This study develops an instability prediction model for surrounding rock in tunnels, highlighting energy evolution and support optimization methods.
This study focuses on tunnel construction in fault fracture zones and systematically investigates the energy evolution and damage catastrophe mechanisms of surrounding rock during excavation, based on energy conservation principles and cusp catastrophe theory. A tunnel instability prediction and support optimization framework integrating energy damage evolution and intelligent optimization algorithms was developed. Field tests, rock mechanics experiments, and Discrete Fracture Network (DFN) numerical simulations reveal the intrinsic relationships among energy input, dissipation, damage accumulation, and instability under complex geological conditions. Particle Swarm Optimization–Back Propagation (PSO-BP) is applied to optimize tunnel support parameters. Model performance is evaluated using the Mean Absolute Error (MAE), Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), and R-squared (R2). The results show that upon reaching structural mutation zones, the system damage variable (ds), displacement, and dissipated energy increase abruptly, indicating critical instability. Numerical simulation and catastrophe feature analysis demonstrate that energy-related damage accumulation is effectively suppressed, the system damage variable decreases significantly, and crown stability is greatly enhanced. These findings provide a theoretical basis and practical reference for optimizing tunnel support design and controlling instability risks in complex geological settings.
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Sun et al. (2025) studied this question.
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