Analytical and Numerical Wear Modeling of Metallic Interfaces: A Statistical Asperity Approach

Abstract

Prediction of the wear rate based on fundamental material properties is to date an elusive goal due to the nonlinearity of wear mechanisms, the stochastic nature of the surface morphology, and the multiscale nature of the phenomenon. In the present work, a previously developed dual-scale model that addresses the above issues by employing single-asperity interactions at the microscale and the interaction between stochastic surface morphologies at the macroscale is applied. The microscale model can be analytical, based on slip-line field theory; semi-empirical, based on generalizing the observed mechanisms; or numerical, based on the mesh-free smooth particle hydrodynamics method. The macroscale model transforms the surface topography into a multivariate distribution of asperity parameters and maps the microscale model's response; then it simulates the wear process via a Monte Carlo simulation by querying the map and integrating over the interface to maintain a load-separation equilibrium. The multiscale model is applied to the case of abrasive and adhesive wear of mild steel, and the results corresponding to various analytical and numerical microscale models are compared.