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Results for “interpretive analysis”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Laboratory studies, analysis, and interpretation of the spectra of hydrocarbons present in planetary atmospheres including cyanoacetylene, acetylene, propane, and ethane

Combining broadband Fourier transform spectrometers (FTS) from the McMath facility at NSO and from NRC in Ottawa and narrow band TDL data from the laboratories with computational physics techniques has produced a broad range of results for the study of planetary atmospheres. Motivation for the effort flows from the Voyager/IRIS observations and the needs of Voyager analysis for laboratory results. In addition, anticipation of the Cassini mission adds incentive to pursue studies of observed and potentially observable constituents of planetary atmospheres. Current studies include cyanoacetylene, acetylene, propane, and ethane. Particular attention is devoted to cyanoacetylen (H3CN) which is observed in the atmosphere of Titan. The results of a high resolution infrared laboratory study of the line positions of the 663, 449, and 22.5/cm fundamental bands are presented. Line position, reproducible to better than 5 MHz for the first two bands, are available for infrared astrophysical searches. Intensity and broadening studies are in progress. Acetylene is a nearly ubiquitous atmospheric constituent of the outer planets and Titan due to the nature of methane photochemistry. Results of ambient temperature absolute intensity measurements are presented for the fundamental and two two-quantum hotband in the 730/cm region. Low temperature hotband intensity and linewidth measurements are planned.

Blass, William E.↗
NASA NTRS1991

Analysis and interpretation of high energy cosmic rays measured on Spacelab-2

Under the contract with NASA's Marshall Space Flight Center (NAS8-32828) the University of Chicago designed, built and delivered the CRN instrument for flight in the Spacelab-2 configuration. The instrument was flown from July 29 to August 5, 1985 on the Space Shuttle Challenger. The performance of our experiment was entirely successful and we reached our scientific goals. The contract included funds for the first year of data analysis. Further data analysis was carried out under the grant NAGW-1311 which ran from January 1, 1988 through December 31, 1990, and on which we report. The final products of this grant are the published scientific papers with the results from the experiment. We attach copies of the papers that have been published to date, and which we consider the most important part of this report. However, in order to put them into context we give a brief account of the project as a whole for which the grant covered the final phase.

Mueller, Dietrich↗
DOE OSTI2022

Analysis of Interpretable Data Representations for 4D-STEM Using Unsupervised Learning

Abstract Understanding the structure of materials is crucial for engineering devices and materials with enhanced performance. Four-dimensional scanning transmission electron microscopy (4D-STEM) is capable of mapping nanometer-scale local crystallographic structure over micron-scale field of views. However, 4D-STEM datasets can contain tens of thousands of images from a wide variety of material structures, making it difficult to automate detection and classification of structures. Traditional automated analysis pipelines for 4D-STEM focus on supervised approaches, which require prior knowledge of the material structure and cannot describe anomalous or deviant structures. In this article, a pipeline for engineering 4D-STEM feature representations for unsupervised clustering using non-negative matrix factorization (NMF) is introduced. Each feature is evaluated using NMF and results are presented for both simulated and experimental data. It is shown that some data representations more reliably identify overlapping grains. Additionally, real space refinement is applied to identify spatially distinct sample regions, allowing for size and shape analysis to be performed. This work lays the foundation for improved analysis of nanoscale structural features in materials that deviate from expected crystallographic arrangement using 4D-STEM.

Bruefach, Alexandra (ORCID:0000000209323477)↗
NASA NTRS1986

Analysis and interpretation of the shocklike electrostatic noise observed during the AMPTE solar wind lithium releases

During the AMPTE (Active Magnetospheric Particle Tracer Explorers) solar wind lithium release on September 11, and again on September 20, 1984, an intense burst of electrostatic noise was observed near the upstream edge of the ion cloud. Comparisons with measurements by the IMP-6 and ISEE-1 spacecraft show that the spectrum and overall features of this noise are very similar to electrostatic noise observed at the Earth's bow shock. A stability analysis using realistic parameters shows that the electrostatic noise can be accounted for by an ion beam-plasma instability caused by the solar wind proton beam streaming through the nearly stationary lithium cloud. The growth rate of this instability is largest when the ion density and solar wind proton density are similar, which explains why the noise only occurs near the outer edge of the ion cloud. The similarity to the noise in the Earth's bow shock suggest that a shock may exist in the solar wind plasma flow upstream of the ion cloud. If the noise is associated with a shock, then it must be an electrostatic shock, since the ion cyclotron radii are too small for the existence of a MHD shock. Since the electrostatic instability occurs at phase velocities near the lithium thermal velocity, the electrostatic turbulence may play a role in heating the lithium ions and transferring momentum from the solar wind to the ion cloud.

Gurnett, D. A.↗
DOE OSTI2025

Development of a data-driven neural network model for electron thermal transport in NSTX

A data-driven electron thermal transport neural network (ETT-NN) model, trained on TRANSP interpretative analysis results of National Spherical Torus Experiment (NSTX), was developed to enable faster and more accurate ETT computation for spherical tokamaks (STs). The model incorporates both convolutional NNs and recurrent NNs, allowing it to simultaneously account for the spatial and temporal non-localities and multi-scale features of turbulent transport, which have been considered only in a limited manner in conventional models. The model was validated through interpretative analysis and predictive simulations using Tokamak Reactor Integrated Automated Suite for Simulation and Computation, demonstrating relatively high accuracy. Additionally, parameter scans were performed on test discharges known to exhibit specific turbulent modes, such as microtearing mode, trapped electron mode, kinetic ballooning mode, and electron temperature gradient mode. The scanning results revealed that the ETT-NN model exhibits the same trends as those observed in conventional gyrokinetic simulations or theories, while also capturing the global nature of turbulent transport, indicating that the data-driven model accurately reflects the underlying physical characteristics. Furthermore, due to the dimensionless nature of the model, we can feasibly expand its applicability by incorporating data from other devices and uncovering the characteristics of ETT in STs in the future.

NSTX↗
NASA NTRS1992

Data analysis and interpretation of lunar dust exosphere

The lunar horizon glow observed by Apollo astronauts and captured on film during the Surveyor mission is believed to result from the scattering of sunlight off lunar fines suspended in a dust layer over the lunar surface. For scale heights on the order of tens of kilometers, it is anticipated that the size of the dust particles will be small enough to admit Rayleigh scattering. Such events would result in scattered light which is polarized to a degree which is a function of observation angle and produce spectra containing large high frequency components ('bluing'). Believing these signatures to be observable from ground based telescopes, observational data has been collected from McDonald Observatory and the task of reduction and analysis of this data is the focus of the present report.

Andrews, George A., Jr.↗
NASA NTRS1993

Data analysis and interpretation of lunar dust exosphere

The lunar horizon glow observed by Apollo astronauts and recorded during the Surveyor missions is believed to result from the scattering of sunlight off lunar fines suspended in a dust layer above the lunar surface. For scale heights of tens of kilometers, theory and astronaut's observations suggest that the size of the dust particles will be smaller than 0.1 microns in radius and will act as Rayleigh scatters. This means that the dust scattered light will be 100 percent polarized at a 90 degree scattering angle and will depend on wavelength to the inverse fourth power ('bluing'). Believing these signatures to be observable from ground based telescopes, observational data in the form of CCD images has been collected from McDonald Observatory's 36 in. telescope, and the reduction and analysis of this data is the focus of the present report.

Andrews, George A., Jr.↗
NASA NTRS1990

Analysis and interpretation of Wide Field Planetary Camera outgas data collected in the temperature range from -20 C to -100 C

The data from the Wide Field Planetary Camera (WFPC) are analyzed to determine the absolute source-emission parameters and contaminant reemission parameters of outgassing mass accumulation. The data correspond to the mass accumulated on a -100 C quartz crystal microbalance and then desorbed at -50 C as a function of time. The parameters investigated include contaminant mass, first-order rate constants, and characteristic energies. The data are modeled in terms of a minimum number of species characterized by source-rate and reemission-rate parameters. The modeling technique is found to produce adequate fits, and the contaminants that accumulate at -100 C and desorb at -50 C do not accumulate at -50 C. The data analysis is found to be an adequate technique for assessing outgassing parameters for the prediction of WFPC internal contamination.

Barengoltz, Jack B.↗
DOE OSTI2023

Microscopic theory, analysis, and interpretation of conductance histograms in molecular junctions

Molecular electronics break-junction experiments are widely used to investigate fundamental physics and chemistry at the nanoscale. Reproducibility in these experiments relies on measuring conductance on thousands of freshly formed molecular junctions, yielding a broad histogram of conductance events. Experiments typically focus on the most probable conductance, while the information content of the conductance histogram has remained unclear. Here we develop a microscopic theory for the conductance histogram by merging the theory of force-spectroscopy with molecular conductance. The procedure yields analytical equations that accurately fit the conductance histogram of a wide range of molecular junctions and augments the information content that can be extracted from them. Our formulation captures contributions to the conductance dispersion due to conductance changes during the mechanical elongation inherent to the experiments. In turn, the histogram shape is determined by the non-equilibrium stochastic features of junction rupture and formation. The microscopic parameters in the theory capture the junction’s electromechanical properties and can be isolated from separate conductance and rupture force (or junction-lifetime) measurements. The predicted behavior can be used to test the range of validity of the theory, understand the conductance histograms, design molecular junction experiments with enhanced resolution and molecular devices with more reproducible conductance properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

DeepDataProfiler: A Platform and Methodology for the Analysis and Interpretation of Neural Networks

The DeepDataProfiler is a methodology and framework for providing interpretability to trained neural networks. Its approach is to decompose a network into a weighted graph of neurons and synapses and link the components of the graph to human identifiable concepts. By identifying concepts important to the network and tracking the decision process employed by the network, the network becomes more transparent and less like a black box. Spurious decisions and poor generalization strategies can be identified and a measure of trustworthiness can be established.

97 MATHEMATICS AND COMPUTING↗