Advancements in 3D Edge Long-Pulse Tokamak Scenarios with Instability & Transport Control

Here, we present advancements in enhancing the predictive capabilities of 3D tokamak models and demonstrating 3D field applications for transport and instability control in long-pulse high-performance plasmas. The project focuses on validating the physics basis for predictive ELM suppression, integrating plasma response into core and edge transport models for long-pulse scenario optimizations, and achieving high confinement long pulse in KSTAR using 3D fields. Significant progress in both linear and nonlinear MHD models was made in predicting ELM suppression criteria. Integration efforts include combining linear and neoclassical kinetic-MHD models with SOL transport models to predict heat flux to KSTAR's PFCs. Fast ion transport models are validated through KSTAR's fast ion diagnostics. Integration of M3D-C1 and GTC provides gyrokinetic simulations of microturbulent transport with magnetic islands. Adaptive real-time control and optimization of 3D fields, combined with pre-programmed stability and transport recipes, aim to achieve high confinement long pulse ELM-suppressed discharges in KSTAR. Recent advancements include machine learning-based triggering, active probing ELM precursor detection, and ML surrogate model acceleration of GPEC-based edge resonant phasing optimization.