The reliability and safety of bridge infrastructure are crucial for socio-economic development, yet bridges are increasingly subjected to complex dynamic loads, including blasts, heavy traffic, and environmental forces. This study presents a comprehensive numerical and mathematical fragility assessment framework that focuses on the cumulative fatigue damage caused by repeated non-linear loading events. Unlike traditional static or linear analyses, the proposed approach integrates non-linear material behavior and fatigue damage mechanisms within detailed finite element models of cable-stayed and suspension bridges, capturing progressive deterioration under realistic service conditions. By simulating repeated blast loads and cyclic traffic stresses, the research identifies critical vulnerabilities in bridge components such as cables, decks, and pylons, highlighting failure modes including cable loss, deck deformation, and pylon instability. Probabilistic fragility curves are developed to quantify the likelihood of different damage states as functions of load intensity and repetition, incorporating uncertainties in material properties and damage thresholds. Validation against case studies and sensitivity analyses ensure robustness and practical relevance. The study also underscores the need for multi-hazard fragility frameworks that consider simultaneous effects of fatigue, blast, seismic, and environmental loads to better reflect real-world complexities. Furthermore, the integration of real-time structural health monitoring data and machine learning techniques is proposed to enable dynamic, adaptive fragility assessments and predictive maintenance strategies. Findings contribute valuable insights for targeted reinforcement, improved design guidelines emphasizing structural redundancy, and enhanced safety standards. Overall, this research advances the understanding of fatigue-induced fragility in bridges under non-linear repeated loads, offering a scientific basis to develop more resilient and longer-lasting infrastructure capable of withstanding evolving dynamic threats.
Kumari et al. (Sat,) studied this question.