Bridge infrastructure resilience assessment against seismic hazard using Bayesian best worst method

The transportation agencies are experiencing numerous challenges in endorsing resilient bridge infrastructure against natural disasters such as earthquakes, floods, and hurricanes. Therefore, assessing bridge infrastructure resiliency against a seismic hazard is critical to improve the bridge's endurance and effective recovery. In this study, assessment of bridge infrastructure resilience against the seismic hazard is performed using Bayesian best-worst method (BWM). Based on a literature review, 15 resilience parameters were identified for bridge infrastructure resiliency against seismic hazard under two primary aspects, namely reliability and recovery. The Bayesian BWM was used to calculate the weight of the seismic resilience variables based on the experts' judgment. Finally, a bridge resiliency index was developed to determine the weights of the parameters. To demonstrate the applicability of the proposed model, the infrastructure resiliency against the seismic hazard of a bridge located in Vancouver Island, British Columbia, Canada is assessed using two sets of data from two different sources. It is mentionable that the resiliency index was close for both of the data sets. The outcome of this study is that the model for determining bridge resiliency index will assist the bridge engineer and policymakers make effective decisions in the face of future seismic danger.