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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A reference-area-free strain mapping method using precession electron diffraction data

Here, in this work, we developed a method using precession electron diffraction data to map the residual elastic strain at the nano-scale. The diffraction pattern of each pixel was first collected and denoised. Template matching was then applied using the center spot as the mask to identify the positions of the diffraction disks. Statistics of distances between the selected diffracted disks enable the user to make an informed decision on the reference and to generate strain maps. Strain mapping on an unstrained single crystal sapphire shows the standard deviation of strain measurement is 0.5%. With this method, we were able to successfully measure and map the residual elastic strain in VO 2 on sapphire and martensite in a Ni 50.3 Ti 29.7 Hf 20 shape memory alloy. This approach does not require the user to select a “strain-free area” as a reference and can work on datasets even with the crystals oriented away from zone axes. This method is expected to provide a robust and more accessible alternative means of studying the residual strain of various material systems that complements the existing algorithms for strain mapping.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Slow Electron Holes in the Earth's Magnetosheath

Here, we present a statistical analysis of electrostatic solitary waves observed aboard Magnetospheric Multiscale spacecraft in the Earth's magnetosheath. Applying single-spacecraft interferometry to several hundred solitary waves collected in about 2-minute interval, we show that almost all of them have the electrostatic potential of positive polarity and propagate quasi-parallel to the local magnetic field with plasma frame velocities of the order of 100 km/s. The solitary waves have typical parallel half-widths from 10 to 100 m that is between 1 and 10 Debye lengths and typical amplitudes of the electrostatic potential from 10 to 200 mV that is between 0.01% and 1% of local electron temperature. The solitary waves are associated with quasi-Maxwellian ion velocity distribution functions, and their plasma frame velocities are comparable with ion thermal speed and well below electron thermal speed. We argue that the solitary waves of positive polarity are slow electron holes and estimate the time scale of their acceleration, which occurs due to interaction with ions, to be of the order of one second. The observation of slow electron holes indicates that their lifetime was shorter than the acceleration time scale. We argue that multi-spacecraft interferometry applied previously to these solitary waves is not applicable because of their too-short spatial scales. The source of the slow electron holes and the role in electron-ion energy exchange remain to be established.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Using Temporal Deep Learning Models to Estimate Daily Snow Water Equivalent Over the Rocky Mountains

Abstract In this study we construct and compare three different deep learning (DL) models for estimating daily snow water equivalent (SWE) from high‐resolution gridded meteorological fields over the Rocky Mountain region. To train the DL models, Snow Telemetry (SNOTEL) station‐based SWE observations are used as the prediction target. All DL models produce higher median Nash‐Sutcliffe Efficiency (NSE) values than a conceptual SWE model and interpolated gridded data sets, although mean squared errors also tend to be higher. Sensitivity of the SWE prediction to the model's input variables is analyzed using an explainable artificial intelligence (XAI) method, yielding insight into the physical relationships learned by the models. This method reveals the dominant role precipitation and temperature play in snowpack dynamics. In applying our models to estimate SWE throughout the Rocky Mountains, an extrapolation problem arises since the statistical properties of SWE (e.g., annual maximum) and geographical properties of individual grid points (e.g., elevation) differ from the training data. This problem is solved by normalizing the SWE with its historical maximum value to alleviate extrapolation for all tested DL models. Our work shows that the DL models are promising tools for estimating SWE, and sufficiently capture relevant physical relationships to make them useful for spatial and temporal extrapolation of SWE values.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Measurement of ambient radon progeny decay rates and energy spectra in liquid argon using the MicroBooNE detector

We report measurements of radon progeny in liquid argon within the MicroBooNE time projection chamber (LArTPC). The presence of specific radon daughters in MicroBooNE’s 85 metric tons of active liquid argon bulk is probed with newly developed charge-based low-energy reconstruction tools and analysis techniques to detect correlated Bi 214 − Po 214 radioactive decays. Special datasets taken during periods of active radon doping enable new demonstrations of the calorimetric capabilities of single-phase neutrino LArTPCs for β and α particles with electron-equivalent energies ranging from 0.1 to 3.0 MeV. By applying Bi 214 − Po 214 detection algorithms to data recorded over a 46-day period, no statistically significant presence of radioactive Bi 214 is detected, and a limit on the activity is placed at < 0.35 mBq / kg at the 95% confidence level. This bulk Bi 214 radiopurity limit—the first ever reported for a liquid argon detector incorporating liquid-phase purification—is then further discussed in relation to the targeted upper limit of 1 mBq / kg on bulk Rn 222 activity for the DUNE neutrino detector. Published by the American Physical Society 2024

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Emergent Ergodicity at the Transition between Many-Body Localized Phases

Strongly disordered systems in the many-body localized (MBL) phase can exhibit ground state order in highly excited eigenstates. The interplay between localization, symmetry, and topology has led to the characterization of a broad landscape of MBL phases ranging from spin glasses and time crystals to symmetry protected topological phases. Understanding the nature of phase transitions between these different forms of eigenstate order remains an essential open question. In this work, we conjecture that no direct transition between distinct MBL orders can occur in one dimension; rather, an ergodic phase always intervenes. Motivated by recent advances in Rydberg-atom-based quantum simulation, we propose an experimental protocol where the intervening ergodic phase can be diagnosed via the dynamics of local observables.

1-dimensional spin chains↗
DOE OSTI2025

Measurement of Atmospheric Neutrino Oscillation Parameters Using Convolutional Neural Networks with 9.3 Years of Data in IceCube DeepCore

The DeepCore subdetector of the IceCube Neutrino Observatory provides access to neutrinos with energies above approximately 5 GeV. Data taken between 2012 and 2021 (3387 days) are utilized for an atmospheric ν μ disappearance analysis that studied 150 257 neutrino-candidate events with reconstructed energies between 5 and 100 GeV. An advanced reconstruction based on a convolutional neural network is applied, providing increased signal efficiency and background suppression, resulting in a measurement with both significantly increased statistics compared to previous DeepCore oscillation results and high neutrino purity. For the normal neutrino mass ordering, the atmospheric neutrino oscillation parameters and their 1 σ errors are measured to be Δ m 32 2 = 2.40 − 0.04 + 0.05 × 10 − 3 eV 2 and sin 2 θ 23 = 0.54 − 0.03 + 0.04 . The results are the most precise to date using atmospheric neutrinos, and are compatible with measurements from other neutrino detectors including long-baseline accelerator experiments. Published by the American Physical Society 2025

Abbasi, R.↗
DOE OSTI2020

A Shift Selection Strategy for Parallel Shift-invert Spectrum Slicing in Symmetric Self-consistent Eigenvalue Computation

The central importance of large-scale eigenvalue problems in scientific computation necessitates the development of massively parallel algorithms for their solution. Recent advances in dense numerical linear algebra have enabled the routine treatment of eigenvalue problems with dimensions on the order of hundreds of thousands on the world’s largest supercomputers. In cases where dense treatments are not feasible, Krylov subspace methods offer an attractive alternative due to the fact that they do not require storage of the problem matrices. However, demonstration of scalability of either of these classes of eigenvalue algorithms on computing architectures capable of expressing massive parallelism is non-trivial due to communication requirements and serial bottlenecks, respectively. In this work, we introduce the SISLICE method: a parallel shift-invert algorithm for the solution of the symmetric self-consistent field (SCF) eigenvalue problem. The SISLICE method drastically reduces the communication requirement of current parallel shift-invert eigenvalue algorithms through various shift selection and migration techniques based on density of states estimation and k-means clustering, respectively. This work demonstrates the robustness and parallel performance of the SISLICE method on a representative set of SCF eigenvalue problems and outlines research directions that will be explored in future work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Improving MicroBooNE's Inclusive Single-Photon Search with Low-Energy Hadronic Identification

This analysis aims to further investigate MicroBooNE’s inclusive single-photon search results, which reported a 2.2$\sigma$ excess below 600 MeV in shower energy for events with no reconstructed protons using roughly half of MicroBooNE's dataset. Taken together with MiniBooNE’s long-standing low-energy excess and MicroBooNE’s recent electron-like search results showing no observable excess with respect to Standard Model predictions, this result provides strong impetus for expanded exploration of the single-photon channel in Fermilab’s short-baseline liquid-argon time projection chamber (LArTPC) experiments. By identifying and classifying isolated MeV-scale energy depositions, or blips, in the vicinity of single-photon events selected by the Wire-Cell reconstruction framework, we establish a more comprehensive labeling scheme for nearby hadronic content. In particular, blips found backwards along the shower axis indicate the presence of previously-unidentified final-state protons, while elevated blip counts at wide angles signal the presence of final-state neutrons. By applying this new technique to its full dataset, MicroBooNE will perform a purer and higher-statistics test of the truly isolated nature of its modest photon-like excess, furthering its hunt for the presence of unexpected new physics beyond the Standard Model.

Andrade Aldana, Diego [Los Alamos; IIT, Chicago (m↗
NASA NTRS1972

Flow direction determination of lava flows.

The flow direction technique, previously applied to ash-flow sheets, can be used to determine direction of movement and locate eruptive centers for lava flows. The method provides statistically stronger and more consistent flow direction data for lava than ash-flow tuff. The accuracy and reliability of the technique was established on the porphyritic basaltic andesite of Mount Taylor, New Mexico, which erupted from a known center, the Mount Taylor Amphitheater. The technique was then applied to volcanic units with unknown sources: the John Kerr Peak Quartz Latite and mid-Tertiary andesite flows in the Mogollon Mountains, both in southwestern New Mexico. The flow direction technique indicated flow patterns and suggested source areas for each rock unit. In the Mogollon Mountains flow direction measurements were supported by independent directional criteria such as dips of cross beds, stratigraphic thickening, facies changes, and megascopic textures.-

Smith, E. I.↗
NASA NTRS1974

Parameter estimation using an a posteriori criterion

A procedure for estimating noise statistics as well as system model parameters, based on a maximum likelihood criterion, has been successfully applied to a number of aircraft parameter-identification problems. In the present investigation, an a posteriori criterion is examined for use in such an application, when it is desired to model process noise. The criteria lead to identical results when there is no process noise.

Bach, R. E., Jr.↗
NASA NTRS1975

Mathematical techniques: A compilation

Articles on theoretical and applied mathematics are introduced. The articles cover information that might be of interest to workers in statistics and information theory, computational aids that could be used by scientists and engineers, and mathematical techniques for design and control.

Source record↗
NASA NTRS1976

Time-dependent MOS breakdown

A general model for time-dependent breakdown in metal-oxide-silicon (MOS) structures is developed and related to experimental measurements on samples deliberately contaminated with Na. A statistical method is used for measuring the breakdown probability as a function of log time and applied field. It is shown that three time regions of breakdown can be explained respectively in terms of silicon surface defects, ion emission from the metal interface, and lateral ion diffusion at the silicon interface.

Li, S. P.↗
NASA NTRS1976

Sample size and sampling errors as the source of dispersion in chemical analyses

The paper describes a Monte Carlo model for simulation of two-dimensional representations of thin sections of some of the more common igneous rock textures. These representations are extrapolated to three dimensions to develop a volume of 'rock'. The model (here applied to a medium-grained high-Ti basalt) can be used to determine a statistically significant sample for a lunar rock or to predict the probable errors in the oxide contents that can occur during the analysis of a sample that is not representative of the parent rock.

Clanton, U. S.↗
NASA NTRS1980

Construction and application of a questionnaire for the social scientific investigation of environmental noise effects

A social psychological questionnair has been developed to study the effects of environmental noise and was applied to 636 people living in 19 different areas of Hamburg. The theoretical foundations and the statistical means employed in its development are described. Four main reactions to noise are isolated statistically, and it is determined that these are moderated by several intervening variables, chief of which are coping capacity for noise, the perceived dangerousness of the noise souce, other daily loads and the individual's liability.

Guski, R.↗
NASA NTRS1989

Model atmospheres for SN 1987A and the distance to the Large Magellanic Cloud

A code which simultaneously solves the non-LTE equations of statistical equilibrium and the time-independent equation of radiation transport in an expanding atmosphere is applied to analyze the spectrum of SN 1987A. The behavior of a model atmosphere in which the density structure is a power-law function of radius has been studied and compared closely with SN 1987A data. This model atmosphere is used to derive corrections to the expanding photosphere method for determining distances to supernovae. The distance to the Large Magellanic Cloud derived from SN 1987A observations by this 'custom yardstick' is 49 + or - 6 kpc in excellent accord with results for RR Lyrae stars and for Cepheids. This empirical test of the expanding photosphere method provides the basis for hope that it may make a significant contribution to the extragalactic distance scale at cosmologically interesting distances.

Eastman, Ronald G.↗
NASA NTRS1990

Nimbus 7 SMMR precipitation observations calibrated against surface radar during TAMEX

This paper compares recent (Petty and Katsaros, 1990) satellite passive microwave observations of tropical cloud clusters over the South China Sea, using the 37-GHz channels of the Nimbus-7 SMMR, to the surface digital radar observations of oceanic precipitation during the Taiwan Area Mesoscale Experiment (TAMEX) conducted in May and June, 1987 (Kuo and Chen, 1990). The data confirm the existence of useful statistical relationships between surface rainfall parameters and satellite microwave observations. It is suggested that the approach applied in this study can be expanded to include other microwave frequencies (for example, the 19- and 85-GHz channels of the SSM/I)

Petty, Grant W.↗
NASA NTRS1993

Properties of high-redshift Lyman-alpha clouds. I - Statistical analysis of the Schneider-Schmidt-Gunn quasars

Techniques for statistical analysis of the Lyman-alpha forest in high-redshift quasars are developed, and applied to the low-resolution (25 A) spectra of 29 of the 33 quasars in the Schneider-Schmidt-Gunn sample. We extrapolate each quasar's continuum shortward of Lyman-alpha emission, then consider each spectral bin of each quasar to be an (approximately) independent measurement of the absorption due to the Lyman-alpha clouds. With several thousand such measurements thus available, we can obtain good determinations of some interesting properties of clouds in the redshift range 2.5-4.3 without actually resolving any single cloud. We find that the mean absorption increases with z approximately as a power law (1 + z) exp (gamma + 1) with gamma = 2.46 +/- 0.37. The mean ratio of Lyman-alpha to Lyman-beta absorption in the clouds is 0.476 +/- 0.054. We also detect, and obtain ratios, for Lyma-gamma, delta, and possibly epsilon.

Press, William H.↗
NASA NTRS1992

Fault detection and diagnosis using neural network approaches

Neural networks can be used to detect and identify abnormalities in real-time process data. Two basic approaches can be used, the first based on training networks using data representing both normal and abnormal modes of process behavior, and the second based on statistical characterization of the normal mode only. Given data representative of process faults, radial basis function networks can effectively identify failures. This approach is often limited by the lack of fault data, but can be facilitated by process simulation. The second approach employs elliptical and radial basis function neural networks and other models to learn the statistical distributions of process observables under normal conditions. Analytical models of failure modes can then be applied in combination with the neural network models to identify faults. Special methods can be applied to compensate for sensor failures, to produce real-time estimation of missing or failed sensors based on the correlations codified in the neural network.

Kramer, Mark A.↗