北京航空航天大学学报 ›› 2019, Vol. 45 ›› Issue (2): 277-282.doi: 10.13700/j.bh.1001-5965.2018.0295

• 论文 • 上一篇    下一篇

一种考虑过滤的短纤维增强复合材料RVE建模方法

刘丰睿1, 骈瑢1, 赵丽滨1, 张建宇2   

  1. 1. 北京航空航天大学 宇航学院, 北京 100083;
    2. 重庆大学 航空航天学院, 重庆 400044
  • 收稿日期:2018-05-22 出版日期:2019-02-20 发布日期:2019-03-04
  • 通讯作者: 刘丰睿 E-mail:frliu@buaa.edu.cn
  • 作者简介:刘丰睿男,博士,讲师,硕士生导师。主要研究方向:复合材料结构失效分析、多学科优化设计;骈瑢女,硕士研究生。主要研究方向:复合材料结构力学;赵丽滨女,博士,教授,博士生导师。主要研究方向:飞行器结构分析与优化设计、复合材料结构的破坏理论和力学设计、多场条件下多功能结构设计;张建宇男,博士,研究员,博士生导师。主要研究方向:金属多轴疲劳、复合材料疲劳断裂、疲劳可靠性工程。
  • 基金资助:
    国家自然科学基金(11772028,11702012,11572058,11372020)

A filter based modeling method of RVE for short fiber reinforced composite

LIU Fengrui1, PIAN Rong1, ZHAO Libin1, ZHANG Jianyu2   

  1. 1. School of Astronautics, Beihang University, Beijing 100083, China;
    2. College of Aerospace Engineering, Chongqing University, Chongqing 400044, China
  • Received:2018-05-22 Online:2019-02-20 Published:2019-03-04
  • Supported by:
    National Natural Science Foundation of China (11772028,11702012,11572058,11372020)

摘要: 代表性体积单元(RVE)法是短纤维增强复合材料性能预测的常用方法,其RVE生成效率是预测效率的重要影响因素。针对现有的随机顺序吸附(RSA)方法生成RVE时,布尔运算次数多、效率低的问题,通过在布尔运算前加入对纤维形心距的判断,过滤掉一部分随机生成的且与已有纤维相交的纤维,以减少布尔运算次数,提出了一种考虑过滤的随机顺序吸附(FRSA)方法。通过将改进后的FRSA方法在不同RVE参数和方法参数下生成RVE所需布尔运算次数和所需时间与基于布尔运算的随机顺序吸附(BORSA)方法进行比较,证明了FRSA方法的先进性。

关键词: 短纤维增强复合材料, 数值建模, 随机顺序吸附(RSA)方法, 过滤法, 纤维形心距

Abstract: The representative volume element (RVE) method is a common numerical modeling method for predicting the material properties of short fiber reinforced composites. The RVE generation efficiency is an important factor affecting the efficiency of the property prediction. For the problem of too many Boolean operation times which cause low efficiency of Boolean operation when the existing random sequential adsorption (RSA) method is used to generate RVE, the centroid distance calculations between the lasted randomly generated fibers and the existing fibers are introduced. Using the centroid distance, some randomly generated fibers, which are intersecting with the existing fibers, are filtered out to reduce the number of Boolean operations. And a filter based random sequential adsorption (FRSA) method for modeling RVE is presented. By comparing the number of Boolean operations and the time cost for generating RVE, the FRSA method has been verified, and the verification is performed with different RVE parameters and method parameters using improved FRSA method and Boolean operation based random sequential adsorption (BORSA).

Key words: short fiber reinforced composite, numerical modeling, random sequential adsorption (RSA) method, filtering method, centroid distance of the fiber

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