Multi-objective optimization of a novel vortex finder for performance improvement of cyclone separator

Abstract

This study proposed a multi-objective optimization of novel vortex finder, called Slotted Vortex Finder (SVF), applied in the Stairmand cyclone separator, to obtain a most appropriate geometric configuration for performance improvement as the Stairmand cyclone separator had been widely used in industry for dust removal since last century. The Optimal Latin Hypercube Sampling (OLHS) method was utilized to conduct design of experiment for four significant design variables, including slot number (Ls), slot length (N), span angle (alpha) and inclination angle (beta). Computational Fluid Dynamics (CFD) and Response Surface Model (RSM) were adopted to get precise output response and construct accurate fitness functions between design variables and objectives. Multi -objective Genetic algorithm was employed to find out the best solution with maximum collection efficiency and minimum Euler number based on the well-constructed fitness functions. The finally selected optimal model provided Euler number reduction of 34.51%, collection efficiency increasing of 4.32% and cut off size reduction of 5.53%, compared with original model. The obtained optimal geometry shape of novel vortex finder could be used as an effective reference for industrial factories to gain enough considerable cyclone performance improvement and high economic benefits by making only small modifications on the in-using cyclone separator.