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Quantitative Analysis of Dynamic Fault Trees Based on the Coupling of Structure Functions and Monte Carlo Simulation
Author(s) -
Merle G.,
Roussel J. M.,
Lesage J. J.,
Perchet V.,
Vayatis N.
Publication year - 2016
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.1728
Subject(s) - monte carlo method , fault tree analysis , computer science , function (biology) , statistical physics , fault (geology) , exploit , coupling (piping) , sensitivity (control systems) , mode (computer interface) , algorithm , monte carlo molecular modeling , mathematics , markov chain monte carlo , engineering , physics , reliability engineering , statistics , computer security , evolutionary biology , electronic engineering , seismology , biology , geology , operating system , mechanical engineering
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. Copyright © 2014 John Wiley & Sons, Ltd.