Research on Discrepancy of Fiber Reinforced Composite Effective Performance

SONG Ying-dong; SUN Zhi-gang; GAO Xi-guang

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Research on Discrepancy of Fiber Reinforced Composite Effective Performance

更新时间：2026-07-07

- Research on Discrepancy of Fiber Reinforced Composite Effective Performance
- Vol. 20, Issue 2, (2005)
- 作者机构：
  
  南京航空航天大学能源与动力学院,江苏,南京,210016
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2005
- 稿件说明：
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SONG Ying-dong, SUN Zhi-gang, GAO Xi-guang. Research on Discrepancy of Fiber Reinforced Composite Effective Performance[J]. 2005, 20(2).
DOI：

SONG Ying-dong, SUN Zhi-gang, GAO Xi-guang. Research on Discrepancy of Fiber Reinforced Composite Effective Performance[J]. 2005, 20(2). DOI：

摘要

利用改进算法的宏-细观统一通用单胞本构模型

采用Monte-Carlo方法研究了不同纤维形状、不同纤维排列方式以及纤维体积含量对纤维增强复合材料弹性模量、泊松比和热膨胀系数的分散性的影响。研究结果表明:复合材料有效性能的分散性小于组分的分散性。随着纤维体积比的增加

纵向有效性能的分散性加大;而横向有效性能除了椭圆形纤维的短轴方向的热膨胀系数之外

其它性能的分散性则都是下降趋势。纤维截面形状和排列方式对纵向性能的分散性几乎没有影响。方形和圆形纤维时

横向性能的分散性几乎相同

而椭圆形纤维时

则与它们有明显的差别。不同纤维排列方式下

横向性能的分散性都是不一样的。对于E11和G12

六角形和方形对角排列时其分散性较大

而矩形排列引起的分散性最小。随着纤维体积比的增加

不同排列方式下

横向热膨胀系数的分散性趋近于一致。本文得到的结论为复合材料及结构的概率设计提供了重要的参考。

Abstract

Discrepancies of elastic modulus

Poisson ratios and thermal expansion coefficients of fiber reinforced composites were investigated using the constitutive model of Cell and Monte-Carlo method.The results indicate that the discrepancies of fiber reinforced composite effective performance are smaller than the ones of their elements. With the increase of the percentage of fiber volume

the discrepancies of longitudinal effective performance increase

but that of transverse effective performances decrease

except the thermal expansion coefficient in the short-axial direction.The fiber shapes and packing arrays have little effect on the discrepancies of longitudinal effective performance.Composites with hexagonal section fibers and square cross section fibers have the same discrepancies of transverse effective performance.Different fiber packing arrays give different discrepancies.The presented conclusions in this paper are very useful to probabilistic design of composites.

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