周珂, 王德禹. 水下爆炸载荷下舰船结构的多目标优化[J]. 中国舰船研究, 2013, 8(6): 27-32. DOI: 10.3969/j.issn.1673-3185.2013.06.005
引用本文: 周珂, 王德禹. 水下爆炸载荷下舰船结构的多目标优化[J]. 中国舰船研究, 2013, 8(6): 27-32. DOI: 10.3969/j.issn.1673-3185.2013.06.005
ZHOU Ke, WANG Deyu. Multi-Objective Optimization of Ship Structures Subjected to an Underwater Explosion[J]. Chinese Journal of Ship Research, 2013, 8(6): 27-32. DOI: 10.3969/j.issn.1673-3185.2013.06.005
Citation: ZHOU Ke, WANG Deyu. Multi-Objective Optimization of Ship Structures Subjected to an Underwater Explosion[J]. Chinese Journal of Ship Research, 2013, 8(6): 27-32. DOI: 10.3969/j.issn.1673-3185.2013.06.005

水下爆炸载荷下舰船结构的多目标优化

Multi-Objective Optimization of Ship Structures Subjected to an Underwater Explosion

  • 摘要: 水面舰船对轻量化和抗爆性能均有特殊的需求,而这两个目标此消彼长的关系又使得实现它们的途径相互矛盾。为找到能同时提高轻量化和抗爆性能的满意解,建立以板厚为变量的多目标优化模型。在优化过程中,通过参数化建模技术实现建模的自动化,数值模拟采用船体三舱段有限元模型,使用ABAQUS/EXPLICIT求解器进行非线性有限元分析,并在优化流程中引入实验设计和近似模型进行响应预报,在此基础上,还通过NSGA-II遗传算法进行多目标优化,得到优解。通过对优化后的船舯舱段与优化前的进行对比分析,发现重量和抗爆性能这两个目标分别有0.46%和22.51%的改进,实现了轻量化和抗爆性能的双向提升。

     

    Abstract: Naval vessels usually have special requirements in weight and anti-explosion performance, yet the push-pull between these two makes the realization of both objectives quite difficult. In this paper, a multi-objective optimization model is established to find a satisfactory solution that reduces the weight and improves the anti-explosion performance simultaneously, where the optimal design is achieved by adjusting the thickness of double side hulls. Specifically, a FE model with three compartments is used for analysis, and the technology of parametric modeling is introduced to accomplish automatic modeling. The ABAQUS/EXPLICIT solver is used for nonlinear finite element analysis, and DOE approximation models are adopted to forecast outputs. Also, the NSGA-II genetic algorithm is applied to obtain optimal solution in the multi-objective optimization process. Results show that compared with the initial design, the optimal design presented here achieves a decrease in weight(0.46%) as well as an increase in anti-explosion performance (22.51%), which successfully validates the method.

     

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