Bulletin of the American Physical Society
64th Annual Meeting of the APS Division of Plasma Physics
Volume 67, Number 15
Monday–Friday, October 17–21, 2022; Spokane, Washington
Session CT02: Tutorial: Magnetic Confinement Fusion ILive Streamed
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Chair: Rachel Myers, Univ. Wisconsin, Madison Room: Ballroom 100 B |
Monday, October 17, 2022 2:00PM - 3:00PM |
CT02.00001: Interpretable Machine Learning Accelerating Fusion Research Invited Speaker: Cristina Rea It has become widely accepted that Machine Learning (ML) accelerated research can enable reactor-relevant solutions for a broad spectrum of fusion challenges. Both inertial and magnetic confinement fusion need to address complex multi-scale, multi-physics systems whose integrated modeling implies extremely expensive computations, and ML can assist via surrogate modeling for accelerating such demanding simulation loops [Rodriguez-Fernandez 2022 NF 62 076036, Humbird 2021 PoP 28 042709]. Further relevant examples of ML applications in fusion include its adoption to enhance the analysis of instrumentation data [Samuell 2021 RSI 92 043520], to optimize experimental design and performances [Gopalaswamy 2019 Nature 565 581, Humphreys 2020 JFE 39 123–55], and for real-time monitoring of the proximity to different boundaries of plasma stability [Rea 2021 IAEA EX/P1–25]. |
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