Dataset for surface and internal damage after impact on CFRP laminates
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 delaminatio...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-08-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340922006576 |
| _version_ | 1811216081432346624 |
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| author | Saki Hasebe Ryo Higuchi Tomohiro Yokozeki Shin-ichi Takeda |
| author_facet | Saki Hasebe Ryo Higuchi Tomohiro Yokozeki Shin-ichi Takeda |
| author_sort | Saki Hasebe |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T06:33:28Z |
| format | Article |
| id | doaj.art-2a5cdefb3d934b91ab870efbaf3c0c73 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-04-12T06:33:28Z |
| publishDate | 2022-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-2a5cdefb3d934b91ab870efbaf3c0c732022-12-22T03:43:57ZengElsevierData in Brief2352-34092022-08-0143108462Dataset for surface and internal damage after impact on CFRP laminatesSaki Hasebe0Ryo Higuchi1Tomohiro Yokozeki2Shin-ichi Takeda3Corresponding author.; Department of Aeronautics and Astronautics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 JapanDepartment of Aeronautics and Astronautics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 JapanDepartment of Aeronautics and Astronautics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 JapanAeronautical Technology Directorate, Japan Aerospace Exploration Agency (JAXA), 6-13-1 Osawa, Mitaka-shi, Tokyo 181-0015, JapanVarious 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.http://www.sciencedirect.com/science/article/pii/S2352340922006576BVIDMachine learningThermoset CFRPNon-destructive testing |
| spellingShingle | Saki Hasebe Ryo Higuchi Tomohiro Yokozeki Shin-ichi Takeda Dataset for surface and internal damage after impact on CFRP laminates Data in Brief BVID Machine learning Thermoset CFRP Non-destructive testing |
| title | Dataset for surface and internal damage after impact on CFRP laminates |
| title_full | Dataset for surface and internal damage after impact on CFRP laminates |
| title_fullStr | Dataset for surface and internal damage after impact on CFRP laminates |
| title_full_unstemmed | Dataset for surface and internal damage after impact on CFRP laminates |
| title_short | Dataset for surface and internal damage after impact on CFRP laminates |
| title_sort | dataset for surface and internal damage after impact on cfrp laminates |
| topic | BVID Machine learning Thermoset CFRP Non-destructive testing |
| url | http://www.sciencedirect.com/science/article/pii/S2352340922006576 |
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