Long-span bridges located in thunderstorm-prone areas can potentially be struck by downburst transient winds. In this study, the downburst time-varying mean wind was simulated by an impinging jet model based on computational fluid dynamics (CFD). To make the simulation results fit well with the measurements, a parameter optimization method was developed. The objective function was established based on the errors between the simulated characteristic points and the target values from the measurement data. To increase the effectiveness, a Kriging surrogate model that was trained using data from numerical simulations was used. The parameter optimization method and the Kriging model were verified using five groups of test samples. The optimization efficiency was significantly increased by replacing the numerical model with a surrogate model during the optimization iteration. The simulation accuracy was clearly improved by the numerical modeling of a downburst based on optimized parameters. Subsequently, the nonstationary turbulent downburst wind was obtained by the combination of the Hilbert-based nonstationary fluctuations and the CFD-based time-varying trend. Finally, the dynamic response of a long-span bridge subjected to the moving downburst was presented. The results based on the simulation validate the optimized downburst wind field and highlight the significant influence on the bridge’s aerodynamics and buffeting response.

Long-span bridges in mountainous areas are usually exposed to nonstationary winds (e.g., thunderstorms), which pose a significant threat to the driving safety of vehicles. However, current analysis on the wind–vehicle–bridge interaction was mainly implemented based on the assumption of stationary wind input, which would lead to the distortion in the assessment of driving safety under nonstationary extreme wind events. In this study, a nonstationary wind–vehicle–bridge coupling analysis framework was found to investigate the dynamic response and driving safety under nonstationary events. Firstly, the Wavelet–Hilbert scheme was introduced to simulate the nonstationary wind velocity, and the two-dimension indicial function was employed to model the transient aerodynamic loads. Then, the nonstationary wind–vehicle–bridge coupling system was developed, and the separate iteration method was employed to obtain the response of the coupling system. Finally, the driving safety is evaluated based on statistical accident risk coefficients, derived from wheel contact forces. The results show that the vertical contact forces transference ratio, lateral contact forces, and vehicle accident risk coefficients under nonstationary winds are higher than those resulting from equivalent stationary winds. In addition, the accident risk coefficients increase with the transient wind velocity, duration, and vehicle velocity. In particular, the risk coefficient increases by approximately 201%, 36%, and 79%, respectively, with the increase in transient wind velocity, duration, and vehicle velocity.