Accelerating Particle-in-Cell Kinetic Plasma Simulations via Reduced-Order Modeling of Space-Charge Dynamics using Dynamic Mode Decomposition
arXiv (Cornell University)(2023)
摘要
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. We
demonstrate the proposed DMD-EMPIC scheme for reduced-order modeling of current
density, and speed-up in EMPIC simulations involving electron beams under the
influence of magnetic fields and virtual cathode oscillations.
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关键词
plasma,simulations,particle-in-cell,reduced-order,space-charge
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