An RQD-Based Refined Numerical Model and Stability Comprehensive Evaluation Method of Goaf: A Case Study at Alhada Lead–Zinc Mine, Inner Mongolia, China

Abstract

Spatial variability is a key characteristic of engineering rock masses, reflecting their inherent heterogeneity and significantly influencing mining-induced mechanical responses. Traditional homogeneous numerical models often struggle to accurately capture this variability, leading to potential biases when relying on a single evaluation indicator. To address these challenges, this study proposes a comprehensive evaluation method for goaf stability that integrates multisource data and accounts for uncertainties related to boundary conditions and rock mass structures. The approach combines refined geological conditions, mining-induced mechanical responses, and interactions within the goaf. A refined rock quality designation (RQD) block model, based on borehole core data, characterizes geological heterogeneity and serves as the foundation for an improved numerical model. The effectiveness of this model is validated through InSAR-based surface subsidence monitoring, which demonstrates its capability to accurately reflect the combined effects of mining disturbance and rock quality on surface subsidence. Mechanical responses from the simulation are quantified using the roof stability number within the Mathews stability chart framework. Multisource data comprising refined numerical simulation, quantitative analysis, and empirical analysis are then integrated via fuzzy comprehensive evaluation, producing stability assessments that align with field observations of instability, thus confirming the method's reliability. Sensitivity analysis reveals that the primary factors influencing goaf stability are the mechanical responses induced by open-stope mining in low-strength surrounding rock and the geometric dimensions of the goaf. The developed refined numerical model and evaluation method provide a scientific basis for precise assessment and early warning of goaf stability issues, thereby supporting safer and more effective mining operations.