Optimization of passive grooved micromixers based on genetic algorithm and graph theory Article Swipe
Mitsuo Yoshimura
,
Koji Shimoyama
,
Takashi Misaka
,
Shigeru Obayashi
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1007/s10404-019-2201-6
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1007/s10404-019-2201-6
This paper proposes a novel approach for fluid topology optimization using genetic algorithm. In this study, the enhancement of mixing in the passive micromixers is considered. The efficient mixing is achieved by the grooves attached on the bottom of the microchannel and the optimal configuration of grooves is investigated. The grooves are represented based on the graph theory. The mixing performance is analyzed by a CFD solver and the exploration by genetic algorithm is assisted by the Kriging model to reduce the computational cost. The characteristics of the convex and the concave grooves are compared. To balance the global exploration and the reasonable computational cost, this paper investigates three cases with the convex grooves subject to constraint that differs in handling of design variables. In each case, genetic algorithm finds several local optima since the objective function is a multi-modal function, and these optima reveal the specific characteristic for efficient mixing. Moreover, this paper optimizes the micromixer with the concave grooves and reveals the different properties of the mixing. Finally, to guarantee the obtained solutions competitive, the sensitivity analysis is performed to the best solution in each case.
Related Topics
Concepts
Micromixer
Solver
Mixing (physics)
Genetic algorithm
Mathematical optimization
Computer science
Algorithm
Sensitivity (control systems)
Local optimum
Microchannel
Computational fluid dynamics
Mathematics
Materials science
Engineering
Mechanics
Physics
Quantum mechanics
Electronic engineering
Nanotechnology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s10404-019-2201-6
- https://link.springer.com/content/pdf/10.1007/s10404-019-2201-6.pdf
- OA Status
- hybrid
- Cited By
- 30
- References
- 59
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2911452806
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2911452806Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1007/s10404-019-2201-6Digital Object Identifier
- Title
-
Optimization of passive grooved micromixers based on genetic algorithm and graph theoryWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-02-05Full publication date if available
- Authors
-
Mitsuo Yoshimura, Koji Shimoyama, Takashi Misaka, Shigeru ObayashiList of authors in order
- Landing page
-
https://doi.org/10.1007/s10404-019-2201-6Publisher landing page
- PDF URL
-
https://link.springer.com/content/pdf/10.1007/s10404-019-2201-6.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
- OA URL
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https://link.springer.com/content/pdf/10.1007/s10404-019-2201-6.pdfDirect OA link when available
- Concepts
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Micromixer, Solver, Mixing (physics), Genetic algorithm, Mathematical optimization, Computer science, Algorithm, Sensitivity (control systems), Local optimum, Microchannel, Computational fluid dynamics, Mathematics, Materials science, Engineering, Mechanics, Physics, Quantum mechanics, Electronic engineering, NanotechnologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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30Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 8, 2023: 3, 2022: 5, 2021: 5Per-year citation counts (last 5 years)
- References (count)
-
59Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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