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An experimentally validated concurrent three-scale model for 3D woven composite structures

  • Siyang Wu
  • , Licheng Guo*
  • , Ziyi Liu
  • , Zhixing Li
  • , Siyuan Chen
  • , Gang Liu
  • , Heran Wang
  • *Corresponding author for this work
  • Harbin Institute of Technology
  • East China Jiaotong University

Research output: Contribution to journalArticlepeer-review

Abstract

To alleviate the “curse of dimensionality” bottleneck problem in the three-scale concurrent damage evolution computation of composite structures, a FE-SCA2 concurrent multiscale model is developed to investigate the macro-meso-micro damage behavior of 3D woven composite (3DWC) structures. In the model, the Finite Element Method (FEM) is applied for macroscopic structural analysis, and the Self-consistent Clustering Analysis (SCA) method is employed to efficiently compute the damage evolution of mesoscale 3DWC representative volume elements (RVEs) and microscale yarn RVEs. The three-scale models achieve concurrent computation through scale coupling equations, while the cluster-based model enables orders-of-magnitude reduction in overall computational scale. The macroscopic damage variable for the concurrent three-scale computation is defined to characterize the macroscopic crack propagation of 3DWC structures. The experiments of open-hole 3DWC (OH3DWC) plates are conducted, which provides the multiple validation for macroscopic mechanical behavior, full-field strain and macro-meso-micro damage mechanisms. Based on the FE-SCA2 model, the multiscale analysis of OH3DWC plates is performed. For the warp tensile condition and woven architecture studied in the paper, the FE-SCA2 method can accurately predict the macroscopic non-linear mechanical behavior, strain fields and macro-meso-micro damage behavior of OH3DWC plates.

Original languageEnglish
Article number120515
JournalComposite Structures
Volume391
DOIs
StatePublished - Jul 2026

Keywords

  • 3D woven composites
  • Concurrent three-scale model
  • Multiscale damage behavior
  • Self-consistent clustering analysis

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