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Reliability and Remaining Life Assessment of Fatigue Critical Steel Structures: Integration of Inspection and Monitoring Information

机译:疲劳关键钢结构的可靠性和剩余寿命评估:检查和监测信息的整合

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The accurate prediction of the time-dependent damage level under uncertainty is an essential task in the management of fatigue critical steel structures. Structural health monitoring (SHM) and inspection actions can greatly improve the reliability of the prediction process. This is partly achieved by reducing the uncertainties associated with load estimates and actual structural responses. Additionally, SHM and inspections provide a deeper insight into the damage level at the time of application of such actions. This paper proposes a probabilistic approach for quantifying the reliability and the remaining service life of fatigue deteriorating steel bridges based on the information form SHM and inspection actions. The approach utilizes a probabilistic crack growth model which considers uncertainties associated with the damage propagation process and monitoring outcomes to find the remaining fatigue life and predict the lifetime reliability of the analyzed location. Future inspection actions are scheduled based on the predicted lifetime performance profiles. An updating process is employed to find the posterior model parameters based on the damage level quantified during inspections. Updated damage propagation and lifetime reliability profiles are established. The proposed method can support the decision making process and the life-cycle management under uncertainty. An existing fatigue critical detail of a steel bridge is used to illustrate the proposed approach.
机译:在不确定性下,对时间依赖性损害水平的准确预测是疲劳临界钢结构管理中的基本任务。结构健康监测(SHM)和检验动作可以大大提高预测过程的可靠性。这是通过减少与负载估计和实际结构反应相关的不确定性来部分实现的。此外,SHM和检查在应用此类行动时,对损害水平提供更深层次的洞察力。本文提出了一种概率的方法,用于量化疲劳劣化钢结构的可靠性和剩余使用寿命,基于信息形成SHM和检查动作。该方法利用概率裂纹生长模型,其考虑与损伤传播过程和监测结果相关的不确定性,以找​​到剩余的疲劳寿命并预测分析的位置的寿命可靠性。根据预测的寿命性能配置文件安排将来的检查操作。采用更新过程来基于检查期间量化的损坏级别来找到后模型参数。建立更新的损伤传播和终身可靠性配置文件。该方法可以支持不确定性下的决策过程和生命周期管理。钢桥的现有疲劳临界细节用于说明所提出的方法。

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