Chinese Journal of Ship Research, Volume. 19, Issue 6, 108(2024)

Topology optimization analysis of VLCC transverse web based on UNet deep learning

Zhenrong LI1...2, Lijuan XIA1,2, and Shuo FENG12 |Show fewer author(s)
Author Affiliations
  • 1State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • 2School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
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    Objective

    This paper proposes a hull transverse web topology optimization method based on UNet for application in the optimization design of complex ship structures.

    Methods

    Taking the transverse web of a very large crude carrier (VLCC) as the research object, a UNet topology optimization surrogate model is first created according to optimization mathematical principles. The finite element grid physical quantity is then mapped to the tensor to obtain the dataset for model training. Finally, the intersection over union (IoU) method is used to evaluate the training results, and the method is compared with the solid isotropic material with penalization (SIMP) method in terms of topology configuration.

    Results

    The results show that this method can quickly output the material layout of the design domain, and compared with SIMP topology optimization, it can obtain the topology configuration more efficiently.

    Conclusion

    The proposed topology optimization method can provide a new design method for ship transverse web structures.

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    Zhenrong LI, Lijuan XIA, Shuo FENG. Topology optimization analysis of VLCC transverse web based on UNet deep learning[J]. Chinese Journal of Ship Research, 2024, 19(6): 108

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    Paper Information

    Category: Theory and Method of Intelligent Design for Ship and Ocean Engineering

    Received: Sep. 11, 2023

    Accepted: --

    Published Online: Mar. 14, 2025

    The Author Email:

    DOI:10.19693/j.issn.1673-3185.03553

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