Risk modelling of ageing nuclear reactor systems

•Risk assessment Petri Nets overcome restrictive assumptions of traditional methods.•Application of the proposed methodology is demonstrated with a reactor case study.•Detailed statistics and distributions are collected rather than the point estimates.•The probability of various system states over t...

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Veröffentlicht in:Annals of nuclear energy 2022-02, Vol.166, p.108701, Article 108701
Hauptverfasser: Wootton, Mark James, Andrews, John D., Lloyd, Adam L., Smith, Roger, Arul, A. John, Vinod, Gopika, Prasad, M. Hari, Garg, Vipul
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Sprache:eng
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Zusammenfassung:•Risk assessment Petri Nets overcome restrictive assumptions of traditional methods.•Application of the proposed methodology is demonstrated with a reactor case study.•Detailed statistics and distributions are collected rather than the point estimates.•The probability of various system states over time is visualised.•It is shown how the models could be used to calculate system parameter sensitivity. A nuclear reactor is expected to function for extensive periods, during which, coolant circulation and core reactivity must always be maintained safely. Understanding the risks associated with the operation of such systems requires proper consideration of ageing components and the effects of preventative maintenance. The traditional methodologies, such as Fault Trees and Event Trees, have limitations in their abilities to model ageing processes and complex maintenance strategies. Petri Nets have been used in this research as a more suitable alternative. A case study reactor is presented to demonstrate this capability. Petri Nets were developed for five key subsystems: primary coolant circulation, shutdown condensation, emergency core coolant injection, emergency shutdown, and control and monitoring, building a representation which considers their failure modes, reaction of the system to faults, and ongoing component maintenance actions. These models reveal statistics for the timing of failure of these subsystems and relative frequencies of outcome categories.
ISSN:0306-4549
1873-2100
DOI:10.1016/j.anucene.2021.108701