An efficient peridynamics-based statistical multiscale method for fracture in composite structure with randomly distributed particles
Zihao Yang, Shaoqi Zheng, Shangkun Shen, Fei Han

TL;DR
This paper introduces a novel multiscale peridynamics-based framework that efficiently simulates fracture in composite structures with randomly distributed particles by capturing microstructural heterogeneities and their effects on macroscopic failure.
Contribution
The paper develops a statistical multiscale peridynamics method that integrates microstructural heterogeneity characterization with efficient fracture simulation at macro scale.
Findings
The method accurately predicts fracture behavior in composite structures.
It significantly reduces computational costs compared to micro-mechanical models.
Numerical examples validate the method's efficiency and accuracy.
Abstract
The fracture simulation of random particle reinforced composite structures remains a challenge. Current techniques either assumed a homogeneous model, ignoring the microstructure characteristics of composite structures, or considered a micro-mechanical model, involving intractable computational costs. This paper proposes a peridynamics-based statistical multiscale (PSM) framework to simulate the macroscopic structure fracture with high efficiency. The heterogeneities of composites, including the shape, spatial distribution and volume fraction of particles, are characterized within the representative volume elements (RVEs), and their impact on structure failure are extracted as two types of peridynamic parameters, namely, statistical critical stretch and equivalent micromodulus. At the microscale level, a bond-based peridynamic (BPD) model with energy-based micromodulus correction…
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Taxonomy
TopicsNumerical methods in engineering · Composite Material Mechanics · Geotechnical Engineering and Underground Structures
