Bayesian-based seismic risk assessment of shallow tunnels in soft soils

Abstract

Tunnels are critical infrastructure for the sustainable development of urban areas worldwide, especially for modern metropolises. It is important to evaluate the seismic performance of tunnel under a wide range of earthquake intensities. For this purpose, this study firstly illustrates a Bayesian-based framework for evaluation seismic risk of tunnels, in which the probability values of different fragility curves models are treated as random variables, characterized by their probability density functions was proposed in order to propagate inter-model variability in seismic risk assessments. Then the nominal values of seismic risk for the three main damage states, including minor, moderate and extensive were calculated. Moreover, the effects of the weighting of different fragility functions on the expected seismic risk assessments are discussed. The results show that Bayesian-based framework efficiently projects the whole variability of input models into risk estimations. The findings of this study can serve as the basis for decision-making, seismic risk, and resilience management of city infrastructure.