4.5 Article

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

期刊

GEOMECHANICS AND ENGINEERING
卷 30, 期 3, 页码 273-280

出版社

TECHNO-PRESS
DOI: 10.12989/gae.2022.30.3.273

关键词

ground building; neural network; vibration induced by subway operation; Z-vibration

资金

  1. National Natural Science Foundations of China [41877239, 51379112, 51422904, 41772298]
  2. State Key Development Program for Basic Research of China [2013CB036002]
  3. Fundamental Research Funds of Shandong University [2018JC044]
  4. Shandong Provincial Natural Science Foundation [JQ201513]

向作者/读者索取更多资源

In this study, a back-propagation neural network model based on ANSYS numerical simulation results was established to analyze and calculate the vertical Z-vibration level of ground buildings in the New Capital area of Qingdao Metro phase I Project. The research results have good reference and guiding significance for predicting vibration caused by subway operation.
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.

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