OpenFiberSeg: Open-source segmentation of individual fibers and porosity in tomographic scans of additively manufactured short fiber reinforced composites

From a modelling standpoint, the morphology of additively manufactured (AM) high-performance short fiber reinforced polymer (SFRP) is essential to characterize, yet this task poses great challenges. The method presented extracts individual fibers from tomographic scans and produces a segmentation that is 93.1% precise on average on a per-fiber basis across a large range of fiber filling ratios (5-40 wt.%), needs minimal human input and is scalable to full-sized datasets containing & SIM; 105 individual fibers. In addition, this tool allows the analysis of the correlated length and orientation distribution of fibers, and the quantification of shear-induced alignment and fiber breakage. The method is validated by successfully reproducing the segmentation of (continuous) fiber reinforced composites published in 2 separate studies and by predicting the fiber volume fraction and material density directly from the tomographic data of SFRPs. The output can serve as a basis for constituent-level me-chanical modelling, and to gain insight into the relationship between processing parameters, morphology and mechanical behavior of SFRP. The full source code and imaging data are attached to this publication.

Automated summary

A method for segmenting the morphology and fiber distribution of high-performance short fiber reinforced polymers (SFRPs) using tomographic scans is presented. The method is validated and can be used for mechanical modeling and understanding the relationship between processing parameters, morphology, and mechanical behavior of SFRPs.