Development of a DEM method for predicting wear distribution on particle scale

Abstract

Wear is a complex and frequently observed phenomenon in industrial processes. In past studies, the equipment wear has been the major focus for researchers, while particle wear and its distribution have received less attention. However, in processes such as grinding, mass finishing, and polishing, understanding particle wear and its distribution is equally important. Predicting particle wear and its distribution can help predict shape changes during processing and guide production to improve economic efficiency. In this study, a method combining an energy-based wear model IEEM (Impact Energy erosion model) and an intersection algorithm is proposed to obtain the wear distribution within the DEM (Discrete Element Method) framework. The accuracy of the method is validated by the comparison between experiments and corresponding simulations, where the experiment is conducted on cube workpieces using a laboratory-scale planetary ball mill under wet conditions. Furthermore, the influence of particle shape on the wear distribution is investigated by DEM simulations.