5 citations · 6 across the 3 of their papers we have counts for
3 papers
Active Disruption Avoidance and Trajectory Design for Tokamak Ramp-downs with Neural Differential Equations and Reinforcement Learning
Allen M. Wang, Oswin So, Charles Dawson +3
The tokamak offers a promising path to fusion energy, but plasma disruptions pose a major economic risk, motivating considerable advances in disruption avoidance. This work develop…
Autoregressive Transformers for Disruption Prediction in Nuclear Fusion Plasmas
Lucas Spangher, William Arnold, Alexander Spangher +2
The physical sciences require models tailored to specific nuances of different dynamics. In this work, we study outcome predictions in nuclear fusion tokamaks, where a major challe…
Hybridizing Physics and Neural ODEs for Predicting Plasma Inductance Dynamics in Tokamak Fusion Reactors
Allen M. Wang, Darren T. Garnier, Cristina Rea
While fusion reactors known as tokamaks hold promise as a firm energy source, advances in plasma control, and handling of events where control of plasmas is lost, are needed for th…