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

Autor:	Nayak I; ElectroScience Laboratory and Department of Electrical and Computer Engineering, The Ohio State University, Columbus, Ohio 43212, USA., Teixeira FL; ElectroScience Laboratory and Department of Electrical and Computer Engineering, The Ohio State University, Columbus, Ohio 43212, USA., Na DY; Department of Electrical Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, South Korea., Kumar M; LADDCS, Department of Mechanical and Aerospace Engineering, The Ohio State University, Columbus, Ohio 43210, USA., Omelchenko YA; Trinum Research Inc., San Diego, California 92126, USA.
Jazyk:	angličtina
Zdroj:	Physical review. E [Phys Rev E] 2024 Jun; Vol. 109 (6-2), pp. 065307.
DOI:	10.1103/PhysRevE.109.065307
Abstrakt:	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 speedup in EMPIC simulations involving electron beam under the influence of magnetic field, virtual cathode oscillations, and backward wave oscillator.
Databáze:	MEDLINE
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