Mixed mode (I/II) fracture of Glass/PA6 thermoplastic composites based on hybrid distance and correlation-based multiple target tracking methods

Abstract

Conventional methods for predicting crack growth in composite materials often face limitations due to the complex nature of these materials, resulting in inaccurate predictions of crack initiation and propagation. To overcome these limitations, the research employs an advanced image processing technique to capture the behavior of GLASS/PA6 thermoplastic composites. Three algorithms (Euclidean Distance-Based Tracking Algorithm, Correlation-Based Tracking Algorithm, and Corner-Based Tracking Algorithm) are utilized to predict strain and displacement fields. The methodology involves recording displacement values through a sequence of images and applying image processing techniques to identify distinct surface features on the material. The results demonstrate strong consistency between numerical simulations and experimental data, indicating the effectiveness of this approach.

Graphical abstract

Keywords

mixed-mode I/II fracture / thermoplastic composite / digital image correlation method / image processing

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