Quantitative Evaluation of Thermomechanical Fatigue Damage in Composite Materials Using X-Ray Computed Tomography and Machine Learning
Piotr Przystałka, Paweł Chrzanowski, Tomasz Rogala, Andrzej Katunin · 2026
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Description
Composite materials can crack in complex ways when heat and repeated bending act on them at the same time. Piotr Przystałka and co-authors proposed a way to measure that damage in 2026. Their method scans the material with X-ray computed tomography, which builds a three-dimensional view of the inside, and then uses machine learning to sort the damage it finds.
A 3D U-Net model marks out damaged regions, while shape and brightness features help label each damage type. The reported scores for the framework passed 99 percent on the tests used. The authors argue that such checks could help judge how much fatigue life a part has left without cutting it open.
Catalog record
| CREATOR | Piotr Przystałka, Paweł Chrzanowski, Tomasz Rogala, Andrzej Katunin |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 111 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |