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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

A review of the kinetic detail required for accurate predictions of normal shock waves

Several aspects of the kinetic models used in the collision phase of Monte Carlo direct simulations have been studied. Accurate molecular velocity distribution function predictions require a significantly increased number of computational cells in one maximum slope shock thickness, compared to predictions of macroscopic properties. The shape of the highly repulsive portion of the interatomic potential for argon is not well modeled by conventional interatomic potentials; this portion of the potential controls high Mach number shock thickness predictions, indicating that the specification of the energetic repulsive portion of interatomic or intermolecular potentials must be chosen with care for correct modeling of nonequilibrium flows at high temperatures. It has been shown for inverse power potentials that the assumption of variable hard sphere scattering provides accurate predictions of the macroscopic properties in shock waves, by comparison with simulations in which differential scattering is employed in the collision phase. On the other hand, velocity distribution functions are not well predicted by the variable hard sphere scattering model for softer potentials at higher Mach numbers.

Muntz, E. P.↗
NASA NTRS1991

Wave interactions with continuous fractal layers

Many natural structures possess self-similar multiscales which can be characterized by power law spectra. Under appropriate conditions, knowledge of the strength of these scale sizes provides information on the physical processes which formed these objects. In this paper, we investigate wave interactions with continuous fractal layers which model geological and variegated structures. Since fractal characteristics of the layers are embedded in the scattered field, they can be retrieved under appropriate conditions. This inversion can be performed in either the frequency or the time domain as desired.

Kim, Y.↗
NASA NTRS2009

Spectra of Particulate Backscattering in Natural Waters

Hyperspectral profiles of downwelling irradiance and upwelling radiance in natural waters (oligotrophic and mesotrophic) are combined with inverse radiative transfer to obtain high resolution spectra of the absorption coefficient (a) and the backscattering coefficient (bb) of the water and its constituents. The absorption coefficient at the mesotrophic station clearly shows spectral absorption features attributable to several phytoplankton pigments (Chlorophyll a, b, c, and Carotenoids). The backscattering shows only weak spectral features and can be well represented by a power-law variation with wavelength (lambda): b(sub b) approx. Lambda(sup -n), where n is a constant between 0.4 and 1.0. However, the weak spectral features in b(sub b), suggest that it is depressed in spectral regions of strong particle absorption. The applicability of the present inverse radiative transfer algorithm, which omits the influence of Raman scattering, is limited to lambda < 490 nm in oligotrophic waters and lambda < 575 nm in mesotrophic waters.

Gordon, Howard, R.↗
NASA NTRS2022

Reduction of Raman Spectroscopy Data for H2-CO2-Air Tubular Flame Measurements

An approach of reducing spontaneous Raman spectroscopy data, based on the matrix inversion method which logically removes undesired sources of the Raman scattering signals including cross-talk due to the signals from other species, is discussed. The approach contains extensive calibration of temperature-dependent system response. The Raman spectra of several cold and hot calibration flames and their resulting calibration matrix are elaborated. The structure of H2-CO2-air tubular flames, in terms of major species (CO2, O2, N2, H2O, and H2) concentrations and temperature, was successfully measured with the optical technique. The Raman spectra data used in this study are taken from a uniquely designed experimental apparatus – a tubular burner and Raman spectroscopy system at Vanderbilt University. The characteristic uncertainties for chemical species are approximately ±2% by mole fraction for hot products and ±0.5% for room temperature reactants. The approach described here for hydrogen/air tubular flames may be adapted to hydrocarbon/air tubular flames when other necessary major species, for example, CH4 and CO for methane/air tubular flame, are considered in the whole process.

Raman Spectroscopy↗
DOE OSTI2026

Hidden Spin-Valley Locking Stabilizes Nanosecond Spin Polarization in 2D Perovskites

Room-temperature spin control in semiconductors is fundamental to spin-optoelectronics. Although inversion symmetry breaking offers one path for spin control in semiconductors, strong spin dephasing at elevated temperatures remains a persistent limitation. Hidden spin polarization without global symmetry breaking provides another promising material design strategy, but robust spin stabilization from this effect has yet to be experimentally realized. Here we show spin stabilization at room temperature in two-dimensional hybrid organic-inorganic perovskites through hidden spin-valley locking. We use functional non-primary ammonium cations to induce symmetry-breaking distortions in the metal-halide layers, producing giant local spin splitting while preserving global inversion symmetry. Time-resolved circular dichroism measurements reveal optically generated spin-polarized carriers that persist for 686 ps in (AzOH)2PbI4 and 4.7 ns in the lead-free analogue (AzOH)2SnI4 at room temperature, without an external magnetic field. First-principles calculations suggest that these long lifetimes arise from hidden spin valleys, enhanced dielectric screening and reduced spin-orbit-induced scattering in the Sn-based compound. Our design paradigm unlocks inversion-symmetric semiconductors with ultralong spin lifetimes, broadening the materials options for light-driven spin control.

14 SOLAR ENERGY↗
DOE OSTI2026

Elastic and resonance structures of the nucleon from the hadronic tensor in lattice QCD: Implications for neutrino-nucleon scattering and hadron physics

We compute the Euclidean hadronic tensor from charge density operators and extract elastic and resonance structures by employing exponential fits to the four-point function correlator, as well as a Bayesian reconstruction inverse algorithm to obtain the corresponding spectral density for qualitative comparison. We present the determination of the nucleon’s Sachs electric form factor using the hadronic tensor formalism and verify that it is consistent with that from the conventional three-point function calculation. Beyond the elastic peak, we observe a structure located approximately 0.5–0.7 GeV above the nucleon mass in the Bayesian reconstruction. This structure is interpreted as a mixture of the Roper resonance [𝑁⁡(1440)], and states with both positive and negative parities in this mass region, as well as multihadron states. Assuming the observed structure is dominated by 𝐽 𝑃 = 1/2 ± states, we extract the transition electric form factor 𝐺$^*_𝐸$⁡(𝑄 2 ) and the corresponding longitudinal helicity amplitude 𝑆 1/2 ⁡(𝑄 2 ), and compare them with those determined from the CLAS experimental data of nucleon-to-Roper transition. Although fitting to the four-point correlation function or using the inverse algorithm does not resolve individual resonances, it nevertheless enables the determination of total inclusive lepton–nucleon scattering cross sections in appropriate energy bins. This lattice QCD calculation presents the first major step toward studying the inclusive 𝑁 → 𝑋 contributions within the hadronic tensor formalism.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1982

Backscattered UV radiation - Effects of multiple scattering and the lower boundary of the atmosphere

A method is proposed for the calculation of a multiple-scattering correction to the single-scattering calculation of the radiance of the terrestrial atmosphere resulting from backscattered ultraviolet solar radiation in the spectral region used in the ozone profile inversion. This method uses jointly the usual analytical and Monte Carlo methods. Effects of the lower boundary of the atmosphere, cloud tops, and ground surface are investigated both qualitatively and quantitatively. The ratio of multiple to single scattering is determined, and its importance in ozone profile inversion of backscattered UV solar radiation from the terrestrial atmosphere is evaluated. The polarization of the atmospheric radiance is treated briefly.

Aruga, T.↗
DOE OSTI2025

A Monte-Carlo method for Coulomb collisions in moderately coupled plasmas

Here, we introduce a new approach for coupling cumulative and single-scattering distributions, extending Monte Carlo methods for Coulomb collisions in weakly coupled plasmas into the moderately coupled regime. Using time steps typical of cumulative-scattering methods, we show that this approach not only recovers leading-order corrections proportional to the inverse Coulomb logarithm but also solves the full Boltzmann collision integral. A key feature of the method is its simplicity: it can be integrated into cumulative-scattering methods for weakly coupled plasmas with only ~ 10 additional lines of code.

Boltzmann collision integral↗
DOE OSTI2023

In Situ Ultra-Small- and Small-Angle X-ray Scattering Study of ZnO Nanoparticle Formation and Growth through Chemical Bath Deposition in the Presence of Polyvinylpyrrolidone

ZnO inverse opals combine the outstanding properties of the semiconductor ZnO with the high surface area of the open-porous framework, making them valuable photonic and catalysis support materials. One route to produce inverse opals is to mineralize the voids of close-packed polymer nanoparticle templates by chemical bath deposition (CBD) using a ZnO precursor solution, followed by template removal. To ensure synthesis control, the formation and growth of ZnO nanoparticles in a precursor solution containing the organic additive polyvinylpyrrolidone (PVP) was investigated by in situ ultra-small- and small-angle X-ray scattering (USAXS/SAXS). Before that, we studied the precursor solution by in-house SAXS at T = 25 °C, revealing the presence of a PVP network with semiflexible chain behavior. Heating the precursor solution to 58 °C or 63 °C initiates the formation of small ZnO nanoparticles that cluster together, as shown by complementary transmission electron microscopy images (TEM) taken after synthesis. The underlying kinetics of this process could be deciphered by quantitatively analyzing the USAXS/SAXS data considering the scattering contributions of particles, clusters, and the PVP network. A nearly quantitative description of both the nucleation and growth period could be achieved using the two-step Finke–Watzky model with slow, continuous nucleation followed by autocatalytic growth.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Microstructural characterization of a star-linear polymer blend under shear flow by using rheo-SANS

We present an investigation into the dynamic relaxation mechanisms of a polybutadiene blend composed of a four-arm star (10 wt. %) and a linear polymer matrix in the presence of an applied shear flow. Our focus was the response of the star polymer, which cannot be unambiguously assessed via linear viscoelastic measurements since the signature of the star polymer can barely be detected due to the dominant contribution of the linear matrix. By utilizing small-angle neutron scattering (SANS) coupled with a Couette shear device and a deuterated matrix polymer, we investigated the dynamics of the minority star component of the blend. Our results confirm that the stars deform anisotropically with increasing shear rate. We have compared the SANS data with predictions from the well-established scattering adaptation of the state-of-the-art tube model for entangled linear polymer melts undergoing shear, i.e., Graham, Likhtman, Milner, and McLeish (GLaMM) approach, appropriately modified following earlier studies in order to apply to the star. This modified model, GLaMM-R, includes the physics necessary to understand stress relaxation in both the linear and nonlinear flow regimes, i.e., contour length fluctuations, constraint release, convective constraint release, and chain retraction. The full scattering signal is due to the minority star component and, although the contribution of the linear chains is hidden from the neutron scattering, they still influence the star polymer molecular dynamics, with the applied shear rate ranging from approximately 8 to 24 s –1 , below the inverse relaxation time of the linear component. This study provides another confirmation that the combination of rheology and neutron scattering is an indispensable tool for investigating the nonlinear dynamics of complex polymeric systems.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Accuracy Assessments of Cloud Droplet Size Retrievals from Polarized Reflectance Measurements by the Research Scanning Polarimeter

We present an algorithm for the retrieval of cloud droplet size distribution parameters (effective radius and variance) from the Research Scanning Polarimeter (RSP) measurements. The RSP is an airborne prototype for the Aerosol Polarimetery Sensor (APS), which was on-board of the NASA Glory satellite. This instrument measures both polarized and total reflectance in 9 spectral channels with central wavelengths ranging from 410 to 2260 nm. The cloud droplet size retrievals use the polarized reflectance in the scattering angle range between 135deg and 165deg, where they exhibit the sharply defined structure known as the rain- or cloud-bow. The shape of the rainbow is determined mainly by the single scattering properties of cloud particles. This significantly simplifies both forward modeling and inversions, while also substantially reducing uncertainties caused by the aerosol loading and possible presence of undetected clouds nearby. In this study we present the accuracy evaluation of our algorithm based on the results of sensitivity tests performed using realistic simulated cloud radiation fields.

Rainbow↗
NASA NTRS2000

Time-resolved diffusion tomographic 2D and 3D imaging in highly scattering turbid media

A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: wherein W is a matrix relating output at source and detector positions r.sub.s and r.sub.d, at time t, to position r, .LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise, to fluctuations in the absorption (or diffusion) X.sub.j that we are trying to determine: .LAMBDA..sub.ij =.lambda..sub.j .delta..sub.ij with .lambda..sub.j = /<.DELTA.Xj.DELTA.Xj> Y is the data collected at the detectors, and X.sup.k is the kth iterate toward the desired absorption information. An algorithm, which combines a two dimensional (2D) matrix inversion with a one-dimensional (1D) Fourier transform inversion is used to obtain images of three dimensional hidden objects in turbid scattering media.

Alfano, Robert R.↗
NASA NTRS1999

Time-resolved diffusion tomographic 2D and 3D imaging in highly scattering turbid media

A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: ##EQU1## wherein W is a matrix relating output at source and detector positions r.sub.s and r.sub.d, at time t, to position r, .LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise, to fluctuations in the absorption (or diffusion) X.sub.j that we are trying to determine: .LAMBDA..sub.ij =.lambda..sub.j .delta..sub.ij with .lambda..sub.j = /<.DELTA.Xj.DELTA.Xj> Y is the data collected at the detectors, and X.sup.k is the kth iterate toward the desired absoption information. An algorithm, which combines a two dimensional (2D) matrix inversion with a one-dimensional (1D) Fourier transform inversion is used to obtain images of three dimensional hidden objects in turbid scattering media.

Alfano, Robert R.↗
NASA NTRS1977

Inversion methods in temperature and aerosol remote sounding: Their commonality and differences, and some unexplored approaches

The two remote sensing problems of temperature profiling and aerosol characterization (complex refractive index, size distribution) are considered. These problems differ only in the explicit form of the source function which, for aerosols, includes contributions from both single and multiple scattering processes. When the observables are the spectral extinction or the single scattering of the source radiation, the associated problem is completely analogous to the linearized temperature inversion problem. Methods for obtaining the solution of the linear problem are classified following three main categories: (1) derivation of properties that all solutions satisfy, which must then be properties of the actual solution; (2) regularization of the ill-posed problem; and (3) data changes within their domain of uncertainty in order to avoid the basic instability. A number of unexplored methods are indicated.

Fymat, A. L.↗
NASA NTRS1984

Convex profiles from asteroid lightcurves

A lightcurve inversion method that yields a two-dimensional convex profile is introduced. The number of parameters that characterize the profile is limited only by the number of Fourier harmonics used to represent the parent lightcurve. The implementation of the method is outlined by a recursive quadratic programming algorithm, and its application to photoelectric lightcurves and radar measurements is discussed. Special properties of the lightcurves of geometrically scattering ellipsoids are pointed out, and those properties are used to test the inversion method and obtain a criterion for judging whether any lightcurve could actually be due to such an object. Convex profiles for several asteroids are shown, and the method's validity is discussed from a physical as well as purely statistical point of view.

Ostro, S. J.↗
NASA NTRS1985

Convex-profile Inversion of Asteroid Lightcurves

A lightcurve inversion method that yields a two-dimensional convex profile is introduced. The number of parameters that characterize the profile is limited only by the number of Fourier harmonics used to represent the parent lightcurve. The implementation of the method is outlined by a recursive quadratic programming algorithm, and its application to photoelectric lightcurves and radar measurements is discussed. Special properties of the lightcurves of geometrically scattering ellipsoids are pointed out, and those properties are used to test the inversion method and obtained a criterion for judging whether any lightcurve could actually be due to such an object. Convex profiles for several asteroids are shown, and the method's validity is discussed from a physical as well as purely statistical point of view.

Ostro, S. J.↗
DOE OSTI2022

Inverse deep learning methods and benchmarks for artificial electromagnetic material design

In this work we investigate the use of deep inverse models (DIMs) for designing artificial electromagnetic materials (AEMs) – such as metamaterials, photonic crystals, and plasmonics – to achieve some desired scattering properties (e.g., transmission or reflection spectrum). DIMs are deep neural networks (i.e., deep learning models) that are specially-designed to solve ill-posed inverse problems. There has recently been tremendous growth in the use of DIMs for solving AEM design problems however there has been little comparison of these approaches to examine their absolute and relative performance capabilities. In this work we compare eight state-of-the-art DIMs on three unique AEM design problems, including two models that are novel to the AEM community. Our results indicate that DIMs can rapidly produce accurate designs to achieve a custom desired scattering on all three problems. Although no single model always performs best, the Neural-Adjoint approach achieves the best overall performance across all problem settings. As a final contribution we show that not all AEM design problems are ill-posed, and in such cases a conventional deep neural network can perform better than DIMs. We recommend that a deep neural network is always employed as a simple baseline approach when addressing AEM design problems. Furthermore, we publish python code for our AEM simulators and our DIMs to enable easy replication of our results, and benchmarking of new DIMs by the AEM community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Bayesian Neural Network Variational Autoencoder Inverse Mapper (BNN-VAIM) and its application in Compton Form Factors extraction

Abstract We extend the Variational Autoencoder Inverse Mapper (VAIM) framework for the inverse problem of extracting Compton Form Factors (CFFs) from deeply virtual exclusive reactions, such as the unpolarized Deeply virtual exclusive scattering (DVCS) cross section. VAIM is an end-to-end deep learning framework to address the solution ambiguity issue in ill-posed inverse problems, which comprises of a forward mapper and a backward mapper to simulate the forward and inverse processes, respectively. In particular, we incorporate Bayesian Neural Network (BNN) into the VAIM architecture (BNN-VAIM) for uncertainty quantification. By sampling the weights and biases distributions of the BNN in the backward mapper of the VAIM, BNN-VAIM is able to estimate prediction uncertainty associated with each individual solution obtained for an ill-posed inverse problem. We first demonstrate the uncertainty quantification capability of BNN-VAIM in a toy inverse problem. Then, we apply BNN-VAIM to the inverse problem of extracting 8 CFFs from the unpolarized DVCS cross section.

Instruments & Instrumentation↗