在复杂船型开发中，多学科设计优化的应用对提升船舶综合性能、降低成本等具有重要意义。本文搭建多学科优化设计框架，明确综合优化目标，兼顾水动力、结构、稳性和经济性等多方面需求，深入分析各学科约束条件，为优化设计奠定基础。运用改进粒子群算法，借助动态惯性权重调整、自适应学习因子等策略提升搜索能力，在收敛速度和稳定性上优于传统算法，将其应用于复杂船型多学科优化设计，重点研究船首和螺旋桨的多学科优化设计方案，结果表明多学科设计优化方法能有效提升设计效率。
In the development of complex ship type, the application of multidisciplinary design optimization is of great significance to improve the comprehensive performance of the ship and reduce the cost. This study establishes a multidisciplinary optimization design framework, defines the comprehensive optimization objectives, takes into account the hydrodynamic, structural, stability and economic requirements, and deeply analyzes the constraints of each discipline, laying a foundation for the optimization design. Improved particle swarm optimization (PSO) is applied to improve the search capability by means of dynamic inertia weight adjustment, adaptive learning factor and other strategies, which is superior to the traditional algorithm in terms of convergence speed and stability. It is applied to the multidisciplinary optimization design of complex ship types, focusing on the multidisciplinary optimization design scheme of ship bow and propeller, and the results show that the multidisciplinary design optimization method can effectively improve the design efficiency.
2025,47(7): 59-63 收稿日期：2025-2-12
DOI：10.3404/j.issn.1672-7649.2025.07.012
分类号：U667.65
作者简介：章瑾 (1983-),女,硕士,副教授,研究方向为产品设计、数字文创及交互体验设计
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