Seismic retrofit screening of existing highway bridges with consideration of chloride-induced deterioration: A bayesian belief network model

Abstract

Seismically deficient bridges, coupled with their aging and deterioration, pose significant threat to safety, integrity, and functionality of highway networks. Given limited funds available for bridge retrofitting, there is a need for an effective management strategy that will enable decision-makers to identify and prioritize the high-risk bridges for detailed seismic evaluation and retrofit. In this paper, a risk-based preliminary seismic screening technique is proposed to rank or prioritize seismically-deficient bridges. The proposed risk assessment entails hierarchically integrating seismic hazard, bridge vulnerability, and consequences of failure. The bridge vulnerability accounts for chloride-induced corrosion deterioration mechanisms. A Bayesian belief network based modeling technique is used to aggregate through the hierarchy and generate risk indices. The efficacy of the proposed method is illustrated on two existing bridges that are assumed to be located in high seismic zones and designed under different standards concerning their structural safety under seismic loads and durability performance.