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<p>Predicting the performance degradation of defective materials is a significant challenge in solid mechanics, primarily due to the oversimplification of highly irregular defects into basic shapes such as circles or strips. In this study, CT-based defect extraction was employed to capture bubble defects within composite materials, followed by 3D-printed test specimens with a single defect for quantitative analysis of their impact on material performance. Tensile tests were conducted to determine the viscoelastic constitutive model parameters of the resin, and a one-dimensional stress-softening damage variable was established. Deep symbolic regression was used to derive degradation equations for defects at different angles, with a coefficient of determination (R<sup>2</sup>) greater than 0.97. The results show that when the angle between the defect and the principal stress direction is small, the material experiences more significant degradation. For example, the fracture strain of the material with a 45° defect orientation decreases by approximately 34.86%, and the fracture stress decreases by about 57.31%. In contrast, when the defect orientation is perpendicular to the tensile load direction (90° angle), the material suffers less damage, with fracture strain and fracture stress decreasing by approximately 9.96% and 26.81%, respectively. By integrating CT detection with 3D printing, this study links microscopic defects to macroscopic performance, providing a foundation for future optimization of composite material performance and defect control.</p>

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Degradation Performance of the Polymer Material Embedded with the Single Bubble Defect Extracted from CT Detection at Different Angles by 3D Printing

  • 期刊论文

  • 发表日期：

    2025年5月13日

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  • Yong Li,
  • Jinshuai Yao,
  • Yanan Miao,
  • Long Chen,
  • Xunchen Liu,
  • Kai Zheng,
  • Shanling Han

摘要

Predicting the performance degradation of defective materials is a significant challenge in solid mechanics, primarily due to the oversimplification of highly irregular defects into basic shapes such as circles or strips. In this study, CT-based defect extraction was employed to capture bubble defects within composite materials, followed by 3D-printed test specimens with a single defect for quantitative analysis of their impact on material performance. Tensile tests were conducted to determine the viscoelastic constitutive model parameters of the resin, and a one-dimensional stress-softening damage variable was established. Deep symbolic regression was used to derive degradation equations for defects at different angles, with a coefficient of determination (R2) greater than 0.97. The results show that when the angle between the defect and the principal stress direction is small, the material experiences more significant degradation. For example, the fracture strain of the material with a 45° defect orientation decreases by approximately 34.86%, and the fracture stress decreases by about 57.31%. In contrast, when the defect orientation is perpendicular to the tensile load direction (90° angle), the material suffers less damage, with fracture strain and fracture stress decreasing by approximately 9.96% and 26.81%, respectively. By integrating CT detection with 3D printing, this study links microscopic defects to macroscopic performance, providing a foundation for future optimization of composite material performance and defect control.