3 papers
physics.plasm-ph2026
Surrogate modeling of drift-reduced Braginskii turbulence with resistivity-conditioned Koopman neural operators
Ameir Shaa, Kyungtak Lim, Long Shan Chan +1
Machine-learning-driven surrogate operators are developed for three-dimensional, nonlinear, flux-driven simulations of boundary plasma turbulence based on the two-fluid drift-reduc…
physics.plasm-ph2026
Machine learning prediction of plasma behavior from discharge configurations on WEST
Chenguang Wan, Feda Almuhisen, Philippe Moreau +10
Accurately predicting plasma behavior based on discharge configurations is essential for the safe and efficient operation of tokamak experiments. While physics-based integrated mod…
physics.plasm-ph2024
Effect of negative triangularity on SOL plasma turbulence in double-null L-mode plasmas
Kyungtak Lim, Paolo Ricci, Leonard Lebrun
The effects of negative triangularity (NT) on boundary plasma turbulence in double-null (DN) configurations are investigated using global, nonlinear, three-dimensional, flux-driven…