| Contents |
| Granular media, whose features range from the particle scale to the force-chain scale and the bulk scale, are usually modeled as either particulate or continuum materials. In contrast with each of these approaches, network representations are natural for the simultaneous examination of microscopic, mesoscopic, and macroscopic features. In this talk, I treat granular materials as spatially embedded networks in which the nodes (particles) are connected by weighted edges obtained from contact forces. I use ideas from network science to provide insights into how sound propagates through granular materials. I test a variety of network measures to determine their utility in helping to describe sound propagation in granular networks and find that network diagnostics can be used to probe particle-, curve-, domain-, and system-scale structures in granular media. I also use network "community structure" --- a mesoscopic property --- to help characterize sound propagation, and I will illustrate how using different "null models" in community-detection methods can yield different insights into granular force networks. |
|