Probabilistic risk assessment of station blackouts in nuclear power plants

Hindolo George-Williams, Min Lee, Edoardo Patelli

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)
5 Downloads (Pure)


Adequate ac power is required for decay heat removal in nuclear power plants. Station blackout (SBO) accidents, therefore, are a very critical phenomenon to their safety. Though designed to cope with these incidents, nuclear power plants can only do so for a limited time, without risking core damage and possible catastrophe. Their impact on a plant's safety are determined by their frequency and duration, which quantities, currently, are computed via a static fault tree analysis that deteriorates in applicability with increasing system size and complexity. This paper proposes a novel alternative framework based on a hybrid of Monte Carlo methods, multistate modeling, and network theory. The intuitive framework, which is applicable to a variety of SBOs problems, can provide a complete insight into their risks. Most importantly, its underlying modeling principles are generic, and, therefore, applicable to non-nuclear system reliability problems, as well. When applied to the Maanshan nuclear power plant in Taiwan, the results validate the framework as a rational decision-support tool in the mitigation and prevention of SBOs.
Original languageEnglish
Pages (from-to)494-512
Number of pages19
JournalIEEE Transactions on Reliability
Issue number2
Publication statusPublished - 1 Jun 2018


  • accident recovery
  • monte carlo simulation (MCS)
  • nuclear power plant
  • risk assessment
  • blackout (SBO)


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