Experimental and Numerical Investigation on the Scaling-Up of Microsieve Dispersion Mixers

Abstract

Scaling-up is a significant topic for micromixers and their industrialized applications. In this work, the scaling-up of microsieve dispersion mixers (MDMs) is systematically investigated. Two scaling-up ways, including sizing-up of the main channel or the microsieve and numbering-up of microsieves, are studied. The mixing performance is characterized by experiments as well as CFD simulation. The results show that the preference of sizing-up dimensions to optimize the micromixing performance at a low flow rate ratio (R, R = 1) is contrary to that of a high R (R = 8) for both sizing-up choices. Numbering-up of microsieves is superior to sizing-up of microsieves, and numbering up in the l 1 direction is preferred. Equivalent micromixing performance can be maintained as long as the Reynolds number is kept constant during scaling-up. Two flow patterns including unrestricted and restricted flows are observed, which account for the difference in micromixing performance, and are distinguished by a dimensionless number. A mathematical model is established and used to predict the micromixing performance. Moreover, a design procedure for scaling up of MDMs is proposed.

Micromixing Performance and Residence Time Distribution in a Miniaturized Magnetic Reactor: Experimental Investigation and Machine Learning Modeling

“…As the mixing quality of a mixer is influenced by many operational and structural parameters, it is significant to model the relationship between the mixing quality and main design parameters. Exponential expressions , and mechanistic models − have been widely used in the modeling of micromixers. Factor contribution can be clearly reflected in exponential expressions, but the rather simple form is unable to correctly predict the mixing performance in many circumstances as the mixing process is normally highly nonlinear and complex.…”