Numerical Simulation of Long-Span Bridge Response under Downburst: Parameter Optimization Using a Surrogate Model

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.

Automated summary

Long-span bridges in thunderstorm-prone areas were simulated to study the impact of downburst transient winds. A parameter optimization method and a surrogate model were used to improve the simulation accuracy. The nonstationary turbulent downburst wind was obtained through the combination of Hilbert-based nonstationary fluctuations and CFD-based time-varying trend. The dynamic response of a long-span bridge subjected to the moving downburst was presented, validating the optimized downburst wind field and emphasizing its significant influence on the bridge's aerodynamics and buffeting response.