Failure modes and excavation stability of large-scale columnar jointed rock masses containing interlayer shear weakness zones

The mechanical properties of large-scale columnar jointed rock masses (CJRMs) after excavation would be reduced due to the unloading relaxation, in addition to its influence on the stability of underground caverns. Moreover, the cutting of the interlayer shear weakness zones through the cavern complicates the overall stability of CJRM, and brings challenges to the stability control of project. In view of such problems encountered during the construction of underground caverns, we reconstructed the large-scale CJRMs containing interlayer shear weakness zones to conduct the 3D rock failure process analysis. The numerical models of surge tank caverns during excavation were established and the mechanical properties, failure modes and acoustic emission (AE) characteristics were analyzed. The simulation results indicate that the large-scale columnar joints and C2 interlayer shear weakness zones influence the mechanical properties and failure modes significantly. Three types of damage modes in numerical models containing crush-shear failure along columnar joints, tensile-slip failure along C2 interlayer shear weakness zone and crush failure inside and around caverns were summarized. The concentration zones of tensile stress were found around each cavern and gradually shrunk from sector shape to linear shape. The caverns were divided into two parts along C2 shear weakness zone in the process of X stress loading and two sector damage zones occurring on both horizontal sides of each cavern. In the process of Y stress loading, some crack networks consisting of large-scale columnar joints, intralayer joints and C2 shear weakness zone were formed which led to the complete failure of the numerical models. A new method based on BP neural network was proposed to evaluate the stability of rock mass with large-scale columnar joints and interlayer shear weakness zones. The training results show that the method can distinguish the stability of rock mass well, while its accuracy reaches 97.6%.