李振荣, 夏利娟, 冯朔. 基于UNet深度学习的VLCC横框架拓扑优化研究[J]. 中国舰船研究. DOI: 10.19693/j.issn.1673-3185.03553
引用本文: 李振荣, 夏利娟, 冯朔. 基于UNet深度学习的VLCC横框架拓扑优化研究[J]. 中国舰船研究. DOI: 10.19693/j.issn.1673-3185.03553
Topology optimization of VLCC transverse web based on UNet[J]. Chinese Journal of Ship Research. DOI: 10.19693/j.issn.1673-3185.03553
Citation: Topology optimization of VLCC transverse web based on UNet[J]. Chinese Journal of Ship Research. DOI: 10.19693/j.issn.1673-3185.03553

基于UNet深度学习的VLCC横框架拓扑优化研究

Topology optimization of VLCC transverse web based on UNet

  • 摘要: 【目的】人工智能技术具备高效的数据处理能力,可以取代结构优化过程中繁琐的有限元迭代计算,为了将其应用于复杂船舶结构的优化设计,本文提出了基于UNet的船体横剖面拓扑优化方法。【方法】以某VLCC横剖面为研究对象,首先根据优化数学原理创建UNet拓扑优化代理模型;之后将有限元网格物理量映射为张量,获得供模型训练的数据集;最后采用了IOU方法对训练结果进行评估,并将该方法与SIMP法进行了拓扑构型对比。【结果】该拓扑优化方法能够快速输出设计域的材料布局,与SIMP拓扑优化相比,可以更加高效地获得船舶横剖面拓扑构型。【结论】所提出的拓扑优化方法可为船舶横剖面结构提供一种新型设计手段。

     

    Abstract: Objectives Artificial intelligence technology possesses efficient data processing capabilities, which can replace the tedious finite element iterative calculations in the process of structural optimization. In order to apply it to the optimization design of complex ship structures, this paper proposes a hull cross-section topology optimization method based on UNet. Methods Taking a VLCC transverse section as the research object, the UNet topology optimization surrogate model is first created according to the optimization mathematical principles; then the finite element grid physical quantity is mapped to the tensor to obtain the dataset for model training; finally, the IOU method is used to evaluate the training results, and the method is compared with the SIMP method in terms of topology configuration. Results This topology optimization method can quickly output the material layout of the design domain, and compared with SIMP topology optimization, it can obtain the ship transverse section topology configuration more efficiently. Conclusions The proposed topology optimization method can provide a new design method for ship transverse section structures. ?

     

/

返回文章
返回