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A Multicomponent Particle Model and Linear Fitting Calibration Method for Heterogeneous Rocks

Author(s):




Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2019
Page(s): 1-15
DOI: 10.1155/2019/1509719
Abstract:

Deformation and failure of rock are very important to underground space engineering. In this paper, a new three-dimensional multicomponent bonded-particle model is developed for heterogeneous rocks. Granite samples from the Sanshandao Gold Mine are first analyzed using a microscope. Cylindrical and disc models consisting of four minerals (i.e., plagioclase, potash feldspar, quartz, and biotite) are built to simulate the behavior of the granite under compressive and tensile tests. To improve the calibration efficiency, a new method for determining the microparameters of minerals is proposed. Uniaxial compression, triaxial compression, and Brazilian tests are carried out in the lab. The failure pattern and stress-strain curves are obtained from numerical simulations and verified with those observed in the experiments. Furthermore, the Mohr–Coulomb and Hoek–Brown strength parameters are obtained and compared with the experimental results. The multicomponent particle model is shown to well reproduce the behavior of granite under the compressive and tensile tests. The multicomponent bonded-particle model significantly improves the accuracy of three parameters: the ratio of tensile strength to uniaxial compressive strength, the friction angle, and the parametermiof the Hoek–Brown criterion. The linear fitting calibration method provides a fast and efficient way to determine the microparameters of particles in heterogeneous rocks.

Copyright: © 2019 Qifeng Guo et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10311083
  • Published on:
    04/04/2019
  • Last updated on:
    02/06/2021
 
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