The fracture resistance of elastic networks increases with the density of defects like a random walk
Antoine Sanner, Luca Michel, David S. Kammer

TL;DR
This study investigates how increasing defect density in elastic networks enhances fracture resistance, revealing a sqrt(nu) scaling due to crack arrest fluctuations, with implications for predicting fracture energy.
Contribution
It introduces a quantitative link between microstructural disorder and macroscopic fracture energy using a random-walk model of missing bonds.
Findings
Fracture energy $G^c(a)$ increases with crack advance $a$ for fixed defect concentration.
Fluctuations in local fracture energy landscape scale with the square root of defect fraction $ u$.
Probability density of local fracture energy exhibits an exponential tail, leading to a logarithmic increase of $G^c(a)$ with crack length.
Abstract
Disordered spring networks are a well-established model system to study fracture in a wide range of materials, from ceramics to polymer networks and mechanical metamaterials, across length scales from the atomistic to the macroscopic. A central quantity characterizing fracture is the apparent fracture energy , which measures the resistance to the propagation of a preexisting dominant crack. While it is well established that disorder can increase through crack arrest by local inhomogeneities, its dependence on the degree of disorder remains poorly understood. Here, we study the effect of varying concentrations of missing bonds on crack propagation of an otherwise perfect two-dimensional triangular network of springs. For a given network with a fixed concentration of missing bonds, the apparent fracture energy increases with crack advance . This behavior can be…
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