Parametric Reconstruction of Advanced Glass Fiber-reinforced Polymer Composites from X-ray Images

Publication Type:

Conference Abstract

Source:

8th Conference on Industrial Computed Tomography, Wels, Austria (2018)

Keywords:

GFRP, Materials Science, Modeling of Microstructures, Parametric Reconstruction, Tomography, µCT

Abstract:

A novel approach to the reconstruction of glass fiber-reinforced polymers (GFRP) from X‐ray micro‐computed tomography
(μCT) data is presented. The traditional fiber analysis workflow requires complete sample reconstruction, pre-processing and
segmentation, followed by the analysis of fiber distribution, orientation, and other features of interest. Each step in the chain
introduces errors that propagate through the pipeline and impair the accuracy of the estimation of those features. In the
approach presented in this paper, we combine iterative reconstruction techniques and a priori knowledge about the sample, to
reconstruct the volume and estimate the orientation of the fibers simultaneously. Fibers are modeled using rigid cylinders in
space whose orientation and position is then iteratively refined. The output of the algorithm is a non voxel-based dataset of the
fibers’ parametric representation, allowing to directly assess fiber features and distribution characteristics and to simulate the resulting material properties.

Research area: