1 citations · 1 across the 5 of their papers we have counts for
5 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…
Applications of a novel model-based real-time observer for electron density profile control experiments in TCV
F. Pastore, O. Sauter, F. Felici +12
Real-time control of tokamak plasmas encompasses sustaining a high-performance stationary state, avoiding disruptions, and managing ramp-up and ramp-down phases. Real-time estimati…
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…
A tutorial on inversion-based shape control with design application to NSTX-U
J. T. Wai, M. D. Boyer, D. J. Battaglia +5
One of the most common designs for magnetic control in tokamaks is to ``linearize an equilibrium'' to obtain a sensitivity mapping, then invert this mapping in order to determine t…
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…