View/ Open
Kabir_et_al_IEEE_Access_Final.pdf (1.339Mb)
Download
Publication date
2020-05Rights
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/Peer-Reviewed
YesAccepted for publication
2020-05-14
Metadata
Show full item recordAbstract
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.Version
Published versionCitation
Kabir S, Aslansefat K, Sorokos I et al (2020) A hybrid modular approach for dynamic fault tree analysis. IEEE Access. 8: 97175-97188.Link to Version of Record
https://doi.org/10.1109/ACCESS.2020.2996643Type
Articleae974a485f413a2113503eed53cd6c53
https://doi.org/10.1109/ACCESS.2020.2996643