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Multi-objective optimization of the kinematic parameters of fish-like swimming using a genetic algorithm method

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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.

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Acknowledgments

This research was supported by the International Research and Development Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT of Korea (NRF-2017K1A3A1A30084513) and partial support was also obtained from the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (Grant Nos. 2011-0030013, 2018R1A2B2007117).

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Nanyang Technological University, Nanyang, Singapore

    Mahdi Abolfazli Esfahani

  2. School of Mechanical Engineering, Pusan National University, Pusan, 46241, Korea

    Hamid Reza Karbasian & Kyung Chung Kim

Authors
  1. Mahdi Abolfazli Esfahani
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  2. Hamid Reza Karbasian
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  3. Kyung Chung Kim
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Correspondence to Kyung Chung Kim.

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Biography: Mahdi Abolfazli Esfahani (1993-), Male, Ph. D. Candidate

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Esfahani, M.A., Karbasian, H.R. & Kim, K.C. Multi-objective optimization of the kinematic parameters of fish-like swimming using a genetic algorithm method. J Hydrodyn 31, 333–344 (2019). https://doi.org/10.1007/s42241-018-0160-0

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  • DOI: https://doi.org/10.1007/s42241-018-0160-0

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