Abstract
This dataset includes four large field-of-view scanning electron microscopy (SEM) images together with associated Matlab scripts aimed for the analysis used in the joint publication. Each of the four stitched images is generated from a large number (between 15500 and 24500) high-resolution (195nm/pixel) scans, which have been stitched into four images stored as tiff-files. The images show the cross-section of fiber bundles in composite laminate and are well-suited for local fiber volume determination. The image resolution corresponds to between 600 and 2000 pixels covering each fiber. The imaged samples are from composite laminates with an overall fiber volume fraction in the range of 55% to 60%. The local fiber volume fraction is found both for the full cross-section, as an average fiber volume fraction over the individual bundles, and as a local fiber volume fraction found in a moving averaging box with a size corresponding to 5x5 fiber diameter (80x80 µm2) areas.
| Original language | English |
|---|---|
| Article number | 109058 |
| Journal | Data in Brief |
| Volume | 48 |
| Number of pages | 7 |
| ISSN | 2352-3409 |
| DOIs | |
| Publication status | Published - 2023 |
Keywords
- Bundle segmentation
- SEM
- Fiber volume fraction
- Wind turbine blades
Fingerprint
Dive into the research topics of 'Dataset for scanning electron microscopy based local fiber volume fraction analysis of non-crimp fabric glass fiber reinforced composites'. Together they form a unique fingerprint.Research output
- 1 Journal article
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The impact of the fiber volume fraction on the fatigue performance of glass fiber composites
Mortensen, U. A., Rasmussen, S., Mikkelsen, L. P., Fraisse, A. & Andersen, T. L., 2023, In: Composites Part A: Applied Science and Manufacturing. 169, 13 p., 1074936.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile396 Downloads (Orbit)
Datasets
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Dataset for scanning electron microscopy based local fiber volume fraction analysis of non-crimp fabric glass fiber reinforced composites
Mikkelsen, L. P. (Creator), Fæster, S. (Creator) & Dahl, V. A. (Creator), Zenodo, 2022
DOI: 10.5281/zenodo.5820067, https://zenodo.org/record/5820067
Dataset
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