Extending the CFD-DEM coupling algorithm to accurately predict the particle separation in a two-phase air–solid particle flow through an aerofall AG mill

Abstract

One idea to reduce the energy consumption in grinding ore in mineral processing operations is to carefully consider this point during the procedures leading to design of the AG mill system. The CFD simulation methods can greatly help to achieve optimum designs. However, the complex interaction between airflow and solid particle makes serious challenges for the corresponding computational fluid dynamics (CFD) workers. To provide more accurate CFD tools for the researchers/designers, this work benefits from the original capabilities of the CFD and discrete element modeling (DEM) methods and extends a new CFD-DEM coupling algorithm to accurately predict the complex interaction between the two air and solid particles phases. Literature shows that all past CFD-DEM research works have used the CFD-DEM algorithm to simulate the interaction between the slurry/water and the solid particles in two-phase flow simulations such as the wet grinding. Indeed, they neglected the influence of airflow through the AG mill. In contrary, this work uses the CFD method to solve the fluid flow part and the DEM to anticipate the motion and interactions of individual particles with each other and with the corresponding airflow. To validate the results of the CFD and DEM parts, a scaled laboratory AG mill is investigated and the achieved results are compared with experimental data. The comparison shows that the present algorithm accurately predicts the general solid particles’ motion and individual particle trajectory behavior. Eventually, the extended algorithm is used to 1- simulate an actual aerofall AG mill in different working conditions and 2- suggest the suitable working conditions, which can lead to the highest AG mill performances.