publication . Conference object . 2021

Deep Learning-based Anomaly Detection in Nuclear Reactor Cores

Thanos Tasakos; Ioannou, George; Verma, Vasudha; Alexandridis, Georgios; Abdelhamid Dokhane; Stafylopatis, Andreas;
Open Access English
  • Published: 03 Oct 2021
  • Publisher: Zenodo
•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
Funded by
Core monitoring techniques and experimental validation and demonstration
  • Funder: European Commission (EC)
  • Project Code: 754316
  • Funding stream: H2020 | RIA
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Open Access
Conference object . 2021
Provider: Datacite
Open Access
Conference object . 2021
Provider: Datacite
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