Multi-Objective Optimizations of a Serpentine Micromixer with Crossing Channels at Low and High Reynolds Numbers

Abstract

In order to maximize the mixing performance of a micromixer with an integrated three-dimensional serpentine and split-and-recombination configuration, multi-objective optimizations were performed at two different Reynolds numbers, 1 and 120, based on numerical simulation. Numerical analyses of fluid flow and mixing in the micromixer were performed using three-dimensional Navier-Stokes equations and convection-diffusion equation. Three dimensionless design variables that were related to the geometry of the micromixer were selected as design variables for optimization. Mixing index at the exit and pressure drop through the micromixer were employed as two objective functions. A parametric study was carried out to explore the effects of the design variables on the objective functions. Latin hypercube sampling method as a design-of-experiment technique has been used to select design points in the design space. Surrogate modeling of the objective functions was performed by using radial basis neural network. Concave Pareto-optimal curves comprising of Pareto-optimal solutions that represents the trade-off between the objective functions were obtained using a multi-objective genetic algorithm at Re = 1 and 120. Through the optimizations, maximum enhancements of 18.8% and 6.0% in mixing index were achieved at Re = 1 and 120, respectively.

Characterization of Machined Surface Topography Based on the Normal Declination Angle of Microfacets

“…The genetic algorithm (GA) was herein adopted to confirm the characterization model parameters. GA is a global searching method based on biological natural selection and natural genetic mechanism, and the global optimal solution is found in the process of evaluating multiple solutions [22]. In the process of using genetic algorithm to solve the problem, the objective function and variables of the problem should be determined first, then some individuals should be initialized, and finally the optimal solution can be found through iteration.…”

Mixing Performance of a Cost-effective Split-and-Recombine 3D Micromixer Fabricated by Xurographic Method

“…Various methods have been developed to assist passive mixing based on their specific features, briefly listed as: Spiral micromixers [12,13,14], zigzag-shaped channels [15], T-shaped mixers [16], floor-grooved channels [17,18], herringbone mixers [19,20], obstacle-based mixers [21], convergent-divergent walls [22], split and recombine (SAR) mixers [23,24,25,26,27,28,29] and lamination-based mixers [20,30,31]. All of the above-mentioned methods may be used in both planar [12,15,21,22,23,25,28,32] or three-dimensional (3D) [13,14,16,17,18,19,20,24,26,27,29,30,31] systems. 3D passive micromixers typically benefit from spatial structures to generate more effective vortices.…”

Editorial for the Special Issue on Passive Micromixers

“…The important areas being focused upon are the numerical and experimental analyses of flow and mixing in different micromixers [1,2,3,4,5], optimization [6,7,8], and fabrication of micromixers [9]. In the review paper [10], recent developments in both active and passive micromixers are summarized and discussed.…”

“…Computational fluid dynamics (CFD) analysis of flow and mixing is seen as an important tool in designing passive micromixers in eight research articles [1,2,3,4,5,6,7,8]. Javaid et al [1] proposed a serpentine-shaped micromixer with sinusoidal walls and conducted a CFD analysis using COMSOL Multiphysics software.…”

“…The Taguchi method was found to be robust in determining the optimum combination of the design parameters. Raza et al [7] carried out multi-objective optimization of a serpentine micromixer with crossing channels at low and high Reynolds numbers. Pareto-optimal fronts representing the trade-off between conflicting objectives, mixing index and pressure drop were obtained for both low and high Reynolds numbers.…”