Characterization of the fiber orientations in non-crimp glass fiber reinforced composites using structure tensor: Paper

N. Jeppesen; V. A. Dahl; A. N. Christensen; A. B. Dahl; L. P. Mikkelsen

doi:10.1088/1757-899X/942/1/012037

Characterization of the fiber orientations in non-crimp glass fiber reinforced composites using structure tensor: Paper

N. Jeppesen^*, V. A. Dahl, A. N. Christensen, A. B. Dahl, L. P. Mikkelsen

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › Research › peer-review

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Abstract

The mechanical properties of composite fiber materials are highly dependent on the orientation of the fibers. Micro-CT enables acquisition of high-resolution 3D images, where individual fibers are visible. However, manually extracting orientation information from the samples is impractical due to the size of the 3D images. In this paper, we use a Structure Tensor to extract orientation information from a large 3D image of non-crimp glass fiber fabric. We go through the process of segmenting the image and extracting the orientation distribution step-by-step using structure tensor and show the results of the analysis of the studied non-crimp fabric. The Jupyter notebooks and Python code used for the data-analysis are publicly available, detailing the process and allowing the reader to use the method on their own data. The results show that structure tensor analysis works well for determining fiber orientations, which has many useful applications.

Original language	English
Article number	012037
Journal	IOP Conference Series: Materials Science and Engineering
Volume	942
Issue number	1
Number of pages	12
ISSN	1757-8981
DOIs	https://doi.org/10.1088/1757-899X/942/1/012037
Publication status	Published - 2020
Event	41st Risø International Symposium on Materials Science - Online event, Denmark Duration: 7 Sept 2020 → 10 Sept 2020

Conference

Conference	41st Risø International Symposium on Materials Science
Country/Territory	Denmark
City	Online event
Period	07/09/2020 → 10/09/2020

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10.1088/1757-899X/942/1/012037Licence: CC BY

FulltextFinal published version, 11 MBLicence: CC BY

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MicroLab at DTU Wind Energy
Mikkelsen, L. P. (PI), Fæster, S. (PI), Vogeley, E. (PI) & Sørensen, B. F. (PI)
01/01/2021 → …
Project: Research
3DIM: 3D imaging center
Poulsen, H. F. (Project Manager), Gundlach, C. (Project Manager), Dahl, A. B. (Project Participant), Oddershede, J. (Project Participant), Trinderup, C. H. (Project Participant), Simonsen, S. B. (Project Participant), Zheng, Y. (Project Participant), Brink, B. (Project Participant), Lauridsen, T. (Project Participant), Thydén, K. T. S. (Project Participant), Sanna, S. (Project Participant), Baier-Stegmaier, S. M. (Project Participant), Bentzen, J. J. (Project Participant), Christensen, A. N. (Project Participant), Sørensen, H. O. (Project Participant), Mikkelsen, L. P. (Project Participant), Fæster, S. (Project Participant), Johansen, N.F.-J. (PI), Mokso, R. (PI), Kjer, H. M. (PI), Christensen, A. N. (PI), Quagliotti, D. (PI), Zhang, Y. (PI), Rasmussen, P. W. (PI) & Dahl, V. A. (PI)
01/01/2016 → 31/12/2029
Project: Research

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Characterization of the Fiber Orientations in Non-Crimp Glass Fiber Reinforced Composites using Structure Tensor
Jeppesen, N. (Contributor), Christensen, A. (Contributor), Mikkelsen, L. (Contributor), Dahl, A. (Contributor) & Dahl, V. (Contributor), Zenodo, 2020
DOI: 10.5281/zenodo.3877522, https://zenodo.org/record/3877522
Dataset

Cite this

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abstract = "The mechanical properties of composite fiber materials are highly dependent on the orientation of the fibers. Micro-CT enables acquisition of high-resolution 3D images, where individual fibers are visible. However, manually extracting orientation information from the samples is impractical due to the size of the 3D images. In this paper, we use a Structure Tensor to extract orientation information from a large 3D image of non-crimp glass fiber fabric. We go through the process of segmenting the image and extracting the orientation distribution step-by-step using structure tensor and show the results of the analysis of the studied non-crimp fabric. The Jupyter notebooks and Python code used for the data-analysis are publicly available, detailing the process and allowing the reader to use the method on their own data. The results show that structure tensor analysis works well for determining fiber orientations, which has many useful applications.",

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AB - The mechanical properties of composite fiber materials are highly dependent on the orientation of the fibers. Micro-CT enables acquisition of high-resolution 3D images, where individual fibers are visible. However, manually extracting orientation information from the samples is impractical due to the size of the 3D images. In this paper, we use a Structure Tensor to extract orientation information from a large 3D image of non-crimp glass fiber fabric. We go through the process of segmenting the image and extracting the orientation distribution step-by-step using structure tensor and show the results of the analysis of the studied non-crimp fabric. The Jupyter notebooks and Python code used for the data-analysis are publicly available, detailing the process and allowing the reader to use the method on their own data. The results show that structure tensor analysis works well for determining fiber orientations, which has many useful applications.

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Characterization of the fiber orientations in non-crimp glass fiber reinforced composites using structure tensor: Paper

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MicroLab at DTU Wind Energy

3DIM: 3D imaging center

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Characterization of the Fiber Orientations in Non-Crimp Glass Fiber Reinforced Composites using Structure Tensor

Cite this