Failure Evaluation of Bridge Deck Based on Parallel Connection Bayesian Network: Analytical Model

Failure is a major element that causes deterioration, which in turn affects the serviceability of long span bridges. Currently, the Bayesian network, which relates to probability statistics, is widely used for evaluating fatigue failure reliability. In particular, Bayesian network can not only calculate the fatigue failure at the system level, but also deduce the fatigue failure at the weld level. In this study, a system-level fatigue reliability evaluation model of a bridge deck (BD), which is seen as a parallel system, is proposed based on the Bayesian network. A fatigue probability reliability model of the BD was derived using the master S-N curve. In addition, the Monte Carlo (MC) method was applied to solve the multi-dimensional and complex analytical expressions in the Bayesian network. The applicability of the proposed model was demonstrated by three numerical case studies.