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February 21, 2026Journal of Fusion Energy0 citationsOpen Access

Anomaly Detection of Radiative Collapse in Impurity Seeding Experiment Using Imaging Bolometer and Autoencoder

KMKiyofumi MukaiSMSuguru MasuzakiBPByron J. Peterson

Key Points

  • The aim is to detect precursors of radiative collapse in neon seeded plasmas to control impurity injection.
  • Utilized a two-dimensional radiation measurement with an InfraRed Imaging Video Bolometer (IRVB).
  • Employed an AutoEncoder (AE) model for analysis of 1219 plasma images.
  • Analyzed discharges with moderate Ne pulses to identify signs of radiative collapse.
  • Successfully detected an increase in abnormality indicative of radiative collapse before Ne pulses.
  • Observed that anomalous radiation structure persists at the edge plasma without radiative collapse but moves toward the core during collapse.

Abstract

Radiative collapse in neon (Ne) seeded plasmas has been detected using a two-dimensional radiation measurement (InfraRed imaging Video Bolometer, IRVB) and an AutoEncoder (AE) on the Large Helical Device (LHD). In divertor detachment for fusion reactors, while the divertor heat load is mitigated using impurity injection, excessive impurity injection induces radiative collapse. Therefore, it is important to detect the precursor of the radiative collapse for the control of the impurity injection amount to maintain stable divertor detachment. In this study, 1219 images measured with the IRVB were used for training. By using the AE model, in the discharges with moderate Ne pulses, radiative collapse was successfully detected as an increase of abnormality earlier than the Ne pulse just before the radiative collapse. Moreover, by investigating the anomalous radiation structure, it was found to remain at the edge plasma region when radiation increased without radiative collapse, whereas the anomalous radiation structure progressed toward the core plasma when radiative collapse occurred.

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Cite This Study

Mukai et al. (2026) studied this question.

synapsesocial.com/papers/69994bdd873532290d01fe56https://doi.org/10.1007/s10894-026-00556-0
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