Quantitative Evaluation Methods of Brittle Failure Characteristics of Coal: A Case Study of Hard Coal in China

  • Bo Ren
  • Shao-hua WangEmail author
  • Jun-hua Xue
  • Kai-long Qiu
  • Guo-feng Yu
  • Ying-jie Fan
  • Shi-qi Zhao
  • Zhen-yu Du
  • Dong-sheng Deng
  • Xian-jie Hao
Original Paper


Coal brittleness is one of the important indexes to characterize the post-peak characteristics of coal, which is closely related to the efficiency of underground coal mining and the degree of coal disaster. In this paper, the compression characteristics of coal are studied by laboratory experiment, which is characterized by relatively long nonlinear elastic stage, smaller plastic stage and stress drops in post-peak stage. On this basis, the existing brittleness evaluation methods are summarized, and the applicability of 11 indexes of 6 physical parameters to the quantitative evaluation methods of coal brittleness are analyzed and discussed. The results show that: (1) for the coal is a complexity heterogeneous medium with hole and fracture, there are different degrees of limitation on the methods of coal brittleness quantitative evaluation,which can be used to roughly estimate the brittleness of coal, but it can not accurately characterize its brittle characteristics. (2) Based on the whole process stress–strain curve, the brittleness degree index B5 is more suitable for the brittleness characterization of coal by quantitatively considering the relative size and absolute rate of post-peak stress drop.


Coal Brittleness characteristics Quantitative evaluation Stress–strain curve 



The research was supported by the Beijing Natural Science Foundation (8174072), the National Natural Science Foundation (51627804), the National Key R & D Programme of China (2016YFC0801400), an Open Project of The Research Centre of Coal Resources Safe Mining and Clean Coal Utilisation, Liaoning (LNTU16KF08), The State Key Laboratory of Coal Resources and Safe Mining (China University of Mining and Technology) under Grant Nos SKLCRSM16KFB07 and SKLCRSM16DCB01, and The National Natural Science Foundation of China under Grant No. 41272347: this support is gratefully acknowledged.


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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.State Key Laboratory of Deep Coal Mining & Environment ProtectionHuainanChina
  2. 2.School of Resource and Safety EngineeringChina University of Mining and Technology (Beijing)BeijingChina
  3. 3.Coal Mining National Engineering Technology Research InstituteHuainanChina

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