Lateral Convergence Deformation Prediction of Subway Shield Tunnel Based on Kalman Model

Yan Bao, Yexin Zheng, Chao Tang, Xiaolin Meng (), Zhe Sun, Dongliang Zhang and Li Wang
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Yan Bao: The Key Laboratory of Urban Security and Disaster Engineering of China Ministry of Education, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing 100124, China
Yexin Zheng: The Key Laboratory of Urban Security and Disaster Engineering of China Ministry of Education, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing 100124, China
Chao Tang: Beijing Urban Construction Exploration & Surveying Design Research Institute Co., Ltd., Beijing 100101, China
Xiaolin Meng: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Zhe Sun: The Key Laboratory of Urban Security and Disaster Engineering of China Ministry of Education, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing 100124, China
Dongliang Zhang: The Key Laboratory of Urban Security and Disaster Engineering of China Ministry of Education, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing 100124, China
Li Wang: The Key Laboratory of Urban Security and Disaster Engineering of China Ministry of Education, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing 100124, China

Sustainability, 2024, vol. 16, issue 7, 1-21

Abstract: In order to optimize the structure of a subway shield tunnel, minimize injuries, and avoid potential safety hazards, the lateral convergence deformation of subway shield tunnels should be predicted. In terms of accuracy and stability, existing prediction models perform poorly in obtaining the lateral convergence deformation value of a non-stationary small-sized sample of a subway shield tunnel. In this paper, a lateral convergence model of a subway shield tunnel based on the Kalman algorithm is constructed based on Kalman filtering theory. The model is efficient, adaptive, and robust and can accurately predict the lateral convergence deformation of a subway shield tunnel. Taking the horizontal diameter of a 200-ring shield segment in the interval section of a subway tunnel as an example, we have proved that the residuals of the Kalman prediction model are small, the residual distribution conforms to the normal distribution, and the prediction effect is great. The model is suitable for the prediction of more than five periods of data, and the prediction accuracy of the model improves with an increase in the number of data periods. In addition, in this paper, we compare the Kalman model with the GM(1,1) model and the GM–Markov model, and the RMSE, NRMSE, MAPE, and R 2 are used as evaluation indices. The results show that the Kalman model has a higher prediction accuracy and is more suitable for predicting the lateral convergence deformation of a subway shield tunnel.

Keywords: shield tunnel; lateral convergence deformation; Kalman model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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