Computer vision on x-ray data in industrial production and security applications: A comprehensive survey
X-ray imaging technology has been used for decades in clinical tasks to reveal the internal
condition of different organs, and in recent years, it has become more common in other …
condition of different organs, and in recent years, it has become more common in other …
Data-driven multiscale simulation of FRP based on material twins
In this paper, we propose a multiscale data-driven framework for Fiber Reinforced Polymer
(FRP) composites. At the mesoscopic scale, the 3D stress–strain material database is …
(FRP) composites. At the mesoscopic scale, the 3D stress–strain material database is …
Automated segmentation of computed tomography images of fiber-reinforced composites by deep learning
A Badran, D Marshall, Z Legault, R Makovetsky… - Journal of Materials …, 2020 - Springer
A deep learning procedure has been examined for automatic segmentation of 3D
tomography images from fiber-reinforced ceramic composites consisting of fibers and matrix …
tomography images from fiber-reinforced ceramic composites consisting of fibers and matrix …
Continuous fiber-reinforced aramid/PETG 3D-printed composites with high fiber loading through fused filament fabrication
Recent development in the field of additive manufacturing, also known as three-dimensional
(3D) printing, has allowed for the incorporation of continuous fiber reinforcement into 3D …
(3D) printing, has allowed for the incorporation of continuous fiber reinforcement into 3D …
[HTML][HTML] Deep learning based semantic segmentation of µCT images for creating digital material twins of fibrous reinforcements
In this study, a novel approach of processing μCT images to create digital material twins is
presented. A deep convolutional neural network (DCNN) was implemented and used to …
presented. A deep convolutional neural network (DCNN) was implemented and used to …
Direct modeling of the elastic properties of single 3D printed composite filaments using X-ray computed tomography images segmented by neural networks
This study introduces a new method for creating accurate microscale finite element (FE)
models of 3D printed composites. The approach involves utilizing conventional micro …
models of 3D printed composites. The approach involves utilizing conventional micro …
Descriptive modeling of textiles using FE simulations and deep learning
In this work we propose a novel and fully automated method for extracting the yarn
geometrical features in woven composites so that a direct parametrization of the textile …
geometrical features in woven composites so that a direct parametrization of the textile …
X-ray CT based multi-layer unit cell modeling of carbon fiber-reinforced textile composites: Segmentation, meshing and elastic property homogenization
Y Sinchuk, O Shishkina, M Gueguen, L Signor… - Composite …, 2022 - Elsevier
Generation of realistic finite element method (FEM) geometry of a textile composite material
at tow scale remains a challenging stage of material modeling. In this paper, a FE model …
at tow scale remains a challenging stage of material modeling. In this paper, a FE model …
[HTML][HTML] Efficient processing of μCT images using deep learning tools for generating digital material twins of woven fabrics
The greatest challenge in creating digital material twins from μCT images is the lack of a
robust and versatile tool for segmenting the μCT images and post-processing the …
robust and versatile tool for segmenting the μCT images and post-processing the …
[HTML][HTML] Damage evolution in braided composite tubes under torsion studied by in-situ X-ray computed tomography
Here we present the first real-time three dimensional (3D) observations of damage evolution
in a carbon fibre reinforced polymer (CFRP) composite tube under torsion. An in-situ torsion …
in a carbon fibre reinforced polymer (CFRP) composite tube under torsion. An in-situ torsion …