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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 55 records · Page 3

Accelerating kinetic plasma simulations with machine-learning-generated initial conditions

Computational models of plasma technologies often solve for the system operating conditions by time-stepping an initial value problem to a quasi-steady solution. However, the strongly nonlinear and multi-timescale nature of plasma dynamics often necessitate millions, or even hundreds of millions, of steps to reach convergence, reducing the effectiveness of these simulations for computer-aided engineering. We consider acceleration of kinetic plasma simulations via data-driven machine-learning-generated initial conditions, which initialize the simulations close to their final quasi-steady-state, thereby reducing the number of steps to reach convergence. Three machine-learning models are developed to predict the density and ion kinetic profiles of capacitively coupled plasma discharges relevant to the microelectronics industry. The models are trained on kinetic simulations over a range of device operating frequencies and pressures. Best performance was observed when simulations were initialized with ion kinetic profiles generated by a convolutional neural network, reducing the mean number of steps to reach convergence by 17.1× when compared to initialization with a zero-dimensional global model. We also outline a workflow for continuous data-driven model improvement and simulation speedup, with the aim of generating sufficient data for full device digital twins.

Artificial neural networks↗

Plasma viscosity with mass transport in spherical inertial confinement fusion implosion simulations

The effects of viscosity and small-scale atomic-level mixing on plasmas in inertial confinement fusion(ICF) currently represent challenges in ICF research. Many current ICF hydrodynamic codes ignore the effects of viscosity though recent research indicates viscosity and mixing by classical transport processes may have a substantial impact on implosion dynamics. In this paper, we have implemented a Lagrangian hydrodynamic code in one-dimensional spherical geometry with plasmaviscosity and mass transport and including a three temperature model for ions, electrons, and radiation treated in a gray radiation diffusion approximation. The code is used to study ICF implosion differences with and without plasmaviscosity and to determine the impacts of viscosity on temperature histories and neutron yield. It was found that plasmaviscosity has substantial impacts on ICF shock dynamics characterized by shock burn timing, maximum burn temperatures, convergence ratio, and time history of neutron production rates. Finally, plasmaviscosity reduces the need for artificial viscosity to maintain numerical stability in the Lagrangian formulation and also modifies the flux-limiting needed for electron thermal conduction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A multispecies, multifluid model for laser–induced counterstreaming plasma simulations

The interpenetration of counterstreaming plasmas is a critical phenomenon in several application areas, such as astrophysical flows, design of controlled fusion devices, and laser–induced plasma experiments. Multispecies “single-fluid” codes are unable to model this phenomenon due to the single velocity representation for all the species/fluids. Kinetic codes, though capable of modeling interpenetration, are computationally prohibitive for at-scale simulations. Here, we introduce a multifluid model that solves the fluid equations for each ion fluid or stream. This allows distinct flows that interact with each other through electrostatic and collisional forces. We observe and describe our code, EUCLID, that uses a conservative finite-difference formulation to discretize the governing equations in space. The 5th-order Monotonicity-Preserving WENO scheme is used for the upwind approximation of the hyperbolic flux, and the explicit 4th-order Runge–Kutta scheme is used for time integration. The code is verified for several benchmark cases and manufactured solutions. We simulate one- and two-dimensional interactions of counterstreaming plasmas in vacuum as well as in the presence of gas fill, where the setups are representative of laser-induced plasma experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Plasma electron hole kinematics. II. Hole tracking Particle-In-Cell simulation

The kinematics of a 1-D electron hole is studied using a novel Particle-In-Cell simulation code. A hole tracking technique enables us to follow the trajectory of a fast-moving solitary hole and study quantitatively hole acceleration and coupling to ions. We observe a transient at the initial stage of hole formation when the hole accelerates to several times the cold-ion sound speed. Artificially imposing slow ion speed changes on a fully formed hole causes its velocity to change even when the ion stream speed in the hole frame greatly exceeds the ion thermal speed, so there are no reflected ions. The behavior that we observe in numerical simulations agrees very well with our analytic theory of hole momentum conservation and the effects of “jetting.”.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Variational formulation of macro-particle plasma simulation algorithms

A variation formulation of macro-particle kinetic plasma models is discussed. In the electrostatic case, the use of symplectic integrators is investigated and found to offer advantages over typical generic methods. For the electromagnetic case, gauge invariance and momentum conservation are considered in detail. It is shown that, while the symmetries responsible for these conservation laws are broken in the presence of a spatial grid, the conservation laws hold in an average sense. The requirements for exact invariance are explored and it is shown that one viable option is to represent the potentials with a truncated Fourier basis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Artificial Scientist: in-Transit Machine Learning of Plasma Simulations

Large-scale simulations or scientific experiments produce petabytes of data per run. This poses massive challenges for I/O and storage when scientific analysis workflows are run manually offline. Unsupervised deep learning-based techniques to extract patterns and non-linear relations from these large amounts of data provide a way to build scientific understanding from raw data, reducing the need for manual pre-selection of analysis steps, but require exascale compute and memory to process the full dataset available. In this paper, we demonstrate a heterogeneous streaming workflow in which plasma simulation data is streamed directly to a Machine Learning (ML) application training a model on the simulation data in-transit, completely circumventing the capacity-constrained filesystem bottleneck. This workflow employs openPMD to provide a high level interface to describe scientific data and also uses ADIOS2, to transfer volumes of data that exceed the capabilities of the filesystem. We employ experience replay to avoid catastrophic forgetting in learning from this non-steady state process in a continual manner and adapt it to improve model convergence while learning in-transit. As a proof-of-concept, we approach the ill-posed inverse problem of predicting particle dynamics from radiation in a particle-incell (PIConGPU) simulation of the Kelvin-Helmholtz instability (KHI). We detail hardware-software co-design challenges as we scale PIConGPU to full Frontier, the Top-1 system as of June 2024 Top500 list.

Kelling, Jeffrey [Helmholtz-Zentrum Dresden Rossen↗

Simulating plasma production from hypervelocity impacts

Hypervelocity particles, such as meteoroids and space debris, routinely impact spacecraft and are energetic enough to vaporize and ionize themselves and as well as a portion of the target material. The resulting plasma rapidly expands into the surrounding vacuum. While plasma measurements from hypervelocity impacts have been made using ground-based technologies such as light gas guns and Van de Graaff dust accelerators, some of the basic plasma properties vary significantly between experiments. There have been both ground-based and in-situ measurements of radio frequency (RF) emission from hypervelocity impacts, but the physical mechanism responsible and the possible connection to the impact-produced plasma are not well understood. Under certain conditions, the impact-produced plasma can have deleterious effects on spacecraft electronics by providing a new current path, triggering an electrostatic discharge, causing electromagnetic interference, or generating an electromagnetic pulse. Multi-physics simulations of plasma production from hypervelocity impacts are presented. These simulations incorporate elasticity and plasticity of the solid target, phase change and plasma formation, and non-ideal plasma physics due to the high density and low temperature of the plasma. A smoothed particle hydrodynamics method is used to perform a continuum dynamics simulation with these additional physics. By examining a series of hypervelocity impacts, basic properties of the impact produced plasma plume (density, temperature, expansion speed, charge state) are determined for impactor speeds between 10 and 72 km/s. For a large range of higher impact speeds (30–72 km/s), we find the temperature is unvarying at 2.5 eV. We also find that the plasma plume is weakly ionized for impact speeds less than 14 km/s and fully ionized for impact speeds greater than 20 km/s, independent of impactor mass. This is the same velocity threshold for the detection of RF emission in recent Van de Graaff experiments, suggesting that the RF is correlated to the formation of fully ionized plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simulating plasma wave propagation on a superconducting quantum chip

Quantum computers may one day enable the efficient simulation of strongly coupled plasmas that lie beyond the reach of classical computation in regimes where quantum effects are important and the scale separation is large. Here, in this article, we take a first step toward efficient simulation of quantum plasmas by demonstrating linear plasma wave propagation on a superconducting quantum chip. Using high-fidelity and highly expressive device-native gates, combined with an error-mitigation technique, we simulate the scattering of laser pulses from inhomogeneous plasmas. Our approach is made feasible by the identification of a suitable local spin model whose excitations mimic plasma waves, and whose circuit implementation requires a lower gate count than other proposed approaches that would require a future fault-tolerant quantum computer. This work opens avenues to study more complicated phenomena that cannot be simulated efficiently on classical computers, such as nonlinear quantum dynamics when strongly coupled plasmas are driven out of equilibrium.

general physics↗

LANGMUIR WAVE DECAY IN INHOMOGENEOUS SOLAR WIND PLASMAS: SIMULATION RESULTS

Langmuir turbulence excited by electron flows in solar wind plasmas is studied on the basis of numerical simulations. In particular, nonlinear wave decay processes involving ion-sound (IS) waves are considered in order to understand their dependence on external long-wavelength plasma density fluctuations. In the presence of inhomogeneities, it is shown that the decay processes are localized in space and, due to the differences between the group velocities of Langmuir and IS waves, their duration is limited so that a full nonlinear saturation cannot be achieved. The reflection and the scattering of Langmuir wave packets on the ambient and randomly varying density fluctuations lead to crucial effects impacting the development of the IS wave spectrum. Notably, beatings between forward propagating Langmuir waves and reflected ones result in the parametric generation of waves of noticeable amplitudes and in the amplification of IS waves. These processes, repeated at different space locations, form a series of cascades of wave energy transfer, similar to those studied in the frame of weak turbulence theory. The dynamics of such a cascading mechanism and its influence on the acceleration of the most energetic part of the electron beam are studied. Finally, the role of the decay processes in the shaping of the profiles of the Langmuir wave packets is discussed, and the waveforms calculated are compared with those observed recently on board the spacecraft Solar TErrestrial RElations Observatory and WIND.

79 ASTRONOMY AND ASTROPHYSICS↗

Mechanisms for the convergence of time-parallelized, parareal turbulent plasma simulations

Parareal is a recent algorithm able to parallelize the time dimension in spite of its sequential nature. It has been applied to several linear and nonlinear problems and, very recently, to a simulation of fully-developed, two-dimensional drift wave turbulence. The mere fact that parareal works in such a turbulent regime is in itself somewhat unexpected, due to the characteristic sensitivity of turbulence to any change in initial conditions. This fundamental property of any turbulent system should render the iterative correction procedure characteristic of the parareal method inoperative, but this seems not to be the case. In addition, the choices that must be made to implement parareal (division of the temporal domain, election of the coarse solver and so on) are currently made using trial-and-error approaches. Here, we identify the mechanisms responsible for the convergence of parareal of these simulations of drift wave turbulence. We also investigate which conditions these mechanisms impose on any successful parareal implementation. The results reported here should be useful to guide future implementations of parareal within the much wider context of fully-developed fluid and plasma turbulent simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Towards Multifluid Multiphysics Continuum Plasma Simulation for Modeling Magnetically-driven Experiments on Z

Magnetically driven experiments supporting pulsed-power utilize a wide range of configurations, including wire-arrays, gas-puffs, flyer plates, and cylindrical liners. This experimental flexibility is critical to supporting radiation effects, dynamic materials, magneto-inertial-fusion (MIF), and basic high energy density laboratory physics (HEDP) efforts. Ultimately, the rate at which these efforts progress is limited by our understanding of the complex plasma physics of these systems. Our effort has been to begin to develop an advanced algorithmic structure and a R&D code implementation for a plasma physics simulation capability based on the five-moment multi-fluid / full-Maxwell plasma model. This model can be used for inclusion of multiple fluid species (e.g., electrons, multiple charge state ions, and neutrals) and allows for generalized collisional interactions between species, models for ionization/recombination, magnetized Braginskii collisional transport, dissipative effects, and can be readily extended to incorporate radiation transport physics. In the context of pulsed-power simulations this advanced model will help to allow SNL to computationally simulate the dense continuum regions of the physical load (e.g. liner implosions, flyer plates) as well as partial power-flow losses in the final gap region of the inner MITL. In this report we briefly summarize results of applying a preliminary version of this model in the context of verification type problems, and some initial magnetic implosion relevant prototype problems. The MIF relevant prototype problems include results from fully-implicit / implicit-explicit (IMEX) resistive MHD as well as full multifluid EM plasma formulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Compression of tokamak boundary plasma simulation data using a maximum volume algorithm for matrix skeleton decomposition

This report demonstrates satisfactory data compression of SOLPS-ITER simulation output ranging from 2D fields, 1D profiles, and 0D scalar variables with a novel matrix decomposition approach. The singular value decomposition (SVD) scales poorly for large matrix sizes and is unsuited to the application on high dimensional data common to fusion plasma physics simulation. In this work, we employ the columns-submatrix-rows (CUR) matrix factorization technique in order to compute a low-rank approximation up to two orders of magnitude faster than the SVD, but within a nominal L2-norm relative error of ε = 10 –2 . In addition, the CUR approach maintains the original format of the data, in its extracted columns and rows, allowing for interpretable data storage at the original resolution of the simulation. We utilize an iterative algorithm to compute the CUR decomposition of simulation output by maximizing the volume, or linearly independent information content, of a low-rank submatrix contained within the data. Experiments over $\textit{n} × \textit{n}$ randomized test matrices with embedded rank-deficient features show that this maximum volume implementation of CUR matrix approximation has reduced asymptotic computational complexity on the order of n compared to the SVD, which scales approximately as $n^3$. These results show that the CUR technique can be used to effectively select time step snapshots (columns) of over 140 SOLPS-ITER output variables and the associated discretized coordinate timeseries (rows) allowing for reconstruction of the complete simulation dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Implementation of a 9-point stencil in SOLPS-ITER and implications for Alcator C-Mod divertor plasma simulations

The SOLPS-ITER code suite is used worldwide for plasma edge modeling, the interpretation of experiments, as well as for the design of the ITER divertor. The numerical scheme of the plasma solver of the code, B2.5, is based on the assumption of perfectly field-aligned grids, while in practice grids are often strongly distorted to match divertor target shapes. Neglecting these grid distortion leads to qualitatively and quantitatively incorrect results for fluid neutral simulations, and may affect results in cold (detached) divertors even when using kinetic neutral simulations. In this contribution, we present the first results of a newly implemented 9-point stencil in B2.5 to properly handle misaligned grids. The new scheme is then applied to fluid neutral simulations of a well-diagnosed and previously modeled Alcator C-Mod discharge. Results are compared with the original 5-point scheme neglecting grid distortion effects, as well as with simulations including a full kinetic neutral model. We conclude that the 9-point stencil is essential to correctly model the transport of fluid neutrals on distorted grids, and to capture the effects of divertor closure on the fluid neutral behavior.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Response to FESAC survey, non-fusion connections to Fusion Energy Sciences. Applications of the FES-supported beam and plasma simulation code, Warp

The Fusion Energy Sciences Advisory Committee’s subcommittee on non-fusion applications (FESAC NFA) is conducting a survey to obtain information from the fusion community about non-fusion work that has resulted from their DOE-funded fusion research. The subcommittee has requested that members of the community describe recent developments connected to the activities of the DOE Office of Fusion Energy Sciences. Two questions in particular were posed by the subcommittee. This document contains the authors’ responses to those questions.

43 PARTICLE ACCELERATORS↗

Influence of the inverse sheath on divertor plasma performance in tokamak edge plasma simulations

Recently, it was shown that strong electron thermionic emission from material walls could result in the formation of an “inverse sheath”, which prevents the flow of cold ions to the wall. Such regimes look very favorably from the point of view of plasma-material interactions at the edge of magnetic fusion devices, where the problem of the erosion of plasma facing components under ion irradiation is one of the key issues for developing of future magnetic fusion reactors. However, it is not clear whether such regimes are compatible with edge plasma parameters and heat removal requirements in fusion reactors.To address the issue of practicality of the “inverse sheath” regime for edge tokamak plasma conditions, we perform a set of numerical simulations with 2D edge plasma transport code UEDGE for a DIII-D-like geometry and magnetic configuration.To describe both “standard” and “inverse sheath” conditions within the framework of the UEDGE code (which does not consider the sheath region per se), at the material surfaces, we apply effective boundary conditions which emulate both “standard” and“inverse sheath” regimes. We demonstrate that for the same input parameters, spatial distributions of edge plasma parameters corresponding to detached divertor and“inverse sheath” regimes are similar, with only a few minor differences. We discuss the compatibility of “inverse sheath” regimes with core plasma parameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Stochastic Richardson Extrapolation Based Numerical Error Estimation for Kinetic Plasma Simulations

We present a numerical error estimation technique specifically formulated to deal with stochastic code output with multiple discretization parameters. This method is based on multiple fits to an error model with arbitrary convergence rates and cross-coupling terms, performed using nonlinear optimization. The fitting approach varies by the type of residual norm which influences the importance of outliers, and weights which influences the relative importance of data points in the coarse and refined regions of discretization parameter space. To account for the influence of stochastic noise, these fits are performed on multiple bootstrap values based on the underlying response data set. Using an automated discretization domain selection scheme, the fits are performed on a series of reduced sets of discretization levels in order to find an optimal fully-converged result estimate in the minimum variance sense; this automated approach enables straightforward analysis of multiple quantities of interest and/or time and spatially-dependent response data. The overall numerical error analysis method is useful for verification and validation problems for stochastic simulation methods and forms a key component in the overall uncertainty quantification process. The method was demonstrated for steady and unsteady electron diode problems simulated using a particle-in-cell kinetic plasma code, demonstrating excellent results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Verification methods for drift–diffusion reaction models for plasma simulations

Abstract Compared to other computational physics areas such as codes for general computational fluid dynamics, the documentation of verification methods for plasma fluid codes remains under developed. Current analytical solutions for plasma are often highly limited in terms of testing highly coupled physics, due to the harsh assumptions needed to derive even simple plasma equations. This work highlights these limitations, suggesting the method of manufactured solutions (MMSs) as a potential option for future verification efforts. To demonstrate the flexibility of MMS in verifying these highly coupled systems, the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework was utilized. Thanks to the MOOSE framework’s robustness and modularity, as well as to its physics module capabilities and ecosystem applications (i.e. Zapdos and the chemical reaction network) developed for plasma physics modeling and simulation, this report lays the groundwork for a structured method of conducting plasma fluid code verification.

DeChant, Corey (ORCID:0000000293779732)↗

Neural operator transformers capture bifurcating drift-wave turbulence in fusion plasma simulations

Self-consistent modeling of turbulence-driven transport is critical for optimizing confinement in magnetically confined fusion plasmas, such as tokamaks and stellarators. In particular, capturing the long-term co-evolution of turbulence, flow, and background plasma profiles remains computationally challenging. Direct numerical simulation of these multiscale, highly nonlinear processes is often demanding and impractical for real-time control or design optimization. To address this bottleneck, we investigate transformer-based neural operator partial differential equation surrogates for emulating the dynamics of drift-wave turbulence bifurcation mediated by zonal flows, using the modified Hasegawa–Wakatani (MHW) model as a prototypical system. We find that the finetuned neural operator model has excellent performance in capturing the multi-spatiotemporal-scales of MHW turbulence bifurcation and is robust to testing on rare and out-of-distribution dynamics. Specifically, we demonstrate that a single unified model accurately predicts both quasi-steady-state turbulence and a wide range of dynamical transition processes, such as nonlinear saturation, spontaneous suppression of turbulence, and the emergence of macroscopic zonal flows, over time horizons vastly exceeding the local turbulence correlation time. This computationally efficient approach establishes a strong foundation for fast, AI-based modeling of complex, multiscale phenomena in magnetized fusion plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗