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A min cut-set-wise truncation procedure for importance measures computation in probabilistic safety assessment

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  • Duflot, Nicolas
  • Bérenguer, Christophe
  • Dieulle, Laurence
  • Vasseur, Dominique

Abstract

A truncation process aims to determine among the set of minimal cut-sets (MCS) produced by a probabilistic safety assessment (PSA) model which of them are significant. Several truncation processes have been proposed for the evaluation of the probability of core damage ensuring a fixed accuracy level. However, the evaluation of new risk indicators as importance measures requires to re-examine the truncation process in order to ensure that the produced estimates will be accurate enough. In this paper a new truncation process is developed permitting to estimate from a single set of MCS the importance measure of any basic event with the desired accuracy level. The main contribution of this new method is to propose an MCS-wise truncation criterion involving two thresholds: an absolute threshold in addition to a new relative threshold concerning the potential probability of the MCS of interest. The method has been tested on a complete level 1 PSA model of a 900MWe NPP developed by “Electricité de France†(EDF) and the results presented in this paper indicate that to reach the same accuracy level the proposed method produces a set of MCS whose size is significantly reduced.

Suggested Citation

  • Duflot, Nicolas & Bérenguer, Christophe & Dieulle, Laurence & Vasseur, Dominique, 2009. "A min cut-set-wise truncation procedure for importance measures computation in probabilistic safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 94(11), pages 1827-1837.
    • Handle: RePEc:eee:reensy:v:94:y:2009:i:11:p:1827-1837
    DOI: 10.1016/j.ress.2009.05.015
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    References listed on IDEAS

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    1. Jung, Woo Sik & Yang, Joon-Eon & Ha, Jaejoo, 2005. "Development of measures to estimate truncation error in fault tree analysis," Reliability Engineering and System Safety, Elsevier, vol. 90(1), pages 30-36.
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    Cited by:

    1. Di Maio, Francesco & Baronchelli, Samuele & Zio, Enrico, 2014. "Hierarchical differential evolution for minimal cut sets identification: Application to nuclear safety systems," European Journal of Operational Research, Elsevier, vol. 238(2), pages 645-652.
    2. Zaitseva, Elena & Levashenko, Vitaly & Kostolny, Jozef, 2015. "Importance analysis based on logical differential calculus and Binary Decision Diagram," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 135-144.
    3. F Brissaud & A Barros & C Bérenguer, 2010. "Handling parameter and model uncertainties by continuous gates in fault tree analyses," Journal of Risk and Reliability, , vol. 224(4), pages 253-265, December.
    4. Matuzas, V. & Contini, S., 2015. "Dynamic labelling of BDD and ZBDD for efficient non-coherent fault tree analysis," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 183-192.
    5. Vaurio, Jussi K., 2010. "Ideas and developments in importance measures and fault-tree techniques for reliability and risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(2), pages 99-107.

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