An area defuzzification technique to assess nuclear event reliability data from failure possibilities

Julwan Hendry Purba, Jie Lu, Guangquan Zhang, Da Ruan

    Research outputpeer-review

    18 Scopus citations


    Reliability data is essential for a nuclear power plant probabilistic safety assessment by fault tree analysis to assess the performance of the safety-related systems. The limitation of conventional reliability data arises from insufficient historical data for probabilistic calculation. This study describes a new approach to calculate nuclear event reliability data by utilizing the concept of failure possibilities, which are expressed in qualitative natural languages, mathematically represented by membership functions of fuzzy numbers, and subjectively justified by a group of experts based on their working experience and expertise. We also propose an area defuzzification technique to convert the membership function into nuclear event reliability data. The actual event reliability data, which are collected from the operational experiences of the reactor protection system in Babcock & Wilcox pressurized water reactor between 1984 and 1998, are then compared with the reliability data calculated from the new approach. The results show that fuzzy failure rates can be used as alternatives for probabilistic failure rates when nuclear event historical data are insufficient or unavailable for probabilistic calculation. This study also confirms that our proposed area defuzzification technique is a suitable technique to defuzzify failure possibilities into nuclear event reliability data.

    Original languageEnglish
    Article number1250022
    JournalInternational Journal of Computational Intelligence and Applications
    Issue number4
    StatePublished - Dec 2012

    ASJC Scopus subject areas

    • Software
    • Theoretical Computer Science
    • Computer Science Applications

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