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http://dx.doi.org/10.1016/j.ijnaoe.2017.12.005

Hydrofoil optimization of underwater glider using Free-Form Deformation and surrogate-based optimization  

Wang, Xinjing (School of Marine Science and Technology, Northwestern Polytechnical University)
Song, Baowei (School of Marine Science and Technology, Northwestern Polytechnical University)
Wang, Peng (School of Marine Science and Technology, Northwestern Polytechnical University)
Sun, Chunya (School of Marine Science and Technology, Northwestern Polytechnical University)
Publication Information
International Journal of Naval Architecture and Ocean Engineering / v.10, no.6, 2018 , pp. 730-740 More about this Journal
Abstract
Hydrofoil is the direct component to generate thrust for underwater glider. It is significant to improve propulsion efficiency of hydrofoil. This study optimizes the shape of a hydrofoil using Free-Form Deformation (FFD) parametric approach and Surrogate-based Optimization (SBO) algorithm. FFD approach performs a volume outside the hydrofoil and the position changes of control points in the volume parameterize hydrofoil's geometric shape. SBO with adaptive parallel sampling method is regarded as a promising approach for CFD-based optimization. Combination of existing sampling methods is being widely used recently. This paper chooses several well-known methods for combination. Investigations are implemented to figure out how many and which methods should be included and the best combination strategy is provided. As the hydrofoil can be stretched from airfoil, the optimizations are carried out on a 2D airfoil and a 3D hydrofoil, respectively. The lift-drag ratios are compared among optimized and original hydrofoils. Results show that both lift-drag-ratios of optimized hydrofoils improve more than 90%. Besides, this paper preliminarily explores the optimization of hydrofoil with root-tip-ratio. Results show that optimizing 3D hydrofoil directly achieves slightly better results than 2D airfoil.
Keywords
Underwater glider; Hydrofoil; Surrogate-based optimization; Adaptive parallel sampling approach;
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