Effect of Design Parameters of Supporting Structure on the Energy Evolution Characteristic of Surrounding Rock

Abstract

A reasonable support parameter design scheme is the key to ensuring the stability of the roadway. This study established 217 models using FLAC3D to analyze the evolution characteristics of elastic strain energy and plastic dissipation energy of surrounding rock under different shotcrete and rockbolt support structures. Additionally, five single models (BP, DT, ELM, RF, SVM) were introduced to explore the application of machine learning in predicting the stability of the roadway. The study found that in the parameters of the shotcrete layer support structure, the energy evolution of the surrounding rock is more sensitive to isotropic and thickness; in the parameters of the anchor rod support structure, the energy evolution of the surrounding rock is more sensitive to Young’s modulus, cross-sectional area young, and grout stiffness. Additionally, the parameters of the shotcrete layer support structure are not necessarily the larger the better. When isotropic is 100 GPa, both the dissipated energy and the elastic strain energy are higher than that at 25 GPa. The results of the single model test indicate that machine learning is relatively accurate in predicting different shotcrete and anchor support structures. The runtime difference between traditional methods and machine learning models highlights the potential advantages of machine learning.