汪俊泽, 张攀, 刘均, 等. 基于子模型分解的船舶舱段结构代理模型协同优化方法[J]. 中国舰船研究, 2024, 19(2): 98–106. doi: 10.19693/j.issn.1673-3185.03237
引用本文: 汪俊泽, 张攀, 刘均, 等. 基于子模型分解的船舶舱段结构代理模型协同优化方法[J]. 中国舰船研究, 2024, 19(2): 98–106. doi: 10.19693/j.issn.1673-3185.03237
WANG J Z, ZHANG P, LIU J, et al. Collaborative optimization method of surrogate model for ship cabin structure based on sub-model decomposition[J]. Chinese Journal of Ship Research, 2024, 19(2): 98–106 (in both Chinese and English). doi: 10.19693/j.issn.1673-3185.03237
Citation: WANG J Z, ZHANG P, LIU J, et al. Collaborative optimization method of surrogate model for ship cabin structure based on sub-model decomposition[J]. Chinese Journal of Ship Research, 2024, 19(2): 98–106 (in both Chinese and English). doi: 10.19693/j.issn.1673-3185.03237

基于子模型分解的船舶舱段结构代理模型协同优化方法

Collaborative optimization method of surrogate model for ship cabin structure based on sub-model decomposition

  • 摘要:
    目的 为解决船舶舱段结构优化设计参数众多、计算耗时的难题,提出一种基于子模型分解的舱段结构代理模型协同优化方法。
    方法 每次选择一个板架,根据当前舱段方案的有限元模型建立板架结构子模型,基于子模型构建板架结构响应的代理模型并进行优化,得到板架优化解后更新舱段模型,再进行下一个板架的优化,如此迭代,直到完成一轮或多轮包含所有板架的协同优化后停止。最后对舱段结构尺寸进行小范围调整,得到最终优化解。
    结果 某船舶舱段结构优化结果显示,与从整体优化角度出发的基于降维代理模型的舱段结构优化方法相比,在相当计算成本下,所提方法的优化结果重量进一步减小了2.86%,最终实现结构减重4.96%。
    结论 所提方法的优化效果较好,在高维船体结构优化问题上具有较好的应用价值。

     

    Abstract:
    Objectives In order to solve the difficulties of numerous design parameters and time-consuming computation of ship cabin structure optimization, a collaborative optimization method of surrogate model for cabin structure based on sub-model decomposition is proposed.
    Methods A grillage was selected at a time, and the sub-model of grillage structure was established based on the finite element model of the current cabin scheme. The surrogate model was constructed for the grillage structure response and optimized based on the sub-model. After the optimization solution of the grillage was obtained, the cabin model was updated, and then the next grillage was optimized. This iteration stopped until one or more rounds of collaborative optimization including all grillages were completed. Finally, a small scale of adjustment of cabin structure size was conducted to obtain the final optimization solution.
    Results The optimization result of a ship cabin structure shows that, compared with the cabin structure optimization method based on the dimensionality reduction surrogate model from the point of view of overall optimization, under the equivalent computational cost, the weight in the optimization result of the proposed method is further reduced by 2.86%, and the structural weight is reduced by 4.96% eventually.
    Conclusions  The proposed method has better optimization result and better application value on the structure optimization problem of high-dimensional ship hull.

     

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