4.7 Article

Damage smear method for rock failure process analysis

Journal

Publisher

SCIENCE PRESS
DOI: 10.1016/j.jrmge.2019.06.007

Keywords

Failure process; Smear method; Meso-damage; Finite element method (FEM); Rock failure process analysis (RFPA)

Funding

  1. National Natural Science Foundation of China [51679028, 51879034]
  2. Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology [SKLGDUEK1804]
  3. Fundamental Research Funds for the Central Universities [DUT18JC10]

Ask authors/readers for more resources

Damage smear method (DSM) is adopted to study trans-scale progressive rock failure process, based on statistical meso-damage model and finite element solver. The statistical approach is utilized to reflect the mesoscopic rock heterogeneity. The constitutive law of representative volume element (RVE) is established according to continuum damage mechanics in which double-damage criterion is considered. The damage evolution and accumulation of RVEs are used to reveal the macroscopic rock failure characteristics. Each single RVE will be represented by one unique element. The initiation, propagation and coalescence of meso-to macro-cracks are captured by smearing failed elements. The above ideas are formulated into the framework of the DSM and programed into self-developed rock failure process analysis (RFPA) software. Two laboratory-scale examples are conducted and the well-known engineering-scale tests, i.e. Atomic Energy of Canada Limited's (AECL's) Underground Research Laboratory (URL) tests, are used for verification. It shows that the simulation results match with other experimental results and field observations. (C) 2019 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Production and hosting by Elsevier B.V.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available