Risk‐Based Model for Post‐Earthquake Functional Recovery of Bridge Networks

Bridge networks are vital to urban transportation systems but remain vulnerable to earthquake‐induced disruptions. While prior studies have examined post‐earthquake recovery, most focused on individual bridges, which limits the insights that can only be gained from a network‐level assessment. Others used coarse modeling approaches that limit the resolution and relevance of performance outcomes. This study proposes a high‐resolution approach to assessing post‐earthquake functional recovery of bridge networks. The model integrates detailed bridge‐specific representations, component‐level fragilities, and empirical restoration data to enable granular regional‐scale analysis. This level of fidelity enables disaggregation of performance at the component, bridge, and network scales. It introduces a suite of recovery metrics that support both scenario‐based and stochastic event set‐based assessments, capturing both disaggregated (e.g., by component type or subregion) and aggregated (e.g., network‐level) performance outcomes. The framework is applied to the City of Los Angeles network, which has over one thousand bridges. Each bridge is assigned a unique exposure profile based on multiple sources of data and linked to a set of component‐level fragility functions. To highlight the applicability to resilience planning, various enhancement strategies are evaluated, including component retrofitting and post‐earthquake interventions.