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Digital volume correlation for meso/micro in-situ damage analysis in carbon fiber reinforced composites

机译:碳纤维增强复合材料中Meso / Micro原位损伤分析的数字体积相关性

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摘要

Recently, in-situ X-ray Computed Tomography (CT) has shown its potential for 3D damage analysis in composite materials. However, the characterization of damage in X-ray tomograms is not always straightforward, and it requires post-processing of the 3D images. In this study, we explore the potential of Digital Volume Correlation (DVC) for the detection and characterization of damage in fiber-reinforced composites, where fibers provide the required 3D speckle pattern. Preliminary analysis via "digital deformation" of 3D images is performed to verify the applicability of DVC for quantification of deformation and damage in a carbon/epoxy laminate and to estimate the measurement errors. Then, real-deformation images, acquired with synchrotron CT during in-situ tensile loading of the laminate, are analyzed with DVC to detect different damage mechanisms. A rough analysis is performed at the mesoscale using subset-based DVC, followed by a more detailed investigation at the microscale via finite-element-based DVC. Damage appears in the DVC strain fields as local strain magnification. Crack opening displacement can be estimated reliably via the jumps in displacement fields. DVC proves to be a promising tool for damage characterization in X-ray tomograms of fiber-reinforced composites, especially when simple methods such as grayscale thresholding are not adequate.
机译:最近,原位X射线计算机断层扫描(CT)已经显示了复合材料中的3D损伤分析的可能性。然而,X射线断层图像损坏的表征并不总是简单的,并且需要对3D图像的后处理。在这项研究中,我们探讨了数字体积相关(DVC)的潜力,用于检测和表征纤维增强复合材料中的损坏,其中纤维提供所需的3D散斑图案。通过“数字变形”初步分析3D图像的应用,以验证DVC的适用性是否在碳/环氧树脂层压体中的变形和损伤的量化和估计测量误差。然后,用DVC分析用在原位拉伸加载过程中使用同步凝集载荷的同步荷子CT获得的实际变形图像,以检测不同的损伤机制。使用基于子集的DVC在MESSCLE进行粗略分析,然后通过基于有限元的DVC在微观上进行更详细的研究。 DVC应变字段中显示为局部应变放大倍数。通过位移场中的跳跃可以可靠地估计裂缝开口位移。 DVC被证明是纤维增强复合材料X射线断层图像损坏表征的有希望的工具,尤其是当简单的方法如灰度阈值阈值等时不足。

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