A monitoring-based approach for evaluating dynamic responses of riding vehicle on long-span bridge under strong winds

摘要

Serviceability performances of the long span bridge during strong winds, including the safety and comfort condition of driving road vehicle on the bridge, have attracted more and more attention in recent years. The dynamic behavior of the riding vehicle is essential for serviceability performance assessment. The vehicle-bridge coupling (VBC) simulation, featured as time-consuming, is traditionally applied, however, cannot meet the requirement for timely decision. Therefore, a monitoring-based approach, with the hybrid combination of in-situ structural health monitoring (SHM) data and dynamic simulation of single vehicle model, is presented in this paper to estimate the vehicle dynamic responses in a more efficient way. A numerical case study of a quarter vehicle model riding on a simply supported beam bridge is presented to validate the proposed approach. The first step is to investigate the feasibility of reproducing structural responses with the data from limited sensors using interpolation methods. Subsequently, dynamic responses of the riding vehicle are estimated using the monitoring-based approach. The influences of random traffic and wind loads are also considered. The estimated vehicle responses generally match VBC-based results, which proves reliability of the monitoring-based approach. Furthermore, the SHM data of a long-span bridge are utilized to investigate the potential usage of the proposed method. In particular, the dynamic responses of a popular light truck on the bridge and rigid road are respectively estimated and compared with each other. Results show that, among all the factors, i.e., bridge vibration, wind loads, and road roughness, the bridge vibration contributes the majority to the vertical vibration of the vehicle. For the lateral and torsional vibration of the vehicle, wind forces and bridge vibration are dominant factors. To summarize, the monitoring-based approach could help to estimate the dynamic responses of the riding vehicle on the bridge with a good reliability, regardless of the operation condition of the bridge, and provide timely and reliable information for serviceability and safety assessment.