Effective medium theory of random regular networks

TL;DR

This paper develops an effective medium theory for under-constrained random regular spring networks with geometrical disorder, predicting their stiffness behavior under strain and providing a useful tool for experimental analysis.

Contribution

It introduces the first EMT for under-constrained random regular networks, extending the applicability of EMT to geometrically disordered systems.

Findings

Stiffness depends linearly on strain in the rigid phase.

Stiffness shows a nontrivial dependence on tension distribution statistics.

EMT provides qualitative insights despite spatial heterogeneity limitations.

Abstract

Disordered spring networks can exhibit rigidity transitions, due to either the removal of materials in over-constrained networks or the application of strain in under-constrained ones. While an effective medium theory (EMT) exists for the former, there is none for the latter. We, therefore, formulate an EMT for random regular networks, under-constrained spring networks with purely geometrical disorder, to predict their stiffness via the distribution of tensions. We find a linear dependence of stiffness on strain in the rigid phase and a nontrivial dependence on both the mean and standard deviation of the tension distribution. While EMT does not yield highly accurate predictions of shear modulus due to spatial heterogeneities, the noninvasiveness of this EMT makes it an ideal starting point for experimentalists quantifying the mechanics of such networks.