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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Global digital topography mapping with a synthetic aperture scanning radar altimeter

Global digital topography data of the land surface is of importance in a variety of geoscientific and application disciplines. Such a database, with a spatial resolution of 150 to 500 m and height accuracy of 5 m or better can be acquired from an orbiting platform using a synthetic aperture scanning radar altimeter. Near-global coverage can be achieved within 14 days from an orbiting platform in a polar or near-polar orbit.

Elachi, C.↗
DOE OSTI2020

Development of limited-view tomography for measurement of Spray G plume direction and liquid volume fraction

Abstract The method for direct injection of fuel in the cylinder of an IC engines is important to high-efficiency and low-emission performance. Optical spray diagnostics plays an important role in understanding plume movement and interaction for multi-hole injectors, and providing baseline understanding used for computational optimization of fuel delivery. Traditional planar or line-of-sight diagnostics fail to capture the liquid distribution because of optical thickness concerns. This work proposes a high-speed (67 kHz) extinction imaging technique at various injector rotations coupled to computed tomography (CT) for time-resolved reconstruction of liquid volume fraction in three dimensions. The number of views selected and processing were based on synthetic (modeled) liquid volume fraction data where extinction and CT adequately reconstructed each plume. The exercise showed that for an 8-hole, symmetric-design injector (ECN Spray G), only three different views are enough to reproduce the direction of each plume, and particularly the mean plume direction. Therefore, the number of views was minimized for experiments to save expense. Measurements applying this limited-view technique confirm plume–plume variations also detected with mechanical patternation, while providing better spatial and temporal resolution than achieved previously. Uncertainties due to the limited view within pressurized spray chambers, the droplet size, and optically thick regions are discussed. Graphic abstract

42 ENGINEERING↗
DOE OSTI2020

Stochastic Simulation of Daily Suspended Sediment Concentration Using Multivariate Copulas

Estimation of daily suspended sediment concentration (SSC) is required for water resources and environment management. In this paper, a copula-based stochastic method was proposed for daily SSC simulation. Here, the multivariate copula function, constructed based on a bivariate copula and two bivariate conditional probability distributions, was used to model the temporal and cross dependence structures in daily SSCs. Then, the daily SSCs were generated by sampling from the multivariate conditional distribution. As a result, synthetic long-term SSCs data beyond the limited observation period can be provided for water resources managers, which plays a critical role in accurately estimating frequency and magnitude of extreme SSCs events. The proposed method was under rigorous examination by applying to a case study at Pingshan station in the Jinsha River Basin, China. Results showed that the generated daily SSC sequences not only had a high degree of accuracy in preserving the statistical characteristics of the daily SSC observations, but also captured both the temporal correlation and the cross-correlation between the daily streamflow and daily SSC. Specifically, the average daily relative error values corresponding to mean, standard deviation, skewness, lag-1 temporal correlation, and cross correlation were 0.87%, 4.24%, 7.52%, 0.51% and 2.02%, respectively. The multivariate copula framework proposed here can accurately and efficiently generate long-term daily SSC data for water resources management such as frequency analysis and risk assessment of extreme SSC events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

WUS256: An Adjoint Waveform Tomography Model of the Crust and Upper Mantle of the Western United States for Improved Waveform Simulations

Abstract We report a new model (WUS256) of radially anisotropic seismic wavespeeds of the crust and upper mantle of the western United States (WUS) obtained from adjoint waveform tomography for the purpose of improving synthetic waveform fits to observed data. WUS256 is based on inversion of over 94,000 waveforms from 72 earthquakes recorded by nearly 3,400 stations. We started with the SPiRaL global model (Simmons et al., 2021, https://doi.org/10.1093/gji/ggab277 ) and waveforms in the period band of 50–120 s. We followed a conservative multiscale inversion approach with eight stages and 256 total inversion iterations which enabled monotonic misfit reduction to 20‐s minimum‐period waves. WUS256 relied on time‐frequency (TF) phase misfits and a trust region limited memory Broyden–Fletcher–Goldfarb–Shanno (L‐BFGS) optimization. Hessian‐vector products were used to qualitatively assess model resolution. Results indicate that WUS256 has good coverage of the continental regions to depths of about 150 km and is able to resolve features on lateral scales of about 200 km. We quantify waveform fits by the reduction in TF and normalized amplitude difference misfits between WUS256 and the SPiRaL starting model. WUS256 significantly improves waveform fits with misfit reduction 64% for both inversion and validation data sets compared to the SPiRaL starting model and shows even better fits compared to other models. Waveform fits illustrate that WUS256 reproduces body‐waves, fundamental mode surface waves as well as late arriving dispersed and/or scattered short period surface waves. The improvement in waveform fit indicates that WUS256 can be used to reproduce path effects on regional complete waveforms and moment tensor inversions.

58 GEOSCIENCES↗
DOE OSTI2022

The Sensitivity of GPz Estimates of Photo-z Posterior PDFs to Realistically Complex Training Set Imperfections

The accurate estimation of photometric redshifts is crucial to many upcoming galaxy surveys, for example, the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). Almost all Rubin extragalactic and cosmological science requires accurate and precise calculation of photometric redshifts; many diverse approaches to this problem are currently in the process of being developed, validated, and tested. In this work, we use the photometric redshift code GPz to examine two realistically complex training set imperfections scenarios for machine learning based photometric redshift calculation: (i) where the spectroscopic training set has a very different distribution in color–magnitude space to the test set, and (ii) where the effect of emission line confusion causes a fraction of the training spectroscopic sample to not have the true redshift. By evaluating the sensitivity of GPz to a range of increasingly severe imperfections, with a range of metrics (both of photo-z point estimates as well as posterior probability distribution functions, PDFs), we quantify the degree to which predictions get worse with higher degrees of degradation. In particular, we find that there is a substantial drop-off in photo-z quality when line-confusion goes above ~1%, and sample incompleteness below a redshift of 1.5, for an experimental setup using data from the Buzzard Flock synthetic sky catalogs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

First fluctuation measurements using an Imaging Neutral Particle Analyzer on DIII-D

A recent upgrade to the Imaging Neutral Particle Analyzer (INPA) on DIII-D has allowed for the first fluctuation measurements using an INPA to be taken during a neoclassical tearing mode (NTM). The INPA signal tracked the mode over 150 ms as the mode frequency dropped to zero, capturing both the NTM with poloidal and toroidal mode numbers $m/n=2/1$ and a $3/2$ mode at double the frequency. Analysis shows that the signals originate from charge exchange events near the edge of the plasma, and relative fluctuation amplitudes are greater than 25% for the duration of the NTM. Filtered signals show frequency beating patterns that are phase-space dependent. Simulated signal is dominated by prompt transport from the neutral beams to the INPA sightline, while the contribution from the slowing down distribution is significantly lower. Simulated measurements in the range of pitches that the diagnostic is sensitive to (0.5≤|v∥/v|≤ 0.75) show the signal is dominated by trapped orbits that pass through magnetic islands near the edge of the plasma. Calculations of expected fluctuation levels show that only direct interaction with the NTM can provide the strong relative fluctuation levels seen experimentally. The prompt nature of the orbits and thin radial layer found to contribute to synthetic signals suggest INPA passive data may be used to measure the perturbations of confined orbits on a single pass through a plasma instability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

The influence of physical and algorithmic factors on simulated far-field waveforms and source–time functions of underground explosions using unsupervised machine learning

SUMMARY Characterizing explosion sources and differentiating between earthquake and underground explosions using distributed seismic networks becomes non-trivial when explosions are detonated in cavities or heterogeneous ground material. Moreover, there is little understanding of how changes in subsurface physical properties affect the far-field waveforms we record and use to infer information about the source. Simulations of underground explosions and the resultant ground motions can be a powerful tool to systematically explore how different subsurface properties affect far-field waveform features, but there are added variables that arise from how we choose to model the explosions that can confound interpretation. To assess how both subsurface properties and algorithmic choices affect the seismic wavefield and the estimated source functions, we ran a series of 2-D axisymmetric non-linear numerical explosion experiments and wave propagation simulations that explore a wide array of parameters. We then inverted the synthetic far-field waveform data using a linear inversion scheme to estimate source–time functions (STFs) for each simulation case. We applied principal component analysis (PCA), an unsupervised machine learning method, to both the far-field waveforms and STFs to identify the most important factors that control variance in the waveform data and differences between cases. For the far-field waveforms, the largest variance occurs in the shallower radial receiver channels in the 0–50 Hz frequency band. For the STFs, both peak amplitude and rise times across different frequencies contribute to the variance. We find that the ground equation of state (i.e. lithology and rheology) and the explosion emplacement conditions (i.e. tamped versus cavity) have the greatest effect on the variance of the far-field waveforms and STFs, with the ground yield strength and fracture pressure being secondary factors. Differences in the PCA results between the far-field waveforms and STFs could possibly be due to near-field non-linearities of the source that are not accounted for in the estimation of STFs and could be associated with yield strength, fracture pressure, cavity radius and cavity shape parameters. Other algorithmic parameters are found to be less important and cause less variance in both the far-field waveforms and STFs, meaning algorithmic choices in how we model explosions are less important, which is encouraging for the further use of explosion simulations to study how physical Earth properties affect seismic waveform features and estimated STFs.

58 GEOSCIENCES↗
DOE OSTI2024

Estimation of Forest Aboveground Biomass from Derivatives of Vegetation-Structure Profiles

Several studies have found that the vertical Fourier transform of lidar, interferometric Synthetic Aperture Radar (SAR), and stereo photogrammetric profiles at empirically-determined spatial frequencies enables high-performance forest aboveground biomass (AGB) estimation. Linear combinations of real and imaginary parts of Fourier transforms of Tomographic (multi-baseline) SAR (TomoSAR) profiles, from Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) airborne data, generate ~20%-precision estimates of AGB in the Saskatchewan area of Canada. We found that this 20% precision can be improved to ~15%, a factor of 30% improvement in root mean square error (RMSE) if, in addition to using Fourier transforms of the profile itself, we use Fourier transforms of the spatial, vertical derivative of the profile. The formulation of this "derivative" algorithm is the subject of this paper.

Treuhaft, Robert↗
DOE OSTI2021

Methods—Analyzing Electrochemical Kinetic Parameters in Deep Eutectic Solvents Using an Extended Butler-Volmer Equation

Deep eutectic solvents (DESs) are promising electrolytes for electrochemical redox reactions, which can be used in redox flow batteries (RFBs). However, in some systems like the Fe 2+/3+ redox reaction in ethaline, traditional Tafel-based kinetic analysis generates unreasonable kinetic parameters (i.e., large anodic/cathodic charge transfer coefficients ( α a , α c ) along with low exchange current densities ( i 0 )). This hinders a comprehensive kinetic and kinetic mechanism study. Here, we perform a detailed investigation of the Tafel analysis using a series of synthetic rotating disk electrode (RDE) data. We find the Tafel analysis only works well when i 0 < 0.57 i lim (limiting current density) in our scenario and leads to abnormal kinetic values once i 0 exceeds this limiting value. Thus, we propose an extended Butler-Volmer (ex-BV) analysis based on modern non-linear fitting techniques to obtain the actual kinetic parameters for such systems. The results show that this method fits the RDE data closely and generates reliable α a , α c and i 0 values, demonstrating that it is a good replacement for traditional Tafel analysis for kinetic studies in high-viscosity electrolytes such as DES systems.

Electrochemistry↗
DOE OSTI2026

HITMAN

HITMAN (Hermite Interpolation of Trajectories and Measurement Synthesis for Analysis of Navigators) interpolates—or estimates the unknown values between known values—flight trajectories and generates synthetic inertial measurement unit (IMU) data using Hermite splines. This Python library provides modeling and simulation capabilities to synthesize inertial measurements from discrete trajectory points, enabling researchers to create exemplar datasets for evaluating navigation algorithms in various applications, including consumer devices like smartphones and vehicles. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Walker II, Michael [Sandia National Lab. (SNL-CA),↗
DOE OSTI2024

Z-Target Radiography Postprocessing With A Deep Convolution Neural Network

Analyzing X-ray radiographs is crucial for understanding target behavior in Inertial Confinement Fusion (ICF) and High Energy Density (HED) platforms. However, the density of Magneto Raleigh Taylor (MRT) bands and limitations of target materials often obscure relevant spike growth and density information. To address this issue, machine learning postprocessing techniques can be applied to remove darkened regions in radiography images. In this study, a novel method is presented for removing MRT darkened regions from z-target radiographs using a convolutional neural network (CNN). The CNN, consisting of six layers, treats the darkened regions as noise and employs a mixed loss function and end-to-end frameworks to suppress them while preserving sharpness. The six-layer architecture is designed to effectively learn features when provided with a larger volume of learning space. Each layer is optimized using a mixed loss function that combines a standard loss pixel approach with a multi-scaled structural similarity index loss, which considers luminance, contrast, and structure in local neighborhoods. This approach is particularly beneficial for capturing the stochastic structure of MRT limbs. Due to the limited availability of experimental data, training is conducted using synthetic target radiography from 3D Alegra simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

APOGEE Net: Improving the Derived Spectral Parameters for Young Stars through Deep Learning

Machine learning allows for efficient extraction of physical properties from stellar spectra that have been obtained by large surveys. The viability of machine-learning approaches has been demonstrated for spectra covering a variety of wavelengths and spectral resolutions, but most often for main-sequence (MS) or evolved stars, where reliable synthetic spectra provide labels and data for training. Spectral models of young stellar objects (YSOs) and low-mass MS stars are less well-matched to their empirical counterparts, however, posing barriers to previous approaches to classify spectra of such stars. In this work, we generate labels for YSOs and low-mass MS stars through their photometry. We then use these labels to train a deep convolutional neural network to predict logg, T {sub eff}, and Fe/H for stars with Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectra in the DR14 data set. This “APOGEE Net” has produced reliable predictions of logg for YSOs, with uncertainties of within 0.1 dex and a good agreement with the structure indicated by pre-MS evolutionary tracks, and it correlates well with independently derived stellar radii. These values will be useful for studying pre-MS stellar populations to accurately diagnose membership and ages.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Comprehensive Analysis of the Neutrino Process in Core-collapsing Supernovae

We investigate the neutrino flavor change effects due to neutrino self-interaction and shock wave propagation, as well as the matter effects on the neutrino process in core-collapsing supernovae (CCSNe). For the hydrodynamics, we use two models: a simple thermal bomb model and a specified hydrodynamics model for SN1987A. For the presupernova model, we take an updated model, adjusted to explain SN1987A, which employs recent developments in the (n, γ) reaction rates for nuclei near the stability line (A ~ 100). As for the neutrino luminosity, we adopt two different models: equivalent neutrino luminosity and nonequivalent luminosity models. The latter is taken from a synthetic analysis of CCSN simulation data, which quantitatively presented the results obtained by various neutrino transport models. Relevant neutrino-induced reaction rates are calculated using a shell model for light nuclei and a quasiparticle random phase approximation model for heavy nuclei. For each model, we present abundances of the light nuclei ( 7 Li, 7 Be, 11 B, and 11 C) and the heavy nuclei ( 92 Nb, 98 Tc, 138 La, and 180 Ta) produced by the neutrino process. The light nuclei abundances turn out to be sensitive to the Mikheyev–Smirnov–Wolfenstein (MSW) region around O-Ne-Mg layer while the heavy nuclei are mainly produced prior to the MSW region. Through detailed analyses, we find that neutrino self-interaction becomes a key ingredient, in addition to the MSW effect, for understanding the neutrino process and the relevant nuclear abundances. The normal mass hierarchy is shown to be more compatible with the meteorite data. The main nuclear reactions for each nucleus are also investigated in detail.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1974

Design/cost tradeoff studies. Appendix A. Supporting analyses and tradeoffs, book 1. Earth Observatory Satellite system definition study (EOS)

A listing of the Earth Observatory Satellite (EOS) candidate missions is presented for use as a baseline in describing the EOS payloads. The missions are identified in terms of first, second, and third generation payloads. The specific applications of the EOS satellites are defined. The subjects considered are: (1) orbit analysis, (2) space shuttle interfaces, (3) thematic mapping subsystem, (4) high resolution pointable imager subsystem, (5) the data collection system, (6) the synthetic aperture radar, (7) the passive multichannel microwave radiometer, and (8) the wideband communications and handling equipment. Illustrations of the satellite and launch vehicle configurations are provided. Block diagrams of the electronic circuits are included.

Source record↗
NASA NTRS1978

Ocean wave detection and direction measurements with microwave radars

The application of synthetic aperture microwave radar imagery to the measurement of ocean wave direction and wavelength is discussed and an airborne experiment conducted in preparation for the SEASAT-A satellite mission is presented. Models for radar backscattering are examined and it is concluded that the Bragg-Rice model, which represents the ocean surface as a combination of periodic surfaces so that the dominant backscatter matches some portion of the wave spectrum, appears most useful. The experiment was conducted with airborne X-band and L-band synthetic aperture radar (SAR) and data was compared with that obtained from a pitch-and-roll buoy and an instrument package mounted on a sea sled. SAR data was converted to wave spectra and it was found to match data from the buoy, while SAR data on wave direction agrees to within two degrees with the buoy and to within one degree with the sea sled sensors. Wave direction data taken by two real aperture radars is also presented and shown to agree with airborne photographs.

Teleki, P. G.↗
NASA NTRS1978

Relative toxicity of pyrolysis gases from materials - Effects of chemical composition and test conditions

Relative toxicity test data on 270 materials are presented, based on test procedures developed at the University of San Francisco. The effects of chemical composition, using data on 13 types of synthetic polymers and eight types of fabrics, are discussed. Selected materials were evaluated using nine test conditions with the USF method, and using methods developed at the FAA Civil Aeromedical Institute, Douglas Aircraft Company and San Jose State University.

Hilado, C. J.↗