Interactive Exploration and Visualization Using MetaTracts extracted from Carbon Fiber Reinforced Composites

Abstract

This work introduces a tool for interactive exploration and visualization using MetaTracts. MetaTracts is a novel method for extraction and visualization of individual fiber bundles and weaving patterns from X-ray computed tomography (XCT) scans of endless carbon fiber reinforced polymers (CFRPs). It is designed specifically to handle XCT scans of low resolutions where the individual fibers are barely visible, which makes extraction of fiber bundles a challenging problem. The proposed workflow is used to analyze unit cells of CFRP materials integrating a recurring weaving pattern. First, a coarse version of integral curves is used to trace sections of the individual fiber bundles in the woven CFRP materials. We call these sections MetaTracts. In the second step, these extracted fiber bundle sections are clustered using a two-step approach: first by orientation, then by proximity. The tool can generate volumetric representations as well as surface models of the extracted fiber bundles to be exported for further analysis. In addition a custom interactive tool for exploration and visual analysis of MetaTracts is designed. We evaluate the proposed workflow on a number of real world datasets and demonstrate that MetaTracts effectively and robustly identifies and extracts fiber bundles.

open_iA: A tool for processing and visual analysis of industrial computed tomography datasets

“…• Dynamic Volume Lines (Weissenböck, Fröhler, Gröller, Kastner, & Heinzl, 2019) facilitate the comparison of multiple slightly varying volumetric datasets, by mapping them to 1D and applying a nonlinear scaling to highlight regions with large differences. • With MetaTracts (Bhattacharya, Heinzl, Amirkhanov, Kastner, & Wenger, 2015, Bhattacharya et al (2017) one can characterize and analyze fiber bundles as well as weaving patterns in fiber-reinforced polymers.…”

A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science

“…Quan and Vo [QV15] propose a measure based on the center of mass as well as the start and end point of each fiber. Bhattacharya et al [BWW*17] employ distance measures for the clustering of fiber tracts of industrial fiber‐reinforced materials into fiber bundles. While these measures are designed for clustering similar fibers, we are interested in determining matches of the same underlying fiber in different datasets.…”