An Inversion Method for Surrounding Rock Parameters of Tunnels Based on a Probabilistic Baseline Model under a Constructional Environment

Abstract

The uncertainty of surrounding rock parameters varies due to changes in the boundary conditions of the tunnel model, and no suitable method to ensure that the updated parameters of the finite element model (FEM) are applicable throughout the constructional environment. To address this issue, a probabilistic baseline model method was introduced to invert the rock parameters and obtain values suitable for the complete constructional environment. First, the probabilistic statistical theory was applied to statistically analyze the measurement data from tunnels under different constructional environments, which provides insight into the variation in rock parameters. Then, an objective optimization function based on a genetic algorithm (GA) was constructed to optimize the accuracy by minimizing the error between the measurement data and the simulation data. Next, a Kriging model was built that utilized Young’s modulus and cohesion as updated parameters. This approach contributes to overcoming the inefficiency of multi-objective optimization computations. By using the Kriging model, optimal values for the rock parameters were obtained. Finally, the effectiveness and applicability of the proposed method were validated by comparing the measured data with the updated model data under different constructional environments.