Geomechanics and Engineering
Volume 45, Number 1
DOI: 61-77
Partitioned fracture law and prediction method of near-field roof in shallow-buried thin bedrock super-long working faces: a case study
Guohao Meng , Dawei Yin , Liqiang Chen
Abstract
To explore the partitioned fracture law of a near-field roof in shallow-buried, thin-bedrock, super-long working faces, an equivalent stiffness foundation beam mechanical model of super-long working faces was established. The effects of face length l, coal seam mining height mc, main roof elastic modulus E, main roof thickness h, support stiffness k2, and roadway sidewall stiffness K on the bending moment distribution of the main roof were investigated. Results show that the bending moment distribution curve of the main roof occurs in two patterns: single-peak and M-shaped double-peak forms. The main roof exhibits four fracture modes: central bending subsidence, central point fracture, central regional fracture, and bilateral partitioned fracture. The influence patterns of various factors on roof fracture modes were elucidated. The kEIl effect influencing main roof fracture along the working face dip was analyzed, and a composite parameter criterion for main roof fracture along the working face dip was proposed: when [(k/EI)1/4l] [6.7, 7], the roof exhibits central regional fracture, when [(k/EI)1/4l] > 7, the roof shows bilateral partitioned fracture, when [(k/EI)1/4l] < 6.7, the roof shows central point fracture. A prediction method for main roof fracture patterns along the working face dip was established. Through comparative analysis of field measurements and theoretical calculations, the roof fracture characteristics were verified, and the time–space correlation between roof partitioned fracture and support resistance distribution was revealed. The results provide a theoretical basis for disaster prevention in shallow, ultra long working faces with thin bedrock.
Key Words
composite parameter criterion; disaster prevention; partitioned fracture; shallow-buried thin bedrock; super-long working faces
Address
- Guohao Meng, Dawei Yin — College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao, 266590, China; Shandong Key Laboratory of Intelligent Prevention and Control of Dynamic Disaster in Deep Mines, Shandong University of Science and Technology, Qingdao 266590, China
- Liqiang Chen — Shandong Key Laboratory of Intelligent Prevention and Control of Dynamic Disaster in Deep Mines, Shandong University of Science and Technology, Qingdao 266590, China
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