Model-based experimental data evaluation of separation efficiency of multistage coarse particle classification in a zigzag apparatus

Abstract

In most industrial processes dealing with particles, separation of fine (or light) and coarse (or heavy) particles in a fluid flow is an essential part to obtain the required product quality. These separation processes are typically designed based on the particles' terminal settling velocity as the dominant property. In this work, sand and gravel have been selected as suitable model grains representing mineral and agricultural raw materials and products. The terminal settling velocity depends on stochastically distributed physical and granulometric particle properties like size, density, and shape. Separation experiments in a pilot-scale zigzag separator have been performed using different channel velocities and solid mass loadings in order to improve the understanding of the separation process in this complex turbulent flow. Then, classification has been modeled as a multistage cross-flow separation process in a turbulent air flow. Performance has been analyzed and discussed with respect to separation functions and characteristic parameters like cut size, separation sharpness, separation stage utilization, and product quality, quantified by cumulative product purities of over- and underflow as well as specific energy consumption. Finally, a SMART analysis has been used to identify optimal process parameters. The obtained cut sizes differ significantly from those found in literature. Thus, a more detailed analysis accounting for aerodynamics and turbulence is developed to show the significant influence of channel geometry on separation efficiency.