Thermal-mechanical coupling behavior and fragility-based fire resilience assessment for highway tunnels

Highway tunnels face complex operational challenges, particularly under extreme disaster conditions such as fire. This study presents a strain-energy-based resilience framework that links fire-induced structural damage to functional recovery, integrating fragility curves, residual functionality, and recovery modeling into a unified probabilistic assessment. This study investigates the thermal-mechanical response and fire resilience of the Qinling Tiantai Mountain Highway Tunnel using an integrated FDS and ANSYS simulation approach. First, a tanker truck fire inside the tunnel is simulated with FDS to obtain the smoke temperature distribution under various combinations of ventilation velocities and fire locations, thereby identifying the most hazardous cross-section. The extracted temperature data from this section are then imported into an ANSYS model for thermal-mechanical coupling analysis, which enables the determination of the temperature and displacement fields in the tunnel lining. Taking the peak fire source temperature as the fire intensity indicator and the damage depth as the damage indicator, a probabilistic fire resistance demand model is established, and fragility curves under various peak fire source temperatures are constructed to obtain the failure probabilities for different damage states. Furthermore, based on the calculated strain energy per unit length, the post-fire remaining function of the tunnel is defined as the ratio of the strain energy under a given damage state to the damage limit energy. An exponential recovery function is then adopted to describe the functional recovery process. By integrating the fragility curves with the recovery function, the resilience index at different peak fire source temperatures is quantified, enabling a fire resilience analysis for highway tunnels. This study aims to elucidate the performance evolution of tunnel structures under high-temperature exposure and to develop a quantitative resilience assessment framework. The findings provide theoretical decision-making support and practical methodological guidance for tunnel fire protection design and post-fire recovery strategies.