To manage vortex-induced vibration (VIV) risks in long-span bridges under environmental uncertainty, this study proposes a probabilistic framework integrating data-driven risk assessment with reliability-based aerodynamic optimization. Using the Huangjuetuo Yangtze River Bridge in a complex mountainous environment as a case study, an Ali-Mikhail-Haq (AMH) copula model is developed from 20 years of meteorological records to characterize multivariate wind dependencies. This approach identifies a 23.34% theoretical probability of VIV occurrence. Subsequently, a probabilistic cost-benefit analysis (PCBA) framework is introduced to couple structural performance with economic decision-making, establishing a critical suppression efficiency threshold. Guided by this threshold, a surrogate-assisted intelligent system executes global aerodynamic optimization. The optimized configuration achieves suppression efficiencies of 65.76% and 60.52% at critical angles of attack (AOAs). By significantly exceeding the required economic threshold, the proposed strategy provides a robust safety margin against model deviations and uncertainties, ensuring the bridge’s life-cycle reliability and cost-effectiveness.
Li et al. (Thu,) studied this question.