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A plastic strain based statistical damage model for brittle to ductile behaviour of rocks

  • Zhou, Changtai (Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization, Institute of Deep Earth Sciences and Green Energy, College of Civil and Transportation Engineering, Shenzhen University) ;
  • Zhang, Kai (Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization, Institute of Deep Earth Sciences and Green Energy, College of Civil and Transportation Engineering, Shenzhen University) ;
  • Wang, Haibo (Mining Institute, China Coal Research Institute) ;
  • Xu, Yongxiang (Mining Institute, China Coal Research Institute)
  • Received : 2019.08.31
  • Accepted : 2020.04.03
  • Published : 2020.05.25

Abstract

Rock brittleness, which is closely related to the failure modes, plays a significant role in the design and construction of many rock engineering applications. However, the brittle-ductile failure transition is mostly ignored by the current statistical damage constitutive model, which may misestimate the failure strength and failure behaviours of intact rock. In this study, a new statistical damage model considering rock brittleness is proposed for brittle to ductile behaviour of rocks using brittleness index (BI). Firstly, the statistical constitutive damage model is reviewed and a new statistical damage model considering failure mode transition is developed by introducing rock brittleness parameter-BI. Then the corresponding damage distribution parameters, shape parameter m and scale parameter F0, are expressed in terms of BI. The shape parameter m has a positive relationship with BI while the scale parameter F0 depends on both BI and εe. Finally, the robustness and correctness of the proposed damage model is validated using a set of experimental data with various confining pressure.

Keywords

Acknowledgement

Supported by : Department of Science and Technology of Guangdong, Natural Science Foundation of China

The PhD scholarship provided by the China Scholarship Council (CSC) to the first author is gratefully acknowledged. This research is financially supported by the Department of Science and Technology of Guangdong Province (No. 2019ZT08G315) and the Natural Science Foundation of China (No. 51827901).

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