基于MOPSO的潜艇阻力优化  

Optimization of Submarine Resistance Based on MOPSO

作　　者：陈恭 吴禹良 高良田[1] 刘梦颖 马雪晴 CHEN Gong;WU Yuliang;GAO Liangtian;LIU Mengying;MA Xueqing(College of Shipbuilding Engineering,Harbin Engineering University,Harbin 150000,China)

机构地区：[1]哈尔滨工程大学船舶与海洋工程学院,哈尔滨150000

出　　处：《中国造船》2020年第S02期392-401,共10页Shipbuilding of China

基　　金：国家重点研发计划战略性国际科技创新合作重点专项(2016YFE0202700)。

摘　　要：快速性是潜艇作战能力和生存能力的重要指标.基于Suboff-AFF8艇型,以水面和水下阻力为优化对象,利用自编改进的Lackenby参数化几何重构方法对潜艇型线进行变形,采用优化拉丁方(OLHS)试验设计方法获得具有较好正交性和均匀性的试验样本.通过CFD求解器评估试验样本并利用Kriging法构造近似模型,并对近似模型计算结果与数值评估结果进行交叉验证.对自编多目标粒子群算法(MOPSO),用ZDT多目标测试函数验证算法的正确性.在带有约束条件的设计空间进行寻优,获得多目标优化前缘,然后依据一定的规则选择若干优化船型,并与Suboff-AFF8艇型的阻力进行比较和分析.Resistance is one of the important indexes of submarine combat capability and survivability in modern naval warfare. In this paper, the Suboff-AFF8 model was deformed by the improved Lackenby method of parametric geometric reformation, and the samples with good orthogonality and uniformity were obtained by the optimal Latin hypercube(OLHS) method. Test samples were evaluated by a CFD solver, and an approximate model was constructed by the Kriging method. The approximate results and numerical evaluation results are cross validated. In addition, a multi-objective particle swarm optimization algorithm(MOPSO) was developed, and its correctness was verified according to the ZDT multi-objective test functions. The design space with several constraints was optimized, and a Pareto solution set of the multi-objective optimization was obtained. Several optimal schemes were selected according to specified rules and compared with the Suboff-AFF8 model in the resistance.

关 键 词：潜艇 改进的Lackenby法 优化拉丁方 粒子群算法 阻力优化 

分 类 号：U661.31[交通运输工程—船舶及航道工程]