Non-destructive characterization of fiber orientation in reinforced SMC as input for simulation based design
Non-destructive characterization of fiber orientation in reinforced SMC as input for simulation based design
复制标题
增强 SMC 中纤维取向的无损表征作为基于仿真的设计的输入
DOI：
10.1016/j.compstruct.2016.10.019
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发表时间：
2017
影响因子：
6.3
通讯作者：
M. Steinhauser
中科院分区：
文献类型：
--
作者：
K. Schladitz;A. Büter;M. Godehardt;O. Wirjadi;J. Fleckenstein;T. Gerster;U. Hassler;K. Jaschek;M. Maisl;U. Maisl;Stefan Mohr;U. Netzelmann;T. Potyra;M. Steinhauser
材料的宏观性能很大程度上受其微观结构的影响。这对于纤维增强复合材料尤其适用，其中纤维分布和取向对于增强材料达到其目的至关重要。这种重要的微观结构信息可以使用适当的定量图像分析方法从高分辨率图像中获得。片状模塑料具有非常致密的增强纤维层状系统和特别强的 X 射线吸收能力。因此，在这种情况下，基于 X 射线显微断层扫描获得的 3D 图像的最先进的纤维取向分析面临着问题。在本文中，我们通过产生最强滤波器响应的各向异性高斯滤波器的方向来确定每个像素中的局部纤维方向。因此，无需识别单个纤维即可计算局部纤维取向。根据如此确定的面积加权取向分布，导出各向异性程度和主纤维取向。这种极其稳健的分析方法适用于扫描声学显微镜和高分辨率 3D 显微断层扫描的 2D 切片图像。我们表明，基于高斯滤波器的纤维取向分析方法可以为两种成像技术产生可比较的结果。此外，与对相同样本进行的疲劳测试进行比较证明，图像分析确定的纤维取向与失效行为密切相关。特别是，可以识别临界程度的各向异性。对于高于此限制的各向异性程度，样品的机械行为类似于单轴材料。因此，本文为校准微观机械模型提供了经过实验验证的证据，以便随后结合高分辨率成像技术和定量图像分析来模拟宏观材料特性。
The macroscopic properties of materials are strongly influenced by their microstructure. This holds in particular for fiber reinforced composites where fiber distribution and orientation are crucial for the reinforcement to serve its purpose. This essential microstructural information can be obtained from high-resolution images using appropriate methods for quantitative image analysis. Sheet molding compounds feature a very dense layered system of reinforcing fibers and a particularly strong X-ray absorption. Therefore, in this case, state-of-the-art fiber orientation analysis based on 3D images obtained by X-ray microtomography faces problems. In this paper, we determine the local fiber orientation in each pixel by the orientation of the anisotropic Gaussian filter yielding the strongest filter response. Hence, the local fiber orientation can be computed without identifying individual fibers. From the thus determined area weighted orientation distribution, the degree of anisotropy and the main fiber orientation are derived. This extremely robust analysis method is applied to 2D slice images from scanning acoustic microscopy and high-resolution 3D microtomography. We show that the Gaussian filter based fiber orientation analysis method yields comparable results for both imaging techniques. Moreover, comparison with fatigue tests performed on the same specimens proves the image analytically determined fiber orientation and the failure behaviour to be strongly correlated. In particular, a critical degree of anisotropy could be identified. For degrees of anisotropy higher than this limit, the samples behave mechanically like a uniaxial material. The paper thus provides experimentally validated evidence for calibrating micro-mechanical models for subsequent simulation of macroscopic material properties using the combination of high-resolution imaging techniques and quantitative image analysis.