Probabilistic fragility and resilience assessment and sensitivity analysis of bridges incorporating aftershock effects

Abstract

This paper discusses a computationally efficient methodology for probabilistic fragility and resilience analysis of bridges explicitly incorporating the effects of aftershock seismic events, based on nonlinear time history analysis, stochastic simulation and kriging surrogate modeling. Aftershock fragilities dependent on mainshock-induced damage states are developed and used in conjunction with restoration models for estimating bridge functionality and resilience. The input parameter space for the surrogate models consists of uncertain hazard and structural parameters and deterministic structural/geometrical bridge parameters, leading to probabilistic estimates of bridge performance metrics (i.e., fragility, functionality, resilience). Kriging surrogate modeling is used for estimating these metrics, facilitating efficient adoption of these complex structural and probability models. Relative importance of the predictive parameters is quantified by extending and integrating a probabilistic sensitivity analysis into the proposed framework. An illustrative example of the proposed framework is demonstrated through fragility and resilience assessment of a typical bridge in California subjected to mainshock and aftershock.