AI Article Synopsis
- CFRP structures, like aircraft, can suffer both visible and hidden damage from foreign object impacts, leading to a reduction in strength.
- Despite external damage sometimes being minimal, internal issues like matrix cracks and delamination can significantly affect the material's integrity.
- A dataset has been created to help predict internal damage based solely on surface damage profiles using Machine Learning, providing valuable resources for researchers and engineers studying CFRP impact behavior.
Article Abstract
Various foreign objects can collide with CFRP structures, such as CFRP aircraft. Once something impacts with CFRP laminates, both surface damage and internal damage can occur. Even if the external damage is such invisible as called barely visible impact damage, there are matrix cracks or delamination that are the main cause of compressive strength reduction, so it is difficult to find the relationship between external and internal damage on CFRP laminates. This dataset is prepared for predicting impact information only from surface damage profiles using Machine Learning (Hasebe et al., 2022). It includes three data, surface damage image (png), surface depth contour image(png), and internal damage image after ultrasound C-scanning (jpg) after low-velocity impact testing under various impact conditions. The data are helpful for researchers and engineers who deal with the impact behavior of CFRP or data science.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294053 | PMC |
| http://dx.doi.org/10.1016/j.dib.2022.108462 | DOI Listing |
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