Resilience Models for Tunnel Recovery After Earthquakes

Tunnels are a crucial component of urban infrastructure, continuously exposed to various hazards, threats, and stressors. Events such as earthquakes, fires, and floods, along with aging and construction-related disturbances, pose significant challenges to tunnel resilience. Reliable fragility, restoration, and traffic reinstatement models are essential for assessing and quantifying resilience, as they allow infrastructure operators to prioritize maintenance and adapt to evolving threats in complex transportation systems. Although the vulnerability and fragility of tunnels have been widely researched over the last decade, studies focusing on tunnel restoration to quantify resilience remain scarce. This gap prevents operators from implementing proactive and reactive adaptation measures to ensure seamless tunnel functionality. To address this issue, this study presents a novel, fit-for-purpose, damage-level-dependent probabilistic approach for quantifying tunnel recovery. It introduces the first realistic, practice-led restoration models that enable resilience quantification in tunnels. To develop these models, a global expert survey was conducted to establish reinstatement (traffic capacity) and restoration (structural capacity) models tailored to tunnel resilience assessments. A detailed questionnaire was designed to gather expert input on required restoration tasks, their duration, sequencing, and cost. The survey focused primarily on damage induced by seismic events, incorporating idle times and traffic capacity gains over time. The results were then used to generate deterministic and probabilistic reinstatement and restoration models. The deterministic models are intended for practical applications, while the probabilistic models account for epistemic uncertainties and are presented in a reproducible format for further development across different hazards and applications. A case study is included to demonstrate the resilience assessment of a typical tunnel using the newly developed restoration models. The findings will help infrastructure operators and city planners to accurately assess tunnel resilience, enabling informed investment decisions.