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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Atomic Resolution Cryogenic 4D-STEM Imaging via Robust Distortion Correction

Cryogenic four-dimensional scanning transmission electron microscopy (4D-STEM) imaging is a useful technique for studying quantum materials and their interfaces by simultaneously probing charge, lattice, spin, and chemistry on the atomic scale with the sample held at temperatures ranging from room to cryogenic. However, its applications are currently limited by the instabilities of cryo-stages and electronics. To overcome this challenge, we develop an algorithm to effectively correct the complex distortions present in atomic resolution cryogenic 4D-STEM data sets. This method uses nonrigid registration to identify localized distortions in a 4D-STEM and relate them to an undistorted experimental STEM image, followed by a series of affine transformations for distortion corrections. This method allows a minimum loss of information in both reciprocal and real spaces, enabling the reconstruction of sample information from 4D-STEM data sets. This method is computationally cheap, fast, and applicable for on-the-fly data analysis in future in situ cryogenic 4D-STEM experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Radial quasiballistic transport in time-domain thermoreflectance studied using Monte Carlo simulations

Recently, a pump beam size dependence of thermal conductivity was observed in Si at cryogenic temperatures using time-domain thermal reflectance (TDTR). These observations were attributed to quasiballistic phonon transport, but the interpretation of the measurements has been semi-empirical. Here, we present a numerical study of the heat conduction that occurs in the full 3D geometry of a TDTR experiment, including an interface, using the Boltzmann transport equation. We identify the radial suppression function that describes the suppression in heat flux, compared to Fourier's law, that occurs due to quasiballistic transport and demonstrate good agreement with experimental data. We also discuss unresolved discrepancies that are important topics for future study.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Forward fitting of experimental data from a NE213 neutron detector installed with the magnetic proton recoil upgraded spectrometer at JET

In this paper, we present the results obtained from the data analysis of neutron spectra measured with a NE213 liquid scintillator at JET. We calculated the neutron response matrix of the instrument combining MCNPX simulations, a generic proton light output function measured with another detector and the fit of data from ohmic pulses. For the analysis, we selected a set of pulses with neutral beam injection heating (NBI) only and we applied a forward fitting procedure of modeled spectral components to extract the fraction of thermal neutron emission. The results showed the same trend of the ones obtained with the dedicated spectrometer TOFOR, even though the values from the NE213 analysis were systematically higher. This discrepancy is probably due to the different lines of sight of the two spectrometers (tangential for the NE213, vertical for TOFOR). The uncertainties on the thermal fraction estimates were from 4 to 7 times higher than the ones from the TOFOR analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Investigation and quantification of nonlinearity using surrogate data in a glow discharge plasma

Detection of nonlinearity has been carried out in periodic and aperiodic floating potential fluctuations of DC glow discharge plasma by generating surrogate data using iterative amplitude adjusted Fourier transform method. We introduce “delay vector variance” analysis (DVV) for the first time, which allows reliable detection of nonlinearity and provides some easy to interpret diagram conveying information about the nature of the experimental floating potential fluctuations (FPF). The method of false nearest neighbourhood is deployed on the FPF's to find a good embedding so as to be acquainted with the precise knowledge of m, which is desirable for carrying out DVV analysis. The emergence of nonlinearity with increase in discharge voltage has been ensured by taking into consideration the total energy present in different band of frequencies excited due to nonlinear processes. Rejection of null hypothesis has been verified by performing the rank test method that confirms the presence of nonlinearity quantitatively.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2012

SURVIVAL DEPTH OF ORGANICS IN ICES UNDER LOW-ENERGY ELECTRON RADIATION ({<=}2 keV)

Icy surfaces in our solar system are continually modified and sputtered with electrons, ions, and photons from solar wind, cosmic rays, and local magnetospheres in the cases of Jovian and Saturnian satellites. In addition to their prevalence, electrons specifically are expected to be a principal radiolytic agent on these satellites. Among energetic particles (electrons and ions), electrons penetrate by far the deepest into the ice and could cause damage to organic material of possible prebiotic and even biological importance. To determine if organic matter could survive and be detected through remote sensing or in situ explorations on these surfaces, such as water ice-rich Europa, it is important to obtain accurate data quantifying electron-induced chemistry and damage depths of organics at varying incident electron energies. Experiments reported here address the quantification issue at lower electron energies (100 eV-2 keV) through rigorous laboratory data analysis obtained using a novel methodology. A polycyclic aromatic hydrocarbon molecule, pyrene, embedded in amorphous water ice films of controlled thicknesses served as an organic probe. UV-VIS spectroscopic measurements enabled quantitative assessment of organic matter survival depths in water ice. Eight ices of various thicknesses were studied to determine damage depths more accurately. The electron damage depths were found to be linear, approximately 110 nm keV{sup -1}, in the tested range which is noticeably higher than predictions by Monte Carlo simulations by up to 100%. We conclude that computational simulations underestimate electron damage depths in the energy region {<=}2 keV. If this trend holds at higher electron energies as well, present models utilizing radiation-induced organic chemistry in icy solar system bodies need to be revisited. For interstellar ices of a few micron thicknesses, we conclude that low-energy electrons generated through photoionization processes in the interstellar medium could penetrate through ice grains significantly and trigger organic reactions several hundred nanometers deep-bulk chemistry thus competing with surface chemistry of astrophysical ice grains.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

MODELING ATMOSPHERIC EMISSION FOR CMB GROUND-BASED OBSERVATIONS

Atmosphere is one of the most important noise sources for ground-based cosmic microwave background (CMB) experiments. By increasing optical loading on the detectors, it amplifies their effective noise, while its fluctuations introduce spatial and temporal correlations between detected signals. We present a physically motivated 3D-model of the atmosphere total intensity emission in the millimeter and sub-millimeter wavelengths. We derive a new analytical estimate for the correlation between detectors time-ordered data as a function of the instrument and survey design, as well as several atmospheric parameters such as wind, relative humidity, temperature and turbulence characteristics. Using an original numerical computation, we examine the effect of each physical parameter on the correlations in the time series of a given experiment. We then use a parametric-likelihood approach to validate the modeling and estimate atmosphere parameters from the polarbear-i project first season data set. We derive a new 1.0% upper limit on the linear polarization fraction of atmospheric emission. We also compare our results to previous studies and weather station measurements. The proposed model can be used for realistic simulations of future ground-based CMB observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

The five planets in the Kepler-296 binary system all orbit the primary: A Statistical and analytical analysis

Kepler-296 is a binary star system with two M-dwarf components separated by 0.″2. Five transiting planets have been confirmed to be associated with the Kepler-296 system; given the evidence to date, however, the planets could in principle orbit either star. This ambiguity has made it difficult to constrain both the orbital and physical properties of the planets. Using both statistical and analytical arguments, this paper shows that all five planets are highly likely to orbit the primary star in this system. We performed a Markov-Chain Monte Carlo simulation using a five transiting planet model, leaving the stellar density and dilution with uniform priors. Using importance sampling, we compared the model probabilities under the priors of the planets orbiting either the brighter or the fainter component of the binary. A model where the planets orbit the brighter component, Kepler-296A, is strongly preferred by the data. Combined with our assertion that all five planets orbit the same star, the two outer planets in the system, Kepler-296 Ae and Kepler-296 Af, have radii of 1.53 ± 0.26 and 1.80 ± 0.31 R{sub ⊕}, respectively, and receive incident stellar fluxes of 1.40 ± 0.23 and 0.62 ± 0.10 times the incident flux the Earth receives from the Sun. This level of irradiation places both planets within or close to the circumstellar habitable zone of their parent star.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

SPITZER IRAC COLOR DIAGNOSTICS FOR EXTENDED EMISSION IN STAR-FORMING REGIONS

The infrared data from the Spitzer Space Telescope are an invaluable tool for identifying physical processes in star formation. In this study, we calculate the Infrared Array Camera (IRAC) color space of UV fluorescent H{sub 2} and polycyclic aromatic hydrocarbon (PAH) emission in photodissociation regions (PDRs) using the Cloudy code with PAH opacities from Draine and Li. We create a set of color diagnostics that can be applied to study the structure of PDRs and to distinguish between FUV-excited and shock-excited H{sub 2} emission. To test this method, we apply these diagnostics to Spitzer IRAC data of NGC 2316. Our analysis of the structure of the PDR is consistent with previous studies of the region. In addition to UV excited emission, we identify shocked gas that may be part of an outflow originating from the cluster.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Source scaling comparison and validation in Central Italy: data intensive direct S waves versus the sparse data coda envelope methodology

SUMMARY Robustness of source parameter estimates is a fundamental issue in understanding the relationships between small and large events; however, it is difficult to assess how much of the variability of the source parameters can be attributed to the physical source characteristics or to the uncertainties of the methods and data used to estimate the values. In this study, we apply the coda method by Mayeda et al. using the coda calibration tool (CCT), a freely available Java-based code (https://github.com/LLNL/coda-calibration-tool) to obtain a regional calibration for Central Italy for estimating stable source parameters. We demonstrate the power of the coda technique in this region and show that it provides the same robustness in source parameter estimation as a data-driven methodology [generalized inversion technique (GIT)], but with much fewer calibration events and stations. The Central Italy region is ideal for both GIT and coda approaches as it is characterized by high-quality data, including recent well-recorded seismic sequences such as L'Aquila (2009) and Amatrice–Norcia–Visso (2016–2017). This allows us to apply data-driven methods such as GIT and coda-based methods that require few, but high-quality data. The data set for GIT analysis includes ∼5000 earthquakes and more than 600 stations, while for coda analysis we used a small subset of 39 events spanning 3.5 < Mw < 6.33 and 14 well-distributed broad-band stations. For the common calibration events, as well as an additional 247 events (∼1.7 < Mw < ∼5.0) not used in either calibration, we find excellent agreement between GIT-derived and CCT-derived source spectra. This confirms the ability of the coda approach to obtain stable source parameters even with few calibration events and stations. Even reducing the coda calibration data set by 75 per cent, we found no appreciable degradation in performance. This validation of the coda calibration approach over a broad range of event size demonstrates that this procedure, once extended to other regions, represents a powerful tool for future routine applications to homogeneously evaluate robust source parameters on a national scale. Furthermore, the coda calibration procedure can homogenize the Mw estimates for small and large events without the necessity of introducing any conversion scale between narrow-band measures such as local magnitude (ML) and Mw, which has been shown to introduce significant bias.

Morasca, Paola (ORCID:0000000265254867)↗
DOE OSTI2023

DSPS: Differentiable stellar population synthesis

ABSTRACT Models of stellar population synthesis (SPS) are the fundamental tool that relates the physical properties of a galaxy to its spectral energy distribution (SED). In this paper, we present DSPS: a python package for SPS. All of the functionality in DSPS is implemented natively in the JAX library for automatic differentiation, and so our predictions for galaxy photometry are fully differentiable, and directly inherit the performance benefits of JAX, including portability onto GPUs. DSPS also implements several novel features, such as i) a flexible empirical model for stellar metallicity that incorporates correlations with stellar age, ii) support for the Diffstar model that provides a physically-motivated connection between the star formation history of a galaxy (SFH) and the mass assembly of its underlying dark matter halo. We detail a set of theoretical techniques for using autodiff to calculate gradients of predictions for galaxy SEDs with respect to SPS parameters that control a range of physical effects, including SFH, stellar metallicity, nebular emission, and dust attenuation. When forward modelling the colours of a synthetic galaxy population, we find that DSPS can provide a factor of 5 speed-up over standard SPS codes on a CPU, and a factor of 300-400 on a modern GPU. When coupled with gradient-based techniques for optimization and inference, DSPS makes it practical to conduct expansive likelihood analyses of simulation-based models of the galaxy–halo connection that fully forward model galaxy spectra and photometry.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Atomic data and spectral modeling constraints from high-resolution X-ray observations of the Perseus cluster with Hitomi

Here, the Hitomi Soft X-ray Spectrometer spectrum of the Perseus cluster, with ~5 eV resolution in the 2–9 keV band, offers an unprecedented benchmark of the atomic modeling and database for hot collisional plasmas. It reveals both successes and challenges of the current atomic data and models. The latest versions of AtomDB/APEC (3.0.8), SPEX (3.03.00), and CHIANTI (8.0) all provide reasonable fits to the broad-band spectrum, and are in close agreement on best-fit temperature, emission measure, and abundances of a few elements such as Ni. For the Fe abundance, the APEC and SPEX measurements differ by 16%, which is 17 times higher than the statistical uncertainty. This is mostly attributed to the differences in adopted collisional excitation and dielectronic recombination rates of the strongest emission lines. We further investigate and compare the sensitivity of the derived physical parameters to the astrophysical source modeling and instrumental effects. The Hitomi results show that accurate atomic data and models are as important as the astrophysical modeling and instrumental calibration aspects. Substantial updates of atomic databases and targeted laboratory measurements are needed to get the current data and models ready for the data from the next Hitomi-level mission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Feature-agnostic metabolomics for determining effective subcytotoxic doses of common pesticides in human cells

Although classical molecular biology assays can provide a measure of cellular response to chemical challenges, they rely on a single biological phenomenon to infer a broader measure of cellular metabolic response. These methods do not always afford the necessary sensitivity to answer questions of subcytotoxic effects, nor do they work for all cell types. Likewise, boutique assays such as cardiomyocyte beat rate may indirectly measure cellular metabolic response, but they too, are limited to measuring a specific biological phenomenon and are often limited to a single cell type. For these reasons, toxicological researchers need new approaches to determine metabolic changes across various doses in differing cell types, especially within the low-dose regime. Here, the data collected herein demonstrate that LC-MS/MS-based untargeted metabolomics with a feature-agnostic view of the data, combined with a suite of statistical methods including an adapted environmental threshold analysis, provides a versatile, robust, and holistic approach to directly monitoring the overall cellular metabolomic response to pesticides. When employing this method in investigating two different cell types, human cardiomyocytes and neurons, this approach revealed separate subcytotoxic metabolomic responses at doses of 0.1 and 1 µM of chlorpyrifos and carbaryl. These findings suggest that this agnostic approach to untargeted metabolomics can provide a new tool for determining effective dose by metabolomics of chemical challenges, such as pesticides, in a direct measurement of metabolomic response that is not cell type-specific or observable using traditional assays.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Dark Matter Search in a Proton Beam Dump with MiniBooNE

The MiniBooNE-DM Collaboration searched for vector-boson mediated production of dark matter using the Fermilab 8-GeV Booster proton beam in a dedicated run with 1.86 × 10 20 protons delivered to a steel beam dump. The MiniBooNE detector, 490 m downstream, is sensitive to dark matter via elastic scattering with nucleons in the detector mineral oil. Analysis methods developed for previous MiniBooNE scattering results were employed, and several constraining data sets were simultaneously analyzed to minimize systematic errors from neutrino flux and interaction rates. No excess of events over background was observed, leading to a 90% confidence limit on the dark matter cross section parameter, Y = ε 2 α D (m χ /m V ) 4 ≲10 –8 , for α D = 0.5 and for dark matter masses of 0.01 < m χ < 0.3 GeV in a vector portal model of dark matter. This is the best limit from a dedicated proton beam dump search in this mass and coupling range and extends below the mass range of direct dark matter searches. Here, these results demonstrate a novel and powerful approach to dark matter searches with beam dump experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Social Sensor Analytics: Making Sense of Network Models in Social Media

Social networks can be thought of as noisy sensor networks mapping real world information to the web. Owing to the extensive body of literature in sensor network analysis, this work sought to apply several novel and traditional methods in sensor network analysis for the purposes of efficiently interrogating social media data streams from raw data. We carefully revisit our definition of a social media signal from previous work both in terms of time-varying features within the data and the networked nature of the medium. Further, we detail our analysis of global patterns in Twitter over the months of November 2013 and June 2014, detect and categorize events, and illustrate how these analyses can be used to inform graph-based models of Twitter, namely using a recent network influence model called PhySense: similar to PageRank but tuned to behavioral analysis by leveraging a sociologically inspired probabilistic model. We ultimately identify forms of information dissemination via analysis of time series and dynamic graph spectra and corroborate these findings through manual investigation of the data as a requisite step in modeling the diffusion process with PhySense. We hope to sufficiently characterize global behavior in a medium such as Twitter as a means of learning global model parameters one may use to predict or simulate behavior on a large scale. We have made our time series and dynamic graph analytical code available via a GitHub repository https://github.com/cpatdowling/salsa and our data are available upon request.

event detection↗
DOE OSTI2021

Analysis of GPU Data Access Patterns on Complex Geometries for the D3Q19 Lattice Boltzmann Algorithm

GPU performance of the lattice Boltzmann method (LBM) depends heavily on memory access patterns. When implemented with GPUs on complex domains, typically, geometric data is accessed indirectly and lattice data is accessed lexicographically. Although there are a variety of other options, no study has examined the relative efficacy between them. Here, we examine a suite of memory access schemes via empirical testing and performance modeling. We find strong evidence that semi-direct is often better suited than the more common indirect addressing, providing increased computational speed and reducing memory consumption. For the layout, we find that the Collected Structure of Arrays (CSoA) and bundling layouts outperform the common Structure of Array layout; on V100 and P100 devices, CSoA consistently outperforms bundling, however the relationship is more complicated on K40 devices. When compared to state-of-the-art practices, our recommendations lead to speedups of 10–40 percent and reduce memory consumption up to 17 percent. Using performance modeling and computational experimentation, we determine the mechanisms behind the accelerations. We demonstrate that our results hold across multiple GPUs on two leadership class systems, and present the first near-optimal strong results for LBM with arterial geometries run on GPUs.

42 ENGINEERING↗
DOE OSTI2016

A Methodology for the Development of a Reliability Database for an Advanced Reactor Probabilistic Risk Assessment

GE Hitachi Nuclear Energy (GEH) and Argonne National Laboratory are currently engaged in a joint effort to modernize and develop probabilistic risk assessment (PRA) techniques for advanced non-light water reactors. At a high level the primary outcome of this project will be the development of next-generation PRA methodologies that will enable risk-informed prioritization of safety- and reliability-focused research and development, while also identifying gaps that may be resolved through additional research. A subset of this effort is the development of a reliability database (RDB) methodology to determine applicable reliability data for inclusion in the quantification of the PRA. The RDB method developed during this project seeks to satisfy the requirements of the Data Analysis element of the ASME/ANS Non-LWR PRA standard. The RDB methodology utilizes a relevancy test to examine reliability data and determine whether it is appropriate to include as part of the reliability database for the PRA. The relevancy test compares three component properties to establish the level of similarity to components examined as part of the PRA. These properties include the component function, the component failure modes, and the environment/boundary conditions of the component. The relevancy test is used to gauge the quality of data found in a variety of sources, such as advanced reactor-specific databases, non-advanced reactor nuclear databases, and non-nuclear databases. The RDB also establishes the integration of expert judgment or separate reliability analysis with past reliability data. This paper provides details on the RDB methodology, and includes an example application of the RDB methodology for determining the reliability of the intermediate heat exchanger of a sodium fast reactor. The example explores a variety of reliability data sources, and assesses their applicability for the PRA of interest through the use of the relevancy test.

Grabaskas, Dave↗
DOE OSTI2017

Multicell model of La{sub 3}Ga{sub 5}GeO{sub 14} crystal: A new approach to the description of the short-range order of atoms

The multicell model alternative to the model of mixed atomic sites used now is proposed for a single crystal of La{sub 3}Ga{sub 5}GeO{sub 14} belonging to the langasite family. The multicell consists of four unit cells. In three identical cells of the structure, atoms adapt to the Ge atom occupying one of the two 2d positions on the threefold symmetry axis. In the fourth cell, atoms surround the Ge atom located at the 1a position. The multicell model allows one to study the short-range order of atoms by the methods of classical structure analysis based on Bragg scattering. Four high-resolution data sets measured at 295 and 111.5 K are used in the study. The results are obtained with high relative precision (space group P321, Z = 1; at 295 K a = 8.2020(6) Å and c = 5.1065(6) Å, R/wR = 0.81/0.73% for 3829 unique ref lections; at 111.5 K a = 8.1939(1) Å and c = 5.1022(4) Å, R/wR = 0.85/0.76% for 3880 reflections).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗