| Autor: |
Wenhui Li, Kang Liu, Qinghua Guo, Zhiming Zhang, Qiaoling Ji, Zijun Wu |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Frontiers in Bioengineering and Biotechnology, Vol 9 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2296-4185 |
| DOI: |
10.3389/fbioe.2021.781614 |
| Popis: |
This paper proposes an optimization paradigm for structure design of curved-tube nozzle based on genetic algorithm. First, the mathematical model is established to reveal the functional relationship between outlet power and the nozzle structure parameters. Second, genetic algorithms transform the optimization process of curved-tube nozzle into natural evolution and selection. It is found that curved-tube nozzle with bending angle of 10.8°, nozzle diameter of 0.5 mm, and curvature radius of 8 mm yields maximum outlet power. Finally, we compare the optimal result with simulations and experiments of the rotating spinning. It is found that optimized curved-tube nozzle can improve flow field distribution and reduce the jet instability, which is critical to obtain high-quality nanofibers. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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