Study on the Spatiotemporal Evolution Mechanism of Mine Pressure in Gold Mine Mines and its Prediction by FLAC3D Numerical Simulation
DOI:
https://doi.org/10.13052/ejcm2642-2085.3512Keywords:
Mine Pressure Evolution, Spatiotemporal Stress Analysis, Rock Mass Deformation, Plastic Zone Development, FLAC3D numerical simulation, deep underground gold miningAbstract
Deep underground gold mining induces complex stress redistribution due to high in-situ stress, geological heterogeneity, and progressive excavation, resulting in roof instability, floor heave, and pillar deformation. This study aims to develop a physics-based predictive framework to forecast mine pressure evolution, displacement, and plastic deformation under multiple mining scenarios. The objective is to integrate geological zoning, in-situ stress conditions, and excavation sequences into a unified model to identify high-risk zones and optimize mining strategies. This study utilizes the publicly available FLAC3D Gold Mining Dataset from Kaggle to define mining layout, geometric parameters, in-situ stress, and rock mass properties for the simulation. Spatiotemporal analysis evaluates principal stresses, Von Mises stress, displacements, and plastic zone evolution at each excavation step, revealing areas prone to instability. In addition, the spatiotemporal stress development at baseline, high-stress, deep-mining, and critical scenarios was quantitatively assessed by means of parameters derived from the simulations, allowing for the mapping of high-risk areas and the examination of stress redistribution processes. Finally, the framework predicts stress redistribution and deformation trends under baseline, high-stress, deep-mining, and critical scenarios, validated through numerical comparison with FLAC3D outputs to ensure reliability and accuracy. Results indicate accumulated stress increases from 30 MPa to 750 MPa across mining stages, with prediction errors within ±2MPa,R2=0.97, and RMSE=0.964 MPa. The framework effectively identifies critical stress zones and informs optimal excavation planning, demonstrating its potential to enhance safety and operational efficiency in deep gold mining.
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