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<p>This study examines the impact of the flow disruption coupling effect between bridge towers and railings on the bridge deck’s flow field and the aerodynamic stability of vehicles. The wind field distribution pattern of the bridge was determined through particle image velocimetry (PIV) experiments and computational fluid dynamics (CFD) simulations. The transverse controller is designed based on the radial basis neural network with the sliding mode control method (RBF-SMC). Finally, the aerodynamic stability of traffic on the bridge is evaluated by incorporating the two-way coupling method. Results indicate: Bridge deck railing disturbance reduces the high-speed wind zones significantly. Higher equivalent wind speeds occur in Lane 3 (windward) and Lane 6 (leeward), with Lane 6 posing the highest vehicle risk. The RBF-SMC controller achieves excellent anti-interference: peak lateral displacements in Lanes 3 and 6 decrease by over 96% versus uncontrolled cases, dramatically improving stability.</p>

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Vehicle lateral control and stability analysis under the disturbed flow coupling effect in the crosswind region of a bridge tower

  • 期刊论文

  • 发表日期：

    2025年10月24日

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  • Zhiqun Yuan,
  • Diansheng Huo,
  • Yanqiang Chen,
  • Dandan Xia,
  • Huaifeng Wang,
  • Li Lin

摘要

This study examines the impact of the flow disruption coupling effect between bridge towers and railings on the bridge deck’s flow field and the aerodynamic stability of vehicles. The wind field distribution pattern of the bridge was determined through particle image velocimetry (PIV) experiments and computational fluid dynamics (CFD) simulations. The transverse controller is designed based on the radial basis neural network with the sliding mode control method (RBF-SMC). Finally, the aerodynamic stability of traffic on the bridge is evaluated by incorporating the two-way coupling method. Results indicate: Bridge deck railing disturbance reduces the high-speed wind zones significantly. Higher equivalent wind speeds occur in Lane 3 (windward) and Lane 6 (leeward), with Lane 6 posing the highest vehicle risk. The RBF-SMC controller achieves excellent anti-interference: peak lateral displacements in Lanes 3 and 6 decrease by over 96% versus uncontrolled cases, dramatically improving stability.