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Fuzzy Failure Rate for Nuclear Power Plant Probabilistic Safety Assessment by Fault Tree Analysis

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Computational Intelligence Systems in Industrial Engineering

Part of the book series: Atlantis Computational Intelligence Systems ((ATLANTISCIS,volume 6))

Abstract

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 the conventional reliability data comes from insufficient historical data for probabilistic calculation. This chapter proposes and discusses a failure possibility-based reliability algorithm to assess nuclear event reliability data from 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 discuss an area defuzzification technique, which has been developed, to defuzzify nuclear event failure possibilities into their corresponding fuzzy failure rates, which are similar to the probabilistic failure rates probabilistically calculated from historical failure data. A simplified model of a high pressure core spray system is used to mathematically proof the proposed algorithm and defuzzification technique. The results show that fuzzy failure rates can be used in nuclear power plant probabilistic safety assessment by fault tree analysis as alternatives for probabilistic failure rates when nuclear event historical data are insufficient or unavailable for probabilistic calculation.

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Authors and Affiliations

  1. Decision Systems and e-Service Intelligence Laboratory, Centre for Quantum Computation and Intelligent Systems, School of Software, Faculty of Engineering and Information Technology, University of Technology, Sydney (UTS), P.O. Box 123, Broadway, Sydney, NSW, 2007, Australia

    Julwan Hendry Purba, Jie Lu & Guangquan Zhang

Authors
  1. Julwan Hendry Purba
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  2. Jie Lu
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  3. Guangquan Zhang
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Corresponding author

Correspondence to Julwan Hendry Purba .

Editor information

Editors and Affiliations

  1. Fac. Management, Dept. Industrial Engineering, Istanbul Technical University, Campus Macka, Istanbul, 34367, Turkey

    Cengiz Kahraman

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Purba, J.H., Lu, J., Zhang, G. (2012). Fuzzy Failure Rate for Nuclear Power Plant Probabilistic Safety Assessment by Fault Tree Analysis. In: Kahraman, C. (eds) Computational Intelligence Systems in Industrial Engineering. Atlantis Computational Intelligence Systems, vol 6. Atlantis Press, Paris. https://doi.org/10.2991/978-94-91216-77-0_7

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  • DOI: https://doi.org/10.2991/978-94-91216-77-0_7

  • Publisher Name: Atlantis Press, Paris

  • Print ISBN: 978-94-91216-76-3

  • Online ISBN: 978-94-91216-77-0

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