English

Scaling theory for the statistics of slip at frictional interfaces

Disordered Systems and Neural Networks 2022-12-21 v2 Soft Condensed Matter

Abstract

Slip at a frictional interface occurs via intermittent events. Understanding how these events are nucleated, can propagate, or stop spontaneously remains a challenge, central to earthquake science and tribology. In the absence of disorder, rate-and-state approaches predict a diverging nucleation length at some stress σ\sigma^*, beyond which cracks can propagate. Here we argue for a flat interface that disorder is a relevant perturbation to this description. We justify why the distribution of slip contains two parts: a powerlaw corresponding to `avalanches', and a `narrow' distribution of system-spanning `fracture' events. We derive novel scaling relations for avalanches, including a relation between the stress drop and the spatial extension of a slip event. We compute the cut-off length beyond which avalanches cannot be stopped by disorder, leading to a system-spanning fracture, and successfully test these predictions in a minimal model of frictional interfaces.

Keywords

Cite

@article{arxiv.2204.02795,
  title  = {Scaling theory for the statistics of slip at frictional interfaces},
  author = {Tom W. J. de Geus and Matthieu Wyart},
  journal= {arXiv preprint arXiv:2204.02795},
  year   = {2022}
}