CE30 - Physique de la matière condensée et de la matière diluée

Artificial Intelligence Methods for Energetic Particle transport in fusion plasmas – AIM4EP

Submission summary

Energetic particles are ubiquitous in magnetically confined fusion plasmas. They contain a significant fraction of the plasma energy and are thus vital for the performance of fusion devices such as ITER. However, the presence of energetic particles and the fact that fusion plasmas are complex systems heated up to hundred million degrees result in instabilities that reduce the confinement of energetic particles. Understanding, predicting and controlling their transport and losses is of prime importance and constitutes our main goal. This is a high-dimensional multi-scale nonlinear problem, for which a complete description is so far unaffordable. Therefore, we propose a novel and inter-disciplinary approach to develop numerical tools based on Artificial Intelligence techniques applied to two lines of research: (1) derive data-driven reduced models for transport of energetic particles and (2) optimize the information extracted from HPC gyro-kinetic simulations and from experiments.

Project coordination

David Zarzoso Fernandez (Physique des interactions ioniques et moléculaires)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.


I2M Institut de Mathématiques de Marseille
PIIM Physique des interactions ioniques et moléculaires
IRFM Institut de Recherche sur la Fusion par Confinement Magnétique
CIEMAT Centro de Investigaciones Energeticas Medioambientales y Tecnologicas (CIEMAT) / Laboratorio de Fusion

Help of the ANR 367,168 euros
Beginning and duration of the scientific project: December 2021 - 48 Months

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