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Quantitative Analysis of Dynamic Fault Trees Based on the Coupling of Structure Functions and Monte Carlo Simulation

  • G. Merle
  • , J. M. Roussel
  • , J. J. Lesage
  • , V. Perchet
  • , N. Vayatis
  • ENS Cachan
  • Laboratoire de Probabilités et Modèles Aléatoires
  • ENS Paris-Saclay

Résultats de recherche: Contribution à un journalArticle de révisionRevue par des pairs

Résumé

This paper focuses on the quantitative analysis of Dynamic Fault Trees (DFTs) by means of Monte Carlo simulation. In a previous article, we defined an algebraic framework allowing to determine the structure function of DFTs. We exploit this structure function and the minimal cut sequences that it allows to determine, to know the failure mode configuration of the system, which is an input of Monte Carlo simulation. We show that the results obtained are in good accordance with theoretical results and that some results, such as importance measures and sensitivity indexes, are not provided by common quantitative analysis and yet interesting. We finally illustrate our approach on a DFT example from the literature.

langue originaleAnglais
Pages (de - à)7-18
Nombre de pages12
journalQuality and Reliability Engineering International
Volume32
Numéro de publication1
Les DOIs
étatPublié - 1 févr. 2016
Modification externeOui

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