Mainz 2022 – scientific programme
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P: Fachverband Plasmaphysik
P 9: Poster I
P 9.11: Poster
Tuesday, March 29, 2022, 16:00–17:30, P
Viability of NN-based Predictor-Corrector Schemes for Plasma Simulations — •Robin Greif1, Frank Jenko1, and Nils Thuerey2 — 1Boltz- mannstr. 2, 85748 Garching, Germany — 2Boltzmannstr. 3, 85748 Garching, Germany
We investigate the viability of using neural network driven simulation methods based on novel predictor-corrector schemes developed for fluid and smoke simulations for turbulence in plasma. The approach builds on top of successful pioneering work on numerical schemes from Mantaflow and its successor, Phi-Flow, an open-source machine learnign framework aggregator for fluid dynamic simulations. In this project, we extend Phi-Flow to solve the Hasegawa-Wakatani equations as a proof-of-concept of the viability of modern neural-network based numerical simulation techniques for simple plasma models. The use of deep-learning based numerical integration schemes explored here has been shown to provide superior accuracy at coarser grids than classical methods in fluid simulations and is a promising candidate to reduce the computational cost for the next generation of plasma simulations.