Gong-kuang zidonghua (Oct 2024)

Fractal characteristics of mine fracture structures and their impact on rockburst

  • LAN Tianwei,
  • WANG Shunxiang,
  • ZHANG Mancang,
  • LI Zhu,
  • WU Guoqiang,
  • FANG Ping,
  • LU Kaixiang,
  • LIU Yonghao,
  • TANG Xiaofu

DOI
https://doi.org/10.13272/j.issn.1671-251x.2024060092
Journal volume & issue
Vol. 50, no. 10
pp. 112 – 119

Abstract

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Fracture structures in mines are critical geological factors in triggering rockbursts. This study investigated the impact of fracture structures on rockburst, focusing on the Junde mining area. Using geological dynamic zoning, the fracture structures in the mining area were classified into grade Ⅰ-Ⅴ fracture blocks based on length. The box-counting method in fractal theory was employed to calculate the fractal dimension of grade Ⅴ fracture blocks. The study analyzed the overall and partitioned fractal characteristics of the fractures and explored the coupling relationship between the fractal dimension of fracture structures, structural stress distribution, and rockburst. The results showed: ① The overall fractal dimension of the fractures was highly consistent with the fractal dimension of the NW-trending fractures, indicating that NW-trending fractures had a more significant influence on rockburst in the Junde mining area than NE-trending fractures. ② The fractal dimensions varied among fractures of different orientations, demonstrating clear spatial distribution differences and a positive correlation between fractal dimension and fracture complexity. This implied that a greater fractal dimension corresponded to a more complex spatial distribution of fracture structures, thereby increasing the likelihood of rockbursts. ③ Higher structural complexity was associated with higher stress concentration, and rockbursts in coal seams primarily occurred in high-stress regions, showing a high level of consistency between structural complexity and stress concentration. This study provides a new perspective for predicting and mitigating rockburst risks by quantitatively analyzing fracture structures through fractal dimensions.

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