Optimization of micromixer with Cantor fractal baffle based on simulated annealing algorithm

Honglin Lv, Xueye Chen and Xiangwei Zeng

Chaos, Solitons & Fractals, 2021, vol. 148, issue C

Abstract: To maximize the mixing performance of the micromixer with the Cantor fractal baffle structure, single-objective optimization of the micromixer with different Reynolds (Res) is carried out. The three-dimensional Navier-Stokes equation is used to numerically analyze the fluid flow and mixing in the micromixer. We choose three parameters related to the geometry of the Cantor fractal baffle inside the microchannel as the best design variables. The mixing index at the outlet of the micromixer is used as the objective function. And conduct parameter studies to explore the influence of the design variables on the objective function. For the parameter study of the design space, the Latin hypercube sampling (LHS) method is used as an experimental design technique. It is used to select design points in the design space. We use surrogate modeling of response surface functions to approximate the objective function. When Re is different, the simulated annealing algorithm is used to optimize the objective of the established surrogate modeling, and finally the optimal structure configuration of the micromixer is obtained. In this article, we combine the fractal principle with the simulated annealing algorithm to improve the mixing performance of the micromixer. This is not involved in previous studies. The results show that the mixing performance of the optimized micromixer has indeed been significantly improved. When Re = 0.1, 1, 10, and 100, the mixing efficiency of the optimized micromixer is increased by 7.64%, 17.75%, 14.08%, and 0.91%, respectively, compared with the reference design.

Keywords: Cantor structure; Micromixer; Surrogate modeling; Optimization; Simulated annealing algorithm; Pressure drop (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077921004021
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:148:y:2021:i:c:s0960077921004021

DOI: 10.1016/j.chaos.2021.111048

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().