Designing ship hull forms using generative adversarial networks

Kazuo Yonekura; Kotaro Omori; Xinran Qi; Katsuyuki Suzuki

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arXiv · 2311.05470

Designing ship hull forms using generative adversarial networks

Kazuo Yonekura·Kotaro Omori·Xinran Qi·Katsuyuki Suzuki

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Abstract

We proposed a GAN-based method to generate a ship hull form. Unlike mathematical hull forms that require geometrical parameters to generate ship hull forms, the proposed method requires desirable ship performance parameters, i.e., the drag coefficient and tonnage. The requirements of ship owners are generally focused on the ship performance and not the geometry itself. Hence, the proposed model is useful for obtaining the ship hull form based on an owner's requirements. The GAN model was trained using a ship hull form dataset generated using the generalized Wigley hull form. The proposed method was evaluated through numerical experiments and successfully generated ship data with small errors.

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Kazuo Yonekura, Kotaro Omori, Xinran Qi, Katsuyuki Suzuki. 2023-11-09. Designing ship hull forms using generative adversarial networks. https://arxiv.org/abs/2311.05470

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