Extraction of force-chain network architecture in granular materials using community detection. Issue 14 (23rd February 2015)

• Record Type: Journal Article
• Authors: Bassett, Danielle S.; Owens, Eli T.; Porter, Mason A.; Manning, M. Lisa; Daniels, Karen E.
• Is Part Of: Soft matter. Volume 11:Issue 14(2015)
• Page Start: 2731
• Page End: 2744
• Publication Date: 2015-02-23
• Subjects: Soft condensed matter -- Periodicals; 530.413
• DOI: 10.1039/c4sm01821d
• Languages: English
• ISSNs: 1744-683X

Abstract

Abstract : Force chains form heterogeneous physical structures that can constrain the mechanical stability and acoustic transmission of granular media. Abstract : Force chains form heterogeneous physical structures that can constrain the mechanical stability and acoustic transmission of granular media. However, despite their relevance for predicting bulk properties of materials, there is no agreement on a quantitative description of force chains. Consequently, it is difficult to compare the force-chain structures in different materials or experimental conditions. To address this challenge, we treat granular materials as spatially-embedded networks in which the nodes (particles) are connected by weighted edges that represent contact forces. We use techniques from community detection, which is a type of clustering, to find sets of closely connected particles. By using a geographical null model that is constrained by the particles' contact network, we extract chain-like structures that are reminiscent of force chains. We propose three diagnostics to measure these chain-like structures, and we demonstrate the utility of these diagnostics for identifying and characterizing classes of force-chain network architectures in various materials. To illustrate our methods, we describe how force-chain architecture depends on pressure for two very different types of packings: (1) ones derived from laboratory experiments and (2) ones derived from idealized, numerically-generated frictionless packings. By resolving individual force chains, we quantify statistical properties of force-chain shape and strength, which are potentially crucial diagnostics of bulk properties (including material stability). These methods facilitate quantitative comparisons between different particulate systems, regardless of whether they are measured experimentally or numerically.