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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Supernovae and supernova remnants

The basic features and astrophysics of supernovae of types Ia, Ib, and II and of SNRs are discussed, summarizing the results of recent ground-based and space observations obtained at different wavelengths. Typical data are presented in graphs and sample images, and consideration is given to their implications for shock heating by the initial explosion, radioactive energy input, circumstellar interaction, and pulsar energy input. SNRs described include Tycho's remnant, Kepler's remnant, the Cyg loop, Pup A, the Crab Nebula, the Vela and Crab pulsars, and 0540-69.3 in the LMC. The need for high-spatial-resolution IR and X-ray spectra of these objects is indicated.

Chevalier, Roger A.↗
NASA NTRS1989

Three-dimensional quantitative flow diagnostics

The principles, capabilities, and practical implementation of advanced measurement techniques for the quantitative characterization of three-dimensional flows are reviewed. Consideration is given to particle, Rayleigh, and Raman scattering; fluorescence; flow marking by H2 bubbles, photochromism, photodissociation, and vibrationally excited molecules; light-sheet volume imaging; and stereo imaging. Also discussed are stereo schlieren methods, holographic particle imaging, optical tomography, acoustic and magnetic-resonance imaging, and the display of space-filling data. Extensive diagrams, graphs, photographs, sample images, and tables of numerical data are provided.

Miles, Richard B.↗
NASA NTRS1990

Thematic Conference on Remote Sensing for Exploration Geology - Methods, Integration, Solutions, 7th, Calgary, Canada, Oct. 2-6, 1989, Proceedings. Volumes 1 & 2

Recent advances in airborne and satellite remote-sensing technology for application to geological exploration are discussed in reviews and reports. Sections are devoted to basement tectonics and their surface expressions, spectral geology, hydrocarbon exploration applications, radar applications and future systems, engineering and environment issues, geobotanical remote sensing, advanced image processing, data integration and mapping, and mineral exploration. Extensive diagrams, graphs, and sample images are provided.

Source record↗
DOE OSTI2021

Exploring the Value of Nodes with Multicommunity Membership for Classification with Graph Convolutional Neural Networks

Sampling is an important step in the machine learning process because it prioritizes samples that help the model best summarize the important concepts required for the task at hand. The process of determining the best sampling method has been rarely studied in the context of graph neural networks. In this paper, we evaluate multiple sampling methods (i.e., ascending and descending) that sample based off different definitions of centrality (i.e., Voterank, Pagerank, degree) to observe its relation with network topology. We find that no sampling method is superior across all network topologies. Additionally, we find situations where ascending sampling provides better classification scores, showing the strength of weak ties. Two strategies are then created to predict the best sampling method, one that observes the homogeneous connectivity of the nodes, and one that observes the network topology. In both methods, we are able to evaluate the best sampling direction consistently.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Harnessing graph convolutional neural networks for identification of glassy states in metallic glasses

Graph Convolutional Neural Networks (GCNNs) have emerged as powerful tools for analyzing materials. In this study, we employ GCNNs to examine structural characteristics of CuZr metallic glasses (MGs) and identify their states. We use molecular dynamics to simulate the quenching process of CuZr, using cooling rates ranging from 10 9 to 10 15 K/s, to produce six unique glassy states. For each state, we create a dataset comprising 1,800 distinct samples. We evaluate the effectiveness of various GCNNs, including Graph Attention Neural Network (GANN), Graph Sample and AggreGatE (GraphSAGE), Graph Isomorphism Network (GIN), and Relational Graph Convolutional Neural Network (RGCN). GANN and GraphSAGE demonstrate comparable performance, achieving an overall accuracy of 81% in classifying the MG states. Furthermore, these results underscore the potential of GCNNs to detect subtle structural variances in disordered materials and point to broader application of deep learning in the analysis of MGs and other amorphous substances.

36 MATERIALS SCIENCE↗
NASA NTRS1977

Is osmium chemically fractionated in the moon

An investigation was conducted involving the determination of Os in 53 highland samples from the Apollo 14-17 missions. The Os/Ir ratio was found to remain essentially constant at 1.05 as Os and Ir abundances vary over four orders of magnitude. The Os-Au and the Os-Ni correlation in highland samples is presented in graphs. The graphs show that the majority of highland samples have Os/Au and Os/Ni ratios somewhat below the cosmic value. But there is no reason to attribute this trend to a loss of Os by local processes, because two other refractory siderophiles, Ir and Re, show exactly the same trend. Results on more than 150 analyzed highland samples show that meteoritic groups of low (Ir, Re, Os)/Au ratio are much more common at the Apollo landing sites than are groups of high ratio.

Hertogen, J.↗
DOE OSTI2021

VariantStore: an index for large-scale genomic variant search

Abstract Efficiently scaling genomic variant search indexes to thousands of samples is computationally challenging due to the presence of multiple coordinate systems to avoid reference biases. We present VariantStore, a system that indexes genomic variants from multiple samples using a variation graph and enables variant queries across any sample-specific coordinate system. We show the scalability of VariantStore by indexing genomic variants from the TCGA project in 4 h and the 1000 Genomes project in 3 h. Querying for variants in a gene takes between 0.002 and 3 seconds using memory only 10% of the size of the full representation.

Pandey, Prashant↗
DOE OSTI2021

Discrete Graph Structure Learning for Forecasting Multiple Time Series

Time series forecasting is an extensively studied subject in statistics, economics, and computer science. Exploration of the correlation and causation among the variables in a multivariate time series shows promise in enhancing the performance of a time series model. When using deep neural networks as forecasting models, we hypothesize that exploiting the pairwise information among multiple (multivariate) time series also improves their forecast. If an explicit graph structure is known, graph neural networks (GNNs) have been demonstrated as powerful tools to exploit the structure. In this work, we propose learning the structure simultaneously with the GNN if the graph is unknown. We cast the problem as learning a probabilistic graph model through optimizing the mean performance over the graph distribution. The distribution is parameterized by a neural network so that discrete graphs can be sampled differentiably through reparameterization. Empirical evaluations show that our method is simpler, more efficient, and better performing than a recently proposed bilevel learning approach for graph structure learning, as well as a broad array of forecasting models, either deep or non-deep learning based, and graph or non-graph based.

Shang, Chao↗
DOE OSTI2022

Trajectory design via unsupervised probabilistic learning on optimal manifolds

Abstract This article illustrates the use of unsupervised probabilistic learning techniques for the analysis of planetary reentry trajectories. A three-degree-of-freedom model was employed to generate optimal trajectories that comprise the training datasets. The algorithm first extracts the intrinsic structure in the data via a diffusion map approach. We find that data resides on manifolds of much lower dimensionality compared to the high-dimensional state space that describes each trajectory. Using the diffusion coordinates on the graph of training samples, the probabilistic framework subsequently augments the original data with samples that are statistically consistent with the original set. The augmented samples are then used to construct conditional statistics that are ultimately assembled in a path planning algorithm. In this framework, the controls are determined stage by stage during the flight to adapt to changing mission objectives in real-time.

42 ENGINEERING↗
DOE OSTI2021

Trajectory Optimization via Unsupervised Probabilistic Learning On Manifolds

This report investigates the use of unsupervised probabilistic learning techniques for the analysis of hypersonic trajectories. The algorithm first extracts the intrinsic structure in the data via a diffusion map approach. Using the diffusion coordinates on the graph of training samples, the probabilistic framework augments the original data with samples that are statistically consistent with the original set. The augmented samples are then used to construct conditional statistics that are ultimately assembled in a path-planing algorithm. In this framework the controls are determined stage by stage during the flight to adapt to changing mission objectives in real-time. A 3DOF model was employed to generate optimal hypersonic trajectories that comprise the training datasets. The diffusion map algorithm identfied that data resides on manifolds of much lower dimensionality compared to the high-dimensional state space that describes each trajectory. In addition to the path-planing worflow we also propose an algorithm that utilizes the diffusion map coordinates along the manifold to label and possibly remove outlier samples from the training data. This algorithm can be used to both identify edge cases for further analysis as well as to remove them from the training set to create a more robust set of samples to be used for the path-planing process.

42 ENGINEERING↗
NASA NTRS1983

Observational Basis for Velocity Fields in Stellar Atmospheres, Workshop, Trieste, Italy, August-September 1982, Proceedings

Solar and stellar winds and mass-loss phenomena are discussed in reviews of recent observations and current theory. Topics examined include mass loss from the sun, the O-type stars, Wolf-Rayet stars, the Parker theory, B stars, T Tauri stars, Balmer line emission from Be stars, novae, symbiotic stars, planetary nebulae, and dwarf novae. Graphs, tables, diagrams, sample spectra, and extensive discussion on each contribution are provided.

Stalio, R.↗
NASA NTRS1987

Fabrication of imaging X-ray optics

The design, fabrication, and performance of optics for X-ray astronomy and laboratory applications are described and illustrated with diagrams, drawings, graphs, photographs, and sample images. Particular attention is given to the Wolter I telescope developed for spectroscopic observation of 8-30-A cosmic X-ray sources from a rocketborne X-ray Objective Grating Spectrometer; this instrument employs three nested paraboloid-hyperboloid mirrors of 5083 Al alloy, figured by diamond turning and covered with a thin coating of acrylic lacquer prior to deposition of a 40-nm-thick layer of Sn. In calibration tests at NASA Marshall, the FWHM of the line-spread function at 1.33 nm was found to be 240 microns, corresponding to 21 arcsec. Also presented are the results of reflectivity measurements on C and W multilayers sputtered on Si and fusion glass substrates.

Catura, R. C.↗
NASA NTRS1987

Quasar absorption lines and galaxy halos

The evolution of the halo environments of the Galaxy and of other galaxies at early epochs is discussed, summarizing the results of observations of quasar absorption lines obtained with the IUE satellite since its launch in 1978. Topics addressed include the Ly-alpha forest, nearby galaxies, displaced absorption systems, and systems with z(a) approximately equal to z(e). The data are presented in sample spectra and graphs and described in detail. It is suggested that definitive answers on the production of quasar absorption lines by the extended gaseous halos and/or disks of distant galaxies must await the higher-quality observational data to become available with the Hubble Space Telescope.

Bergeron, Jacqueline↗
NASA NTRS1987

Infrared emission from interstellar PAHs

The mid-IR absorption and Raman spectra of polycyclic aromatic hydrocarbons (PAHs) and the mechanisms determining them are reviewed, and the implications for observations of similar emission spectra in interstellar clouds are considered. Topics addressed include the relationship between PAHs and amorphous C, the vibrational spectroscopy of PAHs, the molecular emission process, molecular anharmonicity, and the vibrational quasi-continuum. Extensive graphs, diagrams, and sample spectra are provided, and the interstellar emission bands are attributed to PAHs with 20-30 C atoms on the basis of the observed 3.3/3.4-micron intensity ratios.

Allamandola, L. J.↗
NASA NTRS1987

Solar system radio astronomy at low frequencies

The planetary radio-astronomy observations obtained with the two Voyager spacecraft since their launch in 1977 are briefly characterized and illustrated with graphs, diagrams, and sample spectra. Topics addressed include the spacecraft designs and trajectories, the wavelength coverage of the radio instruments, the Io-controlled LF emission of Jupiter, the solar-wind effect on the Saturn kilometric radiation, the Saturn electrostatic discharges, and the use of the clocklike feature of the Uranus emission to measure the planet's rotation period.

Desch, M. D.↗
NASA NTRS1988

Spaceborne radar remote sensing: Applications and techniques

The operation and applications of spaceborne radars for terrestrial and planetary remote sensing are described in an introduction for advanced students and practicing scientists. Chapters are devoted to imaging radars, wave-surface interactions and geoscientific applications, real- and synthetic-aperture radars, end-to-end system design, SAR data processing, altimeters, and scatterometers. Extensive diagrams, drawings, graphs, photographs, and sample radar images are provided.

Elachi, Charles↗
NASA NTRS1988

Cataclysmic variables

Recent observations of cataclysmic variables (CVs) at different wavelengths are reviewed, with a focus on their implications for theoretical models. Consideration is given to disk CVs (the flux distribution of the disk and changes during dwarf-nova outbursts), magnetic CVs (flux distributions and components), and the underlying stars. Typical data are presented in graphs, tables, and sample spectra, and it is concluded that more detailed multiwavelength observations are needed to improve models of radiative transfer and viscosity effects in accretion disks.

Szkody, Paula↗
NASA NTRS2010

Request to Release CEV Orion TSP Images Acquired at AEDC Tunnel 9

This document reviews the images that are requested for release from the Temperature Sensitive Paint tests of the Crew Exploration Vehicle (CEV) Orion that were conducted at the Arnold Engineering Development Center wind tunnel. Included is a description of the data, sample images, and graphs showing (1) Thermocouple T history under the paint layer at the location where the I/Iref is provided, and the Surface I/Iref history over the thermocouple.

Norris, Joe↗