基于拓扑-几何表征的主船体分舱多目标优化
Multi-objective optimization of main hull subdivision based on topological geometric representation
于磊 1陈顺怀 1杨萌 2汪皓 2孙永炎3
作者信息
- 1. 武汉理工大学 船海与能源动力工程学院,湖北 武汉 430063
- 2. 汉江国家实验室,湖北 武汉 430061
- 3. 武汉船舶设计研究院有限公司,湖北 武汉 430064
- 折叠
摘要
[目的]为降低船舶概念设计对于设计经验和母型船资料的依赖,并提高设计效率和设计质量,提出一种主船体分舱智能优化方法.[方法]首先,对船舶舱室设备间的相互影响关系进行梳理分析,提出影响关系拓扑表征模型和自动辨识方法;结合设计经验和统计规律,构建有利影响拓扑目标函数和空间利用率几何目标函数,并依据设计规范提出概率破舱约束模型.然后,基于多目标遗传算法实现优化求解,从而形成一套主船体分舱智能优化方法.[结果]以"大洋"号综合资源科考船为对象,开展主船体分舱优化设计测试,得到的帕累托前沿解集具有良好的多样性,且与母型分舱方案相比,最优分舱方案有利影响提升 13.717 0,水密舱段数量减少 1 个.[结论]测试结果表明该方法具有一定的合理性.
Abstract
[Objective]In order to reduce the dependence of ship conceptual design on design experience and mother ship data while improving design efficiency and quality,a main hull subdivision intelligent optim-ization method is proposed.[Methods]First,the mutual influence relationships between ship cabin equip-ment are analyzed and a topological representation model and automatic identification method for such rela-tionships are proposed.Based on design experience and statistical rules,a favorable impact topological object-ive function and geometric objective function for the space utilization rate are constructed,and a probability damage constraint model is proposed according to the design specifications.Based on the theory of membrane computing,a multi-objective optimization solution is realized,forming a set of intelligent optimization meth-ods for the main hull subdivision.A main hull subdivision optimization design test is then carried out on the DaYang comprehensive resource survey ship.[Results]The Pareto front solution set obtained from the op-timization has good diversity.Compared with the mother type subdivision scheme,the optimal subdivision scheme has a favorable impact increase of 13.717 0 and reduces the number of watertight compartments by one.[Conclusion]The test results indicate that this method is rational and feasible.
关键词
主船体分舱/多目标优化/拓扑几何/网络科学/概率破舱/遗传算法Key words
main hull subdivision/multi-objective optimization/topological geometry/network science/probability of ship damage/genetic algorithm引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据