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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

CALSPEC: Wide Field Camera 3 Infrared Grism Spectrophotometry

The collections of spectral energy distributions (SEDs) in the Hubble Space Telescope (HST) CALSPEC database are augmented by 19 infrared (IR) SEDs from Wide Field Camera 3 (WFC3) IR grism spectra. Together, the two IR grisms, G102 and G141, cover the 0.8–1.7 μm range with resolutions of R = 200 and 150, respectively. These new WFC3 SEDs overlap existing CALSPEC Space Telescope Imaging Spectrograph (STIS) standard star flux distributions at 0.8–1 μm with agreement to ≲1%. Some CALSPEC standards already have near-IR camera and multi-object spectrogragh (NICMOS) SEDs; but in their overlap region at 0.8–1.7 μm, the WFC3 data have better wavelength accuracy, better spectral resolution, better repeatability, and, consequently, better flux distributions of ~1% accuracy in our CALSPEC absolute flux SEDs versus ~2% for NICMOS. With the improved SEDs in the WFC3 range, the modeled extrapolations to 32 μm for the James Webb Space Telescope flux standards begin to lose precision longward of the 1.7 μm WFC3 limit, instead of at the 1.0-μm-long wavelength limit for STIS. For example, the extrapolated IR flux longward of 1.7 μm for 1808347 increases by ~1% for the model fit to the data with WFC3, instead of just to the STIS SED alone.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Towards next-generation optical potentials for nuclear reactions and structure calculations

Optical-model potentials (OMPs) are critical ingredients for basic and applied nuclear physics. Present-day computational capabilities allow us to generate data-driven nucleon-nucleus OMPs that are non-local and exactly dispersive (as theoretically required to be), include statistically-sound uncertainty quantification, and are trained on both scattering and bound-state data from a wide area of the nuclear chart. Combined together, these features allow for significant improvement in fidelity and extrapolative power of the model. Here, we present preliminary work toward the development and training of such an OMP. The capability of the model to describe data at this first stage is encouraging.

Perrotta, Salvatore Simone [Lawrence Livermore Nat↗
DOE OSTI2024

Towards next-generation optical potentials for nuclear reactions and structure calculations

Optical-model potentials (OMPs) are critical ingredients for basic and applied nuclear physics. Present-day computational capabilities allow us to generate data-driven nucleon-nucleus OMPs that are non-local and exactly dispersive (as theoretically required to be), include statisticallysound uncertainty quantification, and are trained on both scattering and bound-state data from a wide area of the nuclear chart. Combined together, these features allow for significant improvement in fidelity and extrapolative power of the model. Here, we present preliminary work toward the development and training of such an OMP. The capability of the model to describe data at this first stage is encouraging.

Perrotta, S.↗
NASA NTRS1995

ULF waves in the foreshock

We review our current knowledge of ULF waves in planetary foreshocks. Most of this knowledge comes from observations taken within a few Earth radii of the terrestrial bow shock. Terrestrial foreshock ULF waves can be divided into three types, large amplitude low frequency waves (approximately 30-s period), upstream propagating whistlers (1-Hz waves), and 3-s waves. The 30-s waves are apparently generated by back-streaming ion beams, while the 1-Hz waves are generated at the bow shock. The source of the 3-s waves has yet to be determined. In addition to issues concerning the source of ULF waves in the foreshock, the waves present a number of challenges, both in terms of data acquisition, and comparison with theory. The various waves have different coherence scales, from approximately 100 km to approximately 1 Earth radius. Thus multi-spacecraft separation strategies must be tailored to the phenomenon of interest. From a theoretical point of view, the ULF waves are observed in a plasma in which the thermal pressure is comparable to the magnetic pressure, and the rest-frame wave frequency can be moderate fraction of the proton gyro-frequency. This requires the use of kinetic plasma wave dispersion relations, rather than multi-fluid MHD. Lastly, and perhaps most significantly, ULF waves are used to probe the ambient plasma, with inferences being drawn concerning the types of energetic ion distributions within the foreshock. However, since most of the data were acquired close to the bow shock, the properties of the more distant foreshock have to be deduced mainly through extrapolation of the near-shock results. A general understanding of the wave and plasma populations within the foreshock, their interrelation, and evolution, requires additional data from the more distant foreshock.

Greenstadt, E. W.↗
NASA NTRS1999

Interpretation of Lidar and Satellite Data Sets Using a Global Photochemical Model

A primary goal of the NASA Tropospheric Chemistry Program (TCP) is to "contribute substantially to scientific understanding of human impacts on the global troposphere". In order to analyze global or regional trends and factors of the troposphere chemistry, for example, its oxidation capacity or composition, a continuous global/regional data coverage as well as model simulations are needed. The Global Tropospheric Experiment (GTE), a major component of the TCP, provides data vital to these questions via aircraft measurement of key trace chemical species in various remote regions of the world. Another component in NASA's effort are satellite projects for exploration of tropospheric chemistry and dynamics. A unique data product is the Tropospheric Ozone Residual (TOR) utilizing global tropospheric ozone data. Another key research tool are simulation studies of atmospheric chemistry and dynamics for the theoretical understanding of the atmosphere, the extrapolation of observed trends, and for sensitivity studies assessing a changing anthropogenic impact to air chemistry and climate. In the context with model simulations, field data derived from satellites or (airborne) field missions are needed for two purposes: 1. To initialize and validate model simulations, and 2., to interpret field data by comparison to model simulation results in order to analyze global or regional trends and deviations from standard tropospheric chemistry and transport conditions as defined by the simulations. Currently, there is neither a sufficient global data coverage available nor are existing well established global circulation models. The NASA LARC CTM model is currently not yet in a state to accomplish a sufficient tropospheric chemistry simulation, so that the current research under this cooperative agreement focuses on utilizing field data products for direct interpretation. They will be also available for model testing and a later interpretation with a finally utilized model.

Zenker, Thomas↗
DOE OSTI2026

Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics

Spatially distributed prediction of streamflow and nitrogen export dynamics is essential for precision management of agricultural watersheds. While temporal deep learning models such as Long Short-Term Memory (LSTM) have shown strong performance at basin scales, their ability to generalize spatially is limited by insufficient representation of spatial dependencies and flow paths, particularly under data-scarce conditions. To address this gap, we propose HydroGraphNet, a knowledge-guided graph machine learning framework that integrates process-based knowledge and explicit spatial learning into temporal modeling. This framework incorporates directed graph topology to encode watershed connectivity and upstream inflows, with mass balance constraints to improve physical consistency. To enhance generalization in sparsely monitored regions, HydroGraphNet is pretrained on synthetic data generated by the SWAT+ (Soil and Water Assessment Tool Plus) model. We evaluated HydroGraphNet in the Upper Sangamon River Basin (44 HUC-12 subwatersheds, 2001–2020) against two LSTM baselines: a lumped basin-level model and a distributed variant. When benchmarked on SWAT+ simulations in pretraining, HydroGraphNet improved test NSEs by 8.9% (discharge) and 13.7% (NO₃–N load) in temporal extrapolation, and by 27.1% and 34.7% in spatial extrapolation, relative to the Lumped LSTM baseline. After fine-tuning with USGS monitoring data, the model achieved mean test NSE (KGE) scores of 0.768 (0.861) for discharge and 0.626 (0.664) for NO₃–N load, substantially outperforming baselines. Attribution analysis further highlighted the importance of upstream inflow representation and graph-based spatial learning in capturing cross-subwatershed dependencies. The model also reproduced seasonal hydrological and biogeochemical patterns consistent with known processes, demonstrating its robustness and process fidelity for spatially distributed prediction. Altogether, HydroGraphNet advances the integration of physical knowledge and spatially explicit learning in hydrological modeling, offering a generalizable framework for distributed modeling to support spatially targeted water quality management in data-scarce watersheds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Statistical Studies on Thin Cirrus from MODIS Data

The 1.38 micron channel on the MODerate resolution Imaging Spectroradiomater (MODIS) is an ideal channel to identify and quantify thin cirrus on a global basis. This channel is used to produce the cirrus reflectance product in MOD06 and also used extensively by the MODIS aerosol algorithms to mask clouds for the MOD04 product. The aerosol product uses a lower threshold of the 1.38 micron channel reflectance of 0.01. A cirrus channel reflectance of 0.01 corresponds to approximately an aerosol optical thickness of 0.10. Therefore, the ambiguity due to the minor cirrus contamination may introduce artificial optical thickness in the aerosol products. The questions arise: How prevalent are the thinnest cirrus clouds over the globe? Do they persist over specific regions and seasons? Can we distinguish between the noise of the channel and the actual cloudiness by extrapolating the cloudiness signal to very dark scenes, statistically. We analyze the Terra data, over land and ocean to answer these questions.

Li, Rong-Rong↗
NASA NTRS1992

Venus lower thermosphere studies

Studies undertaken in this project have sought to understand lower thermospheric structure and dynamics (less than or equal to 145 km), particularly the processes responsible. This is a region just below the reach of in-situ instruments onboard PVO (Pioneer Venus Orbiter) during the first few diurnal cycles. PVO remote airglow observations (nitric oxide, O2, visible, O 1304A) have been coupled with ground-based observations (CO densities, winds, temperatures, O2 IR nightglow) to address the behavior of lower thermospheric winds and chemistry over 95 to 150 km. This interpretation of PVO and related data is accomplished by using the NCAR Venus thermospheric general circulation model (VTGCM) (Bougher et al., 1988; 1990). This model has been modified over the last two years to improve its ability to calculate O, CO, and O2 densities, temperatures, nightglow, and subsolar-to-antisolar and zonal winds over 95 to 150 km (Bougher and Borucki, 1992). Our VTGCM studies show that: (1) O2 visible and IR nightglow distributions can be used to trace lower thermosphere / upper mesosphere winds over 100-130 km. Typically, weak zonal winds (less than or equal to 25 m/sec) and nightglow maximum patches near 0100 LT prevail. Occasionally, strong zonal winds (30-60 m/sec) and airglow patches peaking near 0300 LT characterize the Venus lower thermosphere. (2) It is clear that the dynamics of the Venus 90-130 km region is highly variable on time scales as short as an hour. This is most likely due to the time variable nature of upward propagating gravity waves, which grow in amplitude and eventually break. The resulting turbulence gives rise to local time variable eddy diffusion and momentum drag, both of which strongly impact global density and nightglow distributions. (3) The oxygen chemistry (O, O2, etc.) over 90-120 km is strongly dependent on HO(x) and CLO(x) tracer species that must be properly included in any coupled chemical dynamical model. (4) The density profiles of light species (O, CO, N, He) are strongly affected by large-scale transport by the winds. Strong eddy diffusion is not a suitable model parameterization for approximating these light species, especially for extrapolation into the region below 140 km where PVO in-situ data is lacking. Instead, the fully coupled chemical dynamical VTGCM model should be used to improve estimates of densities within the VTS3 empirical model (Hedin et al., 1983) below 140 km.

Bougher, Stephen W.↗
DOE OSTI2021

Model fusion with physics-guided machine learning: Projection-based reduced-order modeling

The unprecedented amount of data generated from experiments, field observations, and large-scale numerical simulations at a wide range of spatiotemporal scales has enabled the rapid advancement of data-driven and especially deep learning models in the field of fluid mechanics. Although these methods are proven successful for many applications, there is a grand challenge of improving their generalizability. This is particularly essential when data-driven models are employed within outer-loop applications like optimization. In this work, we put forth a physics-guided machine learning (PGML) framework that leverages the interpretable physics-based model with a deep learning model. Leveraging a concatenated neural network design from multi-modal data sources, the PGML framework is capable of enhancing the generalizability of data-driven models and effectively protects against or inform about the inaccurate predictions resulting from extrapolation. We apply the PGML framework as a novel model fusion approach combining the physics-based Galerkin projection model and long- to short-term memory (LSTM) network for parametric model order reduction of fluid flows. We demonstrate the improved generalizability of the PGML framework against a purely data-driven approach through the injection of physics features into intermediate LSTM layers. Our quantitative analysis shows that the overall model uncertainty can be reduced through the PGML approach, especially for test data coming from a distribution different than the training data. Moreover, we demonstrate that our approach can be used as an inverse diagnostic tool providing a confidence score associated with models and observations. The proposed framework also allows for multi-fidelity computing by making use of low-fidelity models in the online deployment of quantified data-driven models.

42 ENGINEERING↗
NASA NTRS2002

A Quantitative Comparison of Leading-edge Vortices in Incompressible and Supersonic Flows

When requiring quantitative data on delta-wing vortices for design purposes, low-speed results have often been extrapolated to configurations intended for supersonic operation. This practice stems from a lack of database owing to difficulties that plague measurement techniques in high-speed flows. In the present paper an attempt is made to examine this practice by comparing quantitative data on the nearwake properties of such vortices in incompressible and supersonic flows. The incompressible flow data are obtained in experiments conducted in a low-speed wind tunnel. Detailed flow-field properties, including vorticity and turbulence characteristics, obtained by hot-wire and pressure probe surveys are documented. These data are compared, wherever possible, with available data from a past work for a Mach 2.49 flow for the same wing geometry and angles-of-attack. The results indicate that quantitative similarities exist in the distributions of total pressure and swirl velocity. However, the streamwise velocity of the core exhibits different trends. The axial flow characteristics of the vortices in the two regimes are examined, and a candidate theory is discussed.

Wang, F. Y.↗
NASA NTRSDate not supplied

Modeling Measurement Error in Dose-Response Models of Community Annoyance to Low-Noise Supersonic Flight

The primary research goal of the forthcoming NASA Quesst mission community test campaign is to collect representative community response data in support of the development of supersonic overflight noise certification standards. Beginning in 2026, NASA will fly the novel X-59 demonstrator aircraft over select communities in United States in order to demonstrate the possibility of low-noise supersonic flight over land and to collect objective measurements and subjective data on the perceptual experience of this new noise source. It is believed that a regression of a binary perceptual response (‘highly annoyed’ or ‘not’) on estimated noise levels (doses, measured in decibels) will provide a useful dose-response relationship for regulators. However, as these estimated doses will be subject to measurement error, naïve estimators of regression coefficients are inconsistent and slopes may be subject to attenuation bias. In this presentation, I contrast functional modeling of measurement error via simulation extrapolation (SIMEX) with structural Bayesian measurement error models. These methods are applied to available data collected during two NASA risk reduction studies in California in 2011 and Texas in 2018. I’ll conclude noting that in the presence of nonnegligible measurement errors, probabilities of annoyance may be overpredicted for low noise levels and underpredicted for high noise levels, therefore, methods of correcting for measurement error will be necessary to improve the utility of the dose-response relationship for policy-making purposes.

simulation↗
NASA NTRS2019

2 mm GISMO Observations of the Galactic Center. I. Dust Emission

The Central Molecular Zone (CMZ), covering the inner ~1degree of the Galactic plane has been mapped at 2 mm using the GISMO bolometric camera on the 30 m IRAM telescope. The 21" resolution maps show abundant emission from cold molecular clouds, from star forming regions, and from one of the Galactic center nonthermal filaments. In this work we use the Herschel Hi-GAL data to model the dust emission across the Galactic center. We find that a single-temperature fit can describe the 160 - 500 mu m emission for most lines of sight, if the long-wavelength dust emissivity scales as lambda (exp beta) with beta approximately equal 2.25. This dust model is extrapolated to predict the 2 mm dust emission. Subtraction of the model from the GISMO data provides a clearer look at the 2 mm emission of star-forming regions and the brightest nonthermal lament.

Richard G Arendt↗
DOE OSTI2025

FY2025 Status Report: Model 9975 O Ring Fixture Long-Term Leak Performance

Leak testing experiments to monitor the aging performance of Viton® GLT and GLT-S O-rings used in the model 9975 shipping package have been ongoing since 2004 at Savannah River National Laboratory. Seventy tests using mock-up 9975 primary containment vessels (PCVs) with GLT O-rings were assembled and heated to temperatures ranging from 200 to 450 °F. Due to material substitution, fourteen tests with GLT-S O-rings were initiated in 2008 and heated to temperatures ranging from 200 to 400 °F. The conditioning temperatures are elevated compared to the calculated maximum O-ring temperature in a 9975 package in storage, 158 °F, to accelerate aging and enable observations of O-ring failures in a reasonable time frame. The mock-up PCV fixtures are leak tested periodically, and all GLT O-ring fixtures aged at 350 °F or above have failed to maintain a leak-tight seal. Eight GLT O-ring fixtures aged at 300 °F have failed after 2.8 to 5.7 years at temperature while the remaining fixtures at 300 °F were retired from testing following more than five years of aging without failure. Two of these retired fixtures were returned to testing and heated to 350 °F to evaluate the impact of additional heating at higher temperature for aged O-rings. Fixture #20 failed after 3 months while fixture #18 failed after 9 months at 350 °F. These O-rings demonstrated that aged and in-service O-rings can continue to be used, even at higher temperatures, after being in storage, and their leak performance are consistent with other samples at 350 °F. There has been one GLT O-ring fixture which failed after 13.4 years of aging at 200 °F. However, 20 other GLT O-rings aging at 200 °F have remained leak-tight for over 16.9 years and remain in test. There are two GLT O-ring fixtures at 270 °F; one fixture has failed after 12.9 years while the other fixture remains in test after 12.5 years. All GLT-S O-ring fixtures aged at 300 °F or above have failed their leak test. No failures have yet been observed in GLT-S O-ring fixtures aging at 250 °F for 14.9 years, while one GLT-S O-ring fixture failed after 12.4 years at 200 °F. The leak testing data to date suggest the GLT and GLT-S O-rings aging in the K-Area Complex (KAC) storage at temperatures of 158 °F might maintain a leak-tight seal for up to 59 years. Data from the O-ring fixtures are generally consistent with results from compression stress-relaxation testing and provide confidence in the predictive models based on those results. However, uncertainty exists in extrapolating these elevated temperature results to the lower temperatures of interest for normal storage in KAC. The collective data from these test efforts suggest the minimum O-ring service life at KAC normal storage conditions should be at least 34 years for GLT and GLT-S O-rings. Measurement of compression set in O-rings removed from failed fixtures, compared to that from KAC surveillance O-rings, indicate significant margin remains for O-rings still in service in 9975 packages in KAC. Aging and periodic leak testing will continue for the remaining 24 mock-up PCV fixtures.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1981

Comparison of three thrust calculation methods using in-flight thrust data

The gross thrust of an experimental airplane was determined by each method using the same flight maneuvers and generally the same data parameters. Coefficients determined from thrust stand calibrations for each of the three methods were then extrapolated to cruise flight conditions. The values of total aircraft gross thrust calculated by the three methods for cruise flight conditions agreed within + or - 3 percent. The disagreement in the values of thrust calculated by the different techniques manifested itself as a bias in the data. There was little scatter (0.5 percent) for the thrust levels examined in flight.

Hughes, D. L.↗
DOE OSTI2023

The quest for superheavy elements and the limit of the periodic table

The borders of the periodic table of the elements and of the chart of nuclides are not set in stone. The desire to explore the properties of atoms and their nuclei in a regime of very large numbers of electrons, protons and neutrons has motivated new experimental facilities to create new elements and nuclides at the limits of atomic number and mass. But the small production rates and short lifetimes of superheavy nuclei and their atoms mean that ‘atom-at-a-time’ studies are the only experimental way to probe them. The physical and chemical data obtained so far, augmented by theoretical calculations, indicate significant deviations from extrapolations from lighter elements and isotopes. This situation raises the following question: how much further can one push the limits of the periodic table? Here, in this Review, we describe the major challenges in the field of the superheavy elements and speculate about future directions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Evaluating the impact of anatomical and physiological variability on human equivalent doses using PBPK models

Abstract Addressing human anatomical and physiological variability is a crucial component of human health risk assessment of chemicals. Experts have recommended probabilistic chemical risk assessment paradigms in which distributional adjustment factors are used to account for various sources of uncertainty and variability, including variability in the pharmacokinetic behavior of a given substance in different humans. In practice, convenient assumptions about the distribution forms of adjustment factors and human equivalent doses (HEDs) are often used. Parameters such as tissue volumes and blood flows are likewise often assumed to be lognormally or normally distributed without evaluating empirical data for consistency with these forms. In this work, we performed dosimetric extrapolations using physiologically based pharmacokinetic (PBPK) models for dichloromethane (DCM) and chloroform that incorporate uncertainty and variability to determine if the HEDs associated with such extrapolations are approximately lognormal and how they depend on the underlying distribution shapes chosen to represent model parameters. We accounted for uncertainty and variability in PBPK model parameters by randomly drawing their values from a variety of distribution types. We then performed reverse dosimetry to calculate HEDs based on animal points of departure for each set of sampled parameters. Corresponding samples of HEDs were tested to determine the impact of input parameter distributions on their central tendencies, extreme percentiles, and degree of conformance to lognormality. This work demonstrates that the measurable attributes of human variability should be considered more carefully and that generalized assumptions about parameter distribution shapes may lead to inaccurate estimates of extreme percentiles of HEDs.

Toxicology↗
DOE OSTI2025

Evaluation of data driven low-rank matrix factorization for accelerated solutions of the Vlasov equation

Low-rank methods have shown success in accelerating simulations of a collisionless plasma described by the Vlasov equation, but still rely on computationally costly linear algebra every time step. We propose a data-driven factorization method using artificial neural networks, specifically with convolutional layer architecture, that trains on existing simulation data. At inference time, the model outputs a low-rank decomposition of the distribution field of the charged particles, and we demonstrate that this step is faster than the standard linear algebra technique. Numerical experiments show that the method achieves comparable reconstruction accuracy for interpolation tasks, generalizing to unseen test data in a manner beyond just memorizing training data; patterns in factorization also inherently followed the same numerical trend as those within algebraic methods (e.g., truncated singular-value decomposition). However, when training on the first 70% of a time-series data and testing on the remaining 30%, the method fails to meaningfully extrapolate. Despite this limiting result, the technique may have benefits for simulations in a statistical steady-state or otherwise showing temporal stability. These results suggest that while the model offers a computationally efficient alternative for datasets with temporal stability, its current formulation is best suited for interpolation rather than for predicting future states in time-evolving systems. This study thus lays the groundwork for further refinement of neural network-based approaches to low-rank matrix factorization in high-dimensional plasma simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Effects of spin-orbit coupling and very large supercells on the description of acceptors in CdTe

Predicting accurate shallow donor and acceptor levels in semiconductors has been quite challenging using periodic boundary conditions as implemented in current density functional theory codes. The reason is that the wave functions associated with the shallow centers are quite extended and are not fully contained in the supercell (typically with a few hundred atoms) so impurities in the periodically repeated image cells interact with each other. Errors of ~0.1 eV are expected, and these are of the same order of magnitude as the ionization energies themselves. In the case of acceptors in CdTe, this problem is exacerbated by the strong spin-orbit coupling that split the Te-related states at the top of the valence band, making the calculations at least 8 times more expensive. CdTe is an important solar-cell material with record high efficiency of 22%. One of the main limiting factors to increasing the efficiency towards the theoretical limit of ~30% is the often reported very low hole concentration. Pushing to the limit of computational capability by using very large supercells with spin-orbit coupling we report the results of hybrid functional calculations of group-V acceptors in CdTe. We show that extrapolation to the dilute limit leads to an interpretation of the experimental data that is qualitatively different from previous DFT and hybrid functional calculation reports. We find that the group-V impurities indeed behave as shallow acceptors and that the corresponding compensating AX-centers are unstable and do not limit p-type doping. We address the differences between our results and previous theoretical predictions and show that our calculated ionization energies predict hole concentrations that are in excellent agreement with recent temperature-dependent Hall measurements on high-quality single-crystal samples.

14 SOLAR ENERGY↗