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Image-Based RKPM for Accessing Failure Mechanisms in Composite Materials

2024/11/17 by Yanran Wang, Yichun Tang, Wang, Yanran +7
Engineering · #Computational Engineering #FOS: Computer and information sciences #Finance #Industrial Vision Systems and Defect Detection #Infrastructure Maintenance and Monitoring #and Science (cs.CE)

paper · pdf · doi:10.48550/arxiv.2411.10998

openalex publication_date 2024/11/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Stress distributions and the corresponding fracture patterns and evolutions in the microstructures strongly influence the load-carrying capabilities of composite structures. This work introduces an enhanced phase-field fracture model incorporating interface decohesion to simulate fracture propagation and interactions at material interfaces and within the constituents of composite microstructures. The proposed method employs an interface-modified reproducing kernel (IM-RK) approximation for handling cross-interface discontinuities constructed from image voxels and guided by Support Vector Machine (SVM) ma-terial classification. The numerical models are directly generated from X-ray microtomography image voxels, guided by SVM using voxel color code information. Additionally, a strain energy-based phase field variable is introduced, eliminating the need to solve coupled field problems. The effectiveness of this method is demonstrated in modeling crack growth both along interfaces and across matrix and inclusion domains and in predicting the corresponding structural-scale mechanical behavior in composite structures. Furthermore, the proposed method has been validated against experimentally observed crack patterns.

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