Two Approaches to Quantification of Force Networks in Particulate Systems

Abstract

The interactions between particles in dense particulate systems are organized in force networks, mesoscale features that influence the macroscopic response to applied stresses. The detailed structure of these networks is, however, difficult to extract from experiments that cannot resolve individual contact forces. In this study, we showed that certain persistent homology (PH) measures extracted from data accessible to experiment are strongly correlated with the same features extracted from the full contact force network. We performed simulations known to accurately model experiments on an intruder being pushed through a two-dimensional (2D) granular layer and compared PH properties of full contact force networks and networks constructed using only the sum of the normal forces on each grain. We found that the main features were highly correlated, suggesting that data commonly available in experiments are sufficient for quantifying the structure of force networks in evolving granular systems.