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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Edge Reconstruction in a Quantum Spin Hall Insulator

We study interaction-driven edge reconstruction in a quantum spin Hall insulator described by the Bernevig-Hughes-Zhang model with Kanamori-Hubbard interactions using the real-space density matrix renormalization group method in both the grand-canonical and canonical ensembles. For a two-dimensional cylinder with a smooth edge, we identify discrete particle-number transitions that lead to a spin-polarized edge state stabilized by an emergent ferromagnetic exchange interaction. The reconstruction is orbital-selective, occurring predominantly in the 𝑠-orbital channel. Our results reveal a microscopic mechanism for emergent fluctuating moments at the edge that could compromise the topological protection of helical edge states by time-reversal symmetry.

Soni, Rahul [ORNL] (ORCID:0000000317714299)↗
DOE OSTI2024

Anti-symmetric and positivity preserving formulation of a spectral method for Vlasov-Poisson equations

We analyze the anti-symmetric properties of a spectral discretization for the one-dimensional Vlasov-Poisson equations. The discretization is based on a spectral expansion in velocity with the symmetrically weighted Hermite basis functions, central finite differencing in space, and an implicit Runge Kutta integrator in time. The proposed discretization preserves the anti-symmetric structure of the advection operator in the Vlasov equation, resulting in a stable numerical method. We apply such discretization to two formulations: the canonical Vlasov-Poisson equations and their continuously transformed square-root representation. The latter preserves the positivity of the particle distribution function. We derive analytically the conservation properties of both formulations, including particle number, momentum, and energy, which are verified numerically on the following benchmark problems: manufactured solution, linear and nonlinear Landau damping, two-stream instability, bump-on-tail instability, and ion-acoustic wave.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Comparing the MELCOR Aerosol Deposition Model with Exact Analytical Solutions

Exact analytical solutions are presented for the evolution of the aerosol particle mass density function in a control volume for particle deposition due to gravitational settling, thermophoresis, and diffusion. The solutions are for arbitrary initial mass density functions and are applied for an initial lognormal density function. Integration of these solutions provides the suspended mass in the control volume as a function of time. These solutions serve as an exact benchmark to assess the accuracy of numerical methods. For the numerical algorithm used in MELCOR, excellent agreement is obtained for gravitational settling, diffusive deposition, and thermophoretic deposition for the suspended aerosol mass. In all cases, the default number of discrete particle size bins of 10 is shown to converge, with hardly any advantage to using 20 size bins.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2015

Comprehensive Thematic T-Matrix Reference Database: A 2014-2015 Update

The T-matrix method is one of the most versatile and efficient direct computer solvers of the macroscopic Maxwell equations and is widely used for the computation of electromagnetic scattering by single and composite particles, discrete random media, and particles in the vicinity of an interface separating two half-spaces with different refractive indices. This paper is the seventh update to the comprehensive thematic database of peer-reviewed T-matrix publications initiated by us in 2004 and includes relevant publications that have appeared since 2013. It also lists a number of earlier publications overlooked previously.

electromagnetic scattering↗
DOE OSTI2024

Multiphysics Degradation Modeling of Energy Storage Materials via RKPM with a Neural Network-Enhancement

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. A coupled electro-chemo-mechanical reproducing kernel particle method (RKPM) formulation is developed, and a patch-test is formulated to certify optimal convergence of the proposed RKPM method for the coupled physics system. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based model construction by RKPM is then used to represent the complex material microstructures for modeling the coupled physics of these systems. Further, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1, 2] is introduced to effectively model damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. Reference: [1] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022. [2] Baek, J., Chen, J. S., "A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture", Computer Methods in Applied Mechanics and Engineering Vol. 410, 116590, 2024.

electro-chemo-mechanical coupling↗
DOE OSTI2023

Biomass Feedstock Flow Modeling at Exascale

Variable biomass feedstock handling in hoppers and screw conveyors can cause upstream failures and disrupt downstream conversion operations. Understanding how particle size, shape, and moisture content affect feedstock flowability is important for efficient biorefinery operation. We present the use of our open-source discrete element method (DEM) solver for predicting flows in large scale hoppers and assess its performance on state-of-the-art high performance computing platforms that use heterogenous computing architectures.

bioenergy↗
DOE OSTI2020

Multi-physics modeling of injected nanoparticles effect on remediation of CO 2 leakage through cracks

One potential risk in CO 2 sequestration is the leakage of carbon dioxide, which can result in contamination of underground water, creating potential threats to existing ecosystems. The common leakage pathway is through the pre-existing fractures or discontinuities within cement in the wellbore, incurred by the environmental conditions imposed on the cement. Injecting nanoparticles into pre-existing cracks is one of the most recently proposed ideas for mitigating fracture propagation in cement CO 2 sequestration. To demonstrate the feasibility of this new technology, a numerical approach was taken in this work, as it is challenging to investigate it in a laboratory setting. We proposed a coupled ALE (Arbitrary Lagrangian–Eulerian)–DEM (Discrete Element Method)–peridynamic modeling strategy within the LS-Dyna package to investigate the intertwined interaction among the CO 2 fluid flow, native fluid (e.g., brine), particle clusters, and cracks within the cement. The numerical results demonstrate that injected nanoparticles can effectively reduce the pressure exerted on the crack surface. Accordingly, the potential fracture propagation at the crack tip would be reduced compared to corresponding cases without nanoparticels as pressurized by fluid flow. This result verifies the effectiveness of proposed nanoparticle injection technology. Finally, using this established modeling strategy, the effect of filling particles on the fracture mitigation for different crack geometries (e.g. particle cluster patterns, aspect ratio of crack aperture and length) and CO 2 reservoir pressure are examined. The result shows that injected particles successfully reduce the fracture propagation in these scenarios.

42 ENGINEERING↗
NASA NTRS2010

Comprehensive T-Matrix Reference Database: A 2007-2009 Update

The T-matrix method is among the most versatile, efficient, and widely used theoretical techniques for the numerically exact computation of electromagnetic scattering by homogeneous and composite particles, clusters of particles, discrete random media, and particles in the vicinity of an interface separating two half-spaces with different refractive indices. This paper presents an update to the comprehensive database of T-matrix publications compiled by us previously and includes the publications that appeared since 2007. It also lists several earlier publications not included in the original database.

Mishchenko, Michael I.↗
DOE OSTI2025

CLPNets: Coupled Lie–Poisson neural networks for multi-part Hamiltonian systems with symmetries

To accurately compute data-based prediction of Hamiltonian systems, it is essential to utilize methods that preserve the structure of the equations over time. We consider a particularly challenging case of systems with interacting parts that do not reduce to pure momentum evolution. Such systems are essential in scientific computations, such as discretization of a continuum elastic rod, which can be viewed as the group of rotations and translations $SE(3)$. The evolution involves not only the momenta but also the relative positions and orientations of the particles. The presence of Lie group-valued elements, such as relative positions and orientations, poses a problem for applying previously derived methods for data-based computing. We develop a novel method of data-based computation and complete phase space learning of such systems. We follow the original framework of SympNets (Jin et al., 2020) and LPNets (Eldred et al., 2024), building the neural network from phase space mappings that preserve the Lie–Poisson structure. We derive a novel system of mappings that are built into neural networks describing the evolution of such systems. We call such networks Coupled Lie–Poisson Neural Networks, or CLPNets. We consider increasingly complex examples for the applications of CLPNets, starting with the rotation of two rigid bodies about a common axis, progressing to the free rotation of two rigid bodies, and finally to the evolution of two connected and interacting $SE(3)$ components, describing the discretization of an elastic rod into two elements. Our method preserves all Casimir invariants to machine precision, preserves energy to high accuracy, and shows good resistance to the curse of dimensionality, requiring only a few thousand data points for all cases studied (three to eighteen dimensions). Additionally, the method is highly economical in memory requirements, requiring only about 200 parameters for the most complex case considered.

Data-based modeling↗
DOE OSTI2024

Masked Particle Modeling on Sets: Towards Self-Supervised High Energy Physics Foundation Models

Abstract We propose masked particle modeling (MPM) as a self-supervised method for learning generic, transferable, and reusable representations on unordered sets of inputs for use in high energy physics (HEP) scientific data. This work provides a novel scheme to perform masked modeling based pre-training to learn permutation invariant functions on sets. More generally, this work provides a step towards building large foundation models for HEP that can be generically pre-trained with self-supervised learning and later fine-tuned for a variety of down-stream tasks. In MPM, particles in a set are masked and the training objective is to recover their identity, as defined by a discretized token representation of a pre-trained vector quantized variational autoencoder. We study the efficacy of the method in samples of high energy jets at collider physics experiments, including studies on the impact of discretization, permutation invariance, and ordering. We also study the fine-tuning capability of the model, showing that it can be adapted to tasks such as supervised and weakly supervised jet classification, and that the model can transfer efficiently with small fine-tuning data sets to new classes and new data domains.

Heinrich, Lukas (ORCID:0000000240487584)↗
NASA NTRS1985

Hybrid simulation techniques applied to the earth's bow shock

The application of a hybrid simulation model, in which the ions are treated as discrete particles and the electrons as a massless charge-neutralizing fluid, to the study of the earth's bow shock is discussed. The essentials of the numerical methods are described in detail; movement of the ions, solution of the electromagnetic fields and electron fluid equations, and imposition of appropriate boundary and initial conditions. Examples of results of calculations for perpendicular shocks are presented which demonstrate the need for a kinetic treatment of the ions to reproduce the correct ion dynamics and the corresponding shock structure. Results for oblique shocks are also presented to show how the magnetic field and ion motion differ from the perpendicular case.

Winske, D.↗
NASA NTRS2004

Current State of Modeling the Photochemistry of Titan's Mutually Dependent Atmosphere and Ionosphere

In the context of recent observations, microphysical models, and laboratory data, a photochemical model of Titan's atmosphere, including updated chemistry focusing on rate coefficients and cross sections measured under appropriate conditions, has been developed to increase understanding of these processes and improve upon previous Titan photochemical models. The model employs a two-stream discrete ordinates method to characterize the transfer of solar radiation, and the effects of electron-impact, cosmic-ray deposition, and aerosol opacities from fractal and Mie particles are analyzed. Sensitivity studies demonstrate that an eddy diffusion profile with a homopause level of 850 km and a methane stratospheric mole fraction of 2.2% provides the best fit of stratospheric and upper atmosphere observations and an improved fit over previous Titan photochemical models. Lack of fits for C3H8, HC3N, and possibly C2H3CN can be resolved with adjustments in aerosol opacity. The model presents a benzene profile consistent with its detection in Titan's stratosphere [Coustenis et al., 2003], which may play an important role in the formation of Titan hazes. An electron peak concentration of 4200 cm(exp -3) is calculated, which exceeds observations by 20%, considerably lower than previous ionosphere models. With adjustments in aerosol opacities and surface fluxes the model illustrates that reasonable fits to existing observations are possible with a single eddy diffusion profile, contrary to the conclusions of previous Titan models. These results will aid in the receipt and interpretation of data from Cassini-Huygens, which will arrive at Titan in 2004 and deploy a probe into Titan's atmosphere in January 2005.

ion chemistry↗
NASA NTRS2017

Electromagnetic Scattering by Spheroidal Volumes of Discrete Random Medium

We use the superposition T-matrix method to compare the far-field scattering matrices generated by spheroidal and spherical volumes of discrete random medium having the same volume and populated by identical spherical particles. Our results fully confirm the robustness of the previously identified coherent and diffuse scattering regimes and associated optical phenomena exhibited by spherical particulate volumes and support their explanation in terms of the interference phenomenon coupled with the order-of-scattering expansion of the far-field Foldy equations. We also show that increasing non-sphericity of particulate volumes causes discernible (albeit less pronounced) optical effects in forward and backscattering directions and explain them in terms of the same interference/multiple-scattering phenomenon.

Electromagnetic scattering; Multi-particle groups;↗
NASA NTRSDate not supplied

Nonlinear Homogenization of Finitely Deformed Viscoelastic-Viscoplastic Composites Using Mechanics of Structure Genome

The objective of this paper is to develop a micromechanics approach to homogenizing finitely deformed viscoelastic-viscoplastic composites using the mechanics of structure genome. The incremental constitutive relation for glassy polymers, formulated in the spatial configuration, is implemented in the present approach.This involves (1) pulling-back the constitutive model to the material configuration and (2)choosing the deformation gradient tensor and the first Piola–Kirchhoff stress tensor as the strain and the stress measures during homogenization, respectively. An Euler–Newton predictor–corrector method is developed for homogenization. Each step involves formulating a variational statement using the mechanics of structure genome, discretizing the statement in a finite-dimensional space, and solving the problem using an Euler/multilevel Newton method. The present approach is demonstrated by homogenizing fiber- and particle-reinforced composites undergoing uniaxial, biaxial, or shear deformation, at different stain rates.

Multi-scale modeling, High Strain Composites, Visc↗
NASA NTRS1987

Statistical analysis of secondary particle distributions in relativistic nucleus-nucleus collisions

The use is described of several statistical techniques to characterize structure in the angular distributions of secondary particles from nucleus-nucleus collisions in the energy range 24 to 61 GeV/nucleon. The objective of this work was to determine whether there are correlations between emitted particle intensity and angle that may be used to support the existence of the quark gluon plasma. The techniques include chi-square null hypothesis tests, the method of discrete Fourier transform analysis, and fluctuation analysis. We have also used the method of composite unit vectors to test for azimuthal asymmetry in a data set of 63 JACEE-3 events. Each method is presented in a manner that provides the reader with some practical detail regarding its application. Of those events with relatively high statistics, Fe approaches 0 at 55 GeV/nucleon was found to possess an azimuthal distribution with a highly non-random structure. No evidence of non-statistical fluctuations was found in the pseudo-rapidity distributions of the events studied. It is seen that the most effective application of these methods relies upon the availability of many events or single events that possess very high multiplicities.

Mcguire, Stephen C.↗
NASA NTRS1999

Plasma Pressure in the Topside Ionosphere

A previous three year NASA-funded project resulted in the first 2-D maps of magnetotail pressure, density and temperature. A proposal to continue the work was declined, but modest funding was provided for one year to ramp down of the work. During the phase-out year, we used a time when 5 DMSP satellites were simultaneously active to produce the first instantaneous partial image of the magnetotail. The results have been submitted to the proceedings of the 1998 Huntsville Meeting on "The New Millennium Magnetosphere: Integrating Imaging, Discrete Observations and Global Simulations". A method of inferring central plasma sheet (CPS) temperature, density, and pressure from ionospheric observations was developed under a previous 3-year grant. These particles properties are calculated from data taken by particle instruments on DMSP satellites. Ion spectra occurring in conjunction with electron acceleration events are excluded. Because of the variability of magnetotail stretching, mapping to the plasma sheet was done using a modified Tsyganenko 1989 magnetic field model adjusted to agree with the actual magnetotail stretch. On May 25, 1997, five DMSP satellites (F10-F14) passed through the southern hemisphere nightside oval within a 19 minute period. Attached is the first magnetotail image, which results from applying our technique to that data set.

Newell, Patrick T.↗
DOE OSTI2020

A quadratic programming flux correction method for high-order DG discretizations of S transport

In this work, we present a new flux-fixup approach for arbitrarily high-order discontinuous Galerkin (DG) discretizations of the S N transport equation, and we demonstrate the compatibility of this approach with the Variable Eddington Factor (VEF) method. The new fixup approach is sweep-compatible: during a transport sweep (block Gauss-Seidel iteration in which the scattering source is lagged), a local quadratic programming (QP) problem is solved in each spatial element to ensure that the solution satisfies certain physical constraints, including local particle balance. In this paper, we describe two choices of physical constraints, resulting in two variants of the method: QP Zero (QPZ) and QP Maximum Principle (QPMP). In QPZ, the finite element coefficients of the solution are constrained to be nonnegative. In QPMP, they are constrained to adhere to an approximate discrete maximum principle. There are two primary takeaways in this paper. First, when the positive Bernstein basis is used for DG discretization, the QPMP method eliminates negativities, preserves high-order accuracy for smooth problems, and significantly dampens unphysical oscillations in the solution. The latter feature – the dampening of unphysical oscillations – is an improvement upon standard, simpler fixup approaches such as the approach described in (denoted as the “zero and rescale” (ZR) method in this paper). This improvement comes at a moderate computational cost, but it is not prohibitive. Our results show that, even in an unrealistic worst-case scenario where 83% of the spatial elements require a fixup, the computational cost of performing a transport sweep with fixup is only ~31% greater than performing one without fixup. The second takeaway is that the VEF method can be used to accelerate the convergence of transport sweeps even when a fixup is applied. When optically thick regions are present, transport sweeps converge slowly, regardless of whether a fixup is applied, and acceleration is needed. However, attempting to apply standard diffusion synthetic acceleration (DSA) to fixed-up transport sweeps results in divergence for optically thick problems. Our results show that the same is not true for VEF. When VEF is combined with fixed-up transport sweeps, the result is a scheme that produces a nonnegative solution, converges independently of the mean free path, and, in the case of the QPMP fixup, adheres to an approximate discrete maximum principle.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2017

Comprehensive Thematic T-Matrix Reference Database: A 2015-2017 Update

The T-matrix method pioneered by Peter C. Waterman is one of the most versatile and efficient numerically exact computer solvers of the time-harmonic macroscopic Maxwell equations. It is widely used for the computation of electromagnetic scattering by single and composite particles, discrete random media, periodic structures (including metamaterials), and particles in the vicinity of plane or rough interfaces separating media with different refractive indices. This paper is the eighth update to the comprehensive thematic database of peer-reviewed T-matrix publications initiated in 2004 and lists relevant publications that have appeared since 2015. It also references a small number of earlier publications overlooked previously.

T-matrix method↗