Abstract

This study introduces a novel multivariate stochastic process simulation algorithm to generate fluctuating wind velocity time histories of the vehicle–bridge united system. The Kaimal spectrum and wind spectrum relative to a moving point were applied to the bridge and the vehicle (train) in operation, respectively. The wind time series of the vehicle–bridge united system were generated simultaneously by considering the correlation between the moving point fixed on a vehicle in operation and the static points on a bridge. This algorithm is of high computational efficiency, as it takes advantage of explicit decomposition for the coherence function matrix and frequency truncation method. Based on an error estimation, this simulation method is proven to be accurate. Numerical examples of a vehicle running on a simply supported continuous beam bridge with the speeds of 20, 40, 60 and 80 m/s were performed. The result shows that the auto-/cross-correlation functions and auto-spectrum of the simulated wind samples are in good agreement with the targets. The proposed method can facilitate the analysis of wind–vehicle–bridge aerodynamic response with high efficiency and accuracy, and avoids the discontinuity problem of wind time history of the moving point.

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