Assessing seismic induced traffic capacity loss of bridges considering both post-earthquake traffic control measures and vehicle passing speed
Year: 2025
Type: article
Abstract: Bridge seismic resilience is typically defined as the average functionality of a bridge over a specified period. However, in most existing studies, the post-earthquake functionality of bridges is assessed based on subjective judgment. The absence of objective, reliable functionality metrics has emerged as a critical limitation to advancing the development of bridge seismic resilience. In this paper, a new method of assessing post-earthquake traffic capacity of bridges by integrating the traffic control measures and the vehicle passing speed is proposed. Firstly, to more accurately analyse the impact of seismic damage on the number of open lanes on the bridge, a post-earthquake traffic load-carrying capacity analysis was conducted employing the limit state equation of the load-carrying capacity, with the post-earthquake assessed reliability as the benchmark. Secondly, by analysing the influence of seismic damage to expansion joints on the vertical vibration of vehicles and the impact of intensity of vibration on the vehicle speed, the method assesses the post-earthquake speed of vehicles crossing the bridge. Finally, via a numerical example of a 3-span continuous girder bridge, the effectiveness of the proposed method of evaluating bridge seismic traffic capacity loss is verified. Comparing with current studies of bridge seismic loss, most of which rely on empirical rules, the proposed method explicitly considers the influence of bridge components’ damage on traffic flow at a physical level. It provides a new highly practical and operable way of more accurately assessing seismic traffic loss of bridges.
Authors: Tianyi Li, Dongyu Zhang, Xiaoyu Zhang, Hui Li
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,900
Awards: G1089746461, G5344789382, G8605214048
OpenAlex ID: W4407673554
