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Optimization of Helical Microreactors by a Genetic Algorithm Technique
Author(s) -
Beigzadeh Reza,
Izadi Mahtab,
Rahimi Masoud
Publication year - 2020
Publication title -
chemical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.403
H-Index - 81
eISSN - 1521-4125
pISSN - 0930-7516
DOI - 10.1002/ceat.202000301
Subject(s) - microreactor , pressure drop , micromixing , curvature , drop (telecommunication) , materials science , genetic algorithm , mixing (physics) , mechanics , chemistry , mechanical engineering , microfluidics , engineering , mathematics , physics , nanotechnology , geometry , mathematical optimization , biochemistry , quantum mechanics , catalysis
Micromixing in coiled microreactors is attained by a higher pressure drop and more pumping power. The optimum geometries of helically coiled microreactors were determined by multiobjective optimization based on a genetic algorithm (GA). The segregation index ( X s ) values of the Villermaux/Dushman reaction were measured in twelve coiled microchannels. The effects of the geometries including curvature diameter and coil pitch on the mixing performance and pressure drop were investigated. The mixing performance of the microreactors and the pressure drop were considered as the GA objectives. The optimum geometries of the studied coiled microchannels with a trade‐off between X s and friction factors were obtained using GA‐based multiobjective optimization.