A Stochastic Approach for the Analysis of Dynamic Fault Trees With Spare Gates Under Probabilistic Common Cause Failures


A redundant system typically consists of primary and standby modules. The therefore-referred to as spare gate is extensively used to model the dynamic behavior of redundant systems in the applying of dynamic fault trees (DFTs). Many methodologies have been proposed to judge the reliability of DFTs containing spare gates by computing the failure likelihood. However, either a complicated analysis or vital simulation time are sometimes needed by such an approach. Moreover, it's difficult to compute the failure chance of a system with part failures that are not exponentially distributed. Additionally, probabilistic common cause failures (PCCFs) have been widely reported, sometimes occurring during a statistically dependent manner. Failure to account for the result of PCCFs overestimates the reliability of a DFT. In this paper, stochastic computational models are proposed for an economical analysis of spare gates and PCCFs in a very DFT. Using these models, a DFT with spare gates under PCCFs will be efficiently evaluated. In the proposed stochastic approach, a symbol likelihood is encoded as a non-Bernoulli sequence of random permutations of mounted numbers of ones and zeros. The component's failure chance isn't limited to an exponential distribution, thus this approach is applicable to a DFT analysis in an exceedingly general case. Several case studies are evaluated to point out the accuracy and efficiency of the proposed approach, compared to both an analytical approach and Monte Carlo (MC) simulation.

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