Disruption Modeling
Disruption codes simulate the rapid loss of confinement and current, predicting the thermal, electromagnetic, and runaway-electron loads a device must survive.
What a disruption is
A disruption is a sudden, uncontrolled termination of the plasma: confinement collapses (the thermal quench), then the plasma current decays rapidly (the current quench). The energy release and induced currents impose severe loads on the machine, making disruption prediction, avoidance, and mitigation essential engineering concerns.
The load chain
- Thermal quench: stored thermal energy dumps onto plasma-facing surfaces
- Current quench: fast current decay induces large forces in structures
- Halo currents: currents flowing partly through the vessel create asymmetric loads
- Runaway electrons: a beam of relativistic electrons that can damage surfaces
Modeling approaches
Different aspects use different tools: extended-MHD codes simulate the nonlinear instability and thermal quench, electromagnetic codes compute induced and halo currents and the resulting forces, and dedicated models track runaway-electron generation and avalanche. A full picture couples these together.
Mitigation
Because disruptions cannot be entirely eliminated, machines carry mitigation systems, typically massive injection of gas or shattered pellets to radiate the stored energy quickly and benignly. Modeling predicts how much material, injected how fast, is needed to spread the thermal load and suppress runaways.
Prediction and avoidance
The best mitigation is avoidance. Disruption-prediction models, increasingly using machine learning on diagnostic signals, aim to flag an oncoming disruption early enough to recover or trigger mitigation. These predictors are trained and tested in simulation and on experimental databases.
Disruption analysis is part of establishing the structural and protection requirements for any tokamak, defining loads the vessel, coils, and first wall must withstand.