POD-based identification approach for powder mixing mechanism in Eulerian–Lagrangian simulations

Abstract

Numerous products are manufactured through powder mixing. Understanding the mixing mechanism is essential to improve product quality. Convection, diffusion, and shear are well-known classifications in the powder mixing mechanism. During powder mixing, plural mixing mechanisms may occur simultaneously. In this study, to identify the main mixing mechanisms and investigate the transition of the main mixing mechanisms, an advanced identification technique is developed by incorporating the proper orthogonal decomposition (POD) method into numerical modeling for powder mixing. The discrete element method (DEM) coupled with computational fluid dynamics (CFD) is employed to simulate powder mixing. Several investigations are performed to show the adequacy of the developed technique. First, numerous CFD–DEM simulations for solid–liquid flows are performed in a rotating paddle mixer. Next, an efficient Lanczos-based POD (LPOD) method is proposed to characterize the main features of powder mixing via the POD analysis. The results show that the mixing mechanism is dominated by convection in the early stage and by diffusion in the late stage. Besides, a novel mixing identification technique is established by giving the relation between POD modes and mixing mechanisms, namely, clumped and random spatial distributions of the POD modes appear in convective and diffusive mixing, respectively. Consequently, it is shown that combining the CFD–DEM simulation with the LPOD method is effective to identify the main mixing mechanism and to explain the time transition of mixing mechanisms between convective and diffusive mixing.