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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 OSTI2025

Diffusion Quantum Monte Carlo Benchmarking of Magnetic Moments in MnBi 2 Te 4

The intrinsically antiferromagnetic topological insulator, MnBi 2 Te 4 (MBT), has garnered significant attention recently due to its potential to host numerous exotic topological quantum states. Unfortunately, their consistent realization has been hindered by intrinsic antisite defects among the Mn and Bi sublattices. In this work, we establish Mn magnetization of pristine MBT through high level diffusion Monte Carlo calculations, which can serve as a precise starting point for various models to estimate antisite defect concentrations in actual MBT samples. The benchmark quality of DMC calculations is further identified from out model estimating antisite defect concentrations, which combines the benchmarked Mn magnetization with data from magnetic susceptibility and intermediate field magnetization measurements. This reproduces well Bi Mn and Mn Bi concentrations measured in the experiments. Here, we anticipate these theoretically based magnetic purity measures may be used as minimization targets in cycles of refinement to synthesize MBT with low antisite defect concentrations and more reproducible topological properties.

Defects↗
DOE OSTI2016

Diffusivities of Ag, Cs, Sr, and Kr in TRISO fuel particles and graphite

Tri-structural isotropic (TRISO) coated particles have been developed and studied since the late 1950s when the concept of coated particles was invented by Roy Huddle of the United Kingdom Atomic Energy Authority. Several decades of work by half a dozen countries on fission product transport in TRISO fuel through numerous irradiation and heating experiments have led to several recommendations of transport data and to the adoption of various sets of diffusion coefficients. In 1997, the International Atomic Energy Agency (IAEA) gathered all these historical results and issued a technical document (TECDOC-978 [IAEA]) that summarizes these sets of recommended diffusion coefficients. Table 1 shows the reference literature articles for the diffusivities that have historically been recommended by the American and German TRISO fuel development programs and that are summarized in the IAEA report (see section 7 for full references of these articles).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Spectral Denoising for Accelerated Analysis of Correlated Ionic Transport

Computation of correlated ionic transport properties from molecular dynamics in the Green-Kubo formalism is expensive, as one cannot rely on the affordable mean square displacement approach. We use spectral decomposition of the short-time ionic displacement covariance to learn a set of diffusion eigenmodes that encode the correlation structure and form a basis for analyzing the ionic trajectories. This allows systematic reduction of the uncertainty and accelerate computations of ionic conductivity in systems with a steady-state correlation structure. We provide mathematical and numerical proofs of the method’s robustness and demonstrate it on realistic electrolyte materials.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Сoncentric GaAs Nanorings Growth Modelling

The nanostructures formation process using the droplet epitaxy technique was investigated by Monte Carlo simulation. The simulation was fulfilled for two-dimensional and three-dimensional geometry substrates. The nanostructures morphology dependence on the growth temperature was presented. Crystal clusters, single and double rings were observed. The nanostructures shape was shown to be determined by the gallium diffusion length. The conditions of double rings formation during the droplet epitaxy were considered using analytical and numerical approaches. The factors that determine the rings location and shape were analyzed. The growth morphology was demonstrated to be dependent on the initial distance L between the droplets. The double ring formation was possible at a low droplet density only, when the As-stabilized region could be created between the droplets.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A reaction–diffusion model for phenotypic evolution

We present a reaction–diffusion mathematical model for the evolutionary dynamics of phenotypic evolution. A detailed deduction of the equations is presented for the one-dimensional version, from which a more general model is proposed. Particular cases are studied using analytical approximations and numerical simulations. Results indicate that the approach proposed produces results that are coherent with mainstream models in evolutionary dynamics, suggesting that the reaction–diffusion model could be an alternative tool in the analysis of evolutionary dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

A Study of the von Neumann Stability Analysis of a Semi-implicit Numerical Method Applied Over the Radial Impurity Transport Equation in Tokamak Plasma

The radial impurity transport equation for tokamak plasma is a form of diffusion–convection–reaction equation. The impurity transport equation is solved to determine the distribution of impurity (non-fuel) ion species with different ionization states perpendicular to magnetic surfaces of tokamak plasma. The equation for each charge (ionization) state Z is a non-linear, second-order in space, first-order in time, parabolic partial differential equation coupled to the previous Z − 1 and the next Z + 1 charge states of the impurity species through its reaction term. The number of differential equations to be solved simultaneously is hence determined by the number of ionization states of the impurity species studied. The solution to the set of these coupled equations can be obtained using a semi-implicit numerical method applied on it. The present study describes the application of von Neumann stability analysis over the semi-implicit numerical method applied over the radial impurity transport equation and determines a generic stability criterion for the method. The stability analysis is further illustrated using the geometry of Aditya tokamak installed at the Institute for Plasma Research Gandhinagar, India as an example. The impurity species considered is oxygen (Atomic number = 8). This leads to a set of eight coupled equations for charge states Z = 1 to 8 over which von Neumann analysis is illustrated in present study.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Microstructural Modeling of the α + β Phase in Ti-6Al-4V: A Diffusion-Based Approach

Complex heat treatment operations and advanced manufacturing processes such as laser or electron-beam welding will see the metallic workpiece experience a considerable range of temperatures and heating/cooling rates. These intrinsic conditions will have a significant bearing upon the microstructure of the material, and in turn upon the thermo-mechanical properties. In this work, a diffusion-based approach to model the growth and shrinkage of precipitates in the alpha + beta field of the common titanium alloy Ti-6Al-4V is established. Further, the numerical model is extended using a JMA-type approach to explore the dependency of the beta-transus temperature on extremely high heating rates, whereby dissolution alone is too slow to accurately describe the alpha to beta-phase transformation. Experimental heat treatments at rates of 5, 50, and 500 °C/s were performed, and metallographic analysis of the samples was used to validate the numerical modeling framework predictions for lamellar shrinkage, while data from the literature has been used to evaluate the numerical modeling framework for the growth of equiaxed microstructures. The agreement between measurements and numerical predictions was found to be good.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Gas Flow and Ion Transfer in Heated ESI Capillary Interfaces

Transfer capillaries are the preferred means to transport ions, generated by electrospray ionization, from ambient conditions to vacuum. During the transfer of ions through the narrow, long tubes into vacuum, substantial losses are typical. However, recently it was demonstrated that these losses can be avoided altogether. To understand the experimental observation and provide a general model for the ion transport, here, we investigate the ion transport through capillaries by numerical simulation of interacting ions. The simulation encompasses all relevant factors, such as space charge, diffusion, gas flow, and heating. Special attention is paid to the influence of the gas flow on the transmission and especially the change imposed by heating. The gas flow is modeled by a one-dimensional gas dynamics description. A large number of ions are treated as point particles in this gas flow. This allows to investigate the influence of the capillary heating on the gas flow and by this on the ion transport. The results are compared with experimental findings. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

HomPINNs: Homotopy physics-informed neural networks for learning multiple solutions of nonlinear elliptic differential equations

Physics-informed neural networks (PINNs) based machine learning is an emerging framework for solving nonlinear differential equations. However, due to the implicit regularity of neural network structure, PINNs can only find the flattest solution in most cases by minimizing the loss functions. In this paper, we combine PINNs with the homotopy continuation method, a classical numerical method to compute isolated roots of polynomial systems, and propose a new deep learning framework, named homotopy physics-informed neural networks (HomPINNs), for solving multiple solutions of nonlinear elliptic differential equations. The implementation of an HomPINN is a homotopy process that is composed of the training of a fully connected neural network, named the starting neural network, and training processes of several PINNs with different tracking parameters. The starting neural network is to approximate a starting function constructed by the trivial solutions, while other PINNs are to minimize the loss functions defined by boundary condition and homotopy functions, varying with different tracking parameters. These training processes are regraded as different steps of a homotopy process, and a PINN is initialized by the well-trained neural network of the previous step, while the first starting neural network is initialized using the default initialization method. Finally, several numerical examples are presented to show the efficiency of our proposed HomPINNs, including reaction-diffusion equations with a heart-shaped domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Pressure falloff testing to characterize CO 2 plume and dry-out zone during CO 2 injection in saline aquifers

The fluid mobilities and the lateral extent of the CO 2 plume and the dry-out zone are among important unknowns required to effectively manage CO 2 storage in saline aquifers projects. These unknowns can be derived from pressure falloff testing which has been widely used to characterize the subsurface. This paper provides a three-region analytical solution for falloff pressure during the infinite-acting period of CO 2 injection in saline aquifers. The solution is derived using Laplace transformation technique of the governing diffusivity equations and the accompanying initial and boundary conditions. The exact solution is validated against numerical results obtained from a black-oil reservoir simulator for two cases. The solution is approximated into simple forms in real-time domain considering different time periods. Then, a graphical semi-log analysis technique based on the approximate solutions is provided as an interpretation tool of falloff tests where the fluid mobilities and the extents of dry-out zone and CO 2 plume can be inferred. The interpretation technique is applied to synthetic falloff test data to investigate its potential and reliability.

02 PETROLEUM↗
DOE OSTI2016

What is the surface temperature of a solid irradiated by a Petawatt laser?

In this paper, when a solid target is irradiated by a Petawatt laser pulse, its surface is heated to tens of millions of degrees within a few femtoseconds, facilitating a diffusive heat wave and the acceleration of electrons to MeV energies into the target. Using numerically converged collisional particle-in-cell simulations, we observe a competition between two surface heating mechanisms–inverse bremsstrahlung in solid density on the one hand and electron scattering on turbulent electric fields on the other. Collisionless heating effectively dominates above the relativistic intensity threshold. Our numerical results show that a high-contrast 40 fs, f/5 laser pulse with 1 J energy will heat the skin layer to 5 keV, and the inside of the target over several microns deep to bulk temperatures in the range of 10–100 eV at solid density.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Learning effective stochastic differential equations from microscopic simulations: Linking stochastic numerics to deep learning

We identify effective stochastic differential equations (SDEs) for coarse observables of fine-grained particle- or agent-based simulations; these SDEs then provide useful coarse surrogate models of the fine scale dynamics. We approximate the drift and diffusivity functions in these effective SDEs through neural networks, which can be thought of as effective stochastic ResNets. The loss function is inspired by, and embodies, the structure of established stochastic numerical integrators (here, Euler–Maruyama and Milstein); our approximations can thus benefit from backward error analysis of these underlying numerical schemes. They also lend themselves naturally to “physics-informed” gray-box identification when approximate coarse models, such as mean field equations, are available. Existing numerical integration schemes for Langevin-type equations and for stochastic partial differential equations can also be used for training; we demonstrate this on a stochastically forced oscillator and the stochastic wave equation. Our approach does not require long trajectories, works on scattered snapshot data, and is designed to naturally handle different time steps per snapshot. We consider both the case where the coarse collective observables are known in advance, as well as the case where they must be found in a data-driven manner.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Multiphysics and Multiscale Modeling of Coupled Transport of Chloride Ions in Concrete

Chloride ions (Cl−)-induced corrosion is one of the main degradation mechanisms in reinforced concrete (RC) structures. In most situations, the degradation initiates with the transport of Cl− from the surface of the concrete towards the reinforcing steel. The accumulation of Cl− at the steel-concrete interface could initiate reinforcement corrosion once a threshold Cl− concentration is achieved. An accurate numerical model of the Cl− transport in concrete is required to predict the corrosion initiation in RC structures. However, existing numerical models lack a representation of the heterogenous concrete microstructure resulting from the varying environmental conditions and the indirect effect of time dependent temperature and relative humidity (RH) on the water adsorption and Cl− binding isotherms. In this study, a numerical model is developed to study the coupled transport of Cl− with heat, RH and oxygen (O2) into the concrete. The modeling of the concrete microstructure is performed using the Virtual Cement and Concrete Testing Laboratory (VCCTL) code developed by the U.S. National Institute of Standards and Technology (NIST). The concept of equivalent maturation time is utilized to eliminate the limitation of simulating concrete microstructure using VCCTL in specific environmental conditions such as adiabatic. Thus, a time-dependent concrete microstructure, which depends on the hydration reactions coupled with the temperature and RH of the environment, is achieved to study the Cl− transport. Additionally, Cl− binding isotherms, which are a function of the pH of the concrete pore solution, Cl− concentration, and weight fraction of mono-sulfate aluminate (AFm) and calcium-silicate-hydrate (C-S-H), obtained from an experimental study by the same authors are utilized to account for the Cl− binding of cement hydration products. The temperature dependent RH diffusion was considered to account for the transport of Cl− with moisture transport. The temperature and RH diffusion in the concrete domain, composite theory, and Cl− binding and water adsorption isotherms are used in combination, to estimate the ensuing Cl− diffusion field within the concrete. The coupled transport process of heat, RH, Cl−, and O2 is implemented in the Multiphysics Object-Oriented Simulation Environment (MOOSE) developed by the U.S. Idaho National Laboratory (INL). The model was verified and validated using data from multiple experimental studies with different concrete mixture proportions, curing durations, and environmental conditions. Additionally, a sensitivity analysis was performed to identify that the water-to-cement (w/c) ratio, the exposure duration, the boundary conditions: temperature, RH, surface Cl− concentration, Cl− diffusion coefficient in the capillary water, and the critical RH are the important parameters that govern the Cl− transport in RC structures. In a case study, the capabilities of the developed numerical model are demonstrated by studying the complex 2D diffusion of Cl− in a RC beam located in two different climatic regions: warm and humid weather in Galveston, Texas, and cold and dry weather in North Minnesota, Minnesota, subjected to time varying temperature, RH, and surface Cl− concentrations.

composite theory↗
DOE OSTI2017

An accurate and asymptotically compatible collocation scheme for nonlocal diffusion problems

Here, in this paper, we develop and analyze a collocation scheme for solving the linear nonlocal diffusion problem with general kernels. To approximate the nonlocal diffusion operator, we take a classic trapezoidal rule based on the linear interpolation as the starting point, and then carefully derive a new improved quadrature rule, which is not only more accurate but also could avoid the evaluations of singular integrals. We then use this rule to construct a collocation scheme for solving the nonlocal diffusion equations, that produces a symmetric positive definite stiffness matrix with Toeplitz structure. The proposed scheme is rigorously shown to be of second order accurate with respect to the mesh size for the nonlocal problem with fixed horizon, and in particular, it can achieve higher order accuracy for the commonly used kernels in the literature. Furthermore, we also prove that the scheme is asymptotically compatible, i.e., the approximate solution of the nonlocal diffusion problem converges to the exact solution of the corresponding local PDE problem when the horizon and the mesh size both go to zero. Finally, numerical experiments are presented to verify the theoretical results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Cosmic-Ray Transport in Heliospheric Magnetic Structures. II. Modeling Particle Transport through Corotating Interaction Regions

The transport of cosmic rays (CRs) in the heliosphere is determined by the properties of the solar wind plasma. The heliospheric plasma environment has been probed by spacecraft for decades and provides a unique opportunity for testing transport theories. Of particular interest for the three-dimensional (3D) heliospheric CR transport are structures such as corotating interaction regions (CIRs), which, due to the enhancement of the magnetic field strength and magnetic fluctuations within and due to the associated shocks as well as stream interfaces, do influence the CR diffusion and drift. In a three-fold series of papers, we investigate these effects by modeling inner-heliospheric solar wind conditions with the numerical magnetohydrodynamic (MHD) framework Cronos (Wiengarten et al., referred as Paper I), and the results serve as input to a transport code employing a stochastic differential equation approach (this paper). While, in Paper I, we presented results from 3D simulations with Cronos, the MHD output is now taken as an input to the CR transport modeling. We discuss the diffusion and drift behavior of Galactic cosmic rays using the example of different theories, and study the effects of CIRs on these transport processes. In particular, we point out the wide range of possible particle fluxes at a given point in space resulting from these different theories. The restriction of this variety by fitting the numerical results to spacecraft data will be the subject of the third paper of this series.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Numerical analyses of exponential time-differencing schemes for the solution of atmospheric models

In high-resolution numerical weather prediction models, fast-moving acoustic waves must be treated in a stable manner. Among the implicit–explicit (IMEX) schemes used for the solution of these models, horizontally explicit, vertically implicit (HEVI) methods show good stability and scalability on massively parallel machines. In this work, we present two classes of exponential time-differencing (ETD) methods for atmospheric models that use a HEVI splitting strategy, one being a three-stage method with the addition of artificial diffusion, the second based on a Strang splitting approach. Overall, the stability properties of the methods are analyzed and numerical examples are provided, which compare time-step restrictions and cost-to-accuracy ratios of the new methods with those for existing approaches.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

THE AGORA HIGH-RESOLUTION GALAXY SIMULATIONS COMPARISON PROJECT. II. ISOLATED DISK TEST

Using an isolated Milky Way-mass galaxy simulation, we compare results from nine state-of-the-art gravito-hydrodynamics codes widely used in the numerical community. We utilize the infrastructure we have built for the AGORA High-resolution Galaxy Simulations Comparison Project. This includes the common disk initial conditions, common physics models (e.g., radiative cooling and UV background by the standardized package Grackle) and common analysis toolkit yt, all of which are publicly available. Subgrid physics models such as Jeans pressure floor, star formation, supernova feedback energy, and metal production are carefully constrained across code platforms. With numerical accuracy that resolves the disk scale height, we find that the codes overall agree well with one another in many dimensions including: gas and stellar surface densities, rotation curves, velocity dispersions, density and temperature distribution functions, disk vertical heights, stellar clumps, star formation rates, and Kennicutt–Schmidt relations. Quantities such as velocity dispersions are very robust (agreement within a few tens of percent at all radii) while measures like newly formed stellar clump mass functions show more significant variation (difference by up to a factor of ∼3). Systematic differences exist, for example, between mesh-based and particle-based codes in the low-density region, and between more diffusive and less diffusive schemes in the high-density tail of the density distribution. Yet intrinsic code differences are generally small compared to the variations in numerical implementations of the common subgrid physics such as supernova feedback. Our experiment reassures that, if adequately designed in accordance with our proposed common parameters, results of a modern high-resolution galaxy formation simulation are more sensitive to input physics than to intrinsic differences in numerical schemes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

A numerical hybrid model for outdoor sound propagation in complex urban environments

Noise mapping in large and dense urban areas is computationally challenging, if not impossible, with the use of conventional numerical techniques. Recently, promising results have shown the potential of energy-based models to compete with conventional numerical techniques. In this study, a hybrid full-wave/diffusion propagation model is proposed to address some of the flaws of the traditional diffusion model. The full-wave model is used for predicting sound propagation (i) near the source, where interactions between waves are important, and (ii) outside the cluttered environment, where free-field-like conditions apply. Finally, the diffusion model is used in regions where diffusion conditions are met.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗