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

Author

Listed:
  • Nicolas Duflot

    (LM2S - Laboratoire Modélisation et Sûreté des Systèmes - ICD - Institut Charles Delaunay - UTT - Université de Technologie de Troyes - CNRS - Centre National de la Recherche Scientifique)

  • Christophe Bérenguer

    (LM2S - Laboratoire Modélisation et Sûreté des Systèmes - ICD - Institut Charles Delaunay - UTT - Université de Technologie de Troyes - CNRS - Centre National de la Recherche Scientifique)

  • Laurence Dieulle

    (LM2S - Laboratoire Modélisation et Sûreté des Systèmes - ICD - Institut Charles Delaunay - UTT - Université de Technologie de Troyes - CNRS - Centre National de la Recherche Scientifique)

  • Dominique Vasseur

    (EDF R&D MRI - Management des Risques Industriels - EDF R&D - EDF R&D - EDF - EDF)

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 900 MWe 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

  • Nicolas Duflot & Christophe Bérenguer & Laurence Dieulle & Dominique Vasseur, 2009. "A min cut-set-wise truncation procedure for importance measures computation in probabilistic safety assessment," Post-Print hal-02284361, HAL.
    • Handle: RePEc:hal:journl:hal-02284361
    DOI: 10.1016/j.ress.2009.05.015
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    Cited by:

    1. 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.
    2. 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.
    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.

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