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

被引:0
作者
Cunegatto, Eduardo Henrique Taube [1 ]
Zinani, Flavia Schwarz Franceschini [2 ]
Rigo, Sandro Jose [1 ]
机构
[1] Univ Vale Rio dos Sinos UNISINOS, Polytech Sch, Ave Unisinos 950, BR-93022000 Sao Leopoldo, Brazil
[2] Univ Fed Rio Grande do Sul UFRGS, Inst Hydraul Res IPH, Ave Bento Goncalves 9500, BR-91501970 Porto Alegre, Brazil
关键词
micromixer; multi-objective optimisation; genetic algorithm; constructal design; computational fluid dynamics; CFDs; multi-criteria decision algorithm; MCDA; microfluidics; mass transfer; evolutionary design; ENHANCED MIXING EFFICIENCY; CONSTRUCTAL DESIGN; HEAT-TRANSFER; FLOW; CFD; CHAMBER;
D O I
10.1504/IJHM.2024.140573
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
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.
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页码:224 / 249
页数:27
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