Stress-strain state zoning model and novel large deformation classification method for squeezing tunnels

Abstract

Accurately assessing the level of large deformation in squeezing tunnels is of great importance for the design of support structures. The current large deformations classification methods fail to account for the effect of support pressure on the relative deformation of surrounding rock. In this study, a theoretical model for the stress–strain state zoning of the surrounding rock in squeezing tunnels is established. A sensitivity analysis of the model parameters is conducted. The distribution law of the strength-stress ratio, relative deformation, and relative support pressure indices in 43 field monitoring squeezing tunnels are statistically analyzed. A novel large-deformation classification method based on the relative support pressure index is proposed and applied in case studies. The parameter sensitivity analysis shows that mechanical parameters of the surrounding rock significantly affect the deformation and the stress–strain state zoning of the surrounding rock. The stress–strain state zoning and deformation of the surrounding rock are also primarily dependent on the matching relationship between strength-stress ratio and support pressure. Statistical analyses indicate that there is a nonlinear negative correlation between the relative deformation of the surrounding rock and the strength-stress ratio, as well as the relative support pressure, which includes the steel arch relative support pressure index (SSPI) and the anchor bolt relative support pressure Index (ASPI). The key to controlling surrounding rock deformation lies in the rational matching of support pressure to the strength-stress ratio. In the novel large deformation classification method, three key indexes of strong stress ratio, relative deformation and relative support pressure are quantitatively included, and squeezing large deformation is divided into three levels. Moreover, the case study demonstrated that the novel large deformation classification method has significant guiding importance in verifying feasibility and optimizing support design schemes during both the design and construction phases.