Optimized derivation of hazard-consistent seismic fragility curves using Bayesian approach and multiple stripe analysis

Abstract

This study presents a methodology to optimize the analytical derivation of seismic fragility curves of structures located at a given site. Hazard-consistent ground motions in a Multiple Stripe Analysis (MSA) framework are used for this task. The approach aims to reduce the high computational cost typically associated with conducting numerous nonlinear dynamic analyses especially on complex structural models, without compromising the accuracy of the results. The process begins by initializing the fragility parameters’ values from simplified analyses, which are then iteratively updated through a Bayesian approach that incorporates Markov Chain Monte Carlo and Metropolis–Hasting sampling, thereby drastically reducing the number of required analyses. Validation on both SDOF and MDOF structures across various damage states demonstrated convergence to benchmark results within a few iterations. An automated stopping criterion, based on prior and posterior comparison of the fragility parameters’ values, enhances the efficiency of the method. Sensitivity analysis shows that a smaller number of stripes each with fewer records than those utilized in conventional methods can yield stable results, significantly reducing computational demands. In addition, a user-friendly Python tool is provided to facilitate both the reproducibility of the presented results and the application of the proposed method to real-life cases.