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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Size of the accretion disk in the graviationally lensed quasar SDSS J1004+4112 from the statistics of microlensing magnifications

We present eight monitoring seasons of the four brightest images of the gravitational lens SDSS J1004+4112 observed between 2003 December and 2010 October. Using measured time delays for the images A, B, and C and the model predicted time delay for image D we have removed the intrinsic quasar variability, finding microlensing events of about 0.5 and 0.7 mag of amplitude in the images C and D. From the statistics of microlensing amplitudes in images A, C, and D, we have inferred the half-light radius (at λ{sub rest}=2407 A-ring ) for the accretion disk using two different methods, R{sub 1/2}=8.7{sub −5.5}{sup +18.5}√(M/0.3M{sub ⊙}) (histogram product) and R{sub 1/2}=4.2{sub −2.2}{sup +3.2}√(M/0.3M{sub ⊙}) lt-days (χ{sup 2}). The results are in agreement within uncertainties with the size predicted from the black hole mass in SDSS J1004+4112 using thin disk theory.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Active Galactic Nuclei Continuum Reverberation Mapping Based on Zwicky Transient Facility Light Curves

We perform a systematic survey of active galactic nuclei (AGNs) continuum lags using ~3 days cadence gri-band light curves from the Zwicky Transient Facility. We select a sample of 94 type 1 AGNs at z < 0.8 with significant and consistent inter-band lags based on the interpolated cross-correlation function method and the Bayesian method JAVELIN. Within the framework of the "lamp-post" reprocessing model, our findings are: (1) The continuum emission (CE) sizes inferred from the data are larger than the disk sizes predicted by the standard thin-disk model. (2) For a subset of the sample, the CE size exceeds the theoretical limit of the self-gravity radius (12 lt-days) for geometrically thin disks. (3) The CE size scales with continuum luminosity as R CE ∝ L 0.48±0.04 with a scatter of 0.2 dex, analogous to the well-known radius–luminosity relation of broad Hβ. These findings suggest a significant contribution of diffuse continuum emission from the broad-line region (BLR) to AGN continuum lags. We find that the R CE –L relation can be explained by a photoionization model that assumes ~23% of the total flux comes from the diffuse BLR emission. In addition, the ratio of the CE size and model-predicted disk size anticorrelates with the continuum luminosity, which is indicative of a potential nondisk BLR lag contribution evolving with the luminosity. Finally, a robust positive correlation between the CE size and black hole mass is detected.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1971

TLD measurements of gamma heating in heavy elements.

Measurements and calculations of gamma heating in polyethylene and lead containers were done and compared. The objective was to provide a workable method of getting good values for gamma heating in in-pile experiments containing materials of high atomic numbers. It was inferred that a combination of thermoluminescent dosimeter measurements, using Bragg-Gray theory, with photon transport calculations using the ANISN computer program, would meet this objective.

Reilly, H. J.↗
NASA NTRS1985

The future of solar physics

Outstanding problems for the future of solar physics and stellar physics are examined. The physics of stellar interiors has been called into serious question by the very low measured neutrino flux from the sun. The Ga-71 neutrino detection experiment is the next step in unravelling this mystery. The new methods of helioseismology, for probing the interior of the sun, have already found the primordial rapid rotation of the central core. The forthcoming worldwide helioseismology observing network will permit fuller exploitation of the method, promising to provide the first direct sounding of the interior of a star, hitherto known to us only through theoretical inference and the discrepant neutrino emission. An essential step in developing the physics of stellar activity will be the Solar Optical Telescope (presently planned by NASA to be launched early in the next decade) to permit a 'microscopic' examination of the surface of the sun to study the source of the action. The activity and X-ray emission of other stars depend on much the same effects, so that the study of the sun is essential to determining the significance of the X-ray emission from other stars.

Parker, E. N.↗
NASA NTRS2009

Effects of Cryogenic Temperatures on Spacecraft Internal Dielectric Discharges

Abstract Most calculations of internal dielectric charging on spacecraft use tabulated values of material surface and bulk conductivities, dielectric constants, and dielectric breakdown strengths. Many of these properties are functions of temperature, and the temperature dependences are not well known. At cryogenic temperatures, where it is well known that material conductivities decrease dramatically, it is an open question as to the timescales over which buried charge will dissipate and prevent the eventual potentially disastrous discharges of dielectrics. In this paper, measurements of dielectric charging and discharging for cable insulation materials at cryogenic temperatures (approx. 90 K) are presented using a broad spectrum electron source at the NASA Marshall Space Flight Center. The measurements were performed for the James Webb Space Telescope (JWST), which will orbit at the Earth-Sun L2 point, and parts of which will be perennially at temperatures as low as 40 K. Results of these measurements seem to show that Radiation Induced Conductivity (RIC) under cryogenic conditions at L2 will not be sufficient to allow charges to bleed off of some typical cable insulation materials even over the projected JWST lifetime of a dozen years or more. After the charging and discharging measurements are presented, comparisons are made between the material conductivities that can be inferred from the measured discharges and conductivities calculated from widely used formulae. Furthermore, the measurement-inferred conductivities are compared with extrapolations of recent measurements of materials RIC and dark conductivities performed with the charge-storage method at Utah State University. Implications of the present measurements are also given for other spacecraft that may operate at cryogenic temperatures, such as probes of the outer planets or the permanently dark cratered areas on the moon. The present results will also be of interest to those who must design or operate spacecraft in more moderate cold conditions. Finally, techniques involving shielding and/or selective use of somewhat conductive insulators are presented to prevent arc-inducing charge buildup even under cryogenic conditions.

Ferguson, Dale c.↗
NASA NTRS2019

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a pilot flying an airplane; in this case, activities with distinct visual signatures might be things like communicating, navigating, monitoring, etc. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. We compare, not individual fixations, but groups of fixations aggregated over a fixed time interval (Tau). We assume that the environment has been divided into a finite set of discrete areas-of-interest (AOIs). For a given time interval, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector, where N is the number of AOIs. These proportions can be converted to integer counts by multiplying by Tau divided by the average fixation duration, a parameter that we fix at 283 milliseconds. We compare different intervals by computing the chi-squared statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. We cluster the intervals, first by merging adjacent intervals that are sufficiently similar, optionally shifting the boundary between non-merged intervals to maximize the difference. Then we compare and cluster non-adjacent intervals. The method is evaluated using synthetic data generated by a hand-crafted set of activities. While the method generally finds more activities than put into the simulation, we have obtained agreement as high as 80 percent between the inferred activity labels and ground truth.

Eye Movements↗
DOE OSTI2023

Criticality Experiments to Reduce Compensating Errors in Plutonium Nuclear Data

Compensating errors between nuclear data observables in a library can adversely impact application simulations. The primary goal of the EUCLID project (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) is to reduce compensating errors in nuclear data. A new criticality experiment, described in this work, was designed with the specific target nuclear data of 239 Pu fission, inelastic scattering, elastic scattering, capture, nu-bar, and prompt fission neutron spectrum (PFNS). This work will focus on the design and execution of the EUCLID experiment, performed on the Planet vertical lift critical assembly machine at the National Criticality Experiments Research Center (NCERC). The criticality experiment includes two different configurations with very different geometries: one is cube-like to minimize neutron leakage while the other is slab-like to maximize leakage. Having these two widely varying configurations allows the scattering sensitivities of 239 Pu to the neutron multiplication factor to be greatly changed while minimally impacting the other cross section sensitivities. Both configurations utilize the Pu ZPPR (Zero Power Physics Reactor) plates as fuel. The experiments were designed using a D-Optimality criteria, which is an optimization method minimizing the log-determinant of the adjusted nuclear data covariance for the target reactions. These experiments include not only inference of k eff , as done in all critical benchmark experiments, but several other responses as well, such as neutron multiplication measurements and reaction rate ratios. After analysis of the measured data is complete, adjustment of nuclear data will be performed to assess whether the new experimental data successfully reduced compensating errors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Inference of Experimental Radial Impurity Transport on Alcator C-Mod: Bayesian Parameter Estimation and Model Selection.

We present a fully Bayesian approach for the inference of radial profiles of impurity transport coefficients and compare its results to neoclassical, gyrofluid and gyrokinetic modeling. Using nested sampling, the Bayesian Impurity Transport InferencE (BITE) framework can handle complex parameter spaces with multiple possible solutions, offering great advantages in interpretative power and reliability with respect to previously demonstrated methods. BITE employs a forward model based on the pySTRAHL package, built on the success of the well-known STRAHL code [Dux, IPP Report, 2004], to simulate impurity transport in magnetically-confined plasmas. In this paper, we focus on calcium (Ca, Z=20) Laser Blow-Off injections into Alcator C-Mod plasmas. Multiple Ca atomic lines are diagnosed via high-resolution X-ray Imaging Crystal Spectroscopy and Vacuum Ultra-Violet measurements. We analyze a sawtoothing I-mode discharge for which neoclassical and turbulent (quasilinear and nonlinear) predictions are also obtained. We find good agreement in diffusion across the entire radial extent, while turbulent convection and density profile peaking are estimated to be larger in experiment than suggested by theory. Efforts and challenges associated with the inference of experimental pedestal impurity transport are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Learning physics-based reduced-order models from data using nonlinear manifolds

Here we present a novel method for learning reduced-order models of dynamical systems using nonlinear manifolds. First, we learn the manifold by identifying nonlinear structure in the data through a general representation learning problem. The proposed approach is driven by embeddings of low-order polynomial form. A projection onto the nonlinear manifold reveals the algebraic structure of the reduced-space system that governs the problem of interest. The matrix operators of the reduced-order model are then inferred from the data using operator inference. Numerical experiments on a number of nonlinear problems demonstrate the generalizability of the methodology and the increase in accuracy that can be obtained over reduced-order modeling methods that employ a linear subspace approximation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Inference of experimental radial impurity transport on Alcator C-Mod: Bayesian parameter estimation and model selection

We present a fully Bayesian approach for the inference of radial profiles of impurity transport coefficients and compare its results to neoclassical, gyrofluid and gyrokinetic modeling. Using nested sampling, the Bayesian Impurity Transport InferencE (BITE) framework can handle complex parameter spaces with multiple possible solutions, offering great advantages in interpretative power and reliability with respect to previously demonstrated methods. BITE employs a forward model based on the pySTRAHL package, built on the success of the well-known STRAHL code [Dux, IPP Report, 2004], to simulate impurity transport in magnetically-confined plasmas. In this paper, we focus on calcium (Ca, Z=20) Laser Blow-Off injections into Alcator C-Mod plasmas. Multiple Ca atomic lines are diagnosed via high-resolution X-ray Imaging Crystal Spectroscopy and Vacuum Ultra-Violet measurements. We analyze a sawtoothing I-mode discharge for which neoclassical and turbulent (quasilinear and nonlinear) predictions are also obtained. Here, we find good agreement in diffusion across the entire radial extent, while turbulent convection and density profile peaking are estimated to be larger in experiment than suggested by theory. Efforts and challenges associated with the inference of experimental pedestal impurity transport are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

A Versatile and Accurate Method for Halo Mass Determination from Phase-space Distribution of Satellite Galaxies

We propose a versatile and accurate method to estimate the halo mass and concentration from the kinematics of satellite galaxies. We construct the 6D phase-space distribution function of satellites from a cosmological simulation based on the similarity of internal dynamics for different halos. Within the Bayesian statistical framework, not only can we efficiently infer the halo mass and concentration, we can also treat various observational effects, including the selection function, incomplete data, and measurement errors, in a rigorous and straightforward manner. Through tests with mock samples, we show that our method is valid and accurate, as well as more precise than pure steady-state methods. It can constrain the halo mass to within ~20% using only 20 tracers and has a small intrinsic uncertainty of ~10%. In addition to the clear application to the Milky Way and similar galaxies, our method can be extended to galaxy groups or clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Statistical data analysis of x-ray spectroscopy data enabled by neural network accelerated Bayesian inference

Bayesian inference applied to x-ray spectroscopy data analysis enables uncertainty quantification necessary to rigorously test theoretical models. However, when comparing to data, detailed atomic physics and radiation transfer calculations of x-ray emission from non-uniform plasma conditions are typically too slow to be performed in line with statistical sampling methods, such as Markov Chain Monte Carlo sampling. Furthermore, differences in transition energies and x-ray opacities often make direct comparisons between simulated and measured spectra unreliable. Here, we present a spectral decomposition method that allows for corrections to line positions and bound–bound opacities to best fit experimental data, with the goal of providing quantitative feedback to improve the underlying theoretical models and guide future experiments. In this work, we use a neural network (NN) surrogate model to replace spectral calculations of isobaric hot-spots created in Kr-doped implosions at the National Ignition Facility. The NN was trained on calculations of x-ray spectra using an isobaric hot-spot model post-processed with Cretin, a multi-species atomic kinetics and radiation code. The speedup provided by the NN model to generate x-ray emission spectra enables statistical analysis of parameterized models with sufficient detail to accurately represent the physical system and extract the plasma parameters of interest.

47 OTHER INSTRUMENTATION↗
NASA NTRS1972

The inference of temperature from the infrared spectra of planets.

The paper is concerned primarily with the determination of the temperature of planetary atmospheres from ground-based observations of the vibration-rotation spectra of their constituent gases. The paper is divided into two parts. The first is a discussion of the theoretical basis and analytical methods for the interpretation of planetary spectra formed by reflection of solar radiation, in the ideal case of a clear, nonscattering atmosphere; this is followed by a brief description of the effects of scattering in cloudy atmospheres on the formation of spectral lines and on the inferred temperatures. In the second part examples are given of the results which have been obtained for effective temperatures and thermal structures, for both the pure absorbing and the scattering cases, and these are compared with the results of flyby and entry probe measurements.

Farmer, C. B.↗
DOE OSTI2025

Spatially Aware Linear Transformer (SAL-T) for Particle Jet Tagging

Transformers are very effective in capturing both global and local correlations within high-energy particle collisions, but they present deployment challenges in high-data-throughput environments, such as the CERN LHC. The quadratic complexity of transformer models demands substantial resources and increases latency during inference. In order to address these issues, we introduce the Spatially Aware Linear Transformer (SAL-T), a physics-inspired enhancement of the linformer architecture that maintains linear attention. Our method incorporates spatially aware partitioning of particles based on kinematic features, thereby computing attention between regions of physical significance. Additionally, we employ convolutional layers to capture local correlations, informed by insights from jet physics. In addition to outperforming the standard linformer in jet classification tasks, SAL-T also achieves classification results comparable to full-attention transformers, while using considerably fewer resources with lower latency during inference. Experiments on a generic point cloud classification dataset (ModelNet10) further confirm this trend. Our code is available at https://github.com/aaronw5/SAL-T4HEP.

Wang, Aaron [Illinois U., Chicago] (ORCID:00000003↗
DOE OSTI2018

Prediction of Metabolite Concentrations, Rate Constants and Post-Translational Regulation Using Maximum Entropy-Based Simulations with Application to Central Metabolism of Neurospora crassa

We report the application of a recently proposed approach for modeling biological systems using a maximum entropy production rate principle in lieu of having in vivo rate constants. The method is applied in four steps: (1) a new ordinary differential equation (ODE) based optimization approach based on Marcelin’s 1910 mass action equation is used to obtain the maximum entropy distribution; (2) the predicted metabolite concentrations are compared to those generally expected from experiments using a loss function from which post-translational regulation of enzymes is inferred; (3) the system is re-optimized with the inferred regulation from which rate constants are determined from the metabolite concentrations and reaction fluxes; and finally (4) a full ODE-based, mass action simulation with rate parameters and allosteric regulation is obtained. From the last step, the power characteristics and resistance of each reaction can be determined. The method is applied to the central metabolism of Neurospora crassa and the flow of material through the three competing pathways of upper glycolysis, the non-oxidative pentose phosphate pathway, and the oxidative pentose phosphate pathway are evaluated as a function of the NADP/NADPH ratio. It is predicted that regulation of phosphofructokinase (PFK) and flow through the pentose phosphate pathway are essential for preventing an extreme level of fructose 1,6-bisphophate accumulation. Such an extreme level of fructose 1,6-bisphophate would otherwise result in a glassy cytoplasm with limited diffusion, dramatically decreasing the entropy and energy production rate and, consequently, biological competitiveness.

Cannon, William R.↗
DOE OSTI2016

A SEARCH FOR HYPERLUMINOUS X-RAY SOURCES IN THE XMM-NEWTON SOURCE CATALOG

We present a new method to identify luminous off-nuclear X-ray sources in the outskirts of galaxies from large public redshift surveys, distinguishing them from foreground and background interlopers. Using the 3XMM-DR5 catalog of X-ray sources and the SDSS DR12 spectroscopic sample of galaxies, with the help of this off-nuclear cross-matching technique, we selected 98 sources with inferred X-ray luminosities in the range 10{sup 41} < L{sub X} < 10{sup 44} erg s{sup −1}, compatible with hyperluminous X-ray objects (HLX). To validate the method, we verify that it allowed us to recover known HLX candidates such as ESO 243–49 HLX–1 and M82 X–1. From a statistical study, we conservatively estimate that up to 71 ± 11 of these sources may be foreground- or background sources, statistically leaving at least 16 that are likely to be HLXs, thus providing support for the existence of the HLX population. We identify two good HLX candidates and using other publicly available data sets, in particular the VLA FIRST in radio, UKIRT Infrared Deep Sky Survey in the near-infrared, GALEX in the ultraviolet and Canada–France–Hawaii Telescope Megacam archive in the optical, we present evidence that these objects are unlikely to be foreground or background X-ray objects of conventional types, e.g., active galactic nuclei, BL Lac objects, Galactic X-ray binaries, or nearby stars. However, additional dedicated X-ray and optical observations are needed to confirm their association with the assumed host galaxies and thus secure their HLX classification.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A Sparse Grid Method for Bayesian Uncertainty Quantification with Application to Large Eddy Simulation Turbulence Models

There is wide agreement that the accuracy of turbulence models suffer from their sensitivity with respect to physical input data, the uncertainties of user-elected parameters, as well as the model inadequacy. However, the application of Bayesian inference to systematically quantify the uncertainties in parameters, by means of exploring posterior probability density functions (PPDFs), has been hindered by the prohibitively daunting computational cost associated with the large number of model executions, in addition to daunting computation time per one turbulence simulation. In this effort, we perform in this paper an adaptive hierarchical sparse grid surrogate modeling approach to Bayesian inference of large eddy simulation (LES). First, an adaptive hierarchical sparse grid surrogate for the output of forward models is constructed using a relatively small number of model executions. Using such surrogate, the likelihood function can be rapidly evaluated at any point in the parameter space without simulating the computationally expensive LES model. This method is essentially similar to those developed in Zhang et al. (Water Resour Res 49:6871–6892, 2013) for geophysical and groundwater models, but is adjusted and applied here for a much more challenging problem of uncertainty quantification of turbulence models. Through a numerical demonstration of the Smagorinsky model of two-dimensional flow around a cylinder at sub-critical Reynolds number, our approach is proven to significantly reduce the number of costly LES executions without losing much accuracy in the posterior probability estimation. Here, the model parameters are calibrated against synthetic data related to the mean flow velocity and Reynolds stresses at different locations in the flow wake. The influence of the user-elected LES parameters on the quality of output data will be discussed.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

Shape and Stress Sensing of Multilayered Composite and Sandwich Structures Using an Inverse Finite Element Method

The marked increase in the use of composite and sandwich material systems in aerospace, civil, and marine structures leads to the need for integrated Structural Health Management systems. A key capability to enable such systems is the real-time reconstruction of structural deformations, stresses, and failure criteria that are inferred from in-situ, discrete-location strain measurements. This technology is commonly referred to as shape- and stress-sensing. Presented herein is a computationally efficient shape- and stress-sensing methodology that is ideally suited for applications to laminated composite and sandwich structures. The new approach employs the inverse Finite Element Method (iFEM) as a general framework and the Refined Zigzag Theory (RZT) as the underlying plate theory. A three-node inverse plate finite element is formulated. The element formulation enables robust and efficient modeling of plate structures instrumented with strain sensors that have arbitrary positions. The methodology leads to a set of linear algebraic equations that are solved efficiently for the unknown nodal displacements. These displacements are then used at the finite element level to compute full-field strains, stresses, and failure criteria that are in turn used to assess structural integrity. Numerical results for multilayered, highly heterogeneous laminates demonstrate the unique capability of this new formulation for shape- and stress-sensing.

Cerracchio, Priscilla↗