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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 163 records · Page 9

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NASA NTRS1973

Basic forest cover mapping using digitized remote sensor data and automated data processing techniques

Remote sensing equipment and automatic data processing techniques were employed as aids in the institution of improved forest resource management methods. On the basis of automatically calculated statistics derived from manually selected training samples, the feature selection processor of LARSYS selected, upon consideration of various groups of the four available spectral regions, a series of channel combinations whose automatic classification performances (for six cover types, including both deciduous and coniferous forest) were tested, analyzed, and further compared with automatic classification results obtained from digitized color infrared photography.

Coggeshall, M. E.↗

NASA NTRS1982

The intercrater plains of Mercury and the Moon: Their nature, origin and role in terrestrial planet evolution. Measurement and errors of crater statistics

Planetary imagery techniques, errors in measurement or degradation assignment, and statistical formulas are presented with respect to cratering data. Base map photograph preparation, measurement of crater diameters and sampled area, and instruments used are discussed. Possible uncertainties, such as Sun angle, scale factors, degradation classification, and biases in crater recognition are discussed. The mathematical formulas used in crater statistics are presented.

Leake, M. A.↗

DOE OSTI2021

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at s√ = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb -1 , collected in 2017–2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb -1 , collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2005

Adventures in Parallel Processing: Entry, Descent and Landing Simulation for the Genesis and Stardust Missions

This paper will describe the Entry, Descent and Landing simulation tradeoffs and techniques that were used to provide the Monte Carlo data required to approve entry during a critical period just before entry of the Genesis Sample Return Capsule. The same techniques will be used again when Stardust returns on January 15, 2006. Only one hour was available for the simulation which propagated 2000 dispersed entry states to the ground. Creative simulation tradeoffs combined with parallel processing were needed to provide the landing footprint statistics that were an essential part of the Go/NoGo decision that authorized release of the Sample Return Capsule a few hours before entry.

Lyons, Daniel T.↗

DOE OSTI2026

Measurement of muon antineutrino charged current - 0 meson scattering, using the NOvA Near Detector

Antineutrino interaction cross sections are, at present, poorly constrained, particularly regarding the role of multi-nucleon processes such as 2-particle 2-hole (2p2h) interactions. The associated crosssection systematic uncertainties represent a significant challenge for precision oscillation measurements, especially for the next generation of neutrino experiments such as DUNE. We present a new measurement of the muon antineutrino charged-current cross section without mesons in the final state, using the high-statistics data set of the NOvA Near Detector. The analysis employs a cut-based selection enhanced by machine learning techniques to isolate a high-purity sample dominated by quasielastic (QE) and 2p2h interactions. We present the cross section as a function of the kinetic energy and scattering angle of the outgoing muon. We also present measurements of more model-dependent kinematic variables such as the neutrino energy and momentum transfer, to better probe the underlying nuclear physics. The results are compared against various neutrino event generators to test the robustness of current interaction models.

Vockerodt, Kevin John [Ohio State U.; Queen Mary, ↗

NASA NTRS1978

Processing laser velocimeter high-speed burst counter data

The statistical calculations of the mean and potential bias errors are considered with respect to their applicability to the randomly sampled velocity data obtained from a laser velocimeter. Techniques for displaying the resulting data in the form of arrow plots, flow streamline plots, and contour maps are also discussed. A description is presented of the operation of a new hardware interface between the signal processing electronics and the computer. The interface has been constructed to make it possible to use recently developed data processing techniques for obtaining turbulent power spectra from laser velocimeter data. Additional capabilities which were built into the interface allow the measurement of the velocity vector for each particle passing through the laser velocimeter sample window. By processing the data with extended versions of the turbulent power spectra techniques, cross spectra, interactions between velocity magnitude fluctuations, and flow angle fluctuations may be investigated.

Meyers, J. F.↗

NASA NTRS1991

Dynamics of the 4-day wave in the Southern Hemisphere polar stratosphere

Horizontal wind and temperature data are employed to investigate the dynamics of the 4-day wave in the Southern Hemisphere polar stratosphere. They were derived from synoptic maps of satellite-measured brightness temperatures, which were generated using the fast Fourier synoptic mapping technique of Salby (1982). Circulation statistics from these data are compared to those from the NMC operational stratospheric analyses, demonstrating improvements afforded by detailed treatment of asynoptic sampling effects. The 40-day wave is isolated using temporally filtered data. Several events of wave growth and decay are observed in the upper stratosphere during August 1980. Derived zonal-mean and eddy statistics suggest that the 4-day wave results from an instability of the zonal-mean flow near 55-60S, at and above 1 mb. It is inferred from climatological data that the source of the instability is the 'double-jet' structure in the upper stratosphere and mesosphere.

Randel, William J.↗

NASA NTRS1998

The Marshall Automated Wind Algorithm for Geostationary Satellite Wind Applications

The Marshall Automated Wind (MAW) algorithm was developed over a decade ago in support of specialized studies of mesoscale meteorology. In recent years, the algorithm has been generalized to address global climate issues and other specific objectives related to NASA missions. The MAW algorithm uses a tracking scheme which minimizes image brightness temperature differences in a sequence of satellite images to determine feature displacement (winds). With the appropriate methodology accurate satellite derived winds can be obtained from visible, infrared, and water vapor imagery. Typical errors are less than 4 m/s but depend on the quality and control constraints used in post-processing. Key to this success is the judicious use of template size and search area used for tracking, image resolution and time sampling, and selection of appropriate statistical constraints which may vary with image type and desired application. The conference paper and subsequent poster will provide details of the technique and examples of its application.

Jedlovec, Gary J.↗

NASA NTRS1973

Multiple regression technique for Pth degree polynominals with and without linear cross products

A multiple regression technique was developed by which the nonlinear behavior of specified independent variables can be related to a given dependent variable. The polynomial expression can be of Pth degree and can incorporate N independent variables. Two cases are treated such that mathematical models can be studied both with and without linear cross products. The resulting surface fits can be used to summarize trends for a given phenomenon and provide a mathematical relationship for subsequent analysis. To implement this technique, separate computer programs were developed for the case without linear cross products and for the case incorporating such cross products which evaluate the various constants in the model regression equation. In addition, the significance of the estimated regression equation is considered and the standard deviation, the F statistic, the maximum absolute percent error, and the average of the absolute values of the percent of error evaluated. The computer programs and their manner of utilization are described. Sample problems are included to illustrate the use and capability of the technique which show the output formats and typical plots comparing computer results to each set of input data.

Davis, J. W.↗

NASA NTRS1977

Crop identification and area estimation by computer-aided analysis of Landsat data

This report describes the results of a study involving the use of computer-aided analysis techniques applied to Landsat MSS data for identification and area estimation of winter wheat in Kansas and corn and soybeans in Indiana. Key elements of the approach included use of aerial photography for classifier training, stratification of Landsat data and extension of training statistics to areas without training data, and classification of a systematic sample of pixels from each county. Major results and conclusions are: (1) Landsat data was adequate for accurate identification and area estimation of winter wheat in Kansas, but corn and soybean estimates for Indiana were less accurate; (2) computer-aided analysis techniques can be effectively used to extract crop identification information from Landsat MSS data, and (3) systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county as well as district and state levels.

Bauer, M. E.↗

DOE OSTI2023

Hierarchical reconstruction of 3D well-connected porous media from 2D exemplars using statistics-informed neural network

The relationships between porous microstructures and transport properties are of fundamental importance in various scientific and engineering applications. Due to the intricacy, stochasticity and heterogeneity of porous media, reliable characterization and modeling of transport properties often require a complete dataset of internal microstructure samples. However, it is often an unbearable cost to acquire sufficient 3D digital microstructures by purely using microscopic imaging systems. Herein this paper presents a machine learning-based technique to hierarchically reconstruct 3D well-connected porous microstructures from one isotropic or several anisotropic low-cost 2D exemplar(s). To compactly characterize the large-scale microstructural features, a Gaussian image pyramid is built for each 2D exemplar. Local morphology patterns are collected from the Gaussian image pyramids, and then they serve as the training data to embed the 2D morphological statistics into feed-forward neural networks at multiple length levels. By using a specially-developed morphology integration scheme, the 3D morphological statistics at different levels can be inferred from the statistics-informed neural networks. Gibbs sampling is adopted to hierarchically reconstruct 3D microstructures by using multi-level 3D morphological statistics, where the large-scale, regional and local morphological patterns are statistically generated and successively added to the same 3D random field. The proposed method is tested on a series of porous media with distinct morphologies, and the statistical equivalence between the reconstructed and the real microstructures is systematically evaluated by comparing morphological descriptors and transport properties. The results demonstrate that the proposed 2D-to-3D microstructure reconstruction method is a universal and efficient approach to generating morphologically and physically realistic samples of porous media.

42 ENGINEERING↗

NASA NTRSDate not supplied

Multiscale Modeling of Reconstructed Tricalcium Silicate using NASA Multiscale Analysis Tool

To study microstructure characteristics of cementitious materials hydrated in space; previously, cement binder formations were processed under microgravity conditions and was further compared against ground-based experiments. For accurate estimation of process-structure-property linkage, particularly on samples hydrated in the microgravity environment, it is desired to have a high-fidelity volumetric representation of the microstructure. However, owing to small sample size and high porosity of the space-returned samples, conventional experimental characterization techniques are not viable. Hence, a deep learning-based reconstruction algorithm was employed to obtain high fidelity 3D volumes from sparse high resolution 2D Scanning Electron Microscopy (SEM) images, as inputs to micromechanics-based modeling. This machine learning-based reconstruction methodology validated against low-order statistical descriptors, captured the microstructural topology of both sample types (ground, 1g and microgravity, μg). Due to the lack of gravity, hydration products of the samples processed in space differed from those processed-on ground. Such AI-generated virtual samples were analyzed in a multiscale recursive micromechanics approach using the NASA Multiscale Analysis Tool (NASMAT). Here, we present a methodology to rapidly integrate and evaluate these AI-generated volumes in NASMAT. The synthesized microstructural volumes are directly employed as Representative Volume Elements (RVEs) to preserve the fidelity (1 pixel = 0.54 m). Invariably, analysis of such largescale problems (5123 voxels) requires huge amount of computational resources. By taking advantage of the NASMAT architecture, we also focused on systematic multiscale integration of these AI-reconstructed virtual volumes to reduce the computational demands. In this work, this methodology is demonstrated on the ground-based, 1g samples. The estimated stiffness value of 15.90 GPa is comparable to experimentally obtained modulus of hydrated tricalcium silicate sample. The workflow presented here paves the way for utilizing the NASMAT tool to perform multiscale analyses of other multi-phase material systems using either 3D virtual datasets synthesized using AI or obtained via micro-CT.

Machine Learning↗

DOE OSTI2022

Primordial non-Gaussianity from the completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey II: measurements in Fourier space with optimal weights

ABSTRACT We present measurements of the local primordial non-Gaussianity parameter $f_{\mathrm{NL}}^\mathrm{local} $from the clustering of 343 708 quasars with redshifts 0.8 < z < 2.2 distributed over 4808 deg2 from the final data release (DR16) of the extended Baryon Acoustic Oscillation Spectroscopic Survey (eBOSS), the largest volume spectroscopic survey up to date. Our analysis is performed in Fourier space, using the power spectrum monopole at very large scales to constrain the scale-dependent halo bias. We demonstrate the robustness of our analysis pipeline with EZ-mock catalogues that simulate the eBOSS DR16 target selection. We carefully assess the impact of systematics on our measurement, exploiting a novel neural network scheme for cleaning the DR16 sample as well as test multiple contamination removal methods. We estimate the bias due to the overcorrection of the systematic removal to be sub-dominant compared to the statistical uncertainty. We find fNL = −12 ± 21 (68 per cent confidence) for the main clustering sample including quasars with redshifts between 0.8 and 2.2, after applying redshift weighting techniques, designed for non-Gaussianity measurement from large scales structure, to optimize our analysis, which improve our results by 37 per cent.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Monte Carlo Simulations of Crystal Defects in Open Ensembles

Zero- and two-dimensional crystal defects form in open statistical ensembles, such as the grand canonical, that are usually inaccessible with conventional simulation techniques. This longstanding challenge is overcome with a new Hamiltonian Monte Carlo method that samples energy-biased gradual transformations. In conclusion, the method enables free energy calculations for nonideal point defects and the direct prediction of finite-temperature interface structures.

Grain boundaries↗

NASA NTRS1989

A laboratory investigation into microwave backscattering from sea ice

The sources of scattering of artificial sea ice were determined, backscatter measurements semi-quantitatively were compared with theoretical predictions, and inexpensive polarimetric radars were developed for sea ice backscatter studies. A brief review of the dielectric properties of sea ice and of commonly used surface and volume scattering theories is presented. A description is provided of the backscatter measurements performed and experimental techniques used. The development of inexpensive short-range polarimetric radars is discussed. The steps taken to add polarimetric capability to a simple FM-W radar are considered as are sample polarimetric phase measurements of the radar. Ice surface characterization data and techniques are discussed, including computation of surface rms height and correlation length and air bubble distribution statistics. A method is also presented of estimating the standard deviation of rms height and correlation length for cases of few data points. Comparisons were made of backscatter measurements and theory. It was determined that backscatter from an extremely smooth saline ice surface at C band cannot be attributed only to surface scatter. It was found that snow cover had a significant influence on backscatter from extremely smooth saline ice at C band.

Bredow, Jonathan W.↗

DOE OSTI2023

Status of Error Correction Studies in Support of FFA@CEBAF

In this work, we examine the beam correction requirements for the FFA@CEBAF energy upgrade. Both hardware and software diagnostic and corrector components are under investigation; in particular the relationship between hardware and software optimization will be developed. To generate a representative sample of errors---from the machine lattice and other beam properties---we construct a Markov Chain Monte Carlo (MCMC) sampler which considers different probability distributions for different types of errors. This sample is used to investigate the statistical sensitivity of the beam to various diagnostic and corrective schema. Once statistics are acquired, we plan to use a variety of optimization techniques to minimize correction time for the electron beam in the FFA arcs designed for the CEBAF upgrade.

Benesch, J.↗

DOE OSTI2021

Detection Limits of Low-mass, Long-period Exoplanets Using Gaussian Processes Applied to HARPS-N Solar Radial Velocities

Radial velocity (RV) searches for Earth-mass exoplanets in the habitable zone around Sun-like stars are limited by the effects of stellar variability on the host star. In particular, suppression of convective blueshift and brightness inhomogeneities due to photospheric faculae/plage and starspots are the dominant contribution to the variability of such stellar RVs. Gaussian process (GP) regression is a powerful tool for statistically modeling these quasi-periodic variations. We investigate the limits of this technique using 800 days of RVs from the solar telescope on the High Accuracy Radial velocity Planet Searcher for the Northern hemisphere (HARPS-N) spectrograph. These data provide a well-sampled time series of stellar RV variations. Into this data set, we inject Keplerian signals with periods between 100 and 500 days and amplitudes between 0.6 and 2.4 m s{sup −1}. We use GP regression to fit the resulting RVs and determine the statistical significance of recovered periods and amplitudes. We then generate synthetic RVs with the same covariance properties as the solar data to determine a lower bound on the observational baseline necessary to detect low-mass planets in Venus-like orbits around a Sun-like star. Our simulations show that discovering planets with a larger mass (∼0.5 m s{sup −1}) using current-generation spectrographs and GP regression will require more than 12 yr of densely sampled RV observations. Furthermore, even with a perfect model of stellar variability, discovering a true exo-Venus (∼0.1 m s{sup −1}) with current instruments would take over 15 yr. Therefore, next-generation spectrographs and better models of stellar variability are required for detection of such planets.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Is Terzan 5 the remnant of a building block of the Galactic bulge? Evidence from APOGEE

ABSTRACT It has been proposed that the globular cluster-like system Terzan 5 is the surviving remnant of a primordial building block of the Milky Way bulge, mainly due to the age/metallicity spread and the distribution of its stars in the α–Fe plane. We employ Sloan Digital Sky Survey data from the Apache Point Observatory Galactic Evolution Experiment to test this hypothesis. Adopting a random sampling technique, we contrast the abundances of 10 elements in Terzan 5 stars with those of their bulge field counterparts with comparable atmospheric parameters, finding that they differ at statistically significant levels. Abundances between the two groups differ by more than 1σ in Ca, Mn, C, O, and Al, and more than 2σ in Si and Mg. Terzan 5 stars have lower [α/Fe] and higher [Mn/Fe] than their bulge counterparts. Given those differences, we conclude that Terzan 5 is not the remnant of a major building block of the bulge. We also estimate the stellar mass of the Terzan 5 progenitor based on predictions by the Evolution and Assembly of GaLaxies and their Environments suite of cosmological numerical simulations, concluding that it may have been as low as ∼3 × 108 M⊙ so that it was likely unable to significantly influence the mean chemistry of the bulge/inner disc, which is significantly more massive (∼1010 M⊙). We briefly discuss existing scenarios for the nature of Terzan 5 and propose an observational test that may help elucidate its origin.

79 ASTRONOMY AND ASTROPHYSICS↗