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A numerical simulation method for a repairable dynamic fault tree
Xueli Li 3,4
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State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment, China Nuclear Power Engineering Co., Ltd., Shenzhen 518172, China
School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Key Laboratory of Neutronics and Radiation Safety, Institute of Nuclear Energy Safety Technology, HFIPS, Chinese Academy of Sciences, Hefei, Anhui 230031, China
University of Science and Technology of China, Hefei, Anhui 230026, China
Publication date: 2021-03-31
Eksploatacja i Niezawodność – Maintenance and Reliability 2021;23(1):34–41
  • The adapted sequential failure region is developed to characterize the failure mechanism of a minimal cut sequence.
  • The proposed approach is applicable for nonexponential distribution situations.
  • The proposed approach is more efficient than the Markov chain state space methods.
Dynamic fault trees are important tools for modeling systems with sequence failure behaviors. The Markov chain state space method is the only analytical approach for a repairable dynamic fault tree (DFT). However, this method suffers from state space explosion, and is not suitable for analyzing a large scale repairable DFT. Furthermore, the Markov chain state space method requires the components’ time-to-failure to follow exponential distributions, which limits its application. In this study, motivated to efficiently analyze a repairable DFT, a Monte Carlo simulation method based on the coupling of minimal cut sequence set (MCSS) and its sequential failure region (SFR) is proposed. To validate the proposed method, a numerical case was studied. The results demonstrated that our proposed approach was more efficient than other methods and applicable for repairable DFTs with arbitrary time-to-failure distributed components. In contrast to the Markov chain state space method, the proposed method is straightforward, simple and efficient.
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