首页|期刊导航|中国舰船研究|基于NSGA-Ⅱ算法与离散模块梁单元水弹性方法的连接件优化设计分析

基于NSGA-Ⅱ算法与离散模块梁单元水弹性方法的连接件优化设计分析OA

Optimization design of connectors using discrete-module-beam hydroelasticity method and NSGA-Ⅱ algorithm

中文摘要英文摘要

[目的]在离散模块梁单元(DMB)框架下,针对浮箱型多模块海上漂浮式光伏(OFPV)平台连接件刚度优化问题,提出一种新的方法.[方法]首先,介绍 DMB 水弹性分析方法,给出连接件刚度矩阵的形式并简述水弹性响应的数值建模方法;其次,给出线性加权遗传算法和非支配排序遗传算法 II(NSGA-II)的求解步骤,重点介绍刚度编码的实数码、指数码和科学记数码这 3 种基因编码方式以及其对应的交叉和变异算子,并进行对比分析;最后,引入等效零刚度和等效无穷刚度缩聚解空间.[结果]结果显示,使用 NSGA-II 算法可求解得出最大结构剪力最小和最大结构弯矩最小的 Pareto 前沿,同时,该 Pareto 前沿可视作由线性加权法得到的不同权重设置所对应最优解的集合,且科学记数码的搜索性能优.[结论]所述优化理论模型可针对浮箱型多模块平台用于对连接件刚度进行多目标优化.

[Objective]Based on the discrete-module-beam(DMB)method,this study aims to address the connector stiffness optimization problem of modular box-pontoon-type offshore floating photovoltaic(OFPV)platforms.The floating foundation of such OFPV systems consists of multiple modular units connected by connectors.The connector stiffness design significantly impacts the platform's structural safety and reliability under complex ocean environments.[Methods]This research employs comprehensive methods.First,the DMB hydroelastic analysis method is introduced.The connector stiffness matrix form is given,with stiffness values for different degrees of freedom defined,and the numerical modeling method for hydroelastic response briefly outlined.This method allows for efficient calculation of the structure's response to environmental loads.Second,two genetic-algorithm-based approaches are presented.The linear-weighted genetic algorithm con-verts the multi-objective optimization problem into a single-objective one by assigning weights to different ob-jectives.The NSGA-II(non-dominated sorting genetic algorithm II)is used as a multi-objective optimization algorithm,which can identify a set of Pareto-optimal solutions instead of a single one.Three encoding tech-niques for stiffness,namely real encoding,exponent encoding,and scientific notation encoding,are elaborated.Each encoding method has its own crossover and mutation operators.For example,real encoding directly oper-ates on stiffness values,while exponent encoding and scientific notation encoding have unique operation mechanisms.The performance of these encoding methods is compared through population initialization and individual distribution analysis across different evolutionary generations.In addition,the concept of equiva-lent zero stiffness and equivalent infinite stiffness is introduced to reduce the solution space.This enhances the efficiency of the optimization process.[Results]The results show that the NSGA-II algorithm can obtain the Pareto front with the objectives of minimizing the maximum structural shear force and minimizing the maximum structural bending moment.The Pareto front can be regarded as a set of optimal solutions corre-sponding to different weight settings obtained by the linear-weighted method.Analysis of population initializa-tion and individual distribution reveals that the scientific notation encoding performs better in terms of search efficiency within the solution space.It can explore a wider range of stiffness values,including both low and high magnitudes,compared to the other two encoding methods.[Conclusion]In conclusion,the developed optimization theory model is effective in performing multi-objective optimization on the connector stiffness of modular box-pontoon-type OFPV platforms.The scientific notation encoding provides a more efficient way to search for optimal solutions.However,it should be noted that the OFPV system is complex,and future re-search can focus on considering additional objectives and combinations to further optimize the design.This re-search provides a valuable reference for the design and optimization of floating-type photovoltaic platforms in ocean engineering.

陈永强;张显涛

上海交通大学 海洋工程全国重点实验室,上海 200240||上海交通大学 海南研究院,海南 三亚 572024上海交通大学 海洋工程全国重点实验室,上海 200240||上海交通大学 海南研究院,海南 三亚 572024

交通工程

连接件刚度离散模块梁单元非支配排序遗传算法Ⅱ多目标优化科学记数码

connectorstiffnessdiscrete-module-beamnon-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)multi-objective optimizationscientific notation encoding

《中国舰船研究》 2026 (3)

158-167,10

国家自然科学基金资助项目(42461144208,42476226)三亚崖州湾科技城博士研究生科研创新基金资助项目(HSPHDSRF-2023-01-001)

10.19693/j.issn.1673-3185.04337

评论