Multimodal data fusion enhanced deep learning prediction of crack path segmentation in CFRP composites
P Zhang, K Tang, G Chen, J Li, Y Li - Composites Science and Technology, 2024 - Elsevier
Carbon fiber-reinforced polymer (CFRP) composites are extensively used in various
engineering applications due to their superior strength-to-weight ratio and excellent …
engineering applications due to their superior strength-to-weight ratio and excellent …
[HTML][HTML] Hybrid-Segmentor: Hybrid approach for automated fine-grained crack segmentation in civil infrastructure
It is essential to detect and segment cracks in various infrastructures, such as roads and
buildings, to ensure safety, longevity, and cost-effective maintenance. Despite deep learning …
buildings, to ensure safety, longevity, and cost-effective maintenance. Despite deep learning …
Super-resolution processing of synchrotron CT images for automated fibre break analysis of unidirectional composites
Fibre breaks govern the strength of unidirectional composite materials under tension. The
progressive development of fibre breaks is studied using in situ X-ray computed …
progressive development of fibre breaks is studied using in situ X-ray computed …
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 …
composites is of vital importance to evaluate the service life and improve reliability of the …
The Prediction of Homogenized Effective Properties of Continuous Fiber Composites Based on a Deep Transfer Learning Approach
Z Wang, S Wang, C Ma, Z Yang - Composites Science and Technology, 2025 - Elsevier
The homogenization method based on the representative volume element can effectively
mitigate the computational challenges posed by the significant scale differences in …
mitigate the computational challenges posed by the significant scale differences in …
[HTML][HTML] A deep-learning-based workflow for reconstructing and segmenting challenging sets of time-resolved X-ray micro-computed tomography data
S Waldner, J Huwyler, M Puchkov - SoftwareX, 2024 - Elsevier
We present a deep-learning-based software pipeline for reconstructing and segmenting
large sets of time-resolved micro-computed tomography (µCT) image data. We construct and …
large sets of time-resolved micro-computed tomography (µCT) image data. We construct and …
Advancing X-ray imaging with deep learning: Physics-inspired reconstruction approaches
Y Zhang - 2024 - portal.research.lu.se
The development of high-brilliance X-ray sources, such as the fourth-generation diffraction-
limited storage rings and X-ray free-electron lasers, have opened up new possibilities for X …
limited storage rings and X-ray free-electron lasers, have opened up new possibilities for X …
AI-Driven CFRP Structure Evaluation: Deep Learning-Powered Automated Air-Coupled Ultrasonic Detection of Defect
A Datta, S Kota, V Srinivasa - Journal of Non-Destructive Testing and …, 2023 - jnde.isnt.in
In this study, the successful experiments with air-coupled ultrasonic testing (ACUT)
conducted on a 300 mm x 300 mm CFRP laminate, constructed from unidirectional Carbon …
conducted on a 300 mm x 300 mm CFRP laminate, constructed from unidirectional Carbon …