Single and Multi-Objective Optimization of a Three-Dimensional Unbalanced Split-and-Recombine Micromixer.

Wasim Raza,Sang-Bum Ma,Kwang-Yong Kim

doi:10.3390/mi10100711

Abstract

The three-dimensional geometry of a micromixer with an asymmetrical split-and-recombine mechanism was optimized to enhance the fluid-mixing capability at a Reynolds number of 20. Single and multi-objective optimizations were carried out by using particle swarm optimization and a genetic algorithm on a modeled surrogate surface. Surrogate modeling was performed using the computational results for the mixing. Mixing and flow analyses were carried out by solving the convection–diffusion equation in combination with the three-dimensional continuity and momentum equations. The optimization was carried out with two design variables related to dimensionless geometric parameters. The mixing effectiveness was chosen as the objective function for the single-objective optimization, and the pressure drop and mixing index at the outlet were chosen for the multi-objective optimization. The sampling points in the design space were determined using a design of experiment technique called Latin hypercube sampling. The surrogates for the objective functions were developed using a Kriging model. The single-objective optimization resulted in 58.9% enhancement of the mixing effectiveness compared to the reference design. The multi-objective optimization provided Pareto-optimal solutions that showed a maximum increase of 48.5% in the mixing index and a maximum decrease of 55.0% in the pressure drop in comparison to the reference design.

Highlights

Microfluidics is rapidly emerging for precise control and manipulating fluids in microscale channels, and has found a wide range of applications in bioengineering, the chemical industry, and environmental monitoring [1,2,3]
The numerical diffusion coefficient was 1.04 × 10−8 m2/s. This value is higher than the value of the molecular diffusion coefficient, the grid on further refinement shows a negligible change in the mixing index. This indicates that the mixing index changes negligibly with further reduction in the numerical diffusion, because the numerical diffusion coefficient is proportional to the mesh size
Single and multi-objective optimizations of a 3D-ASAR micromixer were performed at Reynolds number of 20, using surrogate modeling in conjunction with mixing and flow analyses

Summary

Introduction

Microfluidics is rapidly emerging for precise control and manipulating fluids in microscale channels, and has found a wide range of applications in bioengineering, the chemical industry, and environmental monitoring [1,2,3]. Successful completion of the applications requires rapid and efficient mixing, but microfluidic systems exhibit laminar flow characteristics due to their operation at low Reynolds numbers. Over the past two decades, various passive micromixer designs [4,5] have been proposed based on mixing strategies such as parallel/sequential lamination [6,7], hydrodynamic focusing [8], and chaotic advection [9]. Combinations of these strategies can be employed [10,11]. Sharp bends formed by the channel edges and triangular baffles created corner vortices and Dean vortices that promoted chaotic advection and enhanced mixing

Methods

Results

Conclusion