A lattice Monte Carlo model for solid particle erosion: An application to brittle fracture.

Abstract Erosion caused by repeated impact of solid particles entrained in a moving fluid is relevant for many technical applications like resulting wear and reduced service life of turbine blades, propellers and valves. In this work, a lattice Monte Carlo model for erosion of a class of glass submitted to impact of alumina particles reproduces and enhances experimental and simulation results described in Jafar et al., Wear 303, no. 1 (2013): 302–312. The lattice Monte Carlo model of solid particle erosion (LMC-SPE model) is based on a three dimensional representation of the target surface by a cubic lattice, where each cell embodies a small portion of the material susceptible of damage accumulation (in this case, brittle fracture) and subsequent removal. The simulation is driven by a kinetic Monte Carlo method where individual impacts can be generated according to probability distributions of experimental parameters (for example, size, velocity and spatial distributions of particles). In addition, a phenomenological model of the interaction of impacting particles with an already eroded and rough surface is introduced in order to correct unrealistic large final surface roughness and erosion rates obtained otherwise. In spite of its simplicity, the LMC-SPE model can simulate the main topographic features of individual impacts and reproduce correctly dependencies of the erosion rate on velocity, size, and impact angle of the particles. Consequently roughening regimes due to the accumulative effect of thousands of individual impacts acting on relatively large areas are simulated within reasonable computational times. Due to its three dimensional character, LMC-SPE simulations can be compared directly with channels obtained with abrasive jet micro-machining techniques (AJM) described in literature. Highlights • The LMC-SPE model simulates millions of particle impacts on a brittle surface. • Monte Carlo algorithms reproduce statistical distributions of experimental parameters. • Local roughness and accumulated damage are taken into account to reproduce experiments. • Topography and roughness of simulations can be compared with micro-machined surfaces. [ABSTRACT FROM AUTHOR]