Regulation Compliant AI for Fusion: Real-Time Image Analysis-Based Control of Divertor Detachment in Tokamaks
This addresses the need for regulatory-compliant AI control in fusion reactors, which is crucial for future reactor operations, though it is incremental as it builds on existing AI methods with a focus on interpretability.
The study tackled the challenge of implementing AI in regulatory-compliant fusion control by developing a real-time, interpretable AI system for divertor detachment control using the DIII-D lower divertor camera, achieving a mean absolute difference of 2% from the target for detachment and reattachment.
While artificial intelligence (AI) has been promising for fusion control, its inherent black-box nature will make compliant implementation in regulatory environments a challenge. This study implements and validates a real-time AI enabled linear and interpretable control system for successful divertor detachment control with the DIII-D lower divertor camera. Using D2 gas, we demonstrate feedback divertor detachment control with a mean absolute difference of 2% from the target for both detachment and reattachment. This automatic training and linear processing framework can be extended to any image based diagnostic for regulatory compliant controller necessary for future fusion reactors.