Topology counts: force distributions in circular spring networks

TL;DR

This paper analyzes how the topology of circular spring networks influences force distributions, revealing that network structure critically determines force inhomogeneity, which classical mean-field approaches fail to capture.

Contribution

The study introduces a probabilistic and graph-theoretical framework to explicitly derive force distributions in random spring networks based on topology.

Findings

Force mean and variance depend only on connectivity and node count.

Classical mean-field models do not accurately predict force distributions.

Network topology is a key factor in force inhomogeneity.

Abstract

Filamentous polymer networks govern the mechanical properties of many biological materials. Force distributions within these networks are typically highly inhomogeneous and, although the importance of force distributions for structural properties is well recognized, they are far from being understood quantitatively. Using a combination of probabilistic and graph-theoretical techniques we derive force distributions in a model system consisting of ensembles of random linear spring networks on a circle. We show that characteristic quantities, such as mean and variance of the force supported by individual springs, can be derived explicitly in terms of only two parameters: (i) average connectivity and (ii) number of nodes. Our analysis shows that a classical mean-field approach fails to capture these characteristic quantities correctly. In contrast, we demonstrate that network topology is a crucial determinant of force distributions in an elastic spring network.