Title: Multi-objective optimisation of micromixer design using genetic algorithms and multi-criteria decision-making algorithms

Authors: Eduardo Henrique Taube Cunegatto; Flávia Schwarz Franceschini Zinani; Sandro José Rigo

Addresses: Polytechnic School, Universidade do Vale do Rio dos Sinos (UNISINOS), Av. Unisinos 950, 93022-000 São Leopoldo, Brazil ' Institute of Hydraulic Research (IPH), Universidade Federal do Rio Grande do Sul (UFRGS), Av. Bento Gonçalves 9500, 91501-970 Porto Alegre, Brazil ' Polytechnic School, Universidade do Vale do Rio dos Sinos (UNISINOS), Av. Unisinos 950, 93022-000 São Leopoldo, Brazil

Abstract: This work employed the constructal design method (CDM) to optimise a micromixer's shape. The micromixer had five degrees of freedom, optimised to maximise the mixing ratio and minimise the pressure drop across it, for Peclet numbers equal to 250, 500, and 1,000. Computational fluid dynamics (CFD) was used for simulations that generated second-order metamodels, employed within the NSGA-II algorithm for multi-objective optimisation. Upon defining the best set of solutions, multi-criteria decision-making algorithms aided in choosing solutions that would meet the objectives, namely LINMAP, TOPSIS, and VIKOR. Our analysis revealed that shapes with the highest mixing ratios also exhibited the highest pressure drops, with the VIKOR algorithm favouring this trade-off. Conversely, TOPSIS solutions tended to minimise pressure drop and mixing ratios, while LINMAP solutions fell between these extremes. This integrated approach provided a curated selection of optimal choices, a crucial advantage given the many potential solutions inherent in passive micromixer design.

Keywords: micromixer; multi-objective optimisation; genetic algorithm; constructal design; computational fluid dynamics; CFDs; multi-criteria decision algorithm; MCDA; microfluidics; mass transfer; evolutionary design.

DOI: 10.1504/IJHM.2024.140573

International Journal of Hydromechatronics, 2024 Vol.7 No.3, pp.224 - 249

Received: 23 Oct 2023
Accepted: 11 Jan 2024
Published online: 23 Aug 2024 *

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