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Fatigue damage prognosis of steel bridges under traffic loading using a time-based crack growth method

机译:利用基于时间的裂缝生长方法,交通负荷钢结构疲劳损伤预后

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摘要

Traditionally, the fatigue damage assessment of steel bridges is conducted using cycle-based methods. Cyclebased methods require stress time history be transformed to cycle history first before fatigue analysis can be performed. However, well-defined cycle history does not exist for the traffic-induced stress time history of bridges as it contains numerous large and small cycles with random stress ranges embedded together. To address this inherent difficulty, a time-based fatigue crack growth (FCG) model is proposed for fatigue damage prognosis of steel bridges under traffic loading. The time-based FCG method describes the crack growth in the time domain through a crack growth kinetics function derived based on the physical mechanism of fatigue crack propagation. To demonstrate the proposed method, numerical simulations are first performed using full-scale coupled vehiclebridge interaction framework to generate stress time histories of a typical steel bridge under traffic loading. Then, FCG analysis is performed using the time-based method and the effects of road surface roughness and vehicle weight on the FCG are studied. Finally, a case study on the I-10 Twin Span Bridge is presented to demonstrate the time-based FCG method for fatigue damage prognosis using in situ monitoring data. The results show that the proposed method can be used to directly predict the FCG of steel bridges in the time domain using stress time histories obtained either from stress analysis or in situ monitoring.
机译:传统上,使用基于循环的方法进行钢结构的疲劳损伤评估。在执行疲劳分析之前,循环方法需要将应力时间历史转换为循环历史。然而,由于桥梁的交通诱导的应力时间历史,因此不存在明确定义的循环历史,因为它包含许多大而小的周期,其中嵌入在一起随机应力范围。为了解决这种固有的难度,提出了一种基于时间的疲劳裂纹生长(FCG)模型,用于交通负荷下钢结构的疲劳损伤预后。基于时间的FCG方法描述了通过基于疲劳裂纹繁殖的物理机制导出的裂缝生长动力学函数的时域的裂缝生长。为了展示所提出的方法,首先使用满量程耦合的车辆桥接交互框架进行数值模拟,以在交通负荷下产生典型钢桥的应力时间历史。然后,使用基于时间的方法进行FCG分析,研究了路面粗糙度和车辆重量在FCG上的影响。最后,提出了对I-10双跨度桥的案例研究,以展示使用原位监测数据使用疲劳损伤预后的时间的FCG方法。结果表明,该方法可用于使用从应力分析或原位监测中获得的应力时间历史直接在时域中预测钢结构的FCG。

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