Co-simulation reveals dynamic interactions in vehicle–bridge systems, highlighting safety and performance issues related to cable forces.
High-pier partially cable-stayed bridges, with their significant pier heights and relatively low structural stiffness and stability, experience pronounced vehicle–bridge coupling effects during vehicle transit, influencing their dynamic response and safety. This study developed a co-simulation analysis program using easy language and ANSYS to investigate the dynamic behavior of a prestressed concrete five-tower partially cable-stayed bridge under vehicle–bridge interaction, considering factors such as vehicle speed, bridge deck grade, and cable force. The research findings indicate that a reduction in bridge deck grade leads to increases in peak dynamic responses and impact factors, with the dynamic amplification factor showing a deteriorating trend across all cross-sections. Structural responses fluctuate with vehicle speed and exhibit sensitivity to speed variations, with the maximum response observed at a speed of 80 km/h. Adjusting cable forces can reduce the impact factor: a 5% change in cable tension causes the mid-span impact factor to drop sharply from 0.38 to 0.04, a substantial decrease of 89.5%. The structural system can exert an impact on the impact factor by as much as several times: while the dynamic displacement and bending moment of the fixed system are smaller than those of the continuous beam system, its impact factor is as high as 4.22 times that of the continuous beam system. Additionally, dynamic responses are closely related to the position of the fixed bearing, with responses near the fixed bearing being reduced. Notably, the maximum impact factors of critical sections all exceed the 0.05 limit specified in the code for this type of bridge, with values of 0.54 at the mid-span, 0.91 at the pier top, and 0.43 at the tower top anchor zone. This indicates that the provisions regarding dynamic amplification factors in the current code are inappropriate for such bridges. The difference in impact factors between bridge components can reach 2.12 times, this indicates that specific impact factors should be assigned to individual components to achieve an optimal balance between safety and economic performance.
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Wu et al. (2025) studied this question.
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