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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Stochastic multiscale modeling for quantifying statistical and model errors with application to composite materials

This paper provides a coherent and efficient computational framework for stochastic multiscale analysis of material systems in the presence of parametric uncertainties and modeling errors. Uncertainty in those model parameters that are not deduced as upscaled quantities is attributed to an uncertainty “germ”. While such parameters can appear at any scale, they are predominant at the finest analysis scale. Additional uncertainties stemming from statistical estimation, attributed to lack of data and model error, are associated with each submodel contributing to the multiscale system. Here, a robust and efficient framework based on a generalized extended polynomial chaos expansion (gEPCE) is proposed to simultaneously propagate all these uncertainties in order to provide a probabilistic representation of specific quantities of interest (QoI). We characterize the full probability distribution of the QoI and the uncertainty in the failure probability pertaining to its tails. By combining gEPCE with kernel density estimation (KDE) and directional derivatives, we construct sensitivity measures that connect these statistical metrics of QoI to the various sources of uncertainty to assess their individual and combined impacts. An illustrative problem featuring three-point bending of a composite beam is investigated to demonstrate the presented approach.

36 MATERIALS SCIENCE↗
DOE OSTI2024

1D modeling of plasma streamers at ammonia-air flame conditions

Abstract Self-consistent 1D modeling of streamers in ammonia-oxygen-nitrogen-water mixtures has been performed in this work. A fluid model that includes species transport, electrostatic potential, and detailed chemistry was developed and verified. This model is then used to simulate the avalanche, streamer formation and propagation phases, driven by a nanosecond voltage pulse, at different thermochemical conditions derived from a 1D laminar premixed ammonia-air flame. The applicability of the Meek’s criterion in predicting the streamer inception location was successfully confirmed. Streamer formation and propagation duration were found to vary significantly with different thermochemical conditions, due to the difference in ionization rates. The thermochemical state also affected the breakdown characteristics which was tested by maintaining the background reduced electric field constant. Detailed kinetic analyses revealed the importance of O ( 1 D ) in the production of key radicals, such as O, OH, and NH 2 . Furthermore, the contributions of the dissociative electronic excitation of NH 3 towards the production of H and NH 2 radicals have also been reported. Spatial and temporal evolution of the electron energy loss fractions for various inelastic collision processes at different thermochemical states uncovered the input plasma energy spent of fuel dissociation and the large variability in the dominant processes during the avalanche and streamer propagation phases. The methodology and analyses reported in this work are key towards developing effective strategies for controlled nanosecond-pulsed non-equilibrium plasma sources used for ammonia ignition and flame stabilization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Machine learning-assisted identification of potential sources of bias in measurements of prompt-fission neutron spectra

Unrecognized sources of uncertainty (USU) can bias the reported mean and/or covariance of experimental nuclear data. These biases, in turn, can propagate through evaluated nuclear data to application simulations or may poorly inform nuclear theory that is fitted to the experimental data. Such unknown sources of bias must be tied to the inherent physical constituents of the measurements such as the characteristics of a detector response or a background reduction technique. Here, in this article, a sparse Bayesian learning model is used to support experts in their efforts to identify and characterize USU in experimental prompt fission neutron spectra (PFNS) for spontaneous fissioning of 252 Cf by linking observed biases to features of the measurement system. Three different bias components were found. The first acts as a verification case for the algorithm as it identifies a bias coming from a well-known source related to the use of 6 Li in the neutron detection system. The second two cases demonstrate how this method can benefit the evaluation of experimental nuclear data by identifying, quantifying, and relating unknown biases to potential causes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments

In this paper, we developed a machine learning-based Bayesian approach to inversely quantify and reduce the uncertainties of multiphase computational fluid dynamics (MCFD) simulations for bubbly flows. The proposed approach is supported by high-resolution two-phase flow measurements, including those by double-sensor conductivity probes, high-speed imaging, and particle image velocimetry. Local distributions of key physical quantities of interest (QoIs), including the void fraction and phasic velocities, are obtained to support the Bayesian inference. In the process, the epistemic uncertainties of the closure relations are inversely quantified while the aleatory uncertainties from stochastic fluctuations of the system are evaluated based on experimental uncertainty analysis. The combined uncertainties are then propagated through the MCFD solver to obtain uncertainties of the QoIs, based on which probability-boxes are constructed for validation. The proposed approach relies on three machine learning methods: feedforward neural networks and principal component analysis for surrogate modeling, and Gaussian processes for model form uncertainty modeling. The whole process is implemented within the framework of an open-source deep learning library PyTorch with graphics processing unit (GPU) acceleration, thus ensuring the efficiency of the computation. The results demonstrate that with the support of high-resolution data, the uncertainties of MCFD simulations can be significantly reduced. The proposed approach has the potential for other applications that involve numerical models with empirical parameters.

42 ENGINEERING↗
NASA NTRS1980

Emulsion chamber observations of primary cosmic-ray electrons in the energy range 30-1000 GeV

The results of a series of emulsion exposures, beginning in Japan in 1968 and continued in the U.S. since 1975, which have yielded a total balloon-altitude exposure of 98,700 sq m sr s, are presented. The data are discussed in terms of several models of cosmic-ray propagation. Interpreted in terms of the energy-dependent leaky-box model, the spectrum results suggest a galactic electron residence time of 1.0(+2.0, -0.5) x 10 to the 7th yr, which is consistent with results from Be-10 observations. Finally, the possibility that departures from smooth power law behavior in the spectrum due to individual nearby sources will be observable in the energy range above 1 TeV is discussed.

Nishimura, J.↗
NASA NTRS1983

Baroclinic instability in the stratosphere and mesosphere

The energy source of stratospheric planetary waves is largely due to vertical propagation from the troposphere, but the stratospheric zonal mean state which changes with time is not stable against small perturbations, whereby transient perturbation waves are generated at the expense of the stratospheric zonal mean available potential energy. This theoretical conclusion is obtained based on the quasi-geostrophic model in spherical coordinates which calculates the characteristic solutions for the basic zonal mean state changing with time.

Zhang, K. S.↗
NASA NTRS1985

Propagation of injected cosmic rays under distributed reacceleration

The cosmic ray acceleration model in which the particles gain continuously energy from stochastic processes in the interstellar space by encountering shocks leads to a logarithmic increase in the secondary to primary ratios with energy, which is inconsistent with observations. The observed decrease of the secondary to primary ratios may therefore suggest that a considerable part of the acceleration has taken place rapidly at the sources. Astronomical observations on the other hand indicate that shocks from supernovae do exist in the galaxy and observations in the interplanetary space show clear evidence that shock acceleration works.

Simon, M.↗
NASA NTRS2017

Computational Modeling of Meteor-Generated Ground Pressure Signatures

We present a thorough validation of a computational approach to predict infrasonic signatures of centimeter-sized meteoroids. We assume that the energy deposition along the meteor trail is dominated by atmospheric drag and simulate the steady, inviscid flow of air in thermochemical equilibrium to compute the meteoroid's near-body pressure signature. This signature is then propagated through a stratified and windy atmosphere to the ground using a methodology adapted from aircraft sonic-boom analysis. An assessment of the numerical accuracy of the near field and the far field solver is presented. The results show that when the source of the signature is the cylindrical Mach-cone, the simulations closely match the observations. The prediction of the shock rise-time, the zero-peak amplitude of the waveform, and the duration of the positive pressure phase are consistently within 10% of the measurements. Uncertainty in the shape of the meteoroid results in a poorer prediction of the trailing part of the waveform. Overall, our results independently verify energy deposition estimates deduced from optical observations.

Computational↗
DOE OSTI2026

Machine learning for seismic low-frequency extrapolation

The cycle-skipping problem that plagues full waveform inversion (FWI) can be at least partially mitigated if low frequencies (which encode the kinematics of wave propagation in seismic data) are recorded. However, seismic sources and receivers are band-limited, so seismic data does not generally include signals down to 0 Hz. To improve our ability to solve the seismic inverse problem, one can synthesize this missing low-frequency (LF) content from the recorded high-frequency (HF) data using machine learning (ML) models. Deep learning models such as convolutional neural networks (CNNs) demonstrate impressive ability to perform low frequency extrapolation. However, such models require powerful hardware (GPU machines) and careful training. We assess the extrapolation capabilities of three different ML models that do not require GPU machines, namely, random forest, Gaussian process regression and gradient boosting, on both synthetic and real data. Experimental results on two synthetic data sets (generated from a low velocity lens embedded in a homogeneous medium, and the Marmousi model) demonstrate that FWI applied to the extrapolated data consistently improves inversion accuracy relative to FWI applied to the original data sets that do not contain low frequencies. Application of low-frequency extrapolation to real data from the Northwest Shelf of Australia demonstrates that tree-based ML models such as gradient boosting can outperform CNNs in terms of both accuracy and computational cost on non-GPU architectures.

58 GEOSCIENCES↗
NASA NTRS1986

The time-dependent dynamical response of the thermosphere to major geomagnetic disturbances

Several recent observations of thermospheric dynamics, made in the polar regions during extremely disturbed geomagnetic periods are reviewed. In general, the magnitude and the variability of winds in the thermospheric polar regions increases with magnetic activity, as measured by any of the conventional indices. However, none of the conventional indices is a particularly good aid to predicting wind magnitudes. In very general terms, two major factors may be considered in describing the wind system. The magnitude of the Interplanetary Magnetic Field (IMF) and, in particular, its southward component, determine the size of the auroral oval, and the strength of the cross-polar cap potential. This determines the size of the auroral oval, the magnitude of the sunward winds in the auroral oval and of those blowing anti-sunward over the polar cap, and is probably the major factor in determining the rate of geomagnetic energy deposition in the thermosphere. Superimposed on this enhanced polar circulation system are the effects of discrete auroral substorms. From a global view point, the effect of substorms is to generate a series of strong disturbances which propagate from their source region, usually near magnetic midnight in the auroral oval. The energy associated with discrete substorms is, however, usually a rather small proportion of the total global geomagnetic input during disturbed periods. These observations of thermospheric wind disturbances will be evaluated by comparison with global simulations of the thermospheric response to theoretical and semi-empirical models of the polar electric field, and of the effects of magnetospheric particle precipitation.

Rees, D.↗
NASA NTRS2013

Dynamics and Control of a Disordered System in Space

In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of N grains in orbit, with N greater than 10(exp 3). These grains can be large (Cubesat-size) or small (mm-size), and can be active, i.e., a fully equipped vehicle capable sensing their own position and attitude, and enabled with propulsion means, or entirely passive. The ultimate objective would be to study the behavior of the single grains and of large ensembles of grains in orbit and to identify ways to guide and control the shape of a cloud composed of these grains so that it can perform a useful function in space, for instance, as an element of an optical imaging system for astrophysical applications. This concept, in which the aperture does not need to be continuous and monolithic, would increase the aperture size several times compared to large NASA observatories such as ATLAST, allowing for a true Terrestrial Planet Imager that would be able to resolve exo-planet details and do meaningful spectroscopy on distant world. In the paper, we address the modeling and autonomous operation of a distributed assembly (the cloud) of large numbers of highly miniaturized space-borne elements (the grains). A multi-scale, multi-physics model is proposed of the dynamics of the cloud in orbit, as well as a control law for cloud shape maintenance, and preliminary simulation studies yield an estimate of the computational effort, indicating a scale factor of approximately N(exp 1.4) as a function of the number of grains. A granular spacecraft can be defined as a collection of a large number of space-borne elements (in the 1000s) designed and controlled such that a desirable collective behavior emerges, either from the interactions among neighboring grains, and/or between the grains and the environment. In this paper, each grain is considered to be a highly miniaturized spacecraft which has limited size and mass, hence it has limited actuation, limited propulsive capability, limited power, limited sensing, limited communication, limited computational resources, limited range of motion, limited lifetime, and may be expendable. The modeling and dynamics of clouds of vehicles is more challenging than with conventional vehicles because we are faced with a probabilistic vehicle composed of a large number of physically disconnected vehicles. First, different scales of motion occur simultaneously in a cloud: translations and rotations of the cloud as a whole (macro-dynamics), relative rotation and translation of one cloud member with respect to another (meso-dynamics), and individual cloud member dynamics (micro-dynamics). Second, the control design needs to be tolerant of the system complexity, of the system architecture (centralized vs. decentralized large scale system control) as well as robust to un-modeled dynamics and noise sources. Figure 1, top left, shows the kinematic parameters of a 1000 element cloud in orbit. The motion of the system is described with respect to a local vertical-local horizontal (LV-LH) orbiting reference frame (x,y,z)=F(sub ORF) of origin O(sub ORF) which rotates with mean motion omega and orbital semi-major axis R(sub 0). The orbital geometry at the initial time is defined in terms of its six orbital elements, and the orbital dynamics equation for point O(sub ORF) is propagated forward in time under the influence of the gravitational field of the primary and other external perturbations, described below. The origin of this frame coincides with the initial position of the center of mass of the system, and the coordinate axes are z along the local vertical, x toward the flight direction, and y in the orbit normal direction. The assumptions we used to model the dynamics are as follows: 1) The inertial frame is fixed at Earth's center. 2) The orbiting Frame ORF follows Keplerian orbit. 3) the cloud system dynamics is referred to ORF. 4) the attitude of each grain uses the principal body frame as body fixed frame. 5) the atmosphere is assumed to be rigidly rotating with the Earth. Regarding the grains forming the cloud: 1) each grain is modeled as a rigid body; 2) a simple attitude estimator provides attitude estimates, 3) a simple guidance logic commands the position and attitude of each grain, 4) a simple local feedback controller based on PD control of local states is used to stabilize the attitude of the vehicle. Regarding the cloud: 1) the cloud as a whole is modeled as an equivalent rigid body in orbit, and 2) an associated graph establishes agent connectivity and enables coupling between modes of motion at the micro and macro scales; 3) a simple guidance and estimation logic is modeled to estimate and command the attitude of this equivalent rigid body; 4) a cloud shape maintenance controller is based on the dynamics of a stable virtual truss in the orbiting frame. Regarding the environmental perturbations acting on the cloud: 1) a non-spherical gravity field including JO (Earth's spherical field) zonal component, J2 (Earth's oblateness) and J3 zonal components is implemented; 2) atmospheric drag is modeled with an exponential model; 3) solar pressure is modeled assuming the Sun is inertially fixed; and 4) the Earth's magnetic field is model using an equivalent dipole model. The equations of motion are written in a referential system with respect to the origin of the orbiting frame and the state is propagated forward in time using an incremental predictor-corrector scheme. A representative cloud with varying number of grains is simulated to identify the limitations in computation time as the number of grains grows. We derive a control law to track a desired surface in the ORF (equivalently to maintain a reference cloud shape) by defining an error from a desired surface shape, and designing a control law that is exponentially stable and reduces the tracking error to zero. Figure 1 (top right) shows a comparison of various requirements for simulation of single spacecraft vs. granular spacecraft, indicating the high degree of complexity that needs to be taken into consideration. The ORF components of control force required by one of the grains is, for this particular case, in the micro-Newton range. However, no attempt has been made yet to reconfigure (or re-orient) the cloud configuration internally, for which forces in the milli-Newton level are expected, depending on the time required to do the reconfiguration. Figure 1, bottom, shows the computation time as a function of the number of grains, indicating an order N(exp 1.43) scaling on a 8 Gb, 1067 MHz RAM MacOSX computer with a 3.06 GHz Intel Core 2 Duo processor. With this metric, the same simulation for a system of N=1000 grains would take 5.4 hours, and 146 hours (i.e., 6 days) for a system with N=10,000 grains. Therefore, efficient ways to simulate this complex system, where not only the time scales of natural system dynamics, but also the sampling times of the Guidance, Navigation, and Control are included, remain to be explored. Additional details on the cloud modeling, dynamics, and control will be described in the paper.

simulation↗
NASA NTRS1976

Electrons in a closed galaxy model of cosmic rays

The consistency of positrons and electrons was studied using a propagation model in which the cosmic rays are stopped by nuclear collisions or energy losses before they can escape from the galaxy (the closed-galaxy model). The fact that no inconsistency was found between the predictions and the data implies that the protons which produce the positrons by nuclear reactions could have their origin in a large number of distant sources, as opposed to the heavier nuclei which in this model come from a more limited set of sources. The closed-galaxy model predicts steep electron and positron spectra at high energies. None of these are inconsistent with present measurements; but future measurements of the spectrum of high-energy positrons could provide a definite test for the model. The closed-galaxy model also predicts that the interstellar electron intensity below a few GeV is larger than that implied by other models. The consequence of this result is that electron bremsstrahlung is responsible for about 50% of the galactic gamma-ray emission at photon energies greater than 100 MeV.

Ramaty, R.↗
NASA NTRS1976

Electrons in a closed galaxy model of cosmic rays

The paper considers the consistency of positrons and electrons with a propagation model in which the cosmic rays are stopped by nuclear collisions or energy losses before they can escape from the Galaxy (the closed-galaxy model). The fact that no inconsistency is found between the predictions and the data implies that the protons which produce the positrons by nuclear reactions could have their origin in a large number of distant sources, as opposed to the heavier nuclei which in this model come from a more limited set of sources. The closed-galaxy model predicts steep electron and positron spectra at high energies. None of these are inconsistent with present measurements; but future measurements of the spectrum of high-energy positrons could provide a definite test for the model. The closed-galaxy model also predicts that the interstellar electron intensity below a few GeV is larger than that implied by other models. The consequence of this result is that electron bremsstrahlung is responsible for about 50% of the galactic gamma-ray emission at photon energies greater than 100 MeV

Ramaty, R.↗
NASA NTRS1986

A study of methods to predict and measure the transmission of sound through the walls of light aircraft

Progress was made in the following areas: development of a numerical/empirical noise source identification procedure using bondary element techniques; identification of structure-borne noise paths using structural intensity and finite element methods; development of a design optimization numerical procedure to be used to study active noise control in three-dimensional geometries; measurement of dynamic properties of acoustical foams and incorporation of these properties in models governing three-dimensional wave propagation in foams; and structure-borne sound path identification by use of the Wigner distribution.

Bernhard, R. J.↗
NASA NTRS1998

Modeling the Plasmasphere

The plasmasphere has often been considered one of the more boring regions in the magnetosphere. Its low energy plasma doesn't begin to compete against the free sources of energy available in the ring current, auroral zone, or plasma sheet. Its best known feature is its relatively highly density, archived as a result of prolonged accumulation of ionospheric outflow onto corotating flux tubes. On second look, however, the plasmasphere can be found to exhibit a remarkable influence on its more energetic cousins and display convection behavior indicative of physical processes acting throughout the magnetosphere for which we have no explanation. Plasmaspheric plasma densities and composition of heavy ions are particularly sensitive to heating by processes active in the ionosphere and all along field lines. Wave propagation and instabilities, collisional losses in the ring current, and heat transport from superthermal electrons are all equally sensitive to dense, heavy plasmaspheric densities and density gradients. It is in this context that we seek to characterize plasmaspheric populations using event based, empirical, and physical modeling methods. The modeling approaches, the challenges, and some of the results of these efforts will be presented.

Gallagher, Dennis L↗
DOE OSTI2020

unWISE tomography of Planck CMB lensing

CMB lensing tomography, or the cross-correlation between CMB lensing maps and large-scale structure tracers over a well-defined redshift range, has the potential to map the amplitude and growth of structure over cosmic time, provide some of the most stringent tests of gravity, and break important degeneracies between cosmological parameters. In this work, we use the unWISE galaxy catalog to provide three samples at median redshifts z ~ 0.6, 1.1 and 1.5, fully spanning the Dark Energy dominated era, together with the most recent Planck CMB lensing maps. We obtain a combined cross-correlation significance S/N = 79.3 over the range of scales 100 < ℓ < 1000. We measure the redshift distribution of unWISE sources by a combination of cross-matching with the COSMOS photometric catalog and cross-correlation with BOSS galaxies and quasars and eBOSS quasars. We also show that magnification bias must be included in our analysis and perform a number of null tests. In a companion paper, we explore the derived cosmological parameters by modeling the non-linearities and propagating the redshift distribution uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Variable Ion Compositions of Solar Energetic Particle Events in the Inner Heliosphere: A Field Line Braiding Model with Compound Injections

We propose a model for interpreting highly variable ion composition ratios in solar energetic particle (SEP) events recently observed by the Parker Solar Probe (PSP) at 0.3–0.45 au. We use numerical simulations to calculate SEP propagation in a turbulent interplanetary magnetic field with a Kolmogorov power spectrum from large scales down to the gyration scale of energetic particles. We show that when the source regions of different species are offset by a distance comparable to the size of the source regions, the observed energetic particle composition He/H can be strongly variable over more than two orders of magnitude, even if the source ratio is at the nominal value. Assuming a 3 He/ 4 He source ratio of 10% in impulsive 3 He-rich events and the same spatial offset of the source regions, the 3 He/ 4 He ratio at observation sites also vary considerably. The variability of the ion composition ratios depends on the radial distance, which can be tested by observations made at different radial locations. We discuss the implications of these results on the variability of ion composition of impulsive events and on further PSP and Solar Orbiter observations close to the Sun.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Global barotropic response to a tropical forcing

Zonally varying flow has been used to initialize numerical models and has been shown to play an important role in strong localized responses both in extratropics and the tropics. In this study, a climatological 200 mb January mean is used as a steady basic state of a barotropical model which consists of shallow water equations and a mass source centered at 4 deg S/120 deg E to simulate convective heating over Indonesia region. In the experiment, tropical responses appear not only over the western Pacific, where the forcing is located, but also over the eastern Pacific where the response is related to the zonally varying basic state. The westward propagating equatorial Rossby waves excited by the forcing interact with waves out of and into the tropics and the positive and negative phase of the Rossby waves result in blocking circulation over North America and tropical plumes over equatorial eastern Pacific, respectively.

Zhang, Yuxia↗