Research on the construction of multi objective coupling model and optimization method of ship form

IF 1.7 4区 工程技术 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS International Journal for Numerical Methods in Fluids Pub Date : 2024-06-03 DOI:10.1002/fld.5315
Jie Liu, Baoji Zhang, Yuyang Lai, Liqiao Fang
{"title":"Research on the construction of multi objective coupling model and optimization method of ship form","authors":"Jie Liu,&nbsp;Baoji Zhang,&nbsp;Yuyang Lai,&nbsp;Liqiao Fang","doi":"10.1002/fld.5315","DOIUrl":null,"url":null,"abstract":"<p>Multi-objective optimization of ship form can effectively reduce ship energy consumption, and is one of the important research topics of green ships. However, the computational cost of numerical simulation based on computational fluid dynamics (CFD) theory is relatively high, which affects the efficiency of optimization. Traditional subjective weighting methods mostly rely on expert's experience, which affects the scientificity of optimization. This paper effectively integrates the CFD method, the improved multi-objective optimization algorithm and the objective weighting method to build a ship form multi-objective optimization framework. Conduct multi-objective optimization research on resistance and seakeeping performance of a very large crude oil carrier (KVLCC) ship. The improved bare-bones multi-objective particle swarm optimization (IBBMOPSO) algorithm is used to obtain the pareto front, and the kernel principal component analysis (KPCA) method is used to objectively assign the weight of each target. Finally, the optimal ship form scheme with high satisfaction was obtained. The multi-objective optimization framework constructed in this paper can provide a certain theoretical basis and technical support for the development of ship greening and digital transformation.</p>","PeriodicalId":50348,"journal":{"name":"International Journal for Numerical Methods in Fluids","volume":"96 10","pages":"1617-1630"},"PeriodicalIF":1.7000,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal for Numerical Methods in Fluids","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/fld.5315","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

Multi-objective optimization of ship form can effectively reduce ship energy consumption, and is one of the important research topics of green ships. However, the computational cost of numerical simulation based on computational fluid dynamics (CFD) theory is relatively high, which affects the efficiency of optimization. Traditional subjective weighting methods mostly rely on expert's experience, which affects the scientificity of optimization. This paper effectively integrates the CFD method, the improved multi-objective optimization algorithm and the objective weighting method to build a ship form multi-objective optimization framework. Conduct multi-objective optimization research on resistance and seakeeping performance of a very large crude oil carrier (KVLCC) ship. The improved bare-bones multi-objective particle swarm optimization (IBBMOPSO) algorithm is used to obtain the pareto front, and the kernel principal component analysis (KPCA) method is used to objectively assign the weight of each target. Finally, the optimal ship form scheme with high satisfaction was obtained. The multi-objective optimization framework constructed in this paper can provide a certain theoretical basis and technical support for the development of ship greening and digital transformation.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
船型多目标耦合模型构建及优化方法研究
船型多目标优化能有效降低船舶能耗,是绿色船舶的重要研究课题之一。然而,基于计算流体力学(CFD)理论的数值模拟计算成本相对较高,影响了优化效率。传统的主观加权方法大多依赖专家经验,影响了优化的科学性。本文有效整合了 CFD 方法、改进的多目标优化算法和目标权重法,构建了船形多目标优化框架。对超大型原油运输船(KVLCC)船舶的阻力和适航性能进行多目标优化研究。利用改进的裸目标多目标粒子群优化(IBBMOPSO)算法得到帕累托前沿,并利用核主成分分析(KPCA)方法客观分配各目标的权重。最后,得到了满意度较高的最优船形方案。本文构建的多目标优化框架可为船舶绿色化发展和数字化转型提供一定的理论基础和技术支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
International Journal for Numerical Methods in Fluids
International Journal for Numerical Methods in Fluids 物理-计算机:跨学科应用
CiteScore
3.70
自引率
5.60%
发文量
111
审稿时长
8 months
期刊介绍: The International Journal for Numerical Methods in Fluids publishes refereed papers describing significant developments in computational methods that are applicable to scientific and engineering problems in fluid mechanics, fluid dynamics, micro and bio fluidics, and fluid-structure interaction. Numerical methods for solving ancillary equations, such as transport and advection and diffusion, are also relevant. The Editors encourage contributions in the areas of multi-physics, multi-disciplinary and multi-scale problems involving fluid subsystems, verification and validation, uncertainty quantification, and model reduction. Numerical examples that illustrate the described methods or their accuracy are in general expected. Discussions of papers already in print are also considered. However, papers dealing strictly with applications of existing methods or dealing with areas of research that are not deemed to be cutting edge by the Editors will not be considered for review. The journal publishes full-length papers, which should normally be less than 25 journal pages in length. Two-part papers are discouraged unless considered necessary by the Editors.
期刊最新文献
Issue Information Cover Image Issue Information Semi‐implicit Lagrangian Voronoi approximation for the incompressible Navier–Stokes equations A new non‐equilibrium modification of the k−ω$$ k-\omega $$ turbulence model for supersonic turbulent flows with transverse jet
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1