Abstract
Optimisation of fish shape and swim mode is attempted in fully-resolved flow fields by genetic algorithm (GA) facilitated by efficient prediction method of target functions. Arbitrary Lagrangian Eulerian method is employed for solving the flow field around the moving 2-D fish swimming by undulatory motion propagating from head to tail tip. The fish performance is optimised with characteristic five parameters for targeting maximum cruising speed. For identifying the average cruising speed (in steady swimming state), a least square prediction (LSP) method is developed. The LSP is found to effectively reduce the computation time spent for searching the optimal solutions in the above GA process. The results demonstrate the capability of our method for efficiently solving this type of optimisation problem including the surrounding fully resolved flow field in a feasible computational time.
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Takeuchi, S., Kusuda, S., Kajishima, T. (2008). Optimisation of Fish Shape and Swim Mode in Fully Resolved 2-D Flow Field by Genetic Algorithm with the Least Square Prediction Method. In: Kato, N., Kamimura, S. (eds) Bio-mechanisms of Swimming and Flying. Springer, Tokyo. https://doi.org/10.1007/978-4-431-73380-5_13
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DOI: https://doi.org/10.1007/978-4-431-73380-5_13
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-73379-9
Online ISBN: 978-4-431-73380-5
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