An Efficient Approximate Markov Chain Method in Dynamic Fault Tree Analysis

Approximate Markov chain method for dynamic fault tree analysis is suggested for both reparable and non-reparable systems. The approximation is based on truncation, aggregation and elimination of Markov chain states during the process of dynamic fault tree transformation to corresponding Markov chain. The method is valid for small probabilities. For reparable systems, it is true if mean time to repair is much less than mean time to failure. Several examples are studied. Additional simplification is considered in case the system is in a steady state.