Geomechanics and Engineering

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Vertical Z-vibration prediction model of ground building induced by subway operation

  • Zhou, Binghua (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • Xue, Yiguo (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • Zhang, Jun (Qingdao Metro Group Co. Ltd.) ;
  • Zhang, Dunfu (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • Huang, Jian (Qingdao Metro Group Co. Ltd.) ;
  • Qiu, Daohong (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • Yang, Lin (Qingdao Metro Group Co. Ltd.) ;
  • Zhang, Kai (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • Cui, Jiuhua (Geotechnical and Structural Engineering Research Center, Shandong University)
  • Received : 2020.08.07
  • Accepted : 2022.07.12
  • Published : 2022.08.10
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Abstract

A certain amount of random vibration excitation to subway track is caused by subway operation. This excitation is transmitted through track foundation, tunnel, soil medium, and ground building to the ground and ground structure, causing vibration. The vibration affects ground building. In this study, the results of ANSYS numerical simulation was used to establish back-propagation (BP) neural network model. Moreover, a back-propagation neural network model consisting of five input neurons, one hidden layer, 11 hidden-layer neurons, and three output neurons was used to analyze and calculate the vertical Z-vibration level of New Capital's ground buildings of Qingdao Metro phase I Project (Line M3). The Z-vibration level under different working conditions was calculated from monolithic roadbed, steel-spring floating slab roadbed, and rubber-pad floating slab roadbed under the working condition of center point of 0-100 m. The steel-spring floating slab roadbed was used in the New Capital area to monitor the subway operation vibration in this area. Comparing the monitoring and prediction results, it was found that the prediction results have a good linear relationship with lower error. The research results have good reference and guiding significance for predicting vibration caused by subway operation.

Keywords

Acknowledgement

Much of the work presented in this paper was supported by the National Natural Science Foundations of China (grant numbers 41877239, 51379112, 51422904 and 41772298), and the State Key Development Program for Basic Research of China (grant number 2013CB036002), and the Fundamental Research Funds of Shandong University (grant number 2018JC044), and Shandong Provincial Natural Science Foundation (grant number JQ201513). The authors would like to express appreciation to the reviewers for their valuable comments and suggestions that helped improve the quality of our paper.

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