Deep Learning-based Anomaly Detection in Nuclear Reactor Cores

Autor: Thanos Tasakos, George Ioannou, Vasudha Verma, Georgios Alexandridis, Abdelhamid Dokhane, Andreas Stafylopatis
Jazyk: angličtina
Rok vydání: 2021
Předmět:
DOI: 10.5281/zenodo.5575838
Popis: •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
Databáze: OpenAIRE