A structural optimization model of a biochemical detection micromixer based on RSM and MOEA/D

Abstract

Microfluidic mixers are widely applied in biochemical detection experiments. In this study, based on the compact rectangular baffle structure, the structural optimization is performed from the perspectives of baffle length and angle parameters. To shorten the optimization time and reduce the cost of simulation calculation, the response surface method (RSM) is adopted. In the optimization process, different indicators of mixing effects have contradictory objectives and it is prone to generate local optimal solutions of design parameters of the baffle. Therefore, the multi-objective evolutionary algorithm based on decomposition (MOEA/D) is introduced to obtain the Pareto solution set of the optimal baffle parameters. The results of biochemical detection simulation experiments indicated that when the length of the baffle is 140μm, the degree of asymmetry of the velocity curve is the largest and the detection sensitivity is the highest. When the baffle angle is between 60∘ and 80∘, the microchannel fluid can generate obvious vortices near the baffle and reduce the pressure drop. The MOEA/D algorithm obtains a set of rectangular baffle parameters (l=140μm; θ=61.5°). The structural optimization model can improve the concentration distribution level and reduce the pressure drop and the mixed energy cost.