Deformation analysis of underwater shield tunnelling based on HSS model parameter obtained by the Bayesian approach

Deformation analysis and control of underwater large-diameter shield tunnels is a prerequisite for safe tunnel construction. Reasonable selection of constitutive model and its parameters is the key to accurately predicting the deformation induced by underwater shield tunnelling. In this paper, the finite element analysis of cavity expansion during the piezocone penetration test (CPTU) based on the hardening soil model with small strain stiffness (HSS) model was carried out, and the correlation model of the normalized cone tip resistance Q with the reference secant modulus E 50 ref and the effective internal friction angle φ’ was established and verified using mini CPTU chamber test. Then, a Bayesian probability characterization approach for E 50 ref of silty clay based on CPTU was proposed. Furthermore, the deformation analysis of Jinan Yellow River tunnel crossing the south embankment was carried out to verify the reliability of the proposed approach. The good agreement between the field measurement and numerical simulation confirms that the parameters obtained by the Bayesian approach are reliable. Finally, a sensitivity analysis was performed to study the law of riverbed settlement induced by underwater large-diameter shield tunnelling. The results show that the increasing support pressure could effectively reduce the riverbed settlement, but there is an upper limit. The optimal support pressure of established model is between 0.45 MPa and 0.5 MPa. The uphill section causes greater riverbed settlement than the downhill section. Under the same condition, increasing buried depth and water level will lead to a more significant settlement.

[1]  Luqi Wang,et al.  Quantification of model uncertainty and variability for landslide displacement prediction based on Monte Carlo simulation , 2023, Gondwana Research.

[2]  Q. Bai,et al.  Experimental and analytical study of shield tunnel face in dense sand strata considering different longitudinal inclination , 2021, Tunnelling and Underground Space Technology.

[3]  Quansheng Liu,et al.  Analysis on the excavation management system of slurry shield TBM in permeable sandy ground , 2021, Tunnelling and Underground Space Technology.

[4]  Guojun Cai,et al.  Bayesian probabilistic characterization of consolidation behavior of clays using CPTU data , 2021, Acta Geotechnica.

[5]  G. Zheng,et al.  Numerical modelling of retaining structure displacements in multi-bench retained excavations , 2020 .

[6]  C. Ng,et al.  Use of unsaturated small-strain soil stiffness to the design of wall deflection and ground movement adjacent to deep excavation , 2020 .

[7]  Hai‐Sui Yu,et al.  A cavity expansion–based solution for interpretation of CPTu data in soils under partially drained conditions , 2020, International Journal for Numerical and Analytical Methods in Geomechanics.

[8]  J. Zhan,et al.  Face Stability Assessment for Underwater Tunneling Across a Fault Zone , 2019, Journal of Performance of Constructed Facilities.

[9]  Dian-Qing Li,et al.  Bayesian identification of soil stratigraphy based on soil behaviour type index , 2019, Canadian Geotechnical Journal.

[10]  Wengang Zhang,et al.  Estimation of strut forces for braced excavation in granular soils from numerical analysis and case histories , 2019, Computers and Geotechnics.

[11]  Song-yu Liu,et al.  Random field characterization of CPTU soil behavior type index of Jiangsu quaternary soil deposits , 2017, Bulletin of Engineering Geology and the Environment.

[12]  K. Phoon,et al.  Bayesian identification of random field model using indirect test data , 2016 .

[13]  A. Sadrekarimi Evaluation of CPT-based characterization methods for loose to medium-dense sands , 2016 .

[14]  Dian-Qing Li,et al.  Quantification of prior knowledge in geotechnical site characterization , 2016 .

[15]  Yu Wang,et al.  Bayesian perspective on geotechnical variability and site characterization , 2016 .

[16]  B. Lehane,et al.  Numerical derivation of CPT-based p–y curves for piles in sand , 2014 .

[17]  Suched Likitlersuang,et al.  Finite element analysis of a deep excavation: A case study from the Bangkok MRT , 2013 .

[18]  Feng Yu,et al.  Key techniques and important issues for slurry shield under-passing embankments: A case study of Hangzhou Qiantang River Tunnel , 2013 .

[19]  Yu Wang,et al.  Probabilistic characterization of Young's modulus of soil using equivalent samples , 2013 .

[20]  Helmut Schweiger,et al.  Influence of Deep Excavations on Nearby Existing Tunnels , 2013 .

[21]  Barry Lehane,et al.  Pile and penetrometer end bearing resistance in two-layered soil profiles , 2008 .

[22]  K. Phoon,et al.  Characterization of Geotechnical Variability , 1999 .

[23]  M. Randolph,et al.  Design of driven piles in sand , 1994 .

[24]  J. Burland Ninth Laurits Bjerrum Memorial Lecture: "Small is beautiful"—the stiffness of soils at small strains , 1989 .

[25]  A. Fourie,et al.  Studies of the influence of non-linear stress-strain characteristics in soil-structure interaction , 1986 .

[26]  Kok-Kwang Phoon,et al.  Constructing Site-Specific Multivariate Probability Distribution Model Using Bayesian Machine Learning , 2019, Journal of Engineering Mechanics.

[27]  Yubing Yang,et al.  Analysis of ground surface settlement induced by the construction of a large-diameter shield-driven tunnel in Shanghai, China , 2016 .

[28]  Yusuke Suzuki,et al.  Investigation and interpretation of cone penetration rate effects , 2015 .

[29]  Xu Zhong-hua,et al.  Experimental study of parameters of hardening soil model for numerical analysis of excavations of foundation pits , 2012 .

[30]  He Chuan,et al.  Prototype tests on effective bending rigidity ratios of segmental lining structure for shield tunnel with large cross-section , 2011 .

[31]  Xiangtao Xu,et al.  Investigation of the end bearing performance of displacement piles in sand , 2007 .