Abstract:

In order to study the surrounding rock mechanical parameters of the singletrack railway tunnel in the alpine region with central deepburied ditch. Taking Alatao Mountain Tunnel of the newly built Bozhou branch line as the engineering background, based on BP neural network algorithm combined with the FLAC3D numerical simulation software and neural network toolbox in MATLAB. BP neural network algorithm is used to establish forward and inversion models of tunnel excavation displacement, and the inversion analysis of the physical and mechanical parameters of the surrounding rock is carried out. By fitting the tunnel vault and the tunnel arch monitoring data before excavation of the central deepburied ditch, it is found that the tunnel deformation has become stable, and inversion process does not need to consider the secondary disturbance of the surrounding rock in the excavation of center deepburied ditch. The vault settlement value and the arch convergence value before the excavation are taken as input function, and the bulk elastic modulus (K), shear elastic modulus (G), cohesion (c), internal friction of the surrounding rock angle (φ) and the severity (γ) are used as output functions to train the neural network model, and the trained model is used to perform the inverse analysis of the required parameters. After substituting the inversion parameters into the FLAC3D forward model, the settlement value and the arch convergence value of the vault before excavation are extracted, which is close to the actual monitoring value before the excavation of the central deepburied ditch. The results show that the inversion of physical and mechanical parameters of surrounding rock is reasonable, and the prediction of deformation is accurate, which provide reference for the construction and optimization design of subsequent works.

Key words: surrounding rock displacement, BP neural network, central deepburied ditch, inversion analysis, tunnel physical and mechanical parameters