Peng Li, Fen-hua Ren, Mei-feng Cai, Qi-feng Guo, Hao-fei Wang,  and Kang Liu, Investigating the mechanical and acoustic emission characteristics of brittle failure around a circular opening under uniaxial loading, Int. J. Miner. Metall. Mater., 26(2019), No. 10, pp. 1217-1230. https://doi.org/10.1007/s12613-019-1887-5
Cite this article as:
Peng Li, Fen-hua Ren, Mei-feng Cai, Qi-feng Guo, Hao-fei Wang,  and Kang Liu, Investigating the mechanical and acoustic emission characteristics of brittle failure around a circular opening under uniaxial loading, Int. J. Miner. Metall. Mater., 26(2019), No. 10, pp. 1217-1230. https://doi.org/10.1007/s12613-019-1887-5
Research Article

Investigating the mechanical and acoustic emission characteristics of brittle failure around a circular opening under uniaxial loading

+ Author Affiliations
  • Corresponding author:

    Fen-hua Ren    E-mail: renfh_2001@163.com

  • Received: 9 March 2019Revised: 2 July 2019Accepted: 8 July 2019
  • The size of underground openings in rock masses in metal mines is critical to the performance of the openings. In this study, the mechanical and acoustic emission (AE) characteristics of brittle rock-like specimens containing a circular opening with different ratios of opening diameter to sample size λ (λ=0.1, 0.13, 0.17, 0.2, and 0.23) were investigated under uniaxial compression with AE monitoring. The results indicate that the opening size strongly affected the peak strength and the elastic modulus. Crack initiation first started from the upper surface of the specimens, not from the periphery of the openings. Tensile and shear cracks coexisted on the roof and floor of the specimens, whereas tensile cracks were dominant on the two sides. The fracture mode of samples with openings was partially affected by the relative size of the pillars and openings. The AE response curves (in terms of counts, cumulative energy, cumulative counts, and b-value) show that brittle failure was mainly a progressive process. Moreover, the AE information corresponded well with microcrack evolution in the samples and thus can be used to predict sample failure.
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