a Key Laboratory of Geotechnical and Underground Engineering, Ministry of Education, Tongji University, Shanghai, 200092, China
b Department of Geotechnical Engineering, College of Civil Engineering, Tongji University, Shanghai, 200092, China
2022, 14(4): 1100-1114. doi:10.1016/j.jrmge.2022.03.005
Received: 2021-11-09 / Revised: 2022-02-19 / Accepted: 2022-03-15 / Available online: 2022-04-18
2022, 14(4): 1100-1114.
doi:10.1016/j.jrmge.2022.03.005
Received: 2021-11-09
Revised: 2022-02-19
Accepted: 2022-03-15
Available online: 2022-04-18
The influence of a deep excavation on existing shield tunnels nearby is a vital issue in tunnelling engineering. Whereas, there lacks robust methods to predict excavation-induced tunnel displacements. In this study, an auto machine learning (AutoML)-based approach is proposed to precisely solve the issue. Seven input parameters are considered in the database covering two physical aspects, namely soil property, and spatial characteristics of the deep excavation. The 10-fold cross-validation method is employed to overcome the scarcity of data, and promote model's robustness. Six genetic algorithm (GA)-ML models are established as well for comparison. The results indicated that the proposed AutoML model is a comprehensive model that integrates efficiency and robustness. Importance analysis reveals that the ratio of the average shear strength to the vertical effective stress Eur/σv′, the excavation depth H, and the excavation width B are the most influential variables for the displacements. Finally, the AutoML model is further validated by practical engineering. The prediction results are in a good agreement with monitoring data, signifying that our model can be applied in real projects.
Keywords: Soil–structure interaction, Auto machine learning (AutoML), Displacement prediction, Robust model, Geotechnical engineering
Dongmei Zhang
Prof. Dongmei Zhang undertook her PhD in both Tongji University, China, and École Centrale de Nantes, France in 2003. At present, she is the Head of Institute of Tunnel and Underground Engineering in Tongji University. Since July 2014, Prof. Zhang acts as the Secretary-General of the Risk and Insurance Research Branch of China Civil Engineering Society. Her primary research interests include the performance evolution, safety assessment and control for shield tunnel in soft soils. She is the author of over 160 scientific papers published in leading peer-reviewed scientific journals and proceedings. As evidences of her contributions to science and engineering practice, she has won the 16th China Youth Science and Technology Prize (in 2020), First-class of Shanghai Science and Technology Award (ranking No. 1 in 2017), Second-class of National Science and Technology Award (in 2008), First-class of Science and Technology Award of the Ministry of Education (in 2007 and 2010), and was supported by the National Special Support Program for High-level Personnel Recruitment.