[HTML][HTML] Experimental characterization methods and numerical models of woven composite preforms: A review

T Yang, L Zhang, Z Li, K Huang, L Guo - Composites Part A: Applied …, 2024 - Elsevier
The formation of woven preforms is crucial for the quality and performance of textile
composites produced through the Liquid Composite Molding (LCM) process. However, the …

Dynamic mechanical response prediction model of honeycomb structure based on machine learning method and finite element method

X Shen, Q Hu, D Zhu, S Qi, C Huang, M Yuan… - International Journal of …, 2024 - Elsevier
In this study, a novel framework was presented for accelerating the prediction of the
mechanical response of honeycomb structures under dynamic crushing, using 2D cells to …

[HTML][HTML] Automatic yarn path extraction of large 3D interlock woven fabrics with confidence estimation

Y Sinchuk, Y Wielhorski, A Mendoza… - Composites Part A …, 2024 - Elsevier
Modeling realistic textile composite structures remains a challenging task due to their
complex geometry. In this paper, a novel method for reconstructing yarn paths based on …

Deep-learning image enhancement and fibre segmentation from time-resolved computed tomography of fibre-reinforced composites

R Guo, J Stubbe, Y Zhang, CM Schlepütz… - … Science and Technology, 2023 - Elsevier
Monitoring the microstructure and damage development of fibre-reinforced composites
during loading is crucial to understanding their mechanical properties. Time-resolved X-ray …

Automatic segmentation and fibre orientation estimation from low resolution X-ray computed tomography images of 3D woven composites

Y Pannier, P Coupé, T Garrigues, M Gueguen… - Composite …, 2023 - Elsevier
In this work, we compare different methods for the automatic segmentation of
microtomographic images at the mesoscopic scale of 3D woven carbon fibre composite …

Alignment of 3D woven textile composites towards their ideal configurations

M Rubino, A Mendoza, Y Wielhorski… - Computer Methods in …, 2024 - Elsevier
The objective of the present study is to create a parametric model of an ideal 3D woven
textile from a computed tomography at mesoscale without prior knowledge of the fabric …

[HTML][HTML] Obtaining the longitudinal compressive response of unidirectional laminate composites from fiber misalignment micrographs through machine learning

B Liu, S Costa, X Liu, D Wilhelmsson, X Jia - Composites Part A: Applied …, 2025 - Elsevier
The longitudinal compressive behavior of unidirectional composite laminates with fiber
waviness is highly complex and plays a crucial role in determining final failure of …

An improved automatic image labeling and classification algorithm for multi-mode damage quantification of 2.5 D woven composites based on deep learning strategy

J Zheng, K Qian, X Liu, Z Pang, Z Yang, J Sun… - … Science and Technology, 2025 - Elsevier
Accurately identifying and quantifying the complex multi-mode damages in woven
composites is of vital importance to evaluate the service life and improve reliability of the …

Quantitative evaluation of process-induced yarn geometric imperfection effect on mechanical response of plain-woven C/SiC composites: X-ray tomography-based …

Z Gu, X Zhu, X Lu, P Wang, H Lei - Thin-Walled Structures, 2025 - Elsevier
In this paper, the morphology and distribution of yarn imperfections induced by the
fabrication process in C/SiC composites were captured and statistically analyzed by X-ray …

Automatic reconstruction of closely packed fabric composite RVEs using yarn-level micro-CT images processed by convolutional neural networks (CNNs) and based …

C Tang, J Zou, Y Xiong, B Liang, W Zhang - Composites Science and …, 2024 - Elsevier
Micro-CT scanning is an advanced technique to reconstruct inner architectures for RVEs of
fabric composites. Currently, however, there exist few automatic approaches to separate …