4 papers
An Inverse Grad-Shafranov Neural Network Approach to Tokamak Magnetic Control
Allen M. Wang, Adriano Mele, Cosmas Heiß +12
A new approach to tokamak magnetic control enabling high-precision plasma shaping and novel real-time adaptability is experimentally demonstrated on the Tokamak a Configuration Var…
Kinetic Equilibrium Prediction at TCV using RAPTOR and FBT
C. E. Contré, A. Merle, O. Sauter +13
We present results from a new Kinetic-Equilibrium Prediction (KEP) workflow and shot preparation for full TCV discharges, by coupling predict-first RAPTOR transport simulations wit…
FGE: A Fast Free-Boundary Grad-Shafranov Evolutive Solver
Cosmas Heiß, Antoine Merle, Francesco Carpanese +5
Accurate and rapid simulation of the free boundary tokamak plasma equilibrium evolution is essential for modern plasma control, stability analysis, and scenario development. This p…
Learning Plasma Dynamics and Robust Rampdown Trajectories with Predict-First Experiments at TCV
Allen M. Wang, Alessandro Pau, Cristina Rea +12
The rampdown phase of a tokamak pulse is difficult to simulate and often exacerbates multiple plasma instabilities. To reduce the risk of disrupting operations, we leverage advance…