GPU-enhanced DEM analysis of flow behaviour of irregularly shaped particles in a full-scale twin screw granulator

However, how particle shape impacts the conveying characteristics during TSG is not explored nor well understood. In this study, a graphic processor units (GPUs) enhanced discrete element method (DEM) is adopted to examine the effect of particle shape on the conveying characteristics in a full scale twin screw granulator for the first time.

It is found that, TSG with spherical particles has the smallest particle retention number, mean residence time, and power consumption; while for Hexp shaped particles the largest particle retention number is obtained, and TSG with cubic particles requires the maximum power consumption. Furthermore, spherical particles exhibit a flow pattern closer to an ideal plug flow, while cubic particles present a flow pattern approaching a perfect mixing.