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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
NASA NTRS1987

Kinetic aspects of tail dynamics - Theory and simulation

Kinetic theories relevant to the geomagnetic tail are reviewed. The topics discussed include kinetic instabilities, simulations, and current-sheet particle acceleration. Tearing mode and reconnection theories are emphasized. Kinetic treatment is appropriate for these topics since the tail plasma is collisionless. Fluid calculations are appropriate when stochastic processes dominate and for studies where long wavelengths are important. However, fluid treatments of tearing modes and reconnection require a finite resistivity in the diffusion region. Thus, although 'anomalous resistivity' can be guessed or in some cases calculated, ideally the kinetic treatment is often to be preferred. Particle motion and acceleration in the current sheet can give rise to beam-like distributions in the plasma-sheet boundary layer. Studies of current-sheet particle motion have also been used as the basis for 'kinetic' tail equilibrium models. Furthermore, quite recently current-sheet particle motion is used directly in Coroniti's explosive tail reconnection model. The 'inertial conductivity' from the equilibrium models provides the 'dissipation' necessary for reconnection.

Speiser, T. W.↗
DOE OSTI2025

Accelerating high-order continuum kinetic plasma simulations using multiple GPUs

Kinetic plasma simulations solve the Vlasov-Poisson or Vlasov-Maxwell equations to evolve scalar-variable distribution functions in position-velocity phase space and vector-variable electromagnetic fields in configuration space. The immense computational cost of evolving high-dimensional variables, and their large number of degrees of freedom, often limits the utility of continuum kinetic simulations and presents a challenge when it comes to accurately simulating real-world physical phenomena. To address this challenge, we present techniques that accelerate and minimize the computational work required for a scalable Vlasov-Poisson solver. We show theoretical hardware compute and communication bounds for solving a fourth-order finite-volume Vlasov-Poisson system. These bounds are then used to inform and evaluate the design of performance portable algorithms for a multiple graphics processing unit (GPU) accelerated version of the Vlasov-Poisson solver VCK-CPU [1]. We demonstrate that the multi-GPU Vlasov solver implementation, VCK-GPU, simultaneously minimizes required inter-process data transfer while also being bounded by the machine network performance limits. This results in an overall strong scaling speedup per timestep of up to 40x in three-dimensional phase space (one position, two velocity coordinates) and 54x in four dimensional phase space (two position, two velocity coordinates) and a 341x increase in simulation throughput of the GPU accelerated code over the existing CPU code. The GPU code is also able to weak scale up to 256 compute nodes and 1024 GPUs. In conclusion, we demonstrate that the improved compute performance enables exploring configurations which were previously computationally infeasible, including resolving fine-scale distribution function filamentation and multi-species dynamics with realistic electron-proton mass ratios.

Continuum kinetics↗
DOE OSTI2024

Kinetic Plasma Simulation in the MOOSE Framework: Verification of Electrostatic Particle In Cell Capabilities

In magnetic confinement nuclear fusion reactors, the interaction between the plasma edge and plasma facing components is extremely important. At the plasma edge, a kinetic representation such as particle-in-cell (rather than a fluid representation) is required to accurately capture the plasma behavior. General purpose particle-in-cell plasma simulation capabilities have been developed in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. This new capability is a part of the development of a new MOOSE-based framework for modeling plasma facing components, the Fusion ENergy Integrated multiphys-X (FENIX) framework. In this work, the verification of foundational particle-in-cell capabilities in FENIX is presented. This new plasma simulation capability has three main components: moving particles in discrete steps on the finite element mesh, mapping charge density from the particle's location to the finite element mesh, and solving for the electrostatic potential based on the charge density mapped from particles to the mesh. In this paper, simple verification problems demonstrating each of these new capabilities are presented, and future work includes electromagnetic capabilities and Monte Carlo collisions with neutral gas particles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Drift kinetic electrostatic simulations of the edge localized mode heat pulse

In the present work, electrostatic drift kinetic simulations of parallel plasma transport within the tokamak scrape-off layer (SOL) are conducted using the COGENT code. The SOL configuration is represented in one-dimensional slab geometry, incorporating a heat source localized in the midplane. The heat source parameters correspond to those characterizing edge-localized modes observed in the Joint European Torus (JET) tokamak. The numerical model includes kinetic treatment of both ions and electrons, a simplified model for the gyrokinetic Poisson equation that allows one to step over short time scales associated with fast electrostatic shear Alfvèn waves, and the logical sheath boundary condition (LSBC) that enforces global system quasineutrality. A third-order accurate LSBC is derived to be consistent with the third-order accurate upwind advection scheme utilized in the code, and it was shown to noticeably impact the simulation results, especially parallel heat flux at the target plate. The findings of this study are in agreement with results from preceding fluid and kinetic simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

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↗
NASA NTRS1987

Macroscale particle simulation of kinetic Alfven waves

Two types of simulations of the kinetic Alfven wave are presented using a macroscale particle simulation code (Tanaka and Sato, 1986) which enables individual particle dynamics to be followed in the MHD scales. In this code, low frequency electromagnetic fields are solved by eliminating high frequency oscillations such as the light modes, and the scalar potential electric field is solved by eliminating Lagrangian oscillations. The dependences of the frequency and the Landau damping on the perpendicular wavenumber were studied, and good agreement was found between simulation and theoretical predictions. Some fundamental nonlinear interactions of the kinetic Alfven wave with the particles (parallel acceleration of the electrons) were also noted.

Tanaka, Motohiko↗
DOE OSTI2024

Adaptive tau-leaping methods for microscopic-lattice kinetic Monte Carlo simulations

Traditional Kinetic Monte Carlo (KMC) approaches, rooted in Gillespie’s stochastic simulation algorithm, become computationally demanding in systems with a large range of timescales. The goal of this work is to propose and study new adaptive lattice-KMC time integration strategies for spatially non-uniform systems. To that end, two novel adaptive tau-leaping methods and their corresponding time integration strategies are developed based on the idea of the “n-fold” direct KMC method. These strategies allow for the simultaneous execution of multiple reactions, advancing time by adaptively selected coarse increments. We present numerical experiments comparing the proposed methods with existing approaches in a catalytic surface kinetics application involving ammonia decomposition.

Bimolecular reactions↗
DOE OSTI2024

ReactionMechanismSimulator.jl: A modern approach to chemical kinetic mechanism simulation and analysis

Abstract We present ReactionMechanismSimulator.jl (RMS), a modern differentiable software for the simulation and analysis of chemical kinetic mechanisms, including multiphase systems. RMS has already been applied to problems in combustion, pyrolysis, polymers, pharmaceuticals, catalysis, and electrocatalysis. RMS is written in Julia, making it easy to develop and allowing it to take advantage of Julia's extensive numerical computing ecosystem. In addition to its extensive library of optimized analytic Jacobians, RMS can generate and use Jacobians computed using automatic differentiation and symbolically generated analytic Jacobians. RMS is demonstrated to be faster than Cantera and Chemkin in several benchmarks. RMS also implements an extensive set of features for analyzing chemical mechanisms, including a library of easy‐to‐call plotting functions, molecular structure resolved flux diagram generation, crash analysis, traditional sensitivity analysis, transitory sensitivity analysis, and an automatic mechanism analysis toolkit. RMS implements efficient adjoint and parallel forward sensitivity analyses. We also demonstrate the ease of adding new features to RMS.

Johnson, Matthew S.↗
DOE OSTI2025

Semi-implicit continuum kinetic modeling of weakly collisional parallel transport in a magnetic mirror

We present implicit-explicit (IMEX) kinetic simulations of weakly collisional parallel plasma transport in magnetic mirror configurations using the continuum code COGENT. The numerical scheme employs a Jacobian-free Newton–Krylov method with algebraic multigrid preconditioning to overcome the severe time step limitations imposed by strong mirror forces in fully explicit schemes. Applied to parameters relevant to the Wisconsin HTS Axisymmetric Mirror experiment, the IMEX approach enables time steps up to 2.5×10 4 times larger than those permitted by explicit methods, resulting in a 2500× speedup in 1D–2V simulations of parallel transport with kinetic ions and Boltzmann electrons. Additionally, a reduced bounce-averaged model for a square mirror is implemented to support the computationally intensive fully kinetic simulations. The bounce-averaged formulation is used to evaluate the numerical convergence of the velocity-space discretization algorithms and to assess the role of the collision model by comparing simulations employing the nonlinear Fokker–Planck and the simplified Lenard–Bernstein–Dougherty collision operators.

Collision theories↗
DOE OSTI2024

Accelerating particle-in-cell kinetic plasma simulations via reduced-order modeling of space-charge dynamics using dynamic mode decomposition

We present a data-driven reduced-order modeling of the space-charge dynamics for electromagnetic particle-in-cell (EMPIC) plasma simulations based on dynamic mode decomposition (DMD). The dynamics of the charged particles in kinetic plasma simulations such as EMPIC is manifested through the plasma current density defined along the edges of the spatial mesh. We showcase the efficacy of DMD in modeling the time evolution of current density through a low-dimensional feature space. Not only do such DMD based predictive reduced-order models help accelerate EMPIC simulations, they also have the potential to facilitate investigative analysis and control applications. Here, we demonstrate the proposed DMD-EMPIC scheme for reduced-order modeling of current density and speedup in EMPIC simulations involving electron beam under the influence of magnetic field, virtual cathode oscillations, and backward wave oscillator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Direct comparison of gyrokinetic and fluid scrape-off layer simulations

Typically, fluid simulations are used for tokamak divertor design. However, fluid models are only valid if the scrape-off layer (SOL) is highly collisional. This assumption is valid in many present-day experiments but is questionable in the upstream SOL of some high-power scenarios envisioned for burning plasmas and fusion pilot plants. This paper reports on comparisons between fluid and kinetic simulations of the SOL for upstream parameters and geometry representative of the Spherical Tokamak for Energy Production fusion pilot plant. The SOLPS-ITER (fluid) and Gkeyll (gyrokinetic) codes are operated in a two-dimensional axisymmetric mode, which replaces turbulence with ad-hoc diffusivities. In kinetic simulations, we observe that the ions in the upstream SOL experience significant mirror trapping. This substantially increases the upstream temperature and has important implications for impurity dynamics. We show that the mirror force, which is excluded in SOLPS’s fluid equations, enhances the electrostatic potential drop along the field line in the SOL. We also show that the assumption of equal main ion and impurity temperatures, which is made in commonly used fluid codes, is invalid for the regimes explored here. The combination of these effects results in superior confinement of impurities to the divertor region in kinetic simulations, consistent with our earlier predictions [Kotschenreuther et al., in 29th IAEA 29 Fusion Energy Conference (IAEA, London, UK, 2023)]. This effect can be dramatic, reducing the midplane impurity density by orders of magnitude. These results indicate that in lower collisionality SOL’s the tolerable downstream impurity densities may be higher than would be predicted by fluid simulations, allowing for higher radiated power while avoiding unacceptable core contamination. Our results highlight the importance of kinetic simulations for divertor design and optimization for fusion pilot plants.

Computational fluid dynamics↗
NASA NTRS1991

Theory and simulation of cometary shocks

In this paper, recent kinetic simulation studies of cometary bow shocks are reviewed. Cometary shocks are formed due to solar wind mass loading by water group cometary ions. This process is kinetic in nature and varies as a function of the angle between the solar wind flow velocity and the interplanetary magnetic field, as do the properties of cometary shocks. For perpendicular and parallel orientations, quasi-steady shocks with dissipation scales on the order of proton inertial length form. At oblique orientations, no steady shocks are formed; instead, the transition from supersonic to subsonic flow takes place through multiple shocklets (steepened magnetosonic waves) which are generated by the pickup ions via the resonant electromagnetic ion beam instability. This new, time dependent model of cometary bow shocks is further investigated using a large scale kinetic simulation and is compared to the observations at Comet Giacobini-Zinner.

Omidi, N.↗
NASA NTRS1992

A second-order theory for transverse ion heating and momentum coupling due to electrostatic ion cyclotron waves

A second-order theory for electrostatic instabilities driven by counterstreaming ion beams is developed which describes momentum coupling and heating of the plasma via wave-particle interactions. Exchange rates between the waves and particles are derived, which are suitable for the fluid equations simulating microscopic effects on macroscopic scales. Using a fully kinetic simulation, the electrostatic ion cyclotron instability due to counterstreaming H(+) beams has been simulated. A power spectrum from the kinetic simulation is used to evaluate second-order exchange rates. The calculated heating and momentum loss from second-order theory is compared to the numerical simulation.

Miller, Ronald H.↗