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A Hybrid Modular Approach for Dynamic Fault Tree Analysis

Kabir, Sohag; Aslansefat, Koorosh; Sorokos, Ioannis; Papadopoulos, Yiannis; Konur, Savas


Sohag Kabir

Ioannis Sorokos

Savas Konur


Over the years, several approaches have been developed for the quantitative analysis of dynamic fault trees (DFTs). These approaches have strong theoretical and mathematical foundations; however, they appear to suffer from the state-space explosion and high computational requirements, compromising their efficacy. Modularisation techniques have been developed to address these issues by identifying and quantifying static and dynamic modules of the fault tree separately by using binary decision diagrams and Markov models. Although these approaches appear effective in reducing computational effort and avoiding state-space explosion, the reliance of the Markov chain on exponentially distributed data of system components can limit their widespread industrial applications. In this paper, we propose a hybrid modularisation scheme where independent sub-trees of a DFT are identified and quantified in a hierarchical order. A hybrid framework with the combination of algebraic solution, Petri Nets, and Monte Carlo simulation is used to increase the efficiency of the solution. The proposed approach uses the advantages of each existing approach in the right place (independent module). We have experimented the proposed approach on five independent hypothetical and industrial examples in which the experiments show the capabilities of the proposed approach facing repeated basic events and non-exponential failure distributions. The proposed approach could provide an approximate solution to DFTs without unacceptable loss of accuracy. Moreover, the use of modularised or hierarchical Petri nets makes this approach more generally applicable by allowing quantitative evaluation of DFTs with a wide range of failure rate distributions for basic events of the tree.


Kabir, S., Aslansefat, K., Sorokos, I., Papadopoulos, Y., & Konur, S. (2020). A Hybrid Modular Approach for Dynamic Fault Tree Analysis. IEEE Access, 8, 97175-97188.

Journal Article Type Article
Acceptance Date Apr 1, 2020
Online Publication Date May 22, 2020
Publication Date 2020
Deposit Date Feb 17, 2021
Publicly Available Date Feb 17, 2021
Journal IEEE Access
Electronic ISSN 2169-3536
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 8
Pages 97175-97188
Keywords Reliability analysis; Fault tree analysis; Dynamic fault trees; Modularisation; Petri nets
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