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使用离心机模型评估桥梁固有频率作为冲刷指标。

Assessment of bridge natural frequency as an indicator of scour using centrifuge modelling.

作者信息

Kariyawasam Kasun D, Middleton Campbell R, Madabhushi Gopal, Haigh Stuart K, Talbot James P

机构信息

Department of Engineering, University of Cambridge, Cambridge, UK.

出版信息

J Civ Struct Health Monit. 2020;10(5):861-881. doi: 10.1007/s13349-020-00420-5. Epub 2020 Jul 18.

DOI:10.1007/s13349-020-00420-5
PMID:33442503
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7784483/
Abstract

One of the most prevalent causes of bridge failure around the world is "scour"-the gradual erosion of soil around a bridge foundation due to fast-flowing water. A reliable technique for monitoring scour would help bridge engineers take timely countermeasures to safeguard against failure. Although vibration-based techniques for monitoring structural damage have had limited success, primarily due to insufficient sensitivity, these have tended to focus on the detection of local damage. High natural frequency sensitivity has recently been reported for scour damage. Previous experiments to investigate this have been limited as a result of the cost of full-scale testing and the fact that scaled-down soil-structure models tested outside a centrifuge do not adequately simulate full-scale behaviour. This paper describes the development of what is believed to be the first-ever centrifuge-testing programme to establish the sensitivity of bridge natural frequency to scour. A 1/60 scale model of a two-span integral bridge with 15 m spans was tested at varying levels of scour. For the fundamental mode of vibration, these tests found up to a 40% variation in natural frequency for 30% loss of embedment. Models of three other types of foundation, which represent a shallow pad foundation, a deep pile bent and a deep monopile, were also tested in the centrifuge at different scour levels. The shallow foundation model showed lower frequency sensitivity to scour than the deep foundation models. Another important finding is that the frequency sensitivity to "global scour" is slightly higher than the sensitivity to "local scour", for all foundation types. The level of frequency sensitivity (3.1-44% per scour depth equivalent to 30% of embedment of scour) detected in this experiment demonstrates the potential for using natural frequency as an indicator of both local and global scour of bridges, particularly those with deep foundations.

摘要

全球桥梁失效最普遍的原因之一是“冲刷”——由于水流湍急,桥梁基础周围的土壤逐渐被侵蚀。一种可靠的冲刷监测技术将有助于桥梁工程师及时采取对策以防止桥梁失效。尽管基于振动的结构损伤监测技术取得的成功有限,主要是因为灵敏度不足,但这些技术往往侧重于局部损伤的检测。最近有报道称冲刷损伤具有较高的固有频率灵敏度。由于全尺寸测试成本高昂,且在离心机外测试的缩尺土壤-结构模型无法充分模拟全尺寸行为,以往对此进行研究的实验受到了限制。本文描述了首个离心机测试项目的开展情况,该项目旨在确定桥梁固有频率对冲刷的灵敏度。对一座两跨连续桥进行了1/60比例模型测试,其跨度为15米,测试了不同冲刷程度下的情况。对于基本振动模式,这些测试发现,当埋入深度损失30%时,固有频率变化高达40%。还在离心机中对其他三种类型基础的模型进行了不同冲刷程度的测试,这三种基础分别代表浅垫板基础、深桩排架和深单桩。浅基础模型对冲刷的频率灵敏度低于深基础模型。另一个重要发现是,对于所有基础类型,对“整体冲刷”的频率灵敏度略高于对“局部冲刷”的灵敏度。本次实验检测到的频率灵敏度水平(每冲刷深度相当于埋入深度的30%时为3.1 - 44%)表明,固有频率有潜力作为桥梁局部和整体冲刷的指标,特别是对于那些深基础桥梁。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/74e3b3b638ff/13349_2020_420_Fig19_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/e9eb3adc469f/13349_2020_420_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/da0e37144f46/13349_2020_420_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/22c4f1a2bde5/13349_2020_420_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/cd0f4dee830a/13349_2020_420_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/09d65336601d/13349_2020_420_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/411af85e2074/13349_2020_420_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/ddf0aaf47042/13349_2020_420_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/be9f71537310/13349_2020_420_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/62f6ac35dc29/13349_2020_420_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/9ce46460a696/13349_2020_420_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/4059e619c34a/13349_2020_420_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/fd7c276f93d8/13349_2020_420_Fig17_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/d4ab8845fe9f/13349_2020_420_Fig18_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ede1/7784483/74e3b3b638ff/13349_2020_420_Fig19_HTML.jpg

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