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At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Solar-Forecast GridAPPS-D Application [SWR-18-36]

Persistent model serves as the baseline in the intra-hour forecasting of solar radiation due to the extensive computing efforts from the numerical weather prediction (NWP) models and the lack of surface observations in cloud as well as other atmospheric properties. The smart persistent model actively updates the extraterrestrial solar radiation with time and is an important improvement from the persistent model while the cloud conditions are assumed unchanged by giving constant clear-sky indexes. We developed a Physics-based Smart Persistent model for Intra-hour solar forecasting (PSPI) to further improve the accuracy of the smart persistent model. We used a cloud retrieval technique developed by Xie and Liu (2013) to estimate cloudy fraction and cloud albedo using surface-based observations of solar radiation. The solar radiation in future time steps is accurately given by actively computing individual cloud albedo related to the future solar position. Our evaluation studies indicated that the PSPI model significantly increased the accuracy in the short-term forecast of solar radiation, especially in thin cloud conditions or those covered by broken clouds.

Xie, Yu↗
DOE OSTI2026

Dark Energy Survey Year 3 results: Simulation-based 𝑤CDM inference from weak lensing and galaxy clustering maps with deep learning: Analysis design

Data-driven approaches using deep learning are emerging as powerful techniques to extract non-Gaussian information from cosmological large-scale structure. Here, this work presents the first simulation-based inference (SBI) pipeline that combines weak lensing and galaxy clustering maps in a realistic Dark Energy Survey Year 3 (DES Y3) configuration and serves as preparation for a forthcoming analysis of the survey data. We develop a scalable forward model based on the CosmoGridV1 suite of N-body simulations to generate over one million self-consistent mock realizations of DES Y3 at the map level. Leveraging this large dataset, we train deep graph convolutional neural networks on the full survey footprint in spherical geometry to learn low-dimensional features that approximately maximize mutual information with target parameters. These learned compressions enable neural density estimation of the implicit likelihood via normalizing flows in a ten-dimensional parameter space spanning cosmological 𝑤CDM, intrinsic alignment, and linear galaxy bias parameters, while marginalizing over baryonic, photometric redshift, and shear bias nuisances. To ensure robustness, we extensively validate our inference pipeline using synthetic observations derived from both systematic contaminations in our forward model and independent Buzzard galaxy catalogs. Our forecasts yield significant improvements in cosmological parameter constraints, achieving 2−3× higher figures of merit in the 𝛺 𝑚 − 𝑆 8 plane relative to our implementation of baseline two-point statistics and effectively breaking parameter degeneracies through probe combination. These results demonstrate the potential of SBI analyses powered by deep learning for upcoming Stage-IV wide-field imaging surveys.

Thomsen, A. [Zurich, ETH] (ORCID:0000000203099021)↗
NASA NTRS1986

Mechanisms of crustal deformation in the western US

The deformation processes in the western United States were studied, considering both deterministic models and random or statistical models. The role of the intracrustal delamination and mechanisms of crustal thinning were also examined. The application of fractal techniques to understand how the crust is deforming was studied in complex regions. Work continued on the development of a fractal based model for deformation in the western United States. Fractal studies were also extended to the study of topography and the geoid.

Turcotte, Donald L.↗
NASA NTRS2013

Molecular-Based Optical Measurement Techniques for Transition and Turbulence in High-Speed Flow

High-speed laminar-to-turbulent transition and turbulence affect the control of flight vehicles, the heat transfer rate to a flight vehicle's surface, the material selected to protect such vehicles from high heating loads, the ultimate weight of a flight vehicle due to the presence of thermal protection systems, the efficiency of fuel-air mixing processes in high-speed combustion applications, etc. Gaining a fundamental understanding of the physical mechanisms involved in the transition process will lead to the development of predictive capabilities that can identify transition location and its impact on parameters like surface heating. Currently, there is no general theory that can completely describe the transition-to-turbulence process. However, transition research has led to the identification of the predominant pathways by which this process occurs. For a truly physics-based model of transition to be developed, the individual stages in the paths leading to the onset of fully turbulent flow must be well understood. This requires that each pathway be computationally modeled and experimentally characterized and validated. This may also lead to the discovery of new physical pathways. This document is intended to describe molecular based measurement techniques that have been developed, addressing the needs of the high-speed transition-to-turbulence and high-speed turbulence research fields. In particular, we focus on techniques that have either been used to study high speed transition and turbulence or techniques that show promise for studying these flows. This review is not exhaustive. In addition to the probe-based techniques described in the previous paragraph, several other classes of measurement techniques that are, or could be, used to study high speed transition and turbulence are excluded from this manuscript. For example, surface measurement techniques such as pressure and temperature paint, phosphor thermography, skin friction measurements and photogrammetry (for model attitude and deformation measurement) are excluded to limit the scope of this report. Other physical probes such as heat flux gauges, total temperature probes are also excluded. We further exclude measurement techniques that require particle seeding though particle based methods may still be useful in many high speed flow applications. This manuscript details some of the more widely used molecular-based measurement techniques for studying transition and turbulence: laser-induced fluorescence (LIF), Rayleigh and Raman Scattering and coherent anti-Stokes Raman scattering (CARS). These techniques are emphasized, in part, because of the prior experience of the authors. Additional molecular based techniques are described, albeit in less detail. Where possible, an effort is made to compare the relative advantages and disadvantages of the various measurement techniques, although these comparisons can be subjective views of the authors. Finally, the manuscript concludes by evaluating the different measurement techniques in view of the precision requirements described in this chapter. Additional requirements and considerations are discussed to assist with choosing an optical measurement technique for a given application.

Bathel, Brett F.↗
DOE OSTI2023

Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators

Atmospheric correction of airborne hyperspectral imaging spectroscopy (AHIS) to obtain high-quality surface reflectance is the prerequisite for remote sensing applications. Over the last decades, different atmospheric correction methods have been developed based on radiative transfer models (RTMs), however, the relative performances of different algorithms are unclear. Automated operational atmospheric correction methods to process large-volume AHIS data in a high-accurate and high-throughput manner are still lacking. Therefore, this study proposed an operational atmospheric correction pipeline for deriving surface reflectance from AHIS data. To ensure the accuracy and efficiency of the pipeline, we focused on three specific aspects: (1) selecting a suitable RTM for the development of atmospheric lookup tables (LUTs) by comparing the commercial MODerate resolution atmospheric TRANsmission (MODTRAN) and open-sourced Library for Radiative TRANsfer (LibRadTRAN) models, where the widely-used software, Atmospheric/Topographic Correction for Airborne Imagery (ATCOR), was used as benchmarks; (2) identifying key atmospheric correction parameters and determining suitable sources for parameter retrievals including AHIS, Moderate Resolution Imaging Spectroradiometer (MODIS), and AErosol RObotic NETwork (AERONET); and (3) testing the performance of using machine learning emulators to speed up the RTM-based atmospheric correction. Results indicate that (1) atmospheric correction based on MODTRAN LUTs can produce surface reflectance accurately with mean absolute errors < 0.05 and cosine similarities > 0.98 compared to field measurements, which is comparable to the software ATCOR and slightly outperforms the LibRadTRAN LUTs; (2) sobol global sensitivity analysis demonstrates that in the atmospheric correction, visibility and water vapor are two key parameters that can be accurately derived from AHIS in contrast to MODIS or AERONET data; and (3) Random Forest emulators can produce accurate estimations of surface reflectance with mean absolute errors < 0.03 and cosine similarities > 0.98 for higher processing efficiency and determine a suitable set of wavelengths for retrieving atmospheric visibility and water vapor. In conclusion, the proposed atmospheric correction pipeline also improved the four-stream radiative transfer theory for airborne applications by considering adjacent effects from airborne surrounding pixels and can also be applied for atmospheric correction of hyperspectral data from spaceborne missions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2013

Source Physics Experiment modeling: YEARLY REPORT FOR THE PERIOD Jan-Dec 2012

The Office of Nuclear Detonation Detection identifies characterization of the explosion source as a fundamental research area. Our ability to characterize explosion sources from earthquakes relies on empirical laws that are not covering all the possible cases of location, site structure and yields of possible explosions. Our empirical knowledge needs to be completed by a physical understanding of seismic wave generation. NA22 has funded the LANL SPE seismic project to develop a new source model under the Ground-Based Nuclear Explosion Monitoring Research and Development (GNEM-R&D) Program. NA22 also funds computational support of the seismic source model development. Hydrodynamic computations using realistic material response models combined with a comprehensive series of field experiments provided by the SPE program are needed for test and validation of the new seismic source models. The following three essential elements, (1) model development, (2) numerical simulations of non-linear material response, and (2) field experimentation, will be brought to bear on a predictive capability for broadband P and S wavefields with a sound physical basis for seismic monitoring applications. This research will advance our ability to address yield estimation for UNE conducted in proliferant nations and provide a better understanding of the coupling of explosion sources to the seismic wavefield.

58 GEOSCIENCES↗
NASA NTRS2009

Spacecraft Internal Acoustic Environment Modeling

The objective of the project is to develop an acoustic modeling capability, based on commercial off-the-shelf software, to be used as a tool for oversight of the future manned Constellation vehicles. The use of such a model will help ensure compliance with acoustic requirements. Also, this project includes modeling validation and development feedback via building physical mockups and conducting acoustic measurements to compare with the predictions.

Chu, S. Reynold↗
NASA NTRS1992

Multimegawatt dynamic NEP PMAD study

The National Aeronautics and Space Administration Lewis Research Center (NASA LeRC) is developing a FORTRAN-based model of a complete nuclear electric propulsion (NEP) vehicle to be used for piloted or cargo missions to the Moon or Mars. The proposed vehicle will use either a Brayton or K-Rankine power conversion cycle, and either ion or magnetoplasmadynamic (MPD) thrusters. In support of this effort, Rocketdyne evaluated various power management and distribution (PMAD) approaches and selected a low-frequency design that is based on the direct use of the alternator voltage and frequency for power transmission. This approach was compared with dc and high-frequency ac designs, and selected on the basis of mass, efficiency, and qualitative assessment of power quality, reliability and development costs. This low-frequency architecture will be used as the reference in future NEP PMAD studies and for the subsequent FORTRAN model development.

Metcalf, Kenneth J.↗
DOE OSTI2013

Measurement and modeling of muon-induced neutrons in LSM in application for direct dark matter searches

Due to a very low event rate expected in direct dark matter search experiments, a good understanding of every background component is crucial. Muon-induced neutrons constitute a prominent background, since neutrons lead to nuclear recoils and thus can mimic a potential dark matter signal. EDELWEISS is a Ge-bolometer experiment searching for WIMP dark matter. It is located in the Laboratoire Souterrain de Modane (LSM, France). We have measured muon-induced neutrons by means of a neutron counter based on Gd-loaded liquid scintillator. Studies of muon-induced neutrons are presented and include development of the appropriate MC model based on Geant4 and analysis of a 1000-days measurement campaign in LSM. We find a good agreement between measured rates of muon-induced neutrons and those predicted by the developed model with full event topology. The impact of the neutron background on current EDELWEISS data-taking as well as for next generation experiments such as EURECA is briefly discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2011

Modelling of fluorine based high density plasma for the etching of silica glasses

An etching simulator has been developed to study the etching of commercial silica glass (Pyrex, D263, AF45, and Vycor) in a SF{sub 6}/Ar inductively coupled plasma (ICP) discharge. The etching model is based on the development of the plasma kinetic model coupled to a two dimensional (2D) Monte Carlo cellular surface model to predict the etched surface morphology as a function of the operating conditions. The SF{sub 6}/Ar plasma model allows us to predict the neutral and ion species fluxes, as well as the density and the temperature of electrons, as a function of the reactor operating conditions. Such output parameters are used as input parameters in both the sheath and etching models. The 2D Monte Carlo cellular model is based on the representation of both the substrate and the mask by uniform cells, which each represents a real number of sites. The preferential redeposition mechanism of the etched products on the metallic sites seems to play an important role on the formation and the propagation of the etched surface roughness. The results obtained by the model are compared with the experimental results for etching rate and roughness. A satisfactory agreement between the experimental results and the model concerning the etching rate and the etched surface morphology has been obtained for different glasses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Semi-Empirical Material Model for Hydrogen Uptake Kinetics by 1,4-bis(phenylethynyl)benzene (DEB)-based Getters

We report on development of a semi-empirical model describing the kinetics of H 2 /D 2 reaction with 1,4-bis(phenylethynyl)benzene (DEB)-based getters in pellet and powder form. The physical basis of the model is solid-state diffusion of DEB plus reaction of DEB with H atoms on the surface of nanometer-scale Pd catalyst particles. The purpose of this material model is to facilitate more accurate predictions of performance for DEB-based getter assemblies. These predictions will be accomplished by integrating the model presented here into finite element, reaction/diffusion simulations of getter assembly hydrogen uptake performance. As of Fall 2020, this integration is underway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multiscale plasticity of geomaterials predicted via constrained optimization‐based granular micromechanics

Abstract A general framework to derive nonlinear elastic and elastoplastic material models from granular micromechanics is proposed, where a constraint‐based variational structure is introduced to classical grain contact‐based homogenization methods of hyperelasticity. Like the classical hyperelastic methods, reference solutions for closed‐form hyperelastic material models are analytically derived from the grain‐scale contact mechanics. However, unlike prior methods, the proposed homogenization framework defines closed‐form hyperelastoplastic material models that extend multiscale variational methods to granular plasticity. The proposed framework is used to develop novel granular micromechanics‐based macroscopic models for a Mises type solid, Drucker–Prager type plasticity, and grain‐contact cohesive‐debonding with a deviatorically and volumetrically coupled nonlinearly elastic response. Macroscopic plastic parameters and yield criteria are explicitly related to their microscale counterparts, for example, the friction coefficient governing intergranular slip. Numerical examples and comparison to measurements from the literature, including triaxial compaction of concrete, are provided to investigate model predictions and demonstrate calibration to experimental data.

Bryant, E. C.↗
NASA NTRSDate not supplied

A Multi Targeted Dietary Supplement as a Potential Countermeasure for Prolonged, Deep Space Exploration

Deep space exploration, particularly to the Moon and Mars, are currently major goals of NASA and other international space agencies. Long-term space flight presents unique challenges to the human physiology from microgravity, social isolation, altered circadian rhythm and radiation. Oxidative stress has been implicated as a crucial factor in space environment induced injury. Elucidating these detrimental effects on the central nervous system and brain is a primary objective, as they may result in adverse changes in astronaut behavior, mood and performance of critical tasks. We were recently funded by HRP Human Factors Behavioral Performance (HFBP) Element to test the hypothesis that Galactic Cosmic Ray Simulation (GCRsim) Ionizing Radiation (IR), microgravity and social isolation combine synergistically to trigger an oxidative stress response that alters immune homeostasis, brain structure and function, and neurobehavioral and cognitive performance. This project will identify potential biomarkers for, and mechanisms underlying, structural and functional changes in the immune and nervous systems leading to behavioral/cognitive performance deficits, and its potential application to develop effective countermeasures to mitigate negative health effects of long duration space habitation. Countermeasures to offset neurological damaged and cognitive deficits are paramount for protecting astronauts during deep space transits, but many countermeasures have been found to be unsuitable in ground-based model studies. We have developed a multi targeted dietary supplement (MTDS) designed to simultaneously ameliorate oxidative stress, inflammatory processes, energetic shortfalls, and membrane and mitochondrial deterioration. Administration of this MTDS has improved cognition and longevity in age accelerated and normal aging mice. Specifically, the MTDS was found to prevent a decline in mitochondrial complex III activity and cell loss, as well as prevent an increase in protein carbonyls and mitochondrial 3-nitrotyrosine in the brain of these mice. Further, administration of the MTDS was also found to reduce bone marrow chromosomal aberrations, DNA damage, lymphocyte apoptosis after whole body exposure of 2 Gy γ radiation. Mice exposed to a high dose cranially (10 Gy) had decreased cognitive responses (seen as increased latency time to uncover buried food and decreased novel object recognition), increased plasma 8-OHdG levels, increased markers of cell stress in the brain, decreased hippocampal brain-derived neurotrophic factor (BDNF) protein and decreased plasma levels of cytokines, all of which were ameliorated with treatment of the MTDS. As we have shown the supplement is protective in models of cognitive damage similar space environment stressors, particularly increased oxidative stress, we propose it may be a suitable countermeasure for upcoming deep space exploration.

radiation↗
NASA NTRSDate not supplied

A MULTI TARGETED DIETARY SUPPLEMENT AS A POTENTIAL COUNTERMEASURE FOR DEEP SPACE EXPLORATION

Future deep space exploration to the Moon and Mars and beyond are currently major goals of NASA. Space flight presents unique challenges to the human physiology from the combined effects of microgravity, social isolation, altered circadian rhythm and radiation. Oxidative stress has been implicated as a crucial factor in space environment induced injury. Elucidating these detrimental effects on the central nervous system and brain is a primary objective, as they may result in adverse changes in astronaut behavior, mood and performance of critical tasks. We were recently funded by HRP Human Factors Behavioral Performance (HFBP) Element to test the hypothesis that Galactic Cosmic Ray Simulation (GCRsim) Ionizing Radiation (IR), microgravity and social isolation combine synergistically to trigger an oxidative stress response that alters immune homeostasis, brain structure and function, and neurobehavioral and cognitive performance. This project will identify potential biomarkers for, and mechanisms underlying, structural and functional changes in the immune and nervous systems leading to behavioral/cognitive performance deficits, and its potential application to develop effective countermeasures to mitigate negative health effects of long duration space habitation. Countermeasures to offset neurological damaged and cognitive deficits are paramount for protecting astronauts during deep space transits, but many countermeasures have been found to be unsuitable in ground-based model studies. We have developed a multi targeted dietary supplement (MTDS) designed to simultaneously ameliorate oxidative stress, inflammatory processes, energetic shortfalls, and membrane and mitochondrial deterioration. Administration of this MTDS has improved cognition and longevity in age accelerated and normal aging mice. Specifically, the MTDS was found to prevent a decline in mitochondrial complex III activity and cell loss, as well as prevent an increase in protein carbonyls and mitochondrial 3-nitrotyrosine in the brain of these mice. Further, administration of the MTDS was also found to reduce bone marrow chromosomal aberrations, DNA damage, lymphocyte apoptosis after whole body exposure of 2 Gy γ radiation. Mice exposed to a high dose cranially (10 Gy) had decreased cognitive responses (seen as increased latency time to uncover buried food and decreased novel object recognition), increased plasma 8-OHdG levels, increased markers of cell stress in the brain, decreased hippocampal brain-derived neurotrophic factor (BDNF) protein and decreased plasma levels of cytokines, all of which were ameliorated with treatment of the MTDS. As we have shown the supplement is protective in models of cognitive damage similar space environment stressors, particularly increased oxidative stress, we propose it may be a suitable countermeasure for upcoming deep space exploration.

Stephanie Puukila↗
DOE OSTI2025

Enhanced Feedstock Characterization and Modeling to Facilitate Optimal Preprocessing and Deconstruction of Corn Stover (Final Report)

This project addresses the challenge of processing corn stover by fractionating this biomass feedstock to both streamline processing and generate new potential co-products. Additionally, the project developed new field-deployable analytical tools that can be coupled with empirical models that were used to predict feedstock properties and processing performance. The overall scope of this project was: (1) identify conditions for optimal corn stover fractionation using a two- stage physical fractionation, (2) assess how physical fractionation impacts properties, partitioning of biomass, and response to processing, (3) further adapt, develop, and validate several advanced characterization tools for assessing biomass properties that can be linked to processing behavior, and (4) develop and validate predictive models based on measurements that can be performed “in the field” or “at the biorefinery gate” to predict feedstock processing behavior (preprocessing and deconstruction). The first objective employed pre-separation processing (size reduction) which was next subjected to enhanced separations to yield fractions enriched or depleted in select compositional components or properties. For the second objective, fractions were screened for their response to post-separation processing (pretreatment and enzymatic hydrolysis). Detailed characterization profiles were developed and dynamic image analysis to assess distribution of particle size and morphology. For the final objective, we utilized these tools to develop empirical models to assess the relative abundance of tissue type in order to assess fractionation efficacy and to predict fraction performance during pretreatment and enzymatic hydrolysis.

09 BIOMASS FUELS↗
DOE OSTI2024

MODELING AND METHOD FOR OPTICAL PERFORMANCE OF A RECEIVER COATING AND ITS DEGRADATION DUE TO OPERATION

The optical properties of the coating used on a concentrated solar power (CSP)’s receiver directly impact the performance of the power plant. Receiver coatings are designed to absorb as much heat as possible and transfer it to the circulating fluid. Over time, the absorptivity of the receiver coating degrades due to environmental and operational conditions. This project aims to (1) create a test apparatus that allows coatings to undergo accelerated lifetime testing under conditions that mimic what the coating will experience on-tower; and (2) develop a mathematical model that based on the test data predicts absorptivity over time. To create the mathematical model, samples of BrightSource Energy’s Gen1 and Gen2 coatings were tested first looking at individual failure modes (such as high temperature cycling) and then for combined failure modes in the newly developed apparatus. In addition to taking optical measurements, the samples were destroyed to allow for metalogical evaluation to understand what was happening on a microscopic level. Pre-existing models from the literature that describe accelerated testing as well as individual phenomena observed in the coating were then combined to create the model. Additionally, the Gen2 and Gen3 coatings are being testing at the Plataforma Solar de Almería (PSA) facility in Almeria, Spain to confirm that the apparatus test results are similar to those received on-sun. (PSA’s facility closely mimics on-tower conditions). The goal is to enable industry players to test coatings using the new apparatus, gather absorptivity measurements (without needing to destroy samples), and input the information into the model to determine how the coating will perform over time, thus allowing the optical performance of coatings to be compared even before they are used on-tower. The model will be publicly available by the end of the project (currently projected as December 2024).

14 SOLAR ENERGY↗
NASA NTRS1990

Compensating for pneumatic distortion in pressure sensing devices

A general numerical technique for obtaining unsteady pressure measurements using conventional pressure sensing technology has been developed. A pneumatic distortion model, based on the Navier-Stokes equations of momentum and continuity, was reduced to a low-order, state-variable model retaining most of the dynamic characteristics of the full model. The reduced-order model is coupled with results from minimum variance estimation theory to develop an algorithm to compensate the effects of pneumatic distortion. Both postflight and real-time algorithms were developed and evaluated using simulated and flight data.

Whitmore, Stephen A.↗
DOE OSTI2018

SCC Aerosol Transport Model Summary Report

The purpose of the present work is to introduce a generic and reliable numerical model for prediction of aerosol transport, deposition, and plugging in leak paths similar to stress corrosion cracks while accounting for potential plugging formation. The model is dynamic (changing leak path geometry due to plugging) and it relies on the numerical solution of the aerosol transport equation in one dimension using finite differences. An extensive validation exercise (particle diameters: 0.01-10 μm and pressure difference up to 12 kPa) was conducted based on comparisons with experimental and theoretical data. The developed model is fairly general since it is based on a generic mechanistic description of the aerosol flow and particle deposition in the leak path, without requiring experimental fittings other than using the leak rate parameters commonly available in practical applications. Despite the approximate agreement of the model with the experimental data, the obtained predictions can be qualified as realistic. This is a major achievement of the model, which has been based on generic aerosol mechanics with no reference or adjustment to experimental data.

42 ENGINEERING↗