Quantification of particle crushing in consideration of grading evolution of granular soils in biaxial shearing : A probability-based model

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

4 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)488-515
Journal / PublicationInternational Journal for Numerical and Analytical Methods in Geomechanics
Volume42
Issue number3
Online published18 Oct 2017
Publication statusPublished - 25 Feb 2018

Abstract

A probability-based model is presented to estimate particle crushing and the associated grading evolution in granular soils during isotropic compression and prepeak shearing in biaxial tests. The model is based on probability density functions of interparticle and intraparticle stress (ie, particle normalized maximum shear stress and particle average maximum shear stress) derived from discrete element method simulations of biaxial tests. We find that the probability density functions of normalized maximum shear stress are dependent on the current sample grading, implying coupling effects between particle crushing and sample grading such that the particle crushing is affected by the current sample grading, and the grading change is also dependent on the current particle crushing extent. To incorporate these coupling effects into the model, particle crushing and grading change are calculated for each load increment, in which the crushing probability of a particle during any loading increment is denoted as the corresponding increment of probability of the internal maximum shear stress exceeding its maximum shear strength. The model shows qualitative agreement with published experimental data. The effects of the model parameters, including initial porosity, particle strength, initial grading, and crushing mode, on the calculated results are discussed and compared with previous studies. Finally, the strengths and limitations of the model are discussed.

Research Area(s)

  • biaxial test, coupling, discrete element method, grading evolution, particle crushing, probability and statistics

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