GS-DeepNet: mastering tokamak plasma equilibria with deep neural networks and the Grad-Shafranov equation.

ABSTRACT: The force-balanced state of magnetically confined plasmas heated up to 100 million degrees Celsius must be sustained long enough to achieve a burning-plasma state, such as in the case of ITER, a fusion reactor that promises a net energy gain. This force balance between the Lorentz force and the pressure gradient force, known as a plasma equilibrium, can be theoretically portrayed together with Maxwell's equations as plasmas are collections of charged particles. Nevertheless, identifying the plasma equilibrium in real time is challenging owing to its free-boundary and ill-posed conditions, which conventionally involves iterative numerical approach with a certain degree of subjective human decisions such as including or excluding certain magnetic measurements to achieve numerical convergence

SUBMITTER: Joung S 

PROVIDER: S-EPMC10516960 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature