Abstract

Soft granular materials are assemblies of highly deformable grains interacting via surface forces. The large grain deformations of these materials differ them from hard granular systems, in which, their behaviors are essentially governed by grain rearrangements. In this paper, we study the uniaxial compression of soft granular materials using a numerical approach based on the Material Point Method allowing for large grain deformations, coupled with the Contact Dynamics method for the treatment of unilateral frictional contacts between grains. Considering the neo-Hookean and elasto-plastic grains, the compaction of 2D soft granular packings is analyzed. We focus essentially on the evolution of the packing vertical stress as a function of the packing fraction and the predictive models are proposed.

Highlights

  • Soft granular materials such as metallic powders and, many pharmaceutical and food products can deform elastically or plastically without rupture under low confining pressure

  • We proposed three numerical approaches to study the rheology of soft granular materials

  • First method is the Bonded Particle Model (BPM), which consists in modeling each grain as an aggregate

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Summary

Introduction

Soft granular materials such as metallic powders and, many pharmaceutical and food products can deform elastically or plastically without rupture under low confining pressure. It allows them to achieve high packing fractions above the jamming state of hard granular materials. Around the jamming state, the grain shape and volume changes are negligible and the soft granular packing behaves almost like a hard granular medium with a Hertz’s contact law. The value of E⇤, depending on the discretization, is a little larger than the analytical value and increases as the fineness of discretization increases [6] Note that this linear behavior near the jamming sate, can be seen for all types of grain material behavior. This behavior will be studied in the following

Neo-Hookean grain packings
Elasto-plastic grain packings
Conclusions
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