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Analysis of Strain Field Heterogeneity at the Microstructure Level and Inverse Identification of Composite Constituents by Means of Digital Image Correlation

机译:用数字图像相关分析微观结构水平的应变场异质性和复合成分的反向识别

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摘要

The present paper is devoted to the theoretical study on the estimation of the full-field strain at the microstructural level of composite materials by means of Digital Image Correlation (DIC). The main aim of the paper is to investigate the influence of speckle size on the accuracy of the strain field measurement at the microscale. The DIC analysis was conducted based on artificial speckle patterns generated numerically and the deformation behavior of the composites was simulated by using the finite element method (FEM). This approach gives the opportunity to compare the results of the DIC in terms of speckle size with the reference FEM solution. Moreover, the paper focuses on the inverse identification of the material constants of the composite constituents by using information associated with the measured strain field. The inverse problem is solved by using a novel two-step optimization procedure, which reduces the problem complexity. The feasibility and accuracy of the proposed approach are presented by analysis of two exemplary microgeometries representing the microstructures of fiber reinforced composites.
机译:本文致力于通过数字图像相关技术(DIC)估算复合材料微观结构水平下的全场应变的理论研究。本文的主要目的是研究散斑大小对微尺度应变场测量精度的影响。基于数值生成的人工散斑图样进行DIC分析,并使用有限元方法(FEM)模拟复合材料的变形行为。这种方法提供了将散斑大小方面的DIC结果与参考FEM解决方案进行比较的机会。此外,本文着重于通过使用与测得的应变场相关的信息对复合成分的材料常数进行逆识别。通过使用新颖的两步优化过程解决了逆问题,从而降低了问题的复杂性。通过分析代表纤维增强复合材料微观结构的两个示例性微观几何结构,提出了该方法的可行性和准确性。

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