Results of the application and demonstration calculations

Georgios Alexandridis, Christoph Blaesius, Christophe Demaziere, Christophe Destouches, Abdelhamid Dokhane, Aiden Mark Durrant, Vladimir Fiser, Gaëtan Girardin, Joachim Herb, Georgios Ioannou, Robert Jacqmin, Alexander Knospe, Stefanos Kollias, Carsten Lange, Georgios Leontidis, Sandor Lipcsei, Cristina Montalvo, Antonios Mylonakis, Laurent Pantera, Yann PerinChristoph Pohl, Marcus Seidl, Andreas Stafylopatis, Petr Stulik, Luis Alejandro Torres, Gumersindo Verdu Martin, Vasudha Verma, Antoni Vidal-Ferràndiz, Marco Viebach, Paolo Vinai

Research output: Other contribution

Abstract

This report describes the results of the application of the newly developed tools for reactor noise analysis, advanced signal
processing and machine learning methodologies to actual plant data. More specifically, the modeling tools developed in WP1
are used to simulate and analyze real plant measurements from the pre-Konvoi 3-loop NPP at Gösgen, a German pre-Konvoi
4-loop reactor, a Hungarian VVER-440 reactor and a Czech VVER-1000 reactor. Subsequently, the techniques developed in
WP3 are used to identify the root causes of neutron flux fluctuations in the actual plant data for the reactors presented above.
The results are compared with the simulation results corresponding to the selected power plants, based on the hypotheses developed for reactor noise analysis.
Original languageEnglish
PublisherEuropean Commission
Number of pages194
Publication statusPublished - 31 Jul 2020

Keywords

  • nuclear reactors
  • Machine learning
  • Anomaly detection
  • nuclear reactor noise analysis

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