Speaker
Description
Plasma disruptions in Tokamaks are one of the threats to the secure operation of nuclear fusion devices. Disruptions are a sudden loss of plasma confinement. The disruptive events release large amounts of energy that impact the first wall components, affecting their integrity. This work presents the development of a disruption predictor implemented in the ITER Real-Time Framework (RTF). The objective is to test the RTF platform response under very demanding conditions, such as predicting disruptions. The predictor evaluated is the JET Advanced Predictor Of DISruptions (APODIS), developed during the first JET experimental campaign of the ITER-like Wall (ILW). The predictor has been trained and tested with JET data. The real-time prediction meets the strict latency and determinism requirements of real-time control systems for fusion devices. Additionally, the Synchronous Databus Network (SDN) has been utilized for low-latency data transmission via a publisher-subscriber model. To guarantee real-time performance, several optimization techniques have been applied, including real-time threading, CPU core isolation, and network card parameters fine-tuning. Validation was performed through numerical verification and detailed latency characterization. Results demonstrate that each APODIS prediction in the RTF platform requires an average processing time below 100$\mu s$, with a standard deviation under 10$\mu s$ and a maximum outlier of 300$\mu s$. Considering that the sampling period of the signals can be O(1 ms), these times are enough for the problem at hand. Therefore, the proposed solution confirms the feasibility of the RTF platform for real-time demanding tasks (for instance, disruption prediction) in next-generation nuclear fusion devices.
| Minioral | Yes |
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| IEEE Member | Yes |
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