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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Vidyut3d: A GPU accelerated fluid solver for non-equilibrium plasmas on adaptive grids

We present the numerical methods, programming methodology, verification, and performance assessment of a non-equilibrium plasma fluid solver that can effectively utilize current and upcoming central processing and graphics processing unit (CPU+GPU) architectures, in this work. Our plasma fluid model solves the coupled conservation equations for species transport, electrostatic Poisson and electron temperature on adaptive Cartesian grids. Our solver is written using performance portable adaptive-grid/particle management library, AMReX, and is portable over widely available vendor specific GPU architectures. We present verification of our solver using method of manufactured solutions that indicate formal second order accuracy with central diffusion and fifth-order weighted-essentially-non-oscillatory (WENO) advection scheme. We also verify our solver with published literature on capacitive discharges and atmospheric pressure streamer propagation. We demonstrate the use of our solver on two 3D simulation cases: an atmospheric streamer propagation in Ar-H2 mixtures and a low pressure three-electrode radio frequency reactor. Our performance studies on three different CPU+GPU architectures indicate ~ 150-400X speed-up using AMD and NVIDIA GPUs per time step compared to a single CPU core for a 4 million cell simulation with 15 species.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Development of a Performance Portable Non-Equilibrium Plasma Fluid Solver on Adaptive Grids

This presentation will describe the numerical techniques, programming paradigms, verification, and performance of a non-equilibrium plasma fluid solver that can effectively utilize current and upcoming central processing and graphics processing unit (CPU+GPU) architectures. Our plasma fluid model solves the conservation equations for self-consistent electrostatic Poisson, electron and heavy species transport, and electron temperature on adaptive Cartesian grids. Our solver is written using performance portable adaptive mesh management library, AMReX (Zhang et al., JOSS, 4 (37) 1370, 2019), and can be built and run on widely available vendor specific GPU architectures (NVIDIA/AMD/Intel). We utilize a non-subcycled second order semi-implicit time-stepping method where all adaptive mesh refinement (AMR) levels are advanced with the same time step. The composite multi-level multigrid solver from within AMReX is used for each of the governing equations that are cast into a Helmholtz equation form. We have also developed a python based chemical mechanism parser framework that uses a similar format as CANTERA (Goodwin et al., Zenodo, 2018) yaml files as input. Our custom parser reads the yaml file and provides C++ files with transport and production rate functions that can be executed on both host (CPU) and device (GPU). We present verification of our solver using method of manufactured solutions that indicate formal second order accuracy with central diffusion and fifth order weighted-essentially-non-oscillatory (WENO) advection scheme. We also verify our solver with published literature on low-pressure capacitive and high-pressure streamer discharges. Our initial performance studies indicate 10X speed-up using 20 NVIDIA GPUs versus 200 CPUs for an atmospheric streamer discharge problem solved on a 512 x 1024 x 512 grid.

graphics processing units↗
DOE OSTI2026

Collaborative Research: Enabling multi-scale studies of magnetic reconnection with interpretable data-driven models

The development of accurate reduced descriptions and improved closures for magnetic reconnection is an important and a long‐standing challenge in plasma physics. The four‐fluid approach, and associated closures, that were investigated have the potential to improve the accuracy of plasma fluid models, capturing physical effects which would otherwise require a kinetic description. If successful, this approach could have an important impact for the modeling of laboratory and space plasmas. The major goals of this project were to develop new machine learning (ML) tools based on sparse and symbolic regression techniques, and to extract interpretable and generalizable reduced models (e.g., in the form of partial differential equations - PDEs) from data generated by first principles plasma simulations. Preserving interpretability of such data‐driven models is key to addressing the long‐standing theoretical and numerical challenges. Prior proof‐of‐principle studies have demonstrated the enormous potential of this approach, by recovering the well‐established hierarchy of plasma equations (from Vlasov to MHD) from data produced by particle‐in‐cell (PIC) simulations. Our goal in this project was to extend and apply these new tools to construct better kinetic closures for magnetic reconnection; to derive better models of particle injection and acceleration by this fundamental plasma process; and to use this understanding to accelerate the development of multi‐scale plasma algorithms. While our immediate focus was on the problem of magnetic reconnection, the tools that were will developed are general and applicable to other areas of plasma physics, and more broadly to many‐body phenomena. We anticipate that the development of these multi‐scale models will have a significant impact across different areas of plasma science, from fusion to space and astrophysical plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Scalable Multiphysics Block Preconditioning for Low Mach Number Compressible Resistive MHD with Application to Magnetic Confinement Fusion

This study investigates multiphysics block preconditioners that are critical in devising scalable Newton–Krylov iterative solvers for longer time-scale fully implicit fluid plasma models. The specific model of interest is the visco-resistive, low Mach number, compressible magnetohydrodynamics (MHD) model. This model describes the dynamics of conducting fluids in the presence of electromagnetic fields and can be used to study aspects of astrophysical phenomena, important science and technology applications, and basic plasma physics. The specific application of interest that motivates this study is the macroscopic simulation of longer time-scale stability and disruptions of magnetic confinement fusion devices, specifically the ITER Tokamak. The computational solution of the governing balance equations for mass, momentum, heat transfer, and magnetic induction for resistive MHD systems can be extremely challenging. These difficulties arise from both the strong nonlinear, nonsymmetric coupling of fluid and electromagnetic phenomena as well as the significant range of time and length scales that the interactions of these physical mechanisms produce. To handle the range of time and spatial scales of interest, a fully implicit unstructured variational multiscale finite element formulation is employed. For the scalable solution of the Newton linearized systems, fully coupled block preconditioners are designed to leverage algebraic multigrid subsolves. In conclusion, results are presented for the strong and weak scaling of the method as well as the robustness of these techniques for a large range of Lundquist numbers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Jacobian-free Newton–Krylov method for the simulation of non-thermal plasma discharges with high-order time integration and physics-based preconditioning

A preconditioning framework for the numerical simulation of non-thermal streamer discharges is developed using the Jacobian-free Newton-Krylov (JFNK) method. A reduced plasma fluid model is considered, consisting of electrons, one positive ion, one negative ion, and the electrostatic potential. Here, the plasma kinetics model includes ionization, electron-ion recombination, electron attachment, electron detachment, and ion-ion recombination. The governing equations are made dimensionless, discretized in space with finite differences, and integrated in time with a fully implicit method based on high-order backward differentiation formulas. The preconditioning framework is based on a linearized form of the governing equations and physics-based operator splitting. The efficiency of the preconditioning strategy is assessed through two test cases: streamer propagation between parallel plates and an axisymmetric pin-to-pin discharge. The fully implicit approach overcomes traditional restrictions in the time step size due to processes such as electron drift, electron diffusion, and dielectric relaxation. Excellent performance is observed through relevant statistics of the JFNK solver, although the number of linear iterations increases for the pin-to-pin discharge when nonlinear numerical boundary conditions are imposed at the electrodes. Performance studies show scalability with O(100-1000) processors for O(10M) unknowns with ample room for optimization.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Drift reduced Landau fluid model for magnetized plasma turbulence simulations in BOUT++ framework

Recently the drift-reduced Landau fluid six-field turbulence model within the BOUT++ framework has been upgraded. In particular, this new model employs a new normalization, adds a volumetric flux-driven source option, the Landau fluid closure for parallel heat flux and a Laplacian inversion solver which is able to capture $n$ = 0 axisymmetric mode evolution in realistic tokamak configurations. As we report here, these improvements substantially extended model's capability to study a wider range of tokamak edge phenomena, and are essential to build a fully self-consistent edge turbulence model capable of both transient (e.g., ELM, disruption) and transport time-scale simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Asymptotic preserving methods for fluid electron-fluid models in the large magnetic field limit with mathematically guaranteed properties (Final Report)

The current manuscript is a final report on the activities carried out under the Project LDRD-CIS #226834. In scientific terms, the work reported in this manuscript is a continuation of the efforts started with Project LDRD-express #223796 with final report of activities SAND2021-11481, see [83]. In this section we briefly explain what pre-existing developments motivated the current body of work and provide an overview of the activities developed with the funds provided. The overarching goal of the current project LDRD-CIS #226834 and the previous project LDRD-express #223796 is the development of numerical methods with mathematically guaranteed properties in order to solve the Euler-Maxwell system of plasma physics and generalizations thereof. Even though Project #223796 laid out general foundations of space and time discretization of Euler-Maxwell system, overall, it was focused on the development of numerical schemes for purely electrostatic fluid-plasma models. In particular, the project developed a family of schemes with mathematically guaranteed robustness in order to solve the Euler-Poisson model. This model is an asymptotic limit where only electrostatic response of the plasma is considered. Its primary feature is the presence of a non-local force, the electrostatic force, which introduces effects with infinite speed propagation into the problem. Even though instantaneous propagation of perturbations may be considered nonphysical, there are plenty of physical regimes of technical interest where such an approximation is perfectly valid.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Magnetized laser–plasma interactions in high-energy-density systems: Parallel propagation

In this study, we investigate parametric processes in magnetized plasmas, driven by a large-amplitude pump light wave. Our focus is on laser–plasma interactions relevant to high-energy-density (HED) systems, such as the National Ignition Facility and the Sandia MagLIF concept. We present a self-contained derivation of a “parametric” dispersion relation for magnetized three-wave interactions, meaning the pump wave is included in the equilibrium, similar to the unmagnetized work of Drake et al., Phys. Fluids 17, 778 (1974). For this, we use a multi-species plasma fluid model and Maxwell's equations. The application of an external B field causes right- and left-polarized light waves to propagate with differing phase velocities. This leads to Faraday rotation of the polarization, which can be significant in HED conditions. Phase-matching and linear wave dispersion relations show that Raman and Brillouin scattering have modified spectra due to the background B field, though this effect is usually small in systems of current practical interest. We study a scattering process we call stimulated whistler scattering, where a light wave decays to an electromagnetic whistler wave (ω≲ω ce ) and a Langmuir wave. This only occurs in the presence of an external B field, which is required for the whistler wave to exist.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Understanding the depletion of electrons in dusty plasmas at atmospheric pressure

The nucleation and growth of NPs in the gas phase using atmospheric-pressure plasma systems is an important approach to synthesizing novel dimensionally-controlled materials. In this paper, we investigated the effect of the NPs on a typical type of continuous-flow, substrate-free plasma at atmospheric pressure to understand their potential contribution to electron density changes. A tandem plasma system was set up consisting of one plasma reactor that produced carbonaceous NPs from mixtures of argon and hexane, and another identical plasma reactor where the as-grown particles were injected and non-intrusive electrical and optical measurements were performed. The electron densities obtained from conductivity measurements and a plasma fluid model were found to decrease in the presence of NPs. However, control experiments revealed that the main source of the electron depletion was residual vapor or reaction byproducts in the form of molecular species or nanoclusters and not the particles themselves. These results were validated by constant number Monte Carlo simulations which showed that at the experimentally-measured conditions, the NPs were not of sufficiently high enough concentration to reduce the electron density; however, if molecules or clusters are ionizable, they remain in sufficient concentration to deplete electron densities. Our study shows that at atmospheric pressure, because of their typically larger electron density values, particle-producing plasmas are distinct from those at low pressure, and nanoparticle formation does not have the same impact while molecular-scale species may be a more important consideration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Vidyut3d: A Gpu Accelerated Fluid Solver for Non-Equilibrium Plasmas on Adaptive Grids

We present the numerical methods, programming methodology, verification, and performance assessment of a non-equilibrium plasma fluid solver that can effectively utilize current and upcoming central processing and graphics processing unit (CPU+GPU) architectures, in this work. Our plasma fluid model solves the coupled conservation equations for species transport, electrostatic Poisson and electron temperature on adaptive Cartesian grids. Our solver is written using performance portable adaptive-grid/particle management library, AMReX, and is portable over widely available vendor specific GPU architectures. We present verification of our solver using method of manufactured solutions that indicate formal second order accuracy with central diffusion and fifth-order weighted-essentially-non-oscillatory (WENO) advection scheme. We also verify our solver with published literature on capacitive discharges and atmospheric pressure streamer propagation. We demonstrate the use of our solver on two 3D simulation cases: an atmospheric streamer propagation in Ar-H2 mixtures and a low pressure twin electrode radio frequency reactor. Our performance studies on three different CPU+GPU architectures indicate approximately 150-400X speed-up using AMD and NVIDIA GPUs per time step compared to a single CPU core for a 4 million cell simulation with 15 species.

Sitaraman, Hariswaran↗
DOE OSTI2021

Natural hot-ion modes in a rotating plasma

We report that in steady state, the fuel cycle of a fusion plasma requires inward particle fluxes of fuel ions. These particle flows are also accompanied by heating. In the case of classical transport in a rotating cylindrical plasma, this heating can proceed through several distinct channels depending on the physical mechanisms involved. Some channels directly heat the fuel ions themselves, whereas others heat electrons. Which channel dominates depends, in general, on the details of the temperature, density and rotation profiles of the plasma constituents. However, remarkably, under relatively few assumptions concerning these profiles, if the α particles, the by-products of the fusion reaction, can be removed directly by other means, then a hot-ion mode tends to emerge naturally.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Verification of a Fluid-Based Plasma-Edge Model Within the Multiphysics Object-Oriented Simulation Environment (MOOSE) Framework

As the goal of achieving fusion power on the grid comes closer to fruition, fully coupled multiphysics models of fusion devices will be crucial. These models must incorporate the interconnected phenomena of these devices, including plasma physics, neutronics, first wall interactions, and tritium transport. Currently, there are two main approaches to developing these platforms: (1) loosely coupled, where one couples existing codes and solvers together through input and output parameters and data, and (2) tightly coupled, where one develops the necessary models within a singular, integrated framework. This work focuses on the latter approach for magnetically confined fusion devices by developing a fluid-based plasma-edge model within the Multiphysics Object Oriented Simulation Environment (MOOSE) Framework. This effort is coordinated with other efforts to develop, test, demonstrate, and deploy fusion relevant multiphysics capabilities including electromagnetics, particle-in-cell plasma, tritium transport, and fusion blanket design. This new model is an expansion of the MOOSE-based plasma application, Zapdos, which was originally formulated to model low-temperature, non-magnetized plasma processes. Verification studies have been conducted using newly developed magnetic plasma capabilities. These involved convergence analyses utilizing the method of manufactured solutions to verify new operators and case studies. A modular approach was taken here to demonstrate increasingly complicated simulation scenarios, which included a singular fluid with uniform magnetic field case, a singular fluid with spatially varying magnetic field case, and a coupled multifluid case.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Electromagnetic Waves in Cold Plasmas

A collisionless fluid model of a plasma is presented and solved to first order in the cold, high frequency limit. From this model, a homogeneous system of linear equations is obtained for a harmonic electric field perturbation from which the Appleton-Hartree equation is derived. Moreover, the polarization states of electromagnetic waves in cold, collisionless plasmas are examined. Complete sets of equations governing the reflection and transmission of electromagnetic waves in both non magnetized and magnetized plasmas are obtained. In solving the boundary problem, the Booker quartic is derived and the nature of its roots discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Divertor detachment characterization in negative triangularity discharges in DIII-D via 2D edge-plasma transport modeling

Edge fluid modeling of the first divertor-plasma detachment experiments in negative triangularity (NT) discharges in the DIII-D tokamak is presented using the 2D multifluid edge transport code UEDGE, including cross-field particle drifts. Experiments were performed where the lower single-null magnetic equilibrium had a strong NT (δ≈−0.5), that is, where the magnetic X-point is at a larger major radius than the core magnetic axis. Divertor-plasma detachment was induced by increasing the core plasma density in DIII-D via intrinsic gas puffing. Here density scans are performed with UEDGE to reach a detached plasma and to quantitatively recover the experimental rollover of the ion saturation current on the outer divertor target plate. The simulations cover experiments with both signs of the toroidal magnetic field, B T , where the ion magnetic Grad-B drifts are directed into (forward B T ) and out of (reverse B T ) the divertor region. Consistent with experiments with neutral beam power injection, the NT simulations reproduce: 40% higher density is needed to reach detachment onset with forward B T compared with reverse B T , and the absence of deep detachment is found with reverse B T . Similarly, comparison between Ohmic discharges in NT and positive triangularity (PT) shaping confirms that a substantially higher density is needed to achieve detachment in NT than in PT, with NT requiring an line-average density of at least the Greenwald density or higher. Simulation results suggest that higher densities are needed to reach detachment in negative compared to PT because these discharges have a shorter midplane-to-target distance along the total magnetic field B, a shorter outer divertor poloidal leg length (0.06 m vs 0.2 m), and reduced radial transport [near-scrape-off layer (SOL) D ⊥ /χ ⊥ =0.3/0.5 vs D ⊥ /χ ⊥ =1.0/1.0, all in (m 2 /s)].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Statistical inference of anomalous thermal transport with uncertainty quantification for interpretive 2D SOL models

The critical task of inferring anomalous cross-field transport coefficients is addressed in simulations of boundary plasmas with fluid models. A workflow for parameter inference in the UEDGE fluid code is developed using Bayesian optimization with parallelized sampling and integrated uncertainty quantification. In this workflow, transport coefficients are inferred by maximizing their posterior probability distribution, which is generally multidimensional and non-Gaussian. Uncertainty quantification is integrated throughout the optimization within the Bayesian framework that combines diagnostic uncertainties and model limitations. As a concrete example, we infer the anomalous electron thermal diffusivity $\chi_\perp$ from an interpretive 2D model describing electron heat transport in the conduction-limited region with radiative power loss. The workflow is first benchmarked against synthetic data and then tested on H-, L-, and I-mode discharges to match their midplane temperature and divertor heat flux profiles. We demonstrate that the workflow efficiently infers diffusivity and its associated uncertainty, generating 2D profiles that match 1D measurements. Future efforts will focus on incorporating more complicated fluid models and analyzing transport coefficients inferred from a large database of experimental results.

Bayesian optimization↗
DOE OSTI2021

Ion temperature anisotropy in the tokamak scrape-off layer

Understanding tokamak exhaust-power heat loads on divertor plates depends critically on having a realistic model of the scrape-off layer (SOL) plasma. The Braginskii fluid model is often solved to understand the SOL plasma behavior. This model is based on the collisional limit for transport along the magnetic field B → . The ions and electron gyrofrequencies are assumed to be much larger than the Coulomb collision frequencies, which are nonetheless, sufficiently large to yield common parallel and perpendicular temperatures for each species, i.e. the temperatures are assumed to be isotropic. Additionally, in certain circumstances such as encountered for the tokamak H-mode, the ion temperature can be quite anisotropic. In this work, the anisotropy effects are implemented in the two-dimensional (2D) transport code UEDGE. Various geometries (1D slab, 2D slab and a toroidal tokamak geometry) are used to study the 2D structure of ion temperature anisotropy and its effects on plasma transport in detail. Results show that the effects of ion temperature anisotropy on the plasma parallel transport are substantial near the magnetic X-point, which leads to different steady state density profiles in the divertor regions. The extra mirror force introduced by ion temperature anisotropy can be one of the main forces contributing to the plasma flow in the SOL.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗