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A train-bridge system crossing a sea can be subjected to extreme environmental conditions such as the concomitant actions of wind and waves, which adversely affect the entire system. This study proposes an approach to evaluate the train-bridge interaction under wind and wave actions. The wind and wave parameters are collected using structural health monitoring (SHM), then correlated using copula models. The wind-bridge, wind-train, and wave-bridge interactions are solved using a real-time co-simulation (RTCS) solution. Besides, this paper introduces a surrogate model named the Fourier regression model (FRM) and Generalized cross-validation (GCV) algorithm to substitute further RTCS calculations. The best solution is obtained by searching for the optimal K value using the GCV algorithm. The results indicate that the dynamic indices of the system are more sensitive when the wind-wave coupling action is considered than when only the wind load is applied. Moreover, the bridge responses for 100 years return period are about 5%∼50% greater than that of 50 years and 25 years return periods. The train responses increase by 7%∼16% compared to the 50 years and 25 years return periods.

Fourier regression model predicting train-bridge interactions under wind and wave actions