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Modeling as-manufactured fiber-reinforced microstructures based on X-ray microcomputed tomography
- Source :
- Composites Science and Technology. 214:109004
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- A new approach is presented to convert X-ray microcomputed tomography (μCT) image data of as-manufactured fiber-reinforced microstructures into high-fidelity finite element (FE) meshes. The mesh-generation approach leverages existing image segmentation and meshing tools to generate FE meshes of a woven-fabric and fiber-reinforced composite (FRCs), where constituents in each microstructure are represented explicitly. Segmentation of fibers from X-ray μCT images was performed using a template-matching/Kalman-filter estimation algorithm, and flaws were segmented using Trainable Weka Segmentation. Segmentation data were converted into reduced-order images, which were subsequently imported into Simpleware™ for mesh generation. To demonstrate advancements of the mesh-generation process, biaxial and uniaxial FE simulations were performed in Abaqus® for the woven- and FRC microstructures, respectively. Results reveal that the mesh-generation approach allows for modeling of distinct interactions between constituents, including contact/friction between fibers and interactions at the fiber-matrix interfaces. Results from this work demonstrate that X-ray μCT images of complex fiber-reinforced microstructures can be converted into high-fidelity meshes, but the high number of elements required for discretization necessitates additional work to improving mesh efficiency.
- Subjects :
- Materials science
Discretization
Composite number
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
General Engineering
Image segmentation
Finite element method
Computational science
Mesh generation
Ceramics and Composites
Segmentation
Polygon mesh
Fiber
Composite material
ComputingMethodologies_COMPUTERGRAPHICS
Subjects
Details
- ISSN :
- 02663538
- Volume :
- 214
- Database :
- OpenAIRE
- Journal :
- Composites Science and Technology
- Accession number :
- edsair.doi...........c6e670e11d4944350b9c07f6e9ba9e62
- Full Text :
- https://doi.org/10.1016/j.compscitech.2021.109004