Numerical analyses of reasonable drawing parameters of longwall top-coal caving: A case study based on Buertai coal mine
Abstract
To address the technical challenge of significant top coal loss in Longwall Top Coal Caving (LTCC) mining, this study takes the working face 12301 of a coal mine as the engineering background. By employing coupled FLAC3D and PFC3D numerical simulations, a multi-scale “stress-fragmentation-drawbody morphology” analytical model was developed. This model systematically investigates the influence of different mining-drawing ratios (MDR) on the characteristics of top coal fragmentation and the evolution of drawbody morphology under various drawing sequences. The results indicate that the MDR governs fragmentation efficacy by altering the stress distribution ahead of the working face. At an MDR of 3:2, the top coal undergoes extensive shear failure driven by elevated stress, achieving a failure depth of 6.0 m and yielding the most uniform fragment size distribution. Regarding the drawing sequence, the single-round interval drawing (SRICD) method results in drawbodies for odd-numbered shields exhibiting a symmetrical funnel shape, with coal recovery significantly higher than that achieved under the single-round sequential drawing (SRSCD) method. Although even-numbered shields under SRICD experience constraints from the drawing boundaries, the overall coal recovery is still higher than that of the SRSCD method, compensated by the uniform fragmentation of the top coal. Engineering application demonstrates that the optimized process combining a “3:2 MDR with SRICD” achieves a top coal recovery rate of 85%. This study establishes quantitative relationships between the mining-drawing ratio, top coal fragmentation depth, and recovery rate, providing a scientific basis and technical support for optimizing drawing process parameters in similar thick-seam LTCC operations.
Fields of Study & Subjects
Rock Mechanics and Modeling
Geomechanics and Mining Engineering
Grouting
Rheology
and Soil Mechanics
Publication details
- Journal / source
- Computational Particle Mechanics
- Publisher
- Elsevier BV
- Volume
- 15
- Pages
- 26–41
- Publication date
- 2 April 2026
- Language
- EN