Published October 3, 2021 | Version v1
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Deep Learning-based Anomaly Detection in Nuclear Reactor Cores

  • 1. Institute of Communication and Computer Systems National Technical University of Athens
  • 2. Paul Scherrer Institute


•The introduction of a deep learning methodology for the classification of different perturbation types and their position in the reactor core, using convolutional neural networks
•The performance of a complementary robustness analysis to assess the system's performance on noisy or missing data
•The assessment of the system's functionality on plant measurements obtained from the Gösgennuclear power plan in Switzerland



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CORTEX – Core monitoring techniques and experimental validation and demonstration 754316
European Commission