Sixth IAEA Technical Meeting on Fusion Data Processing, Validation and Analysis

Session

Signal Processing and Anomaly Detection

9 Sept 2025, 10:45

Auditorium Hall HGX 102 (Guanghua Twin Tower) (Fudan University, Shanghai, China)

Conveners

Signal Processing and Anomaly Detection

• Andrea Murari (Consorzio RFX)

Signal Processing and Anomaly Detection

• Andrea Murari (Consorzio RFX)

6. A Comprehensive Strategy of Disruption Prediction to Avoid the Collapse of the Configuration in the Next Generation of Tokamak Devices

Michela Gelfusa (University of Rome Tor Vergata)

09/09/2025, 10:45

Signal Processing and Anomaly Detection

Oral (Invited)

Disruptions are catastrophic forms of collapse that have affected all tokamak devices and are therefore one of the main potential showstoppers on the route to a commercial reactor. A new approach to proximity detection has been developed. It allows determining both the probability of and the time interval remaining before an incoming disruption. The methodology has been implemented with...

7. Time series methods for fusion plasma disruption prediction

Teddy CRACIUNESCU (National Institute for Lasers, Plasma and Radiation Physics INFLPR, Magurele, Romania)

09/09/2025, 11:15

Signal Processing and Anomaly Detection

Oral (Regular)

The approaching initial operation of major new tokomaks is rendering more pressing the need for effective disruption prediction techniques. The required tools should be not only accurate but also capable of operating with a minimum number of signals, because in the first campaigns of new devices typically only a very limited number of diagnostics is available. In addition, a very limited...

50. Predictive Maintenance in Fusion Devices: Estimating the Remaining Useful Life of Plasma-Facing Component Units Using a Similarity-Based Approach

Geert Verdoolaege (Ghent University)

09/09/2025, 11:40

Signal Processing and Anomaly Detection

Oral (Regular)

With a view to reliability, availability, maintainability, and inspectability (RAMI) for DEMO, achieving an availability of 30-60\% while minimizing unscheduled shutdowns is a critical prerequisite [1]. Plasma-facing components (PFCs), such as the divertor and first wall, are exposed to extreme thermal loads, shocks, and particle bombardment, conditions that can lead to component failure. In...

37. Determine the mode number and wave-number of plasma instability using harmonics in the spectrum

Liwen Hu (核工业西南物理研究院)

09/09/2025, 12:05

Signal Processing and Anomaly Detection

Oral (Regular)

Harmonic phenomenon occurs frequently in the plasma diagnostic signal spectrum and is often considered useless or even harmful. Because the harmonic of plasma modes may overlap with other modes making it difficult for experimenters to distinguish between these modes. But in some case harmonics of mode may carry important information that helps further study plasma instability modes.
Harmonic...

53. On Data-driven Approaches in Extracting RSAE mode in Tokamak Experiments

Wenyang Li (Nankai University)

09/09/2025, 13:30

Signal Processing and Anomaly Detection

Oral (Short)

Abstract

Reversed Shear Alfvén Wave (RSAE) is an ubiquitous mode driven by energetic particles (EPs). Through RSAE, one can infer the existence of reversed $q$-profile and the EP activities. Therefore it is an important branch of Alfvén wave. In this work, we propose a data-driven approach to identify RSAEs in HL-2A tokamak experiments.

First, by analyzing the diagnostic data...

62. Real-Time Identification of sawtooth on HL-3 using a deep learning framework

Hongjia OuYang (Swip)

09/09/2025, 13:45

Signal Processing and Anomaly Detection

Oral (Short)

Sawtooth instability is one of the most violent magnetohydrodynamic (MHD) instabilities that must be actively controlled in a tokamak fusion reactor.In present tokamak experiments, various auxiliary heating systems, such as neutral beam injection and ion or electron cyclotron resonance heating, are used. Electron cyclotron (EC) beams are particularly well-suited for controlling plasma...