A Framework for Resilient Urban Bridge Network Design under Disruptions

Thesis Abstract

This study addresses the increasing vulnerability of urban bridge networks to disruptions arising from natural hazards, aging infrastructure, and operational contingencies, and develops a framework for resilient design that integrates robustness, redundancy, and recovery dynamics into network-level decision making. The aim is to formulate a theory-driven framework that guides engineers and planners in assessing disruption risks, optimizing bridge network configurations, and prioritizing retrofit and maintenance strategies to minimize system-wide performance losses. Specific objectives include (1) identifying key resilience performance indicators for urban bridge networks, (2) developing a network-analytic model that links single-bridge reliability with citywide accessibility and mobility, (3) integrating probabilistic hazard risk, traffic demand, and repair time distributions into a unified optimization framework, (4) proposing a decision-support tool that prescribes retrofit prioritization under budget constraints, and (5) validating the framework through an empirical case-study of a representative metropolitan corridor comprising 42 interconnected bridges and 15 alternative routing pathways. Methodologically, the research adopts a mixed-methods design grounded in resilience theory and network science. The population comprises metropolitan bridge networks in large urban areas with documented disruption events; a purposive sample of 42 bridges on a metropolitan corridor is analyzed alongside 15 alternative routes. Data collection instruments include structural performance records, inspection and condition indices, historical disruption logs, traffic counts from the national transport authority, and repair duration estimates from municipal maintenance departments. Survey instruments are employed to capture expert judgments on prioritization criteria, supplemented by semi-structured interviews with 12 domain specialists in structural engineering, transportation planning, and disaster risk management. Validity and reliability are established through triangulation of structural data, traffic-flow simulations, and expert consensus elicitation using the Delphi method. The analytical framework combines network reliability analysis, probabilistic hazard modelling, and multi-criteria optimization. Structural reliability for individual bridges is modeled via a probabilistic risk assessment (PRA) approach, incorporating fragility curves, hazard intensity, and seasonality. The network-level performance is quantified using a multi-state connectivity metric and a resilience index that aggregates robustness, redundancy, and recoverability over a 20-year planning horizon. Regression analyses quantify relationships between bridge condition, load-carrying capacity, and network performance under simulated disruption scenarios. A mixed-integer linear programming (MILP) formulation optimizes retrofit allocation and maintenance scheduling subject to a capital budget, while a stochastic simulation framework (Monte Carlo) assesses system-level resilience across 1,000 iterations to capture uncertainty in hazard occurrence and repair times. The theoretical underpinning integrates the Resilience Theory of Complex Systems and Network Science, with explicit reference to the Theory of Critical Infrastructure Interdependencies and the Conceptual Model of Urban Mobility Resilience. Key expected findings include (i) quantification of how targeted improvements to a subset of bridges yield disproportionate gains in network resilience, (ii) identification of critical bridges whose failure most severely degrades accessibility, (iii) delineation of optimal retrofit sequences under varying budget scenarios, and (iv) demonstration of the framework’s ability to maintain acceptable levels of service (LOS) during and after disruptions. The study anticipates that incorporating redundancy and rapid repair pathways substantially reduces system-wide travel time penalties and preserves essential service corridors. The contribution to knowledge lies in delivering a theoretically grounded, practically applicable framework that integrates network reliability, hazard risk, and economic optimization to guide resilience-enhancing interventions for urban bridge networks. The main conclusion posits that resilience emerges from strategically diversified connectivity and proactive maintenance, rather than solely from fortifying the most critical single elements. Recommendations include adopting the proposed decision-support tool within metropolitan planning processes, establishing data-sharing protocols for hazard and repair information, and iterating the framework with real-time monitoring to enable adaptive management. Further research is suggested to extend the model to multi-modal networks, incorporate climate-change projections, and explore participatory governance mechanisms for resilience investments.