| Issue |
EPJ Web Conf.
Volume 249, 2021
Powders & Grains 2021 – 9th International Conference on Micromechanics on Granular Media
|
|
|---|---|---|
| Article Number | 02008 | |
| Number of page(s) | 4 | |
| Section | Granular Solids | |
| DOI | https://doi.org/10.1051/epjconf/202124902008 | |
| Published online | 07 June 2021 | |
https://doi.org/10.1051/epjconf/202124902008
A micro-mechanical compaction model for granular mix of soft and rigid particles
1
LMGC, Université de Montpellier, CNRS, 163 rue Auguste Broussonnet, Montpellier, France
2
Department of Civil, Geological and Mining Engineering, Polytechnique Montréal, 2500 Chemin de Polytechnique, Québec, Canada
3
Institut Universitaire de France (IUF), Paris, France
* e-mail: manuel-antonio.cardenas-barrantes@umontpellier.fr
Published online: 7 June 2021
We use bi-dimensional non-smooth contact dynamics simulations to analyze the isotropic compaction of mixtures composed of rigid and deformable incompressible particles. Deformable particles are modeled using the finite-element method and following a hyper-elastic neo-Hookean constitutive law. The evolution of the packing fraction, bulk modulus and particle connectivity, beyond the jamming point, are characterized as a function of the applied stresses for different proportion of rigid/soft particles and two values of friction coefficient. Based on the granular stress tensor, a micro-mechanical expression for the evolution of the packing fraction and the bulk modulus are proposed. This expression is based on the evolution of the particle connectivity together with the bulk behaviour of a single representative deformable particle. A constitutive compaction equation is then introduced, set by well-defined physical quantities, given a direct prediction of the maximum packing fraction φmax as a function of the proportion of rigid/soft particles.
A video is available at https://doi.org/10.48448/cevr-fq53
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.