Identification of vessel failures provides operators and technical support center personnel with important information to manage severe accidents in a nuclear power plant.
It may be very difficult, however, for operators to identify a reactor vessel failure simply by watching temporal trends of some parameters because they have not experienced severe accidents.
Therefore, we propose a methodology on the identification of pressurized water reactor (PWR) vessel failure for severe accident management using spatiotemporal neural network (STN).
STN can deal directly with the spatial and temporal aspects of input signals and can well identify a time-varying problem.
Target patterns of seven parameter signals were generated for training the network from the modular accident analysis program (MAAP) code, which simulates severe accidents in nuclear power plants.
We integrated MAAP code with STN in on-line system to mimic real accident situation in nuclear power plants.
Using new patterns of signals that had never been used for training, the identification capability of STN was tested in a real-time manner.
At the tests, STN developed in this study demonstrated acceptable performance in identifying the occurrence of a vessel failure.
It is found that STN techniques can be extended to the identification of other key events such as onset of core uncovering, coremelt initiation, containment failure, etc.
Mots-clés Pascal : Théorie, Analyse dommage, Réacteur eau pressurisée, Prévention accident, Réseau neuronal, Système paramètre variable, Logiciel, Simulation ordinateur, Système en ligne, Système temps réel, Accident réacteur nucléaire, Récipient sous pression
Mots-clés Pascal anglais : Reactor vessel failures, Spatiotemporal neural networks, Software package MAAP, Theory, Failure analysis, Pressurized water reactors, Accident prevention, Neural networks, Time varying systems, Computer software, Computer simulation, Online systems, Real time systems, Nuclear reactor accidents, Pressure vessels
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 97-0352790
Code Inist : 001D06B03E. Création : 12/09/1997.