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Dynamic structural health monitoring for concrete gravity dams based on the Bayesian inference
Journal of Civil Structural Health Monitoring ( IF 3.6 ) Pub Date : 2020-02-04 , DOI: 10.1007/s13349-020-00380-w
Giacomo Sevieri , Anna De Falco

The preservation of concrete dams is a key issue for researchers and practitioners in dam engineering because of the important role played by these infrastructures in the sustainability of our society. Since most of existing concrete dams were designed without considering their dynamic behaviour, monitoring their structural health is fundamental in achieving proper safety levels. Structural Health Monitoring systems based on ambient vibrations are thus crucial. However, the high computational burden related to numerical models and the numerous uncertainties affecting the results have so far prevented structural health monitoring systems for concrete dams from being developed. This study presents a framework for the dynamic structural health monitoring of concrete gravity dams in the Bayesian setting. The proposed approach has a relatively low computational burden, and detects damage and reduces uncertainties in predicting the structural behaviour of dams, thus improving the reliability of the structural health monitoring system itself. The application of the proposed procedure to an Italian concrete gravity dam demonstrates its feasibility in real cases.

中文翻译:

基于贝叶斯推理的混凝土重力坝动态结构健康监测

混凝土大坝的保护是大坝工程研究人员和从业人员的关键问题,因为这些基础设施在我们社会的可持续发展中发挥着重要作用。由于大多数现有的混凝土大坝在设计时都没有考虑其动态性能,因此监测其结构健康状况对于达到适当的安全水平至关重要。因此,基于环境振动的结构健康监测系统至关重要。但是,与数值模型有关的高计算负担和影响结果的众多不确定因素迄今阻碍了混凝土大坝结构健康监测系统的开发。这项研究为贝叶斯环境下混凝土重力坝的动态结构健康监测提供了框架。所提出的方法具有相对较低的计算负担,并且可以检测损坏并减少预测大坝结构行为的不确定性,从而提高了结构健康监测系统本身的可靠性。拟议程序在意大利混凝土重力坝上的应用证明了其在实际案例中的可行性。
更新日期:2020-02-04
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