Prioritizing Bridge Rehabilitation Plans through Systemic Risk-Guided Classifications

Abstract

Although highway bridges are among the most critical components in transportation infrastructure systems, different jurisdictions typically allocate only limited annual budgets to address issues pertaining to aging and deteriorating bridges. In addition, most published studies have focused only on component-by-component risk analysis (i.e., risk of individual bridge failure/closure/becoming a safety hazard) to inform bridge rehabilitation project managers. However, the network-level cascade (systemic) impacts of an individual bridge(s) closure on the network-level are often dealt with through, for example, detouring, rather than a systemic-risk-guided strategy. In this respect, the current study first utilizes a complex network theoretic approach to quantify the topological characteristics of bridge networks and subsequently their network-level robustness and node vulnerability. These measures are then integrated into a multiscale (i.e., component and network) bridge classification platform guided by the systemic-risk consequences of possible bridge closure on the entire network. To demonstrate its application, the platform is operationalized in Canada on the Province of Ontario’s bridge network. It is found that component- and network-level measures are not correlated, which highlights the importance of considering the network-level measure to inform bridge rehabilitation decision making. The current study calls for a paradigm shift in the strategy guiding prioritizing bridge rehabilitation projects to account for the risk imparted by specific bridge criticality on the entire network, rather than solely on the individual bridge’s structural conditions.