School of Civil Engineering & Transportation, South China University of Technology, Guangzhou, Guangdong, China.
College of Civil Engineering, Guangzhou University, Guangzhou, Guangdong, China.
Math Biosci Eng. 2019 Jun 18;16(5):5652-5671. doi: 10.3934/mbe.2019281.
Deflection is a crucial indicator to reflect the operating condition of girder bridges, which can be used to evaluate structure condition and identify abnormal loading. The paper analyzed the deflection characteristics of long-span girder bridges based on the coupling vibration between stochastic traffic stream and bridge. First, the latest research advances were integrated to form an analytical model of the coupling vibration between stochastic traffic stream and bridge. Then, a generalized Pareto distribution model based on peaks-over-threshold theory was established to predict the extreme girder deflection. Next, a cellular automaton based microsimulation method was proposed to model the traffic loads on bridges, which utilized the intelligent driver car-following model and acceptance distance based lane-changing model. Finally, these theories were applied in the case study of a long-span prestressed concrete continuous girder bridge. It is discovered from the study that, under the coupling vibration between stochastic traffic stream and bridge, the predicted extreme deflection of the case bridge is far lower than the specified design value. Hence, a grading warning model was established and employed to the analysis of deflection monitoring data of the bridge, showing a wide potential prospect of application.
挠度是反映梁桥运行状况的一个重要指标，可用于评估结构状况和识别异常荷载。本文基于随机交通流与桥梁的耦合振动，分析了大跨度梁桥的挠度特性。首先，综合最新研究进展，建立了随机交通流与桥梁耦合振动的分析模型。然后，建立了基于峰超越阈值理论的广义帕累托分布模型，预测极端梁挠度。接着，提出了一种基于元胞自动机的微观模拟方法来模拟桥梁上的交通荷载，该方法利用智能驾驶员跟驰模型和基于接受距离的变道模型。最后，将这些理论应用于一座大跨度预应力混凝土连续梁桥的实例研究中。研究发现，在随机交通流与桥梁的耦合振动下，实例桥梁的预测极端挠度远低于规定的设计值。因此，建立了分级预警模型，并将其应用于桥梁挠度监测数据的分析，显示出广泛的应用前景。
