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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

New Glass Serves as Window to Cutting-edge Lasers

Since 1997, Marshall Space Flight Center s Electrostatic Levitator (ESL) facility has been used to study the characteristics of new metals, ceramics, and glass compounds - in both their hot molten states and as they are cooled to form solid materials. The ESL provides a unique way to test such substances without having to make contact with a container or crucible that would contaminate the sample. Simply put, objects analyzed in the levitator's chamber float in mid-air with no visible means of support or containment, suspended only by static electricity. While a sample object is levitated, a laser beam heats it until it melts so that scientists can measure its physical properties without interference from a container.

Source record↗
NASA NTRS2005

How Special Are Dark Gamma-Ray Burst: A Diagnostic Tool

We present here a comprehensive study of the optical/near-infrared (IR) upper limits for gamma-ray bursts that have an X-ray afterglow. We have extrapolated the X-ray afterglows to optical wavelengths based on the physics of the fireball blast wave model and compared these results with optical upper limits for a large sample of bursts. We find a small set of only three bursts out of a sample of 20 for which the upper limits are not compatible with their X-ray afterglow properties within the context of any blast wave model. This sparse sample does not allow us to conclusively determine the cause of this optical/near-IR deficit. Extinction in the host galaxy is a likely cause, but high redshifts and different afterglow mechanisms might also explain the deficit in some cases. We note that the three bursts appear to have higher than average gamma-my peak fluxes. In a magnitude versus time diagram the bursts are separated from the majority of bursts with a detected optical/near-IR afterglow. However, two gamma- ray bursts with an optical afterglow (one of which is highly reddened) also fall in this region with dark bursts, making it likely that dark bursts are at the faint end of the set of optically detected bursts, and therefore the dark bursts likely form a continuum with the bursts with a detected optical afterglow. Our work provides a useful diagnostic tool for follow-up observations for potentially dark bursts; applied to the events detected with the Swift satellite, it will significantly increase our sample of truly dark bursts and shed light upon their nature. Subject headings: dust, extinction - gamma rays: bursts Online material: machine-readable tables

Rod, Evert↗
NASA NTRS2007

Chromosome Aberrations in Astronauts

A review of currently available data on in vivo induced chromosome damage in the blood lymphocytes of astronauts proves that, after protracted exposure of a few months or more to space radiation, cytogenetic biodosimetry analyses of blood collected within a week or two of return from space provides a reliable estimate of equivalent radiation dose and risk. Recent studies indicate that biodosimetry estimates from single spaceflights lie within the range expected from physical dosimetry and biophysical models, but very large uncertainties are associated with single individual measurements and the total sample population remains low. Retrospective doses may be more difficult to estimate because of the fairly rapid time-dependent loss of "stable" aberrations in blood lymphocytes. Also, biodosimetry estimates from individuals who participate in multiple missions, or very long (interplanetary) missions, may be complicated by an adaptive response to space radiation and/or changes in lymphocyte survival and repopulation. A discussion of published data is presented and specific issues related to space radiation biodosimetry protocols are discussed.

George, Kerry A.↗
NASA NTRS2008

Binary Colloidal Alloy Test-5: Phase Separation

The Binary Colloidal Alloy Test - 5: Phase Separation (BCAT-5-PhaseSep) experiment will photograph initially randomized colloidal samples onboard the ISS to determine their resulting structure over time. This allows the scientists to capture the kinetics (evolution) of their samples, as well as the final equilibrium state of each sample. BCAT-5-PhaseSep studies collapse (phase separation rates that impact product shelf-life); in microgravity the physics of collapse is not masked by being reduced to a simple top and bottom phase as it is on Earth.

Lynch, Matthew↗
NASA NTRS2003

Analytic Method for Computing Instrument Pointing Jitter

A new method of calculating the root-mean-square (rms) pointing jitter of a scientific instrument (e.g., a camera, radar antenna, or telescope) is introduced based on a state-space concept. In comparison with the prior method of calculating the rms pointing jitter, the present method involves significantly less computation. The rms pointing jitter of an instrument (the square root of the jitter variance shown in the figure) is an important physical quantity which impacts the design of the instrument, its actuators, controls, sensory components, and sensor- output-sampling circuitry. Using the Sirlin, San Martin, and Lucke definition of pointing jitter, the prior method of computing the rms pointing jitter involves a frequency-domain integral of a rational polynomial multiplied by a transcendental weighting function, necessitating the use of numerical-integration techniques. In practice, numerical integration complicates the problem of calculating the rms pointing error. In contrast, the state-space method provides exact analytic expressions that can be evaluated without numerical integration.

Bayard, David↗
NASA NTRS2017

VISAGE Visualization for Integrated Satellite, Airborne and Ground-Based Data Exploration

The primary goal of the VISAGE project is to facilitate more efficient Earth Science investigations via a tool that can provide visualization and analytic capabilities for diverse coincident datasets. This proof-of-concept project will be centered around the GPM Ground Validation program, which provides a valuable source of intensive, coincident observations of atmospheric phenomena. The data are from a wide variety of ground-based, airborne and satellite instruments, with a wide diversity in spatial and temporal scales, variables, and formats, which makes these data difficult to use together. VISAGE will focus on "golden cases" where most ground instruments were in operation and multiple research aircraft sampled a significant weather event, ideally while the GPM Core Observatory passed overhead. The resulting tools will support physical process studies as well as satellite and model validation.

Data fusion↗
NASA NTRSDate not supplied

Heating and Sampling Efficiency Evaluation for the Nephele Venus Cloud Sampling Mission Concept

Nephele is a descent probe concept with a unique combination of entry (3D-CC+HEEET), sampling (flow-through passive impactors), and optics (laser-induced breakdown spectroscopy, or LIBS, and surface-enhanced Raman spectroscopy, or SERS), technologies with two key innovations. The first is the integration of the aerosol sampling inlet into the aeroshell body, allowing the possibility of sampling during passive descent without separation. The second is the use of the aerosol capture surface as an optical analysis substrate, allowing fast-cadence aerosol analysis via a dual optical spectrometer instead of mass spectrometry. Although this concept shares some features with other efforts such as Cupid’s Arrow (single-body sample capture system), DAVINCI and Venera-D (use of an optical spectrometer), Nephele is unique in its physical integration of the sonde body, aerosol and gas sampler, and analysis instrumentation. This innovation is designed to eliminate the need for a controlled descent to achieve a detailed atmospheric aerosol transect, which offers in situ planetary science in a small spacecraft envelope. Aeroshell designs with inlets for free-falling sondes are well-understood, though not yet assessed for aerosol capture efficiency. A HEEET aeroshell with a specialized nose inlet material comprised of Carbon-Carbon is proposed for this mission concept.

Venus↗
DOE OSTI2020

Interfacial control of oxygen vacancy doping and electrical conduction in thin film oxide heterostructures

Systems and methods of reversibly controlling the oxygen vacancy concentration and distribution in oxide heterostructures consisting of electronically conducting In2O3 films grown on ionically conducting Y2O3-stabilized ZrO2 substrates. Oxygen ion redistribution across the heterointerface is induced using an applied electric field oriented in the plane of the interface, resulting in controlled oxygen vacancy (and hence electron) doping of the film and possible orders-of-magnitude enhancement of the film's electrical conduction. The reversible modified behavior is dependent on interface properties and is attained without cation doping or changes in the gas environment in contact with the sample.

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

Completeness of the NASA/IPAC Extragalactic Database (NED) Local Volume Sample

We introduce the NASA/IPAC Extragalactic Database (NED) Local Volume Sample (NED-LVS), a subset of ~1.9 million objects with distances out to 1000 Mpc. We use UV and IR fluxes available in NED from all-sky surveys to derive physical properties, and estimate the completeness relative to the expected local luminosity density. The completeness relative to near-IR luminosities (which traces a galaxy's stellar mass) is roughly 100% at D < 30 Mpc and remains moderate (70%) out to 300 Mpc. For brighter galaxies (≳L * ), NED-LVS is ~100% complete out to ~400 Mpc. When compared to other local Universe samples (GLADE and HECATE), all three are ~100% complete below 30 Mpc. At distances beyond ~80 Mpc, NED-LVS is more complete than both GLADE and HECATE by ~10%–20%. NED-LVS is the underlying sample for the NED gravitational-wave follow-up service (NED-GWF), which provides prioritized lists of host candidates for GW events within minutes of alerts issued by the LIGO–Virgo–KAGRA collaboration. We test the prioritization of galaxies in the volume of GW170817 by three physical properties, where we find that both stellar mass and inverse specific star formation rate place the correct host galaxy in the top 10. In addition, NED-LVS can be used for a wide variety of other astrophysical studies: galaxy evolution, star formation, large-scale structure, galaxy environments, and more. The data in NED are updated regularly, and NED-LVS will be updated concurrently. Consequently, NED-LVS will continue to provide an increasingly complete sample of galaxies for a multitude of astrophysical research areas for years to come.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Single Crystal Growth of Synthetic Sulfide- and Phosphide-Based Minerals for Physical Measurements

In this work, we review recent advances in the use of high-temperature solution growth that allow for the growth of single crystalline samples of synthetic minerals. We outline how low-melting binary or ternary solutions are attractive solvents for solution growth and provide examples of the growth of bismuthinite (Bi 2 S 3 ), galena (PbS) and parkerite (Ni 3 Bi 2 S 2 ). We then focus on the Rh-S, Pd-S and Ni-P phase spaces to discuss how the low-melting regions near transition metal-main group eutectic compositions make excellent solvents for crystal growth of several binary and ternary minerals containing both high melting and volatile elements as well as for the discovery of new materials. We end by discussing the growth of synthetic canfieldite (Ag 8 SnS 6 ) and argyrodite (Ag 8 GeS 6 ) from Ag 2 S–Sn-S-based solutions.

58 GEOSCIENCES↗
DOE OSTI2021

EXPRES. II. Searching for Planets around Active Stars: A Case Study of HD 101501

By controlling instrumental errors to below 10 cm s{sup −1}, the EXtreme PREcision Spectrograph (EXPRES) allows for a more insightful study of photospheric velocities that can mask weak Keplerian signals. Gaussian processes (GP) have become a standard tool for modeling correlated noise in radial velocity data sets. While GPs are constrained and motivated by physical properties of the star, in some cases they are still flexible enough to absorb unresolved Keplerian signals. We apply GP regression to EXPRES radial velocity measurements of the 3.5 Gyr old chromospherically active Sun-like star, HD 101501. We obtain tight constraints on the stellar rotation period and the evolution of spot distributions using 28 seasons of ground-based photometry, as well as recent Transiting Exoplanet Survey Satellite data. Light-curve inversion was carried out on both photometry data sets to reveal the spot distribution and spot evolution timescales on the star. We find that the >5 m s{sup −1} rms radial velocity variations in HD 101501 are well modeled with a GP stellar activity model without planets, yielding a residual rms scatter of 45 cm s{sup −1}. We carry out simulations, injecting and recovering signals with the GP framework, to demonstrate that high-cadence observations are required to use GPs most efficiently to detect low-mass planets around active stars like HD 101501. Sparse sampling prevents GPs from learning the correlated noise structure and can allow it to absorb prospective Keplerian signals. We quantify the moderate to high-cadence monitoring that provides the necessary information to disentangle photospheric features using GPs and to detect planets around active stars.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRSDate not supplied

Meteoritic Carbonates - The Key to Sampling Extraterrestrial Fluids?

Fluid inclusions are naturally occurring mineral features that preserve trapped fluid phases inside a solid phase. These cavities exist as a closed system, recording the environmental conditions present during entrapment – both physical and chemical. As a result, fluid inclusions are great candidates for directly studying past fluid activity on extraterrestrial bodies within the Solar System. On Earth, fluid inclusions are abundant as they occur within numerous host minerals. They are a powerful tool for accurately and directly understanding the driving processes in various geological environments. In contrast, extraterrestrial fluid inclusions have only been positively identified on three separate occasions within host materials ranging from ordinary chondrites to C/B-type asteroid mission return samples. The possibility of directly studying the fluids involved in aqueous alteration and accurately constraining their heliocentric distances drives the hunt for these elusive capsules. Our goals are to locate new fluid inclusion candidates (hereon referred to as candidates) and assess whether fluid inclusions are a common feature within meteoritic carbonates and why they may have eluded detection for so long. We also aim to characterize the host grain’s mineralogical properties and assess the potentially preferential conditions for fluid entrapment on the asteroid parent body.

P A B Krizan↗
NASA NTRS2004

Evaluation and Application of Satellite-Based Latent Heating Profile Estimation Methods

In recent years, methods for estimating atmospheric latent heating vertical structure from both passive and active microwave remote sensing have matured to the point where quantitative evaluation of these methods is the next logical step. Two approaches for heating algorithm evaluation are proposed: First, application of heating algorithms to synthetic data, based upon cloud-resolving model simulations, can be used to test the internal consistency of heating estimates in the absence of systematic errors in physical assumptions. Second, comparisons of satellite-retrieved vertical heating structures to independent ground-based estimates, such as rawinsonde-derived analyses of heating, provide an additional test. The two approaches are complementary, since systematic errors in heating indicated by the second approach may be confirmed by the first. A passive microwave and combined passive/active microwave heating retrieval algorithm are evaluated using the described approaches. In general, the passive microwave algorithm heating profile estimates are subject to biases due to the limited vertical heating structure information contained in the passive microwave observations. These biases may be partly overcome by including more environment-specific a priori information into the algorithm s database of candidate solution profiles. The combined passive/active microwave algorithm utilizes the much higher-resolution vertical structure information provided by spaceborne radar data to produce less biased estimates; however, the global spatio-temporal sampling by spaceborne radar is limited. In the present study, the passive/active microwave algorithm is used to construct a more physically-consistent and environment-specific set of candidate solution profiles for the passive microwave algorithm and to help evaluate errors in the passive algorithm s heating estimates. Although satellite estimates of latent heating are based upon instantaneous, footprint- scale data, suppression of random errors requires averaging to at least half-degree resolution. Analysis of mesoscale and larger space-time scale phenomena based upon passive and passive/active microwave heating estimates from TRMM, SSMI, and AMSR data will be presented at the conference.

Olson, William S.↗
DOE OSTI2021

Solving Inverse Stochastic Problems from Discrete Particle Observations Using the Fokker--Planck Equation and Physics-Informed Neural Networks

The Fokker--Planck (FP) equation governing the evolution of the probability density function (PDF) is applicable to many disciplines, but it requires specification of the coefficients for each case, which can be functions of space-time and not just constants and hence require the development of a data-driven modeling approach. When the data available is directly on the PDF, there exist methods for inverse problems that can be employed to infer the coefficients and thus determine the FP equation and subsequently obtain its solution. Herein, we address a more realistic scenario, where only sparse data are given on the particles' positions at a few time instants, which are not sufficient to accurately construct directly the PDF even at those times from existing methods, e.g., kernel estimation algorithms. To this end, we develop a general framework based on physics-informed neural networks (PINNs) that introduces a new loss function using the Kullback--Leibler divergence to connect the stochastic samples with the FP equation to simultaneously learn the equation and infer the multidimensional PDF at all times. In particular, we consider two types of inverse problems, type I, where the FP equation is known but the initial PDF is unknown, and type II, in which, in addition to the unknown initial PDF, the drift and diffusion terms are also unknown. In both cases, we investigate problems with either Brownian or Lévy noise or a combination of both. Here, we demonstrate the new PINN framework in detail in the one-dimensional (1D) case, but we also provide results for up to five dimensions demonstrating that we can infer both the FP equation and dynamics simultaneously at all times with high accuracy using only very few discrete observations of the particles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Towards robust surrogate models: Benchmarking machine learning approaches to expediting phase field simulations of brittle fracture

Data-driven approaches have the potential to make modeling complex, nonlinear physical phenomena significantly more computationally tractable. For example, computational modeling of fracture is a core challenge where machine learning techniques have the potential to provide a much needed speedup that would enable progress in areas such as multi-scale modeling and uncertainty quantification. Currently, phase field modeling (PFM) of fracture is one such approach that offers a convenient variational formulation to model crack nucleation, branching and propagation. To date, machine learning techniques have shown promise in approximating PFM simulations. While standard fracture benchmarks represent realistic scenarios frequently observed in practice, they typically do not provide sufficiently challenging tests for data-driven methods. Here, to address this gap, we introduce a challenging dataset based on PFM simulations designed to benchmark and advance ML methods for fracture modeling. This dataset includes three energy decomposition methods, two boundary conditions, and 1000 random initial crack configurations for a total of 6000 simulations. Each sample contains 100 time steps capturing the temporal evolution of the crack field. Alongside this dataset, we also implement and evaluate Physics Informed Neural Networks (PINN), Fourier Neural Operators (FNO), and UNet models as baselines, and explore the impact of ensembling strategies on prediction accuracy. With this combination of our dataset and baseline models drawn from the literature we aim to provide a standardized and challenging benchmark for evaluating machine learning approaches to solid mechanics. Our results highlight both the promise and limitations of popular current models, and demonstrate the utility of this dataset as a testbed for advancing machine learning in fracture mechanics research.

Benchmark dataset↗
DOE OSTI2026

Generative models on phase space

Deep generative models such as diffusion and flow matching are powerful machine learning tools capable of learning and sampling from high-dimensional distributions. They are particularly useful when the training data appears to be concentrated on a submanifold of the data embedding space. For high-energy physics data, consisting of collections of relativistic energy-momentum 4-vectors, this submanifold can enforce extremely strong physically-motivated priors, such as energy and momentum conservation. If these constraints are learned only approximately, rather than exactly, this can inhibit the interpretability and reliability of such generative models. To remedy this deficiency, we introduce generative models which are, by construction, confined at every step of their sampling trajectory to the manifold of massless N-particle Lorentz-invariant phase space in the center-of-momentum frame. In the case of diffusion models, the "pure noise" forward process endpoint corresponds to the uniform distribution on phase space, which provides a clear starting point from which to identify how correlations among the particles emerge during the reverse (de-noising) process. We demonstrate that our models are able to learn both few-particle and many-particle distributions with various singularity structures, paving the way for future interpretability studies using generative models trained on simulated jet data.

Bogorad, Zachary [Fermilab]↗
NASA NTRS1994

A statistical analysis of the broadband 0.1 to 3.5 keV spectral properties of X-ray-selected active galactic nuclei

We survey the broadband spectral properties of approximately 500 X-ray-selected active galactic nuclei (AGNs) observed with the Einstein Observatory. Included in this survey are the approximately 450 AGNs in the Extended Medium Sensitivity Survey (EMSS) of Gioia et al. (1990) and the approximately 50 AGNs in the Ultrasoft Survey of Cordova et al. (1992). We present a revised version of the latter sample, based on the post publication discovery of a software error in the Einstein Rev-1b processing. We find that the mean spectral index of the AGNs between 0.1 and 0.6 keV is softer, and the distribution of indices wider, than previous estimates based on analyses of the X-ray spectra of optically selected AGNs. A subset of these AGNs exhibit flux variabiulity, some on timescales as short as 0.05 days. A correlation between radio and hard X-ray luminosity is confirmed, but the data do not support a correlation between the radio and soft X-ray luminosities, or between radio loudness and soft X-ray spectral slope. Evidence for physically distinct soft and hard X-ray components is found, along with the possibility of a bias in previous optically selected samples toward selection of AGNs with flatter X-ray spectra.

Thompson, R. J.↗