Detection and prediction of equilibrium states in kinetic plasma simulations via mode tracking using reduced-order dynamic mode decomposition

JOURNAL OF COMPUTATIONAL PHYSICS

卷:447

Article

Nayak, Indranil^1,2  Kumar, Mrinal³  Teixeira, Fernando L.^1,2 

[1] Ohio State Univ, Electrosci Lab, Columbus, OH 43212 USA

[2] Ohio State Univ, Dept Elect & Comp Engn, Columbus, OH 43212 USA

[3] Ohio State Univ, Dept Mech & Aerosp Engn, Lab Auton Data Driven & Complex Syst, Columbus, OH 43210 USA

关键词: Equilibrium detection;    Kinetic plasma;    Limit cycle detection;    Particle-in-cell;    Reduced-order models;    Dynamic mode decomposition;   

DOI  :  10.1016/j.jcp.2021.110671

来源: Elsevier

【 摘 要 】

A dynamic mode decomposition (DMD) based reduced-order model (ROM) is developed for tracking, detection, and prediction of kinetic plasma behavior. DMD is applied to the high-fidelity kinetic plasma model based on the electromagnetic particle-in-cell (EMPIC) algorithm to extract the underlying dynamics and key features of the model. In particular, the ability of DMD to reconstruct the spatial pattern of the self electric field from high-fidelity data and the effect of DMD extrapolated self-fields on charged particle dynamics are investigated. An in-line sliding-window DMD method is presented for identifying the transition from transient to equilibrium state based on the loci of DMD eigenvalues in the complex plane. The in-line detection of equilibrium state combined with time extrapolation ability of DMD has the potential to effectively expedite the simulation. Case studies involving electron beams and plasma ball are presented to assess the strengths and limitations of the proposed method. (C) 2021 Elsevier Inc. All rights reserved.

【 授权许可】

Free