- CSCD核心中文核心科技核心
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(1. 中铁第一勘察设计院集团有限公司， 陕西 西安 710043; 2. 西安理工大学土木建筑工程学院， 陕西 西安 710048; 3. 长安大学公路学院， 陕西 西安 710064)
网络出版日期: 2023-03-24
Inversion Analysis of Influence of Proximity Construction on Metro Structure Based on Back Propagation Neural Network
(1. China Railway First Survey and Design Institute Group Co., Ltd., Xi′an 710043, Shaanxi, China; 2. School of Civil Engineering and Architecture, Xi′an University of Technology, Xi′an 710048, Shaanxi, China; 3. School of Highway, Chang′an University, Xi′an 710064, Shaanxi, China)
Online published: 2023-03-24
王立新 , 王强 , 钟宇健 , 徐硕硕 , 邱军领 , 赖金星 , 汪珂 . 基于BP神经网络的近接施工对地铁结构影响反演分析[J]. 隧道建设, 2022 , 42(S2) : 102 -113 . DOI: 10.3973/j.issn.2096-4498.2022.S2.013
To investigate the value of soil mechanics parameters in the numerical simulation of underground engineering and the influence of pipe jacking construction on the metro structure, a case study is conducted on a pipe jacking construction spanning a metro tunnel in Xi′an, China. Base on the monitoring data of the local construction section, the designed and constructed back propagation(BP) neural network is employed to inversely calculate the physicomechanical parameters of soils, and the parameters are input into the model constructed by MIDAS GTS NX finite element software. After the project is completed, the actual value of the tunnel structure deformation measurement is obtained, the predicted value of the crown settlement and the arch waist horizontal convergence of the corresponding sections in the numerical simulation is extracted, and the accuracy of the finite element analysis and the rationality of the parameter inversion method are validated by comparing the difference between the two. The results show that the error between the predicted and the actual values is small, the deformation values are 2.6 mm and 0.5 mm respectively, and the error values are 0.24 mm and 0.07 mm respectively at the maximum crown settlement of the tunnel and the peripheral convergence section, indicating that the deformation of the tunnel structure is less affected when the pipe jacking construction is close to the metro tunnel. The inversion of the physicomechanical parameters of the soil layer based on the BP neural network is more reasonable, and the prediction of the deformation is more accurate, which can provide a reference for the construction and optimization design of the later tunnel engineering.
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