Network Analysis of Particles and Grains

TL;DR

This paper reviews how network science tools can be applied to analyze the complex multiscale organization of granular materials, offering new insights into their structure and behavior.

Contribution

It provides a comprehensive overview of network-based approaches to studying granular matter and discusses future research directions in this emerging field.

Findings

Network analysis reveals multiscale structures in granular materials.

Network methods offer new insights into force chains and particle arrangements.

Potential for improved material design through network-based modeling.

Abstract

The arrangements of particles and forces in granular materials have a complex organization on multiple spatial scales that ranges from local structures to mesoscale and system-wide ones. This multiscale organization can affect how a material responds or reconfigures when exposed to external perturbations or loading. The theoretical study of particle-level, force-chain, domain, and bulk properties requires the development and application of appropriate physical, mathematical, statistical, and computational frameworks. Traditionally, granular materials have been investigated using particulate or continuum models, each of which tends to be implicitly agnostic to multiscale organization. Recently, tools from network science have emerged as powerful approaches for probing and characterizing heterogeneous architectures across different scales in complex systems, and a diverse set of methods have yielded fascinating insights into granular materials. In this paper, we review work on network-based approaches to studying granular matter and explore the potential of such frameworks to provide a useful description of these systems and to enhance understanding of their underlying physics. We also outline a few open questions and highlight particularly promising future directions in the analysis and design of granular matter and other kinds of material networks.