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|Title:||Multi-objective optimization of the kinematic parameters of fish-like swimming using a genetic algorithm method||Authors:||Esfahani, Mahdi Abolfazli
Karbasian, Hamid Reza
Kim, Kyung Chun
|Keywords:||Engineering::Electrical and electronic engineering||Issue Date:||2018||Source:||Esfahani, M. A., Karbasian, H. R. & Kim, K. C. (2018). Multi-objective optimization of the kinematic parameters of fish-like swimming using a genetic algorithm method. Journal of Hydrodynamics, 31(2), 333-344. https://dx.doi.org/10.1007/s42241-018-0160-0||Journal:||Journal of Hydrodynamics||Abstract:||This paper investigates the kinematic optimization of fish-like swimming. First, an experiment was performed to detect the motion of the fish tail foil of a fish robot. Next, the kinematic swimming model was verified experimentally using an image processing method. The model includes two rotational motions: caudal foil motion and foil-pitching motion. The kinematic model allows us to evaluate the influence of motion trajectory in the optimization process. To optimize the propulsive efficiency and thrust, a multi-objective genetic algorithm was employed to handle with kinematic, hydrodynamic, and propulsion models. The results show that the caudal length has a significant effect on the performance of the flapping foil in fish-like swimming, and its influence on the motion trajectory may increase the propulsive efficiency to as high as 98% in ideal conditions. The maximum thrust coefficient can also reach approximately 3 in ideal conditions.||URI:||https://hdl.handle.net/10356/152193||ISSN:||1001-6058||DOI:||10.1007/s42241-018-0160-0||Rights:||© 2019 China Ship Scientific Research Center. All rights reserved.||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||EEE Journal Articles|
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