Image-Based RKPM for Accessing Failure Mechanisms in Composite Materials

TL;DR

This paper presents an advanced image-based phase-field fracture model using RKPM and SVM classification to simulate and analyze failure mechanisms in composite materials directly from microstructural images.

Contribution

It introduces an interface-modified RKPM approach combined with SVM-guided voxel classification for direct microstructural modeling of fracture in composites.

Findings

Accurately predicts crack growth along interfaces and within constituents.

Successfully models fracture evolution directly from microtomography images.

Validated against experimental crack patterns.

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.