复合材料科学与工程 ›› 2022, Vol. 0 ›› Issue (5): 61-65.DOI: 10.19936/j.cnki.2096-8000.20220528.008

• 应用研究 • 上一篇    下一篇

考虑隐式约束的复合材料层合板分区优化方法

闫金顺1,2, 孙鹏文3*, 赵雄翔4, 马志坤3, 于泽林3   

  1. 1.内蒙古工业大学 能源与动力工程学院,呼和浩特 010051;
    2.吕梁学院 矿业工程系,吕梁 033001;
    3.内蒙古工业大学 机械工程学院,呼和浩特 010051;
    4.内蒙古自治区能源技术中心,呼和浩特 010010
  • 收稿日期:2022-01-28 出版日期:2022-05-28 发布日期:2022-07-19
  • 通讯作者: 孙鹏文(1966-),男,博士,教授,主要从事机械和风力机叶片结构设计与优化方面的研究,pwsun@imut.edu.cn。
  • 作者简介:闫金顺(1986-),男,博士研究生,讲师,主要从事结构设计与优化方面的研究。
  • 基金资助:
    国家自然科学基金(52165035,51865041);内蒙古自治区研究生科研创新项目(BZ2020037)

Patch optimization method of composite laminates considering implicit constraints

YAN Jin-shun1,2, SUN Peng-wen3*, ZHAO Xiong-xiang4, MA Zhi-kun3, YU Ze-lin3   

  1. 1. College of Energy and Power Engineering, Inner Mongolia University of Technology, Hohhot 010051, China;
    2. Department of Mining Engineering, Luliang University, Luliang 033001, China;
    3. School of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot 010051, China;
    4. Energy Technology Center of Inner Mongolia Autonomous Region, Hohhot 010010, China
  • Received:2022-01-28 Online:2022-05-28 Published:2022-07-19

摘要: 针对传统复合材料层合板优化设计较少考虑隐式约束或通过构建代理模型和惩罚函数等近似方法进行约束处理存在的问题,提出了一种考虑隐式约束的复合材料层合板分区优化方法。通过构建MATLAB-Python-ABAQUS联合仿真优化框架,实现对隐式约束的直接处理。以离散的纤维铺角为设计变量,结构柔顺度最小为目标函数,对称性制造和强度为约束,建立了分区优化数学模型,将联合仿真优化与遗传算法相结合,进行优化求解。数值算例表明:该方法可有效解决隐式约束的求解,获得优化的铺层方案,提高结构性能。

关键词: 隐式约束, 联合仿真优化, 分区优化, 离散铺角, 遗传算法, 复合材料

Abstract: In order to solve the problem that the implicit constraints are less considered in the traditional optimization design of composite laminates, or the constraint processing is carried out by agent models and penalty functions, a patch optimization method considering implicit constraints is proposed. The direct processing of implicit constraints is realized by constructing the MATLAB-Python-ABAQUS joint simulation optimization framework. The mathematical model of patch optimization is established, which takes the discrete fiber orientation as the design variable, the minimum compliance as the objective function, the symmetry manufacturing and the strength as constraints. The joint simulation optimization and genetic algorithm are combined to solve the optimization problem. Numerical examples show that this method can effectively solve the implicit constraint, obtain the optimized ply scheme, and improve the structural performance.

Key words: implicit constraint, joint simulation optimization, patch optimization, discrete fiber orientation, genetic algorithm, composites

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