• Zonal dynamic VF model for mining-induced overburden based on Knothe's time function is constructed. • Crack expansion in fractured zone and gangue compaction in caving zone are revealed. • Quantification of the numerical model's VF uses the zonal VF definition and image processing. • Combining multi-model correlation with measured data comparison verifies the dynamic VF model. Coal mining generates numerous voids, leading to various geological hazards. Grouting filling is a widely used method to prevent and control such hazards, and its effectiveness depends on accurately predicting void distribution. However, most existing studies are limited to single regions, hindering a systematic characterization of voids across the overburden three zones. Therefore, a definition for zonal void fraction (VF) within mining-induced overlying strata is proposed, and a dynamic VF model based on the Knothe’s time function is developed and validated. Numerical simulations are used to analyze the failure process of rock in the fracture zone, reveal the compaction mechanism of crushed rock in the caving zone, and quantitatively characterize the zonal VF. The results indicate that the number of cracks in rock samples increases rapidly after the peak stress, accounting for approximately 95% of the entire failure process. The main factors leading to the reduction of VF in crushed rock are particle breakage, particle structure adjustment, and particle deformation. The development of voids in mining-induced overlying strata undergoes expansion and compaction stages. The VF in the caving zone, fracture zone, and separation zone vary from 10.84%, 1.26%, and 26.35% to 6.48%, 0.46%, and 31.28%, respectively. The theoretically calculated VF shows good agreement with simulation results, demonstrating a high correlation of up to 0.98684. The research findings provide a new method for accurately predicting the VF within mining-induced overlying strata and contribute to promoting the engineering application of filling technology.
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Li et al. (Wed,) studied this question.
synapsesocial.com/papers/69a75d0cc6e9836116a2676b — DOI: https://doi.org/10.1016/j.rineng.2026.109338
Zejun Li
Nan Zhou
Yizhu LEI
Results in Engineering
China University of Mining and Technology
Liupanshui Normal University
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