4.6 Article

Homogenization of linear elastic properties of short-fiber reinforced composites - A comparison of mean field and voxel-based methods

期刊

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijsolstr.2015.02.030

关键词

Mean field homogenization; Full field simulation; Self-consistent method; Interaction direct derivative; Fast Fourier transformation; Short-fiber reinforced composites

资金

  1. German-Canadian research group Integrated engineering of continuous-discontinuous long fiber reinforced polymer structures
  2. Institute of Engineering Mechanics at KIT by German Research Foundation (DFG)

向作者/读者索取更多资源

The main contribution of this work lies in the detailed comparison of the predictions of linear elastic properties of mean field homogenization approaches and full field, voxel-based homogenization methods for short-fiber reinforced materials. In the former case, the self-consistent, the interaction direct derivative and a two-step-bounding approach, applying the Hashin-Shtrikman bounds, are used. In the latter case, the boundary value problem for representative volume elements is solved using fast Fourier transformation. Model microstructures with unidirectional aligned and two misaligned fiber configurations are considered exemplarily. Fiber volume fractions of 13%, 17% and 21% and phase contrasts of 44, 100 and 1000 in the elastic moduli have been taken into account. The different homogenization schemes are compared by means of effective directional dependent Young's modulus. This detailed comparison shows that mean field and full field solutions deliver similar results for moderate phase contrasts and volume fractions. Especially in the range of realistic phase contrasts like 44 for a composite of polypropylene and glass, the mean field approaches pose reliable alternatives for full field solution. Large phase contrasts result in relative deviations of up to 68%. (C) 2015 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据