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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

An ALMA view of star formation efficiency suppression in early-type galaxies after gas-rich minor mergers

Gas-rich minor mergers contribute significantly to the gas reservoir of early-type galaxies (ETGs) at low redshift, yet the star formation efficiency (SFE; the star formation rate divided by the molecular gas mass) appears to be strongly suppressed following some of these events, in contrast to the more well-known merger-driven starbursts. We present observations with the Atacama Large Millimeter/submillimeter Array (ALMA) of six ETGs, which have each recently undergone a gas-rich minor merger, as evidenced by their disturbed stellar morphologies. These galaxies were selected because they exhibit extremely low SFEs. We use the resolving power of ALMA to study the morphology and kinematics of the molecular gas. The majority of our galaxies exhibit spatial and kinematical irregularities, such as detached gas clouds, warps, and other asymmetries. These asymmetries support the interpretation that the suppression of the SFE is caused by dynamical effects stabilizing the gas against gravitational collapse. Through kinematic modelling we derive high velocity dispersions and Toomre Q stability parameters for the gas, but caution that such measurements in edge-on galaxies suffer from degeneracies. We estimate merger ages to be about 100 Myr based on the observed disturbances in the gas distribution. Furthermore, we determine that these galaxies lie, on average, two orders of magnitude below the Kennicutt–Schmidt relation for star-forming galaxies as well as below the relation for relaxed ETGs. We discuss potential dynamical processes responsible for this strong suppression of star formation surface density at fixed molecular gas surface density.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Machine learning neutrino-nucleus cross sections

Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections remains challenging. For a simple but physically motivated toy model of the DUNE experiment, we demonstrate that an accurate neural-network model of the cross section—leveraging only Standard-Model symmetries—can be learned from near-detector data. We perform a neutrino oscillation analysis with simulated far-detector events, finding that oscillation analysis results enabled by our data-driven cross-section model approach the theoretical limit achievable with perfect prior knowledge of the cross section. We further quantify the effects of flux shape and detector resolution uncertainties as well as systematics from cross-section mismodeling. This proof-of-principle study highlights the potential of future neutrino near-detector datasets and data-driven cross-section models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Resimulation-based self-supervised learning for pretraining physics foundation models

Self-supervised learning (SSL) is at the core of training modern large machine learning models, providing a scheme for learning powerful representations that can be used in a variety of downstream tasks. However, SSL strategies must be adapted to the type of training data and downstream tasks required. We propose resimulation-based self-supervised representation learning (RS3L), a novel simulation-based SSL strategy that employs a method of resimulation to drive data augmentation for contrastive learning in the physical sciences, particularly, in fields that rely on stochastic simulators. By intervening in the middle of the simulation process and rerunning simulation components downstream of the intervention, we generate multiple realizations of an event, thus producing a set of augmentations covering all physics-driven variations available in the simulator. Using experiments from high-energy physics, we explore how this strategy may enable the development of a foundation model; we show how RS3L pretraining enables powerful performance in downstream tasks such as discrimination of a variety of objects and uncertainty mitigation. In addition to our results, we make the RS3L dataset publicly available for further studies on how to improve SSL strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Direct visualization of electromagnetic wave dynamics by laser-free ultrafast electron microscopy

Integrating femtosecond lasers with electron microscopies has enabled direct imaging of transient structures and morphologies of materials in real time and space. Here, we report the development of a laser-free ultrafast electron microscopy (UEM) offering the same capability but without requiring femtosecond lasers and intricate instrumental modifications. We create picosecond electron pulses for probing dynamic events by chopping a continuous beam with a radio frequency (RF)–driven pulser with the pulse repetition rate tunable from 100 MHz to 12 GHz. As a first application, we studied gigahertz electromagnetic wave propagation dynamics in an interdigitated comb structure. We reveal, on nanometer space and picosecond time scales, the transient oscillating electromagnetic field around the tines of the combs with time-resolved polarization, amplitude, and local field enhancement. This study demonstrates the feasibility of laser-free UEM in real-space visualization of dynamics for many research fields, especially the electrodynamics in devices associated with information processing technology.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Enhancing Resilience of Urban Systems Against Climate-Induced Floods Using Advanced Data-Driven and Computing Techniques: A Driver-Pressure-State-Impact-Response (DPSIR) Framework

Focal Area: This white paper proposes advanced data-driven and computing techniques to improve the predictability of extreme climate events (precipitation) and focuses on comprehending their impact dynamics to enhance resilience of urban systems. Science Challenge: In urban systems, climate change has presented significant challenges related to accurate spatiotemporal prediction of extreme climate events (heavy precipitation) and their impacts, i.e. flooding. The occurrence of extreme climate events and their compounding repercussions on the built environment make urban systems increasingly more vulnerable. The interactions between extreme climate events, urban systems, and the corresponding impacts are irregular, non-linear, and dynamic, making it difficult to standardize resilience. As it stands, the management of complex urban systems is affected by uncertainties related to the nature of short- and long-term consequences caused by extreme events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Benchmarking State-of-the-Art Theory and Empirical Models of Pionless Neutrino-Argon Scattering in GENIE

Neutrino event generators require a delicate balance between theory and empirically-driven models to achieve reliable simulations. GENIE is the most commonly used generator, bridging theory and experiment in modern neutrino physics. Its flexible framework makes it ideal for comparing different models across all aspects of neutrino interactions—from the nuclear ground state and primary vertex to final-state interactions. Recently, GENIE has incorporated several state-of-the-art, theory-driven models, including spectral-function descriptions of the nuclear ground state, axial form factors from first-principles lattice QCD calculations, and the Liège intranuclear cascade model for simulating final-state interactions. Compared to the previous baseline models in GENIE—such as the local Fermi gas, dipole-like axial form factor, and hA final-state interaction model—the new implementations are more physically realistic and incorporate more complete physics, including nuclear de-excitation. This poster presents the implementation of new models in GENIE and their performance in comparisons among these models against recent MicroBooNE cross-section measurements.

Liu, Liang [Fermilab] (ORCID:000000026753925X)↗
DOE OSTI2026

Machine Learning Neutrino-Nucleus Cross Sections

Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections remains challenging. For a simple but physically motivated toy model of the DUNE experiment, we demonstrate that an accurate neural-network model of the cross section—leveraging only Standard-Model symmetries— can be learned from near-detector data. We perform a neutrino oscillation analysis with simulated far-detector events, finding that oscillation analysis results enabled by our data-driven cross-section model approach the theoretical limit achievable with perfect prior knowledge of the cross section. We further quantify the effects of flux shape and detector resolution uncertainties as well as systematics from cross-section mismodeling. This proof-of-principle study highlights the potential of future neutrino near-detector datasets and data-driven cross-section models.

Tame-Narvaez, Karla [Fermilab] (ORCID:000000022249↗
DOE OSTI2026

Benchmarking State-of-the-Art Theory and Empirical Models of Pionless Neutrino-Argon Scattering in GENIE

Neutrino event generators require a delicate balance between theory and empirically-driven models to achieve reliable simulations. GENIE is the most commonly used generator, bridging theory and experiment in modern neutrino physics. Its flexible framework makes it ideal for comparing different models across all aspects of neutrino interactions—from the nuclear ground state and primary vertex to final-state interactions. Recently, GENIE has incorporated several state-of-the-art, theory-driven models, including spectral-function descriptions of the nuclear ground state, axial form factors from first-principles lattice QCD calculations, and the Liège intranuclear cascade model for simulating final-state interactions. Compared to the previous baseline models in GENIE—such as the local Fermi gas, dipole-like axial form factor, and hA final-state interaction model—the new implementations are more physically realistic and incorporate more complete physics, including nuclear de-excitation. This poster presents the implementation of new models in GENIE and their performance in comparisons among these models against recent MicroBooNE cross-section measurements.

Liu, Liang [Fermilab] (ORCID:000000026753925X)↗
DOE OSTI2019

Stepwise chemical abrasion–isotope dilution–thermal ionization mass spectrometry with trace element analysis of microfractured Hadean zircon

Abstract. The Hadean Jack Hills zircons represent the oldest known terrestrial material, providing a unique and truly direct record of Hadean Earth history. This zircon population has been extensively studied via high-spatial-resolution high-throughput in situ isotopic and elemental analysis techniques, such as secondary ionization mass spectrometry (SIMS), but not by comparatively destructive, high-temporal-precision (<0.05 % two-sigma) thermal ionization mass spectrometry (TIMS). In order to better understand the lead loss and alteration history of terrestrial Hadean zircons, we conduct stepwise chemical abrasion–isotope dilution–thermal ionization mass spectrometry with trace element analysis (CA-ID-TIMS-TEA) on manually microfractured Hadean Jack Hills zircon fragments previously dated by SIMS. We conducted three successive HF leaching steps on each individual zircon fragment, followed by column chromatography to isolate U–Pb and trace element fractions. Following isotopic and elemental analysis, the result is an independent age and trace element composition for each leachate of each zircon fragment. We observe ~50 Myr of age heterogeneity in concordant residues from a single zircon grain, along with a protracted history of post-Hadean Pb loss with at least two modes circa ~0 and 2–4 Ga. Meanwhile, stepwise leachate trace element chemistry reveals enrichments of light rare earth elements, uranium, thorium, and radiogenic lead in early leached domains relative to the zircon residue. In addition to confirming the efficacy of the LREE-I alteration index and providing new insight into the mechanism of chemical abrasion, the interpretation and reconciliation of these results suggest that Pb loss is largely driven by low-temperature aqueous recrystallization and that regional thermal events may act to halt – not initiate – Pb loss from metamict domains in the Hadean Jack Hills zircons.

Brenhin Keller, C. (ORCID:0000000174009428)↗
NASA NTRS1978

The decay of coronal loops brightened by flares and transients

Observations of X-ray emitting loops derived from Skylab S-054 photographs, and combined with temperature and brightness estimates from Solrad data, are used to determine brightness decay times resulting from various coronal energy loss mechanisms. Conductive losses are found to be more rapid than radiative losses. Attention is given to the role of geometrical inhibition of conduction as a possible mechanism of brightness decay. Soft X-ray observations are consistent with the continuation of the 'evaporation' driven by thermal conduction late into the decay phase of the event.

Krieger, A. S.↗
NASA NTRS1987

Transient rotor dynamic rub phenomena - Theory and test

This paper develops an implicit integration scheme for transient rotor dynamic rub prediction and includes a correlation study with actual test results. A Nordsieck-like numerical integration scheme is applied directly to the second-order equations of motion. The assumption that forces and torques on the rotor are functions of the position and velocity at the point of application and its nearest neighbor is made in order to make the computational time proportional to the number of elements in the rotor dynamics model rather than the cube of the number. The test rig consists of a turbine driven, flexible shaft supported by squeeze film dampers. The blade loss event occurs due to collision of a balance bolt on one of the disks with a high speed plunger. The rotor is seen to spiral outward and contact against a stationary assemblage of seal shoes.

Kascak, A. F.↗
NASA NTRS2002

Purification of the small mechanosensitive channel of Escherichia coli (MscS): the subunit structure, conduction, and gating characteristics in liposomes

The small mechanosensitive channel, MscS, is a part of the turgor-driven solute efflux system that protects bacteria from lysis in the event of osmotic downshift. It has been identified in Escherichia coli as a product of the orphan yggB gene, now called mscS (Levina et al., 1999, EMBO J. 18:1730). Here I show that that the isolated 31-kDa MscS protein is sufficient to form a functional mechanosensitive channel gated directly by tension in the lipid bilayer. MscS-6His complexes purified in the presence of octylglucoside and lipids migrate in a high-resolution gel-filtration column as particles of approximately 200 kDa. Consistent with that, the protein cross-linking patterns predict a hexamer. The channel reconstituted in soybean asolectin liposomes was activated by pressures of 20-60 mm Hg and displayed the same asymmetric I-V curve and slight anionic preference as in situ. At the same time, the single-channel conductance is proportional to the buffer conductivity in a wide range of salt concentrations. The rate of channel activation in response to increasing pressure gradient across the patch was slower than the rate of closure in response to decreasing steps of pressure gradient. Therefore, the open probability curves were recorded with descending series of pressures. Determination of the curvature of patches by video imaging permitted measurements of the channel activity as a function of membrane tension (gamma). Po(gamma) curves had the midpoint at 5.5 +/- 0.1 dyne/cm and gave estimates for the energy of opening DeltaG = 11.4 +/- 0.5 kT, and the transition-related area change DeltaA = 8.4 +/- 0.4 nm(2) when fitted with a two-state Boltzmann model. The correspondence between channel properties in the native and reconstituted systems is discussed.

NASA Discipline Cell Biology↗
NASA NTRS2013

Comparison Between Path Lengths Traveled by Solar Electrons and Ions in Ground-Level Enhancement Events

We have examined the Wind/3DP/SST electron and Wind/EPACT/LEMT ion data to investigate the path length difference between solar electrons and ions in the ground-level enhancement (GLE) events in solar cycle 23. Assuming that the onset time of metric type II or decameter-hectometric (DH) type III radio bursts is the solar release time of non-relativistic electrons, we have found that within an error range of plus or minus 10% the deduced path length of low-energy (approximately 27 keV) electrons from their release site near the Sun to the 1 AU observer is consistent with the ion path length deduced by Reames from the onset time analysis. In addition, the solar longitude distribution and IMF topology of the GLE events examined are in favor of the coronal mass ejection-driven shock acceleration origin of observed non-relativistic electrons.We have also found an increase of electron path lengths with increasing electron energies. The increasing rate of path lengths is correlated with the pitch angle distribution (PAD) of peak electron intensities locally measured, with a higher rate corresponding to a broader PAD. The correlation indicates that the path length enhancement is due to the interplanetary scattering experienced by first arriving electrons. The observed path length consistency implies that the maximum stable time of magnetic flux tubes, along which particles transport, could reach 4.8 hr.

electrons↗
DOE OSTI2025

Data-driven model validation for neutrino-nucleus cross section measurements

Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generators in oscillation analyses and cross section measurements alike. We then describe data-driven model validation techniques intended to address this model dependence. The method relies on utilizing various goodness-of-fit tests and the correlations between different observables and channels to probe the model for defects in the phase space relevant for the desired analysis. These techniques shed light on relevant mismodeling, allowing it to be detected before it begins to bias the cross section results. We compare more commonly used model validation methods which directly validate the model against alternative ones to these data-driven techniques and show their efficacy with fake data studies. These studies demonstrate that employing data-driven model validation in cross section measurements represents a reliable strategy to produce robust results that will stimulate the desired improvements to interaction modeling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Data-driven model validation for neutrino-nucleus cross section measurements

Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generators in oscillation analyses and cross section measurements alike. We then describe data-driven model validation techniques intended to address this model dependence. The method relies on utilizing various goodness-of-fit tests and the correlations between different observables and channels to probe the model for defects in the phase space relevant for the desired analysis. These techniques shed light on relevant mismodeling, allowing it to be detected before it begins to bias the cross section results. We compare more commonly used model validation methods which directly validate the model against alternative ones to these data-driven techniques and show their efficacy with fake data studies. These studies demonstrate that employing data-driven model validation in cross section measurements represents a reliable strategy to produce robust results that will stimulate the desired improvements to interaction modeling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

New correlator to detect and characterize the chiral magnetic effect

In this work, a charge-sensitive in-event correlator is proposed and tested for its efficacy to detect and characterize charge separation associated with the chiral magnetic effect (CME) in heavy ion collisions. Tests, performed with the aid of two reaction models, indicate discernible responses for background- and CME-driven charge separation, relative to the second- ( Ψ 2 ) and third-order ( Ψ 3 ) event planes, which could serve to identify the CME. Furthermore, the tests indicate a degree of sensitivity which would enable robust characterization of the CME via anomalous viscous fluid dynamics (AVFD) model comparisons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Characterizing climate pathways using feature importance on echo state networks

The 2022 National Defense Strategy of the United States listed climate change as a serious threat to national security. Climate intervention methods, such as stratospheric aerosol injection, have been proposed as mitigation strategies, but the downstream effects of such actions on a complex climate system are not well understood. The development of algorithmic techniques for quantifying relationships between source and impact variables related to a climate event (i.e., a climate pathway) would help inform policy decisions. Data-driven deep learning models have become powerful tools for modeling highly nonlinear relationships and may provide a route to characterize climate variable relationships. In this paper, we explore the use of an echo state network (ESN) for characterizing climate pathways. ESNs are a computationally efficient neural network variation designed for temporal data, and recent work proposes ESNs as a useful tool for forecasting spatiotemporal climate data. However, ESNs are noninterpretable black-box models along with other neural networks. The lack of model transparency poses a hurdle for understanding variable relationships. We address this issue by developing feature importance methods for ESNs in the context of spatiotemporal data to quantify variable relationships captured by the model. We conduct a simulation study to assess and compare the feature importance techniques, and we demonstrate the approach on reanalysis climate data. In the climate application, we consider a time period that includes the 1991 volcanic eruption of Mount Pinatubo. This event was a significant stratospheric aerosol injection, which acts as a proxy for an anthropogenic stratospheric aerosol injection. Furthermore, we are able to use the proposed approach to characterize relationships between pathway variables associated with this event that agree with relationships previously identified by climate scientists.

black-box models↗
NASA NTRS2010

THEMIS Observations of Directly-Driven Pi2 Pulsations

The THEMIS tail seasons have provided an unprecedented opportunity to examine the causal relationship between midtail plasma flows and low latitude Pi2 pulsations. We present several events where multiple THEMIS spacecraft observed magnetotail flow bursts which were followed up to several minutes later by ground Pi2 pulsations. We find good agreement with the waveforms of the flow bursts and flank Pi2, in agreement with the hypothesis that Pi2 at low-latitude on the flank are directly-driven by periodic variations in the flow bursts. For at least I event we are able to follow the Pi2 impulses from the periodic flow bursts on the nightside. to ground Pi2 at the flanks, and finally through the dayside magnetosphere as observed by GOES. We further place the physical mechanism generating these Pi2 into the context of sub storm onset. We conclude by discussing the sequence and coupling of events that are necessary to explain the correlation, and the constraints this places on models of transient magnetospheric transport.

Kepko, L.↗