Micromechanical description of the compaction of soft pentagon assemblies

Abstract

We analyze the isotropic compaction of assemblies composed of soft pentagons interacting through classical Coulomb friction via numerical simulations. The effect of the initial particle shape is discussed by comparing packings of pentagons with packings of soft circular particles. We characterize the evolution of the packing fraction, the elastic modulus, and the microstructure (particle rearrangement, connectivity, contact force, and particle stress distributions) as a function of the applied stresses. Both systems behave similarly: the packing fraction increases and tends asymptotically to a maximum value φ max , where the bulk modulus diverges. At the microscopic scale we show that particle rearrangements occur even beyond the jammed state, the mean coordination increases as a square root of the packing fraction, and the force and stress distributions become more homogeneous as the packing fraction increases. Soft pentagons experience larger particle rearrangements than circular particles, and such behavior decreases proportionally to the friction. Interestingly, the friction between particles also contributes to a better homogenization of the contact force network in both systems. From the expression of the granular stress tensor we develop a model that describes the compaction behavior as a function of the applied pressure, the Young modulus, and the initial shape of the particles. This model, settled on the joint evolution of the particle connectivity and the contact stress, provides outstanding predictions from the jamming point up to very high densities.

Experimental validation of a micromechanically based compaction law for mixtures of soft and hard grains

“…First, we point out that, even if the system seems to be small, macroscopic measurements stay repeatable. The exponent α of the Z − Z J vs φ − φ J power law is repeatable from one κ value to another and fully in agreement with previous experimental and numerical studies [22][23][24][25]36,43]. As explained in [22,25], this law can be plugged into existing models to obtain an isotropic compaction equation.…”

“…Most of the fundamental aspects of their behavior in many circumstances are now well known [9,14,21]. The behavior of systems made of highly deformable grains at high packing fraction has also been more and more studied [5,6,12,22,23], and at least for compaction, reliable models exist [24,25]. In between, even if they are very common materials, systems composed of grains with very different-soft and hard-rheologies, driven far above the jamming transition, have a bewildering but fascinating behavior that remains mostly misunderstood.…”

“…However, to the best of our knowledge, no local measurements have been performed to understand the microprocesses leading to their characteristic macroscopic behavior. Only very recently, through a numerical approach, was a micromechanical-based compaction model proposed [22,23] to describe the evolution of these systems in compression. However, experimental validation is still lacking, along with a clear understanding of local processes.…”

Understanding slow compression and decompression of frictionless soft granular matter by network analysis

“…Different methods, e.g. , DEM-FEM coupling, could be used to simulate high volume fractions, 52,70,71 however such methods are computationally costly. For simplicity, in the present work we stick to classical DEM, following the phenomenology in a qualitative way, leaving more quantitative considerations of the influence of the change of particle shape (and other aspects related to large volume fractions) to other studies 53 and future research.…”

Photoelastic Stress Response of Complex 3D-Printed Particle Shapes

“…In response to these experimental limitations, there have been advancements in computational modelling using Finite Element Analysis (FEA). This method is capable of efficiently analyzing stress transmission on complex particle systems in a relatively short timeframe [14] and can predict the shapes and forces of deformable particles [15] .…”