上海交通大学学报

上海交通大学学报 ›› 2017, Vol. 51 ›› Issue (3): 308-.

• 海洋工程 • 上一篇    下一篇

基于铺层参数的复合材料耐压壳协同优化设计

李彬a，庞永杰a，程妍雪a，朱枭猛b   

  1. 哈尔滨工程大学  a. 水下机器人技术重点实验室；b. 船舶工程学院，哈尔滨 150001  
  • 发布日期:2017-03-29
  • 基金资助:

    国家高技术研究发展计划（863）项目（2011AA09A106），武器装备预研基金项目（9140C270305120C2701）资助

Collaborative Optimization for Composite Material Pressure Hull#br# Based on Lamination Parameters

LI Bina,PANG Yongjiea,CHENG Yanxuea,ZHU Xiaomengb   

  1. a. Science and Technology on Underwater Vehicle Laboratory;
    b. College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China
  • Published:2017-03-29

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摘要：

摘要：  在给定的材料性能条件下，以耐压壳纤维体积分数和层合板厚度为设计变量，以结构质量最小为优化目标进行复合材料耐压壳的布局优化；以铺层参数作为优化变量，综合考虑结构的稳定性及其材料强度，实现了结构铺层方式的优化设计；通过协调各子系统优化结果，实现了适用于潜水器复合材料耐压壳结构/材料一体化的协同优化设计.结果表明：耐压壳结构质量较优化前的降幅为20.57%，临界失稳压力为30.78MPa，失效指数为0.675，优化结果达到预期效果.所提出的基于铺层参数的协同优化方法能够对复合材料耐压壳进行优化设计，解决了直接以铺层角作为设计变量的优化效率低的问题.

关键词:

潜水器；复合材料耐压壳；铺层参数；布局；铺层方式；协同优化

Abstract:

Abstract： Given that the material performances are certain, the layout optimization is accomplished, where the fiber volume fraction and ply thickness are taken as design variables and the objective is the minimum structural mass. The lamination parameters are introduced as optimization variables to achieve structural layup optimization with the structural stability and material strength taken into consideration. The structure/material collaborative optimization of composite material pressure hull is performed by integrating optimization results of each subsystem. The results show that the mass of the pressure hull decreases by 20.57%, the critical buckling pressure is 30.78 MPa, the failure index is 0.675. The desired results are achieved. The presented collaborative optimization method based on lamination parameters can optimize the composite material pressure hull with high accuracy and solve problem of low efficiency of optimization with ply angle directly set as design variables.

Key words:

submersible; composite material pressure hull; lamination parameters; layout; layup; collaborative optimization

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