Issue 32, 2024

Understanding slow compression of frictional granular particles by network analysis

Abstract

We consider frictional granular packings exposed to quasi-static compression rates, with a focus on systems above the jamming transition. For frictionless packings, earlier work (S. Luding et al., Soft Matter, 2022, 18(9), 1868–1884) has uncovered that the system evolution/response involves smooth evolution phases, interrupted by fast transitions (events). The general finding is that the force networks’ static quantities correlate closely with the pressure, while their evolution resembles the kinetic energy for both frictionless and frictional packings. The former represents reversible (elastic) particle deformations with affine and non-affine components, whereas the latter also involves much stronger, irreversible (plastic) rearrangements of the packings. Events are associated with jumps in the overall kinetic energy as well as dramatic changes in the force networks describing the particle micro-structure. The frictional nature of particle interactions affects both their frequency and the relevant time scale magnitude. For intermediate friction, events are often followed by an unexpected slow-down during which the kinetic energy drops below its average value. We find that these slow-downs are associated with a significant decrease in the non-affine dynamics of the particles, and are strongly influenced by friction. Friction modifies the structure of the networks, both through the typical number of contacts of a particle, and by influencing topological features of the resulting networks. Furthermore, friction modifies the dynamics of the networks, with larger values of friction leading to smaller changes of the more stable networks.

Graphical abstract: Understanding slow compression of frictional granular particles by network analysis

Supplementary files

Article information

Article type
Paper
Submitted
10 May 2024
Accepted
19 Jul 2024
First published
02 Aug 2024
This article is Open Access
Creative Commons BY license

Soft Matter, 2024,20, 6440-6457

Understanding slow compression of frictional granular particles by network analysis

K. Taghizadeh, S. Luding, R. Basak and L. Kondic, Soft Matter, 2024, 20, 6440 DOI: 10.1039/D4SM00560K

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