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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

NUMERICAL SOLUTION FOR THE POTENTIAL AND DENSITY PROFILE OF A THERMAL EQUILIBRIUM SHEET BEAM

In a recent paper, S. M. Lund, A. Friedman, and G. Bazouin, Sheet beam model for intense space-charge: with application to Debye screening and the distribution of particle oscillation frequencies in a thermal equilibrium beam, in press, Phys. Rev. Special Topics - Accel. and Beams (2011), a 1D sheet beam model was extensively analyzed. In this complementary paper, we present details of a numerical procedure developed to construct the self-consistent electrostatic potential and density profile of a thermal equilibrium sheet beam distribution. This procedure effectively circumvents pathologies which can prevent use of standard numerical integration techniques when space-charge intensity is high. The procedure employs transformations and is straightforward to implement with standard numerical methods and produces accurate solutions which can be applied to thermal equilibria with arbitrarily strong space-charge intensity up to the applied focusing limit.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

SU-E-P-04: Transport Theory Learning Module in the Maple Environment

Purpose: The medical physics graduate program at the University of Miami is developing a computerized instructional module which provides an interactive mechanism for students to learn transport theory. While not essential in the medical physics curriculum, transport theory should be taught because the conceptual level of transport theory is fundamental, a substantial literature exists and ought to be accessible, and students should understand commercial software which solves the Boltzmann equation.But conventional teaching and learning of transport theory is challenging. Students may be under prepared to appreciate its methods, results, and relevance, and it is not substantially addressed in textbooks for the medical physicists. Other resources an instructor might reasonably use, while excellent, may be too briskly paced for beginning students. The purpose of this work is to render teaching of transport theory more tractable by making learning highly interactive. Methods: The module is being developed in the Maple mathematics environment by instructors and graduate students. It will refresh the students' knowledge of vector calculus and differential equations, and will develop users' intuition for phase space concepts. Scattering concepts will be developed with animated simulations using tunable parameters characterizing interactions, so that students may develop a “feel” for cross section. Transport equations for one and multiple types of radiation will be illustrated with phase space animations. Numerical methods of solution will be illustrated. Results: Attempts to teach rudiments of transport theory in radiation physics and dosimetry courses using conventional classroom techniques at the University of Miami have had small success, because classroom time is limited and the material has been hard for our students to appreciate intuitively. Conclusion: A joint effort of instructor and students to teach and learn transport theory by building an interactive description of it will lead to deeper appreciation of the transport theoretical underpinnings of dosimetry.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Machine Learning-Driven Conservative-to-Primitive Conversion in Hybrid Piecewise Polytropic and Tabulated Equations of State

We present a novel machine learning (ML)-based method to accelerate conservative-to-primitive inversion, focusing on hybrid piecewise polytropic and tabulated equations of state. Traditional root-finding techniques are computationally expensive, particularly for large-scale relativistic hydrodynamics simulations. To address this, we employ feedforward neural networks (NNC2PS and NNC2PL), trained in PyTorch (2.0+) and optimized for GPU inference using NVIDIA TensorRT (8.4.1), achieving significant speedups with minimal accuracy loss. The NNC2PS model achieves 𝐿 1 and 𝐿 ∞ errors of 4.54 × 10 −7 and 3.44 × 10−6, respectively, while the NNC2PL model exhibits even lower error values. TensorRT optimization with mixed-precision deployment substantially accelerates performance compared to traditional root-finding methods. Specifically, the mixed-precision TensorRT engine for NNC2PS achieves inference speeds approximately 400 times faster than a traditional single-threaded CPU implementation for a dataset size of 1,000,000 points. Ideal parallelization across an entire compute node in the Delta supercomputer (dual AMD 64-core 2.45 GHz Milan processors and 8 NVIDIA A100 GPUs with 40 GB HBM2 RAM and NVLink) predicts a 25-fold speedup for TensorRT over an optimally parallelized numerical method when processing 8 million data points. Moreover, the ML method exhibits sub-linear scaling with increasing dataset sizes. We release the scientific software developed, enabling further validation and extension of our findings. By exploiting the underlying symmetries within the equation of state, these findings highlight the potential of ML, combined with GPU optimization and model quantization, to accelerate conservative-to-primitive inversion in relativistic hydrodynamics simulations.

conservative-to-primitive conversion↗
DOE OSTI2014

A combined kick-out and dissociative diffusion mechanism of grown-in Be in InGaAs and InGaAsP. A new finite difference-Bairstow method for solution of the diffusion equations

Experimental results on the diffusion of grown-in beryllium (Be) in indium gallium arsenide (In{sub 0.53}Ga{sub 0.47}As) and indium gallium arsenide phosphide (In{sub 0.73}Ga{sub 0.27}As{sub 0.58}P{sub 0.42}) gas source molecular beam epitaxy alloys lattice-matched to indium phosphide (InP) can be successfully explained in terms of a combined kick-out and dissociative diffusion mechanism, involving neutral Be interstitials (Be{sub i}{sup 0}), singly positively charged gallium (Ga), indium (In) self-interstitials (I{sub III}{sup +}) and singly positively charged Ga, In vacancies (V{sub III}{sup +}). A new numerical method of solution to the system of diffusion equations, based on the finite difference approximations and Bairstow's method, is proposed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Out-of-time-order correlators and Lyapunov exponents in sparse SYK

We use a combination of analytical and numerical methods to study out-of-time order correlators (OTOCs) in the sparse Sachdev-Ye-Kitaev (SYK) model. We find that at a given order of N, the standard result for the q-local, all-to-all SYK, obtained through the sum over ladder diagrams, is corrected by a series in the sparsity parameter, k. We present an algorithm to sum the diagrams at any given order of 1/(kq) n . We also study OTOCs numerically as a function of the sparsity parameter and determine the Lyapunov exponent. We find that numerical stability when extracting the Lyapunov exponent requires averaging over a massive number of realizations. This trade-off between the efficiency of the sparse model and consistent behavior at finite N becomes more significant for larger values of N.

2D gravity↗
DOE OSTI2022

Data-Centric Approach to Capture Non-Polynomial Nonlinear Dynamics

We propose an analytical construction of observable functions in the extended dynamic mode decomposition (EDMD) algorithm. EDMD is a numerical method for approximating the spectral properties of the Koopman operator. The choice of observable functions is fundamental for applying EDMD to nonlinear problems arising in systems and control. Existing methods either start from a set of dictionary functions and look for the subset that best fits the underlying nonlinear dynamics or rely on machine learning algorithms to “learn” observable functions. Conversely, in this paper, we start from the dynamical system model and lift it through the Lie derivatives, rendering it into a polynomial form. This proposed transformation into a polynomial form is exact and provides an adequate set of observable functions. The strength of the proposed approach is its applicability to a broader class of nonlinear dynamical systems, particularly those with nonpolynomial functions and compositions thereof. Moreover, it retains the physical interpretability of the underlying dynamical system and can be readily integrated into existing numerical libraries. We demonstrate the proposed approach with an application to electric power systems. The modeled system consists of a single generator connected to an infinite bus, where nonlinear terms include sine and cosine functions. The results demonstrate the effectiveness of the proposed procedure in off-attractor nonlinear dynamics for estimation and prediction; the observable functions obtained from the proposed construction outperform methods that use dictionary functions comprising monomials or radial basis functions.

extended dynamic mode decomposition↗
DOE OSTI2017

Discontinuous Galerkin algorithms for fully kinetic plasmas

Here, we present a new algorithm for the discretization of the non-relativistic Vlasov–Maxwell system of equations for the study of plasmas in the kinetic regime. Using the discontinuous Galerkin finite element method for the spatial discretization, we obtain a high order accurate solution for the plasma's distribution function. Time stepping for the distribution function is done explicitly with a third order strong-stability preserving Runge–Kutta method. Since the Vlasov equation in the Vlasov–Maxwell system is a high dimensional transport equation, up to six dimensions plus time, we take special care to note various features we have implemented to reduce the cost while maintaining the integrity of the solution, including the use of a reduced high-order basis set. A series of benchmarks, from simple wave and shock calculations, to a five dimensional turbulence simulation, are presented to verify the efficacy of our set of numerical methods, as well as demonstrate the power of the implemented features.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Quasinormal modes and shadow of a Schwarzschild black hole with GUP

Highlights: • The physics of quantum corrected Schwarzschild Black Hole via GUP is investigated. • Quasinormal Modes (QNM) are obtained via WKB and numeric methods. • The relationship between shadow and QNM in the eikonal limit is established. • The quadratic and linear GUP parameters affect the results in a clear way. We consider quantum corrections for the Schwarzschild black hole metric by using the generalized uncertainty principle (GUP) to investigate quasinormal modes, shadow and their relationship in the eikonal limit. We calculate the quasinormal frequencies of the quantum-corrected Schwarzschild black hole by using the sixth-order Wentzel–Kramers–Brillouin (WKB) approximation, and also perform a numerical analysis that confirms the results obtained from this approach. We also find that the shadow radius is nonzero even at very small mass limit for finite GUP parameter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

PRELIMINARY COUPLING OF THE MONTE CARLO CODE OPENMC AND THE MULTIPHYSICS OBJECT-ORIENTED SIMULATION ENVIRONMENT (MOOSE) FOR ANALYZING DOPPLER FEEDBACK IN MONTE CARLO SIMULATIONS

In recent years the use of Monte Carlo methods for modeling reactors has become feasible due to the increasing availability of massively parallel computer systems. One of the primary challenges yet to be fully resolved, however, is the efficient and accurate inclusion of multiphysics feedback in Monte Carlo simulations. The research in this paper presents a preliminary coupling of the open source Monte Carlo code OpenMC with the open source Multiphysics Object-Oriented Simulation Environment (MOOSE). The coupling of OpenMC and MOOSE will be used to investigate efficient and accurate numerical methods needed to include multiphysics feedback in Monte Carlo codes. An investigation into the sensitivity of Doppler feedback to fuel temperature approximations using a two dimensional 17x17 PWR fuel assembly is presented in this paper. The results show a functioning multiphysics coupling between OpenMC and MOOSE. The coupling utilizes Functional Expansion Tallies to accurately and efficiently transfer pin power distributions tallied in OpenMC to unstructured finite element meshes used in MOOSE. The two dimensional PWR fuel assembly case also demonstrates that for a simplified model the pin-by-pin doppler feedback can be adequately replicated by scaling a representative pin based on pin relative powers.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Exact and efficient hybrid Monte Carlo algorithm for accelerated Bayesian inference of gene expression models from snapshots of single-cell transcripts

Single cells exhibit a significant amount of variability in transcript levels, which arises from slow, stochastic transitions between gene expression states. Elucidating the nature of these states and understanding how transition rates are affected by different regulatory mechanisms require state-of-the-art methods to infer underlying models of gene expression from single cell data. A Bayesian approach to statistical inference is the most suitable method for model selection and uncertainty quantification of kinetic parameters using small data sets. However, this approach is impractical because current algorithms are too slow to handle typical models of gene expression. To solve this problem, we first show that time-dependent mRNA distributions of discrete-state models of gene expression are dynamic Poisson mixtures, whose mixing kernels are characterized by a piecewise deterministic Markov process. Here, we combined this analytical result with a kinetic Monte Carlo algorithm to create a hybrid numerical method that accelerates the calculation of time-dependent mRNA distributions by 1000-fold compared to current methods. We then integrated the hybrid algorithm into an existing Monte Carlo sampler to estimate the Bayesian posterior distribution of many different, competing models in a reasonable amount of time. We demonstrate that kinetic parameters can be reasonably constrained for modestly sampled data sets if the model is known a priori. If there are many competing models, Bayesian evidence can rigorously quantify the likelihood of a model relative to other models from the data. We demonstrate that Bayesian evidence selects the true model and outperforms approximate metrics typically used for model selection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

First-principles studies of p-type nitrogen-doped α-Fe{sub 2}O{sub 3-x}S{sub x} alloys

Based on spin-polarized density functional theory, the characteristics of p-type doping are investigated in the N-doped α-Fe{sub 2}O{sub 3−x}S{sub x} alloys by means of first-principles methods. Numerical results show that when N substitutes O atom in pure α-Fe{sub 2}O{sub 3}, N impurity level is a deeper acceptor state. However, the unoccupied level is much shallower when N doped in the α-Fe{sub 2}O{sub 3−x}S{sub x} alloys, which indicates N impurity can provide good and effective p-type carriers. These predicted numerical results are interesting and useful to understand the α-Fe{sub 2}O{sub 3−x}S{sub x} alloys as a new low-cost solar cell material.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Statistical Mechanics Modeling of Mesoscale Deformation in Metals

The research under this project focused on a theoretical and computational modeling of dislocation dynamics of mesoscale deformation of metal single crystals. Specifically, the work aimed to implement a continuum statistical theory of dislocations to understand strain hardening and cell structure formation under monotonic loading. These aspects of crystal deformation are manifestations of the evolution of the underlying dislocation system under mechanical loading. The project had three research tasks: 1) Investigating the statistical characteristics of dislocation systems in deformed crystals. 2) Formulating kinetic equations of dislocations and coupling these kinetics equations and crystal mechanics. 3) Computational solution of coupled crystal mechanics and dislocation kinetics. Comparison of dislocation dynamics predictions with experimental results in the area of statistical properties of dislocations and their field was also a part of the proposed effort. In the first research task, the dislocation dynamics simulation method was used to investigate the spatial, orientation, velocity, and temporal statistics of dynamical dislocation systems, and on the use of the results from this investigation to complete the kinetic description of dislocations. The second task focused on completing the formulation of a kinetic theory of dislocations that respects the discrete nature of crystallographic slip and the physics of dislocation motion and dislocation interaction in the crystal. Part of this effort also targeted the theoretical basis for establishing the connection between discrete and continuum representation of dislocations and the analysis of discrete dislocation simulation results within the continuum framework. This part of the research enables the enrichment of the kinetic description with information representing the discrete dislocation systems behavior. The third task focused on the development of physics-inspired numerical methods of solution of the coupled dislocation kinetics and crystal mechanics framework. To a large extent, this task has also been successfully started. We have developed a custom finite-element approach with mesh points being a subset of the underlying crystal structure. When used to predict the evolution of the dislocation system, the planar motion of dislocations is naturally captured for all slip systems, thus minimizing numerical errors and providing simple ways to investigate cross slip and dislocation reactions. Preliminary results in this direction show that we are closer than ever in building a predictive framework for dislocation dynamics and mesoscale plasticity based on the first principles of dislocation dynamics. The rest of the report gives and overview of the research performed under this project and highlights the key results and open questions left for future investigations.

36 MATERIALS SCIENCE↗
DOE OSTI2016

DEVELOPMENT OF A VERIFICATION BENCHMARK SUITE FOR THE ATR REACTOR PHYSICS UPGRADE

The result of a numerical algorithm is only as good as the effort made toward its verification. Comprehensive computer codes, especially for application to nuclear reactors, require in-depth assessment of the numerical methods used and their computational implementation. This presentation describes a suite of semi-analytical benchmarks for the ATR Reactor Physics Upgrade as part of the ATR Life Extension Project (LEP). Several neutron transport codes including deterministic codes HELIOS, NEWT and probabilistic codes MCNP6, SERPANT and MC21 are upgrade candidates. To properly evaluate code performance capabilities, code verification is an essential element. A credible verification program requires education to guide proper application, training in proper input preparation and output expectation and verification to instill confidence in the coded numerical procedures. The subset of the benchmark suite to be described here is primarily of the 1D transport variety (however, a 2D case does indeed exist) with the intent to provide unquestionably high order accurate semi-analytical numerical solutions to the transport equation. We base the analytical solutions on analytical Fourier series and discrete ordinates representations. Here we present two 1D benchmarks based on Fourier series.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

Hardness of H13 Tool Steel After Non-isothermal Tempering

A direct method to calculate the tempering response of a tool steel (H13) that exhibits secondary hardening is presented. Based on the traditional method of presenting tempering response in terms of isothermal tempering, we show that the tempering response for a steel undergoing a non-isothermal tempering schedule can be predicted. Experiments comprised (1) isothermal tempering, (2) non-isothermal tempering pertaining to a relatively slow heating to process-temperature and (3) fast-heating cycles that are relevant to tempering by induction heating. After establishing the tempering response of the steel under simple isothermal conditions, the tempering response can be applied to non-isothermal tempering by using a numerical method to calculate the tempering parameter. Calculated results are verified by the experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Characterization of supersonic radiation diffusion waves

Supersonic and diffusive radiation flow is an important test problem for the radiative transfer models used in radiation-hydrodynamics computer codes owing to solutions being accessible via analytic and numeric methods. We present experimental results with which we compare these solutions by studying supersonic and diffusive flow in the laboratory. Here, we present results of higher-accuracy experiments than previously possible studying radiation flow through up to 7 high-temperature mean free paths of low-density, chlorine-doped polystyrene foam and silicon dioxide aerogel contained by an Au tube. Measurements of the heat front position and absolute measurements of the x-ray emission arrival at the end of the tube are used to test numerical and analytical models. We find excellent absolute agreement with simulations provided that the opacity and the equation of state are adjusted within expected uncertainties; analytical models provide a good phenomenological match to measurements but are not in quantitative agreement due to their limited scope.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Estimation of constituent properties of concrete materials with an artificial neural network based method

Multi-scale models are developed for heterogeneous concrete materials to estimate their macroscopic mechanical properties in terms of micro-structural data. One crucial challenge of those models is the identification of local properties of constituent phases. In this paper, we present an efficient method based on Artificial Neural Networks (ANN). Typical concrete materials are taken as example. A macroscopic analytical strength criterion is established from three steps of nonlinear homogenization procedure. The macroscopic strength of materials is determined as a function of the frictional coefficient and cohesion of solid cement particles at nanometer scale, intra-particle pores, inter-particle pores and aggregates (inclusions). The objective is to identify the nanoscopic frictional coefficient and cohesion of cement particle from measured macroscopic values of uniaxial compression and tensile strengths. For this purpose, a numerical method based on the ANN is developed. With the analytical macroscopic strength criterion, sensitivity studies are first realized to identify the most important micro-structural parameters influencing the macroscopic strength of concrete. A simplified analytical macroscopic strength criterion is then proposed. A large dataset is further constructed through the inversion of the analytical strength criterion by using the aggregates volume fraction, porosity, macroscopic uniaxial tensile and compressive strengths as input variables and the frictional coefficient and cohesion of cement particles as output unknowns. An ANN model containing four hidden layers and 100 neurons in each layer is constructed and trained by using this dataset. Various types of validation of the ANN model are performed. It is found that the proposed ANN based model can effectively predict the frictional coefficient and cohesion of porous cement paste at the microscopic scale with a very good accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Modulational instability of electrostatic acoustic waves in an electron-hole semiconductor quantum plasma

The modulational instability of quantum electrostatic acoustic waves in electron-hole quantum semiconductor plasmas is investigated using the quantum hydrodynamic model, from which a modified nonlinear Schrödinger equation with damping effects is derived using the reductive perturbation method. Here, we consider the combined effects of quantum recoil, quantum degenerate pressures, as well as the exchange-correlation effect standing for the electrons (holes) spin. The modulational instability for different semiconductors (GaAs, GaSb, and InP) is discussed. The collision between electron (hole) and phonon is also investigated. The permitted maximum time for modulational instability and the damping features of quantum envelope solitary wave are all determined by the collision. The approximate solitary solution with damping effects is presented in weak collision limit. The damping properties were discussed by numerical method.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Ion sound instability driven by the ion flows

Ion sound instabilities driven by the ion flow in a system of a finite length are considered by analytical and numerical methods. The ion sound waves are modified by the presence of stationary ion flow resulting in negative and positive energy modes. The instability develops due to coupling of negative and positive energy modes mediated by reflections from the boundary. It is shown that the wave dispersion due to deviation from quasineutrality is crucial for the stability. In finite length system, the dispersion is characterized by the length of the system measured in units of the Debye length. The instability is studied analytically and the results are compared with direct, initial value numerical simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗