Classification of Ultrafine Particles Using a Novel 3D-Printed Hydrocyclone with an Arc Inlet: Experiment and CFD Modeling

Ultrafine particle classification can be realized using hydrocyclones with novel structures to overcome the limitations of conventional hydrocyclones with tangential inlets or cone structures. Herein, the hydrocyclones with different inlet structures and cone angles were investigated for classifying ultrafine particles. Computational fluid dynamics (CFD) simulations were performed using the Eulerian-Eulerian method, and ultrafine MnO2 powder was used as a case study. The simulation results show a fine particle (<= 5 mu m) removal efficiency of 0.89 and coarse particle (>5 mu m) recovery efficiency of 0.99 for a hydrocyclone design combining an arc inlet and a 30 degrees cone angle under a solid concentration of 2.5 wt %. Dynamic analysis indicated that the novel arc inlet provided a preclassification effect to reduce the misplacement of fine/coarse particles, which cannot be provided by conventional tangential or involute inlets. Furthermore, the proposed design afforded comprehensive improvement in the flow field by regulating the residence time and radial acceleration. Subsequently, a novel hydrocyclone with an arc inlet and 30 degrees cone angle was manufactured using the three-dimensional (3D) printing technology. Experiments were conducted for classifying ultrafine MnO2 particles using the novel 3D-printed hydrocyclone and conventional hydrocyclone. The results demonstrate that the classification performance of the 3D-printed hydrocyclone was superior to that of the conventional one, in particular, the removal efficiency of fine particles from 0.719 to 0.930 using a 10 wt % feed slurry.

Automated summary

Ultrafine particle classification can be achieved using hydrocyclones with novel structures. Computational fluid dynamics simulations were performed to optimize the design, and a hydrocyclone combining an arc inlet and a 30 degrees cone angle showed promising results in removing fine particles and recovering coarse particles. A 3D-printed hydrocyclone with the same design exhibited superior classification performance compared to a conventional hydrocyclone when classifying ultrafine MnO2 particles.