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  4. Application of a Tensor Interpolation Method on the Determination of Fiber Orientation Tensors From Computed Tomography Images
 
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2022
Conference Paper
Title

Application of a Tensor Interpolation Method on the Determination of Fiber Orientation Tensors From Computed Tomography Images

Abstract
When investigating the mechanical behavior of fiber-reinforced polymers, fiber orientation plays a decisive role concerning anisotropy. Fiber orientation distributions are typically measured in the form of fiber orientation tensors. In order to measure orientation tensors, computed tomography scans and consecutive image processing methods have become one of the leading non-destructive testing methods. The conflict between scan resolution and sample size limits the volume that can be scanned. To obtain the fiber orientation behavior across an entire plate, a direct interpolation of orientation tensors computed from CT scans of smaller volumes at selected coordinates of the plate is implemented. Rather than a component-based interpolation, the authors chose a decomposition and reassembly method interpolating shape and orientation of the tensors separately. While this approach has been implemented and used for e.g. diffusion tensors in medical imaging, the authors consider the application to sparse but measured CT-based data to be a novelty.
Author(s)
Blarr, Juliane
Karlsruher Institut für Technologie -KIT-  
Kresin, Noah
Karlsruher Institut für Technologie -KIT-  
Krauß, Constantin
Karlsruher Institut für Technologie -KIT-  
Weidenmann, Kay André  
Fraunhofer-Institut für Chemische Technologie ICT  
Liebig, Wilfried V.
Fraunhofer-Institut für Chemische Technologie ICT  
Elsner, Peter  
Fraunhofer-Institut für Chemische Technologie ICT  
Mainwork
20th European Conference on Composite Materials, ECCM 2022. Proceedings. Vol.4 - Modeling and Prediction  
Conference
European Conference on Composite Materials 2022  
Open Access
File(s)
Download (668.07 KB)
Rights
CC BY-NC 4.0: Creative Commons Attribution-NonCommercial
DOI
10.24406/publica-1064
Language
English
Fraunhofer-Institut für Chemische Technologie ICT  
Keyword(s)
  • image processing

  • non-destructive testing

  • quaternions

  • tensor algebra

  • tensor mapping

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