A data-free physics-informed neural network surrogate solves the drift kinetic equation accurately and rapidly for neoclassical toroidal viscosity torque modeling in tokamaks.
Park, S M Yang, and Q Hu
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.plasm-ph 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
A Data-Free, Physics-Informed Surrogate Solver for Drift Kinetic Equation: Enabling Fast Neoclassical Toroidal Viscosity Torque Modeling in Tokamaks
A data-free physics-informed neural network surrogate solves the drift kinetic equation accurately and rapidly for neoclassical toroidal viscosity torque modeling in tokamaks.