土工基础 ›› 2020, Vol. 34 ›› Issue (3): 385-390.

• 测试技术 • 上一篇    

太湖明挖隧道围护结构变形监测与参数智能反演

高德风1,周 傲2,冯亚腾2,王海啸1,夏文俊1   

  1. (1.江苏省交通工程建设局,南京 210004;2.中国科学院武汉岩土力学研究所,武汉 430071)
  • 收稿日期:2019-05-15 修回日期:2019-05-26 出版日期:2020-06-20 发布日期:2020-06-22
  • 作者简介:高德风(1973-),男,高级工程师,研究方向为路桥工程。

Deformation Monitoring and Back Analysis of Soil Parameters in the Cut and Cover Installation of Taihu Tunnel

GAO Defeng1, ZHOU Ao2, FENG Yateng2, WANG Haixiao1, XIA Wenjun1   

  1. (1.Jiangsu Provincial Transportation Engineering and Construction Bureau, Nanjing 210004;
    2.Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071)
  • Received:2019-05-15 Revised:2019-05-26 Online:2020-06-20 Published:2020-06-22

摘要: 获得准确的土体参数对软土工程的施工安全和工程质量意义重大,然而,软土具有特殊的工程性质,采用室内或原位试验都不可避免会对土体造成不同程度的扰动,从而影响土体参数的准确获取。反分析方法则可以通过现场大量监测数据的反向挖掘,能够有效的优化和补充原位测试和室内试验测得的参数。依托太湖明挖隧道临时大堤段深基坑工程,分析了基坑围护桩位移的监测数据,采用BP神经网络对该深基坑工程施工参数进行了动态反演,并论证了反演结果的合理性。结果表明,基于反演参数建立的计算模型,能够有效的模拟围护桩的变形位移,较好地吻合了实际监测结果,从而验证了参数反演分析方法的合理性。

关键词: 深基坑, 监测, BP神经网络, 参数反演

Abstract: It is of great significance to obtain appropriate soil parameters for efficient engineering design and safe construction in soft soils. However, different degrees of disturbance are inevitably induced in the soft soil samples in the sampling and test process due to the soft soil properties so that the accuracy of soil properties is affected. The back analysis of soil parameters from a large amount of construction monitoring data can effectively optimize and compensate the soil parameters obtained from the laboratory and in-situ testing. This paper presents the back-analysis results of soft soil parameters from the construction monitoring of a cut and cover tunnel in Taihu Lake by using the BP neurol network analysis method. The results indicates that, based on the back analysis obtained soil parameters, the deformation of the supporting structure could be accurately simulated and consistent with the monitored data.

Key words: Deep Excavations, Construction Instrumentation, BP Neural Network, Back Analysis Method

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