Development of COTSIM+NUBEAMNet Predictive Transport Simulation Capability for Scenario Optimization in NSTX-U

Plasma transport predictive models require a sufficiently small computational effort to enable their use in model-based scenario-control design. The Control Oriented Transport SIMulator (COTSIM), which captures the control-relevant physics involved in a tokamak discharge, has been developed to fulfill these computational-time constraints and to serve the specific purpose of control design. In this work, the predictive capabilities in COTSIM for NSTX-U scenarios have been significantly improved. The dynamics of the plasma is modeled by the magnetic diffusion equation, the heat transport equation for electrons and ions, and the angular momentum equation. The current, torque, and heating depositions by the neutral beam injectors are modeled using a neural network, NUBEAMNet [1], which reproduces the results of NUBEAM in a fraction of the computation time demanded by the original Monte Carlo code. Semi-empirical transport models, Coppi-Tang and Bohm/gyro-Bohm, and fixed boundary equilibrium solvers are also integrated with the transport equations. Predictions by this fast-simulation capability are validated against those by TRANSP. This new version of COTSIM for NSTX-U will enable a myriad of plasma-control applications, including model-based scenario optimization.



[1] M.D. Boyer et al 2019 Nucl. Fusion 59 056008.