Coupled Dynamic Analysis of the Vehicle-Bridge-Wind-Wave System

Slender bridges, often built in harsh coastal environments, may experience dynamic loadings from strong winds and high waves. Busy traffic is expected during normal operating conditions and during evacuation events before extreme weather or emergency-related conditions. Understanding the dynamics of the complex vehicle-bridge-wind-wave (VBWW) system is critical to the safety of both vehicles and bridges. For the present study, an analytical model was developed to evaluate the dynamic performance of the coupled VBWW system. First, the bridge was discretized using the FEM, and vehicles were modeled as mass-spring-damper systems to build the equations for the dynamic equilibrium. Then, the time histories of the wind and wave around the bridge site were simulated as stochastic random processes and generated using the spectral representation method. The dynamic system integrated the conventional buffeting analysis for the wind–bridge interaction, the quasi-static analysis for the wind–vehicle interaction, and the dynamic interaction between the moving vehicles and the bridge according to the geometric and mechanical relationships between the vehicle tires and the bridge deck. In addition, the interaction between the wave and bridge group-pile foundation was included in the system using the Morrison equation. Finally, for demonstration purposes, the dynamic responses of a coastal slender cable-stayed bridge under different vehicle-, wind-, and wave-loading scenarios were analyzed. The case study results indicated that the lateral vibration of the prototype bridge can increase by 13.6–82.4% for different components of the bridge under different lateral incident wave scenarios with varied wave heights and frequencies. The coupled VBWW results also indicated that wind load was the predominant dynamic response of both the vehicle and bridge with slight loading effects from the waves.


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  • Accession Number: 01675779
  • Record Type: Publication
  • Files: TRIS, ASCE
  • Created Date: Jun 4 2018 3:01PM