重车荷载下钢桥结构应力分布与疲劳损伤控制

STRUCTURAL STRESS DISTRIBUTION AND FATIGUE DAMAGE CONTROL OF STEEL BRIDGES UNDER HEAVY TRUCK LOADS

  • 摘要: 该文建立了基于实际车流数据的钢桥等效车辆荷载模型,通过有限元分析确定了移动轮载作用下钢桥焊接节点焊趾处正应力影响范围。采用结构应力指标,探讨了在实际车辆作用下钢桥面板的疲劳应力响应特征。结合线性疲劳损伤累积准则,分析了实际车流下钢桥焊接构件的疲劳损伤,并与我国规范疲劳车辆荷载III预测结果进行了对比。分析了运行车辆限重比例对疲劳寿命的影响,提出了钢桥疲劳荷载限值量化方法。研究发现:顶板焊趾处正应力影响面范围为纵向0.9 m,横向1.3 m;相较于我国规范中的疲劳车辆荷载III,所研究钢桥等效车辆荷载修正系数为0.41;当考虑车辆荷载横向分布时,最不利荷载引起的疲劳损伤占总损伤的78%;为获得100年预期服役寿命,所研究桥梁通行车辆须限重20.23%。该文建立的分析框架旨在为重车荷载作用下的钢桥疲劳损伤控制提供理论依据,亦可以为基于荷载监测的钢桥疲劳性能评估提供参考。

     

    Abstract: An equivalent vehicle loading model for steel bridges is established upon actual traffic data. The normal stress influence range at the weld toe of welded joints under moving wheel loads is determined through finite element analysis. The fatigue stress response characteristics of steel bridge decks under actual vehicle loads are explored using the structural stress index. Fatigue damage of welded components under real traffic conditions is analyzed using the linear fatigue damage cumulative criterion, and compared with the prediction value based on Fatigue Vehicle Load III in Chinese standards. The impact of vehicle weight limit ratios on fatigue life is examined, and a quantitative method for fatigue load limits is proposed. The study reveals that the normal stress influence range at the top plate weld toe extends longitudinally 0.9 m and transversely 1.3 m. Compared to the Fatigue Vehicle Load III in Chinese standards, the loading correction factor for the equivalent vehicle load on the studied steel bridge is 0.41. The most unfavourable load position accounts for 78% of total fatigue damage considering the transverse distribution of vehicle loads. To achieve a 100-year service life, the 20.23% vehicle weight for the studied bridge should be limited. The analytical framework established in this study aims to provide a theoretical basis for fatigue damage control of steel bridges under heavy traffic loads and may serve as a reference for fatigue performance evaluation of steel bridges based on loading monitoring data.

     

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