production (2%) than the spectral model. Phytoplankton relative abundances were very sensitive to the choice of non-spectral wavelength transmittance. The combined effects of neglecting both directional and spectral irradiance exacerbated the differences, despite using attenuation at 500 nm. Global nitrate decreased 33% and chlorophyll decreased 24%. Changes in phytoplankton community structure were considerable, representing a change from chlorophytes to cyanobacteria and coccolithophores. This suggested a shift in community function, from light-limitation to nutrient limitation: lower demands for nutrients from cyanobacteria and coccolithophores favored them over the more nutrient-demanding chlorophytes. Although diatoms have the highest nutrient demands in the model, their relative abundances were generally unaffected because they only prosper in nutrient-rich regions, such as the high latitudes and upwelling regions, which showed the fewest effects from the changes in radiative simulations. The results showed that including directional and spectral irradiance when simulating the ocean light field can be important for ocean biology, but the magnitude varies with variables and regions. The quantitative results are intended to assist ocean modelers when considering improved irradiance representations relative to other processes or variables associated with the issues of interest.

Phytoplankton↗
NASA NTRS1985

Spectral methods for modeling supersonic chemically reacting flow fields

A numerical algorithm was developed for solving the equations describing chemically reacting supersonic flows. The algorithm employs a two-stage Runge-Kutta method for integrating the equations in time and a Chebyshev spectral method for integrating the equations in space. The accuracy and efficiency of the technique were assessed by comparison with an existing implicit finite-difference procedure for modeling chemically reacting flows. The comparison showed that the procedure presented yields equivalent accuracy on much coarser grids as compared to the finite-difference procedure with resultant significant gains in computational efficiency.

Drummond, J. P.↗
NASA NTRS1985

Spectral methods for modeling supersonic chemically reacting flow fields

A partial implicit numerical algorithm has been developed for solving the equations describing chemically reacting supersonic flows. The algorithm employs a two-stage Runge-Kutta method for integrating the equations in time and a Chebyshev spectral method for integrating the equations in space. The accuracy and efficiency of the new technique have been assessed by comparison with an existing implicit finite-difference procedure for modeling chemically reacting flows. The comparison showed that the new procedure yielded equivalent accuracy on much coarser grids as compared to the finite-difference procedure with resultant significant gains in computational efficiency.

Drummond, J. P.↗
DOE OSTI2022

SNICAR-ADv4: a physically based radiative transfer model to represent the spectral albedo of glacier ice

Abstract. Accurate modeling of cryospheric surface albedo is essential for our understanding of climate change as snow and ice surfaces regulate the global radiative budget and sea-level through their albedo and mass balance. Although significant progress has been made using physical principles to represent the dynamic albedo of snow, models of glacier ice albedo tend to be heavily parameterized and not explicitly connected with physical properties that govern albedo, such as the number and size of air bubbles, specific surface area (SSA), presence of abiotic and biotic light absorbing constituents (LACs), and characteristics of any overlying snow. Here, we introduce SNICAR-ADv4, an extension of the multi-layer two-stream delta-Eddington radiative transfer model with the adding–doubling solver that has been previously applied to represent snow and sea-ice spectral albedo. SNICAR-ADv4 treats spectrally resolved Fresnel reflectance and transmittance between overlying snow and higher-density glacier ice, scattering by air bubbles of varying sizes, and numerous types of LACs. SNICAR-ADv4 simulates a wide range of clean snow and ice broadband albedo (BBA), ranging from 0.88 for (30 µm) fine-grain snow to 0.03 for bare and bubble-free ice under direct light. Our results indicate that representing ice with a density of 650 kg m−3 as snow with no refractive Fresnel layer, as done previously, generally overestimates the BBA by an average of 0.058. However, because most naturally occurring ice surfaces are roughened “white ice”, we recommend modeling a thin snow layer over bare ice simulations. We find optimal agreement with measurements by representing cryospheric media with densities less than 650 kg m−3 as snow and larger-density media as bubbly ice with a Fresnel layer. SNICAR-ADv4 also simulates the non-linear albedo impacts from LACs with changing ice SSA, with peak impact per unit mass of LACs near SSAs of 0.1–0.01 m2 kg−1. For bare, bubble-free ice, LACs actually increase the albedo. SNICAR-ADv4 represents smooth transitions between snow, firn, and ice surfaces and accurately reproduces measured spectral albedos of a variety of glacier surfaces. This work paves the way for adapting SNICAR-ADv4 to be used in land ice model components of Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

GenMod: A generative modeling approach for spectral representation of PDEs with random inputs

Here, we propose a method for quantifying uncertainty in high-dimensional PDE systems with random parameters, where the number of solution evaluations is small. Parametric PDE solutions are often approximated using a spectral decomposition based on polynomial chaos expansions. For the class of systems we consider (i.e., high dimensional with limited solution evaluations) the coefficients are given by an underdetermined linear system in a regression formulation. This implies additional assumptions, such as sparsity of the coefficient vector, are needed to approximate the solution. Here, we present an approach where we assume the coefficients are close to the range of a generative model that maps from a low to a high dimensional space of coefficients. Our approach is inspired be recent work examining how generative models can be used for compressed sensing in systems with random Gaussian measurement matrices. Using results from PDE theory on coefficient decay rates, we construct an explicit generative model that predicts the polynomial chaos coefficient magnitudes. The algorithm we developed to find the coefficients, which we call GenMod, is composed of two main steps. First, we predict the coefficient signs using Orthogonal Matching Pursuit. Then, we assume the coefficients are within a sparse deviation from the range of a sign-adjusted generative model. This allows us to find the coefficients by solving a nonconvex optimization problem, over the input space of the generative model and the space of sparse vectors. We obtain theoretical recovery results for a Lipschitz continuous generative model and for a more specific generative model, based on coefficient decay rate bounds. We examine three high-dimensional problems and show that, for all three examples, the generative model approach outperforms sparsity promoting methods at small sample sizes.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

Development of a Fast and Accurate PCRTM Radiative Transfer Model in the Solar Spectral Region

A fast and accurate principal component-based radiative transfer model in the solar spectral region (PCRTMSOLAR) has been developed. The algorithm is capable of simulating reflected solar spectra in both clear sky and cloudy atmospheric conditions. Multiple scattering of the solar beam by the multilayer clouds and aerosols are calculated using a discrete ordinate radiative transfer scheme. The PCRTM-SOLAR model can be trained to simulate top-of-atmosphere radiance or reflectance spectra with spectral resolution ranging from 1 cm(exp −1) resolution to a few nanometers. Broadband radiances or reflectance can also be calculated if desired. The current version of the PCRTM-SOLAR covers a spectral range from 300 to 2500 nm. The model is valid for solar zenith angles ranging from 0 to 80 deg, the instrument view zenith angles ranging from 0 to 70 deg, and the relative azimuthal angles ranging from 0 to 360 deg. Depending on the number of spectral channels, the speed of the current version of PCRTM-SOLAR is a few hundred to over one thousand times faster than the medium speed correlated-k option MODTRAN5. The absolute RMS error in channel radiance is smaller than 10(exp −3) mW∕cm)exp 2)∕sr∕cm(exp −1) and the relative error is typically less than 0.2%.

Liu, Xu↗
DOE OSTI2024

Global fit of electron and neutrino elastic scattering data to determine the strange quark contribution to the vector and axial form factors of the nucleon

We present a global fit of neutral-current elastic (NCE) neutrino-scattering data and parity-violating electron-scattering (PVES) data with the goal of determining the strange quark contribution to the vector and axial form factors of the proton. Previous fits of this form included data from a variety of PVES experiments (PVA4, HAPPEx, G0, SAMPLE) and the NCE neutrino and anti-neutrino data from BNL E734. These fits did not constrain the strangeness contribution to the axial form factor G A s ( Q 2 ) at low Q 2 very well because there was no NCE data for Q 2 < 0.45 GeV 2 . Our new fit includes for the first time MiniBooNE NCE data from both neutrino and antineutrino scattering; this experiment used a hydrocarbon target and so a model of the neutrino interaction with the carbon nucleus was required. Three different nuclear models have been employed: a relativistic Fermi gas model, the superscaling approximation model, and a spectral function model. We find a tremendous improvement in the constraint of G A s ( Q 2 ) at low Q 2 compared to previous work, although more data is needed from NCE measurements that focus on exclusive single-proton final states, for example from MicroBooNE. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1985

Spectral constraints on models of gas in clusters of galaxies

The HEAO 1A2 spectra of clusters of galaxies are used to determine the temperature profile which characterizes the X-ray emitting gas. Strong evidence of nonisothermality is found for the Coma, A85, and A1795 clusters. Properties of the cluster potential which binds the gas are calculated for a range of model parameters. The typical binding mass, if the gas is adiabatic, is 2-4E14 solar masses and is quite centrally concentrated. In addition, the Fe abundance in Coma is .26 + or - .06 solar, less than the typical value (.5) found for rich clusters. The results for the gas in Coma may imply a physical description of the cluster which is quite different from what was previously believed.

Henriksen, M. J.↗
NASA NTRS1985

Spectral constraints on models of gas in clusters of galaxies

The HEAO 1A2 spectra of clusters of galaxies are used to determine the temperature profile which characterizes the X-ray emitting gas. Strong evidence of nonisothermality is found for the Coma, A85, and A1795 clusters. Properties of the cluster potential which binds the gas are calculated for a range of model parameters. The typical binding mass, if the gas is adiabatic, is 2-4E14 solar masses and is quite centrally concentrated. In addition, the Fe abundance in Coma is .26 + or - .06 solar, less than the typical value (.5) found for rich clusters. The results for the gas in Coma may imply a physical description of the cluster which is quite different from what was previously believed.

Henriksen, M. J.↗