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Development of Computational, Image Processing and Deep Learning Methods for the Microstructure Characterization of Carbon Fiber Reinforced Polyamide 6 Based on CT Images
Juliane Blarr
2025
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Discontinuously fiber reinforced polymers exhibit complex microstructures. Quantities to characterize the latter have been developed over time, such as the fiber volume content or fiber orientation distributions, which can be acquired through computed tomography images and subsequent image processing. This thesis deals with the development of (partially AI-based) methods in this context, especially considering challenges of contrast and resolution with carbon fibers and scale-bridging issues.
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Keywords
- artificial intelligence
- Bildauswertung
- CT images
- CT-Bilder
- deep learning
- Faserverstärkte Kunststoffe
- fiber reinforced polymers
- Image processing
- Künstliche Intelligenz
- Maschinelles Lernen
Links
DOI: 10.5445/KSP/1000176200Editions