Characterizing weave geometry in textile ceramic composites using digital image correlation

Techniques for characterizing tow architectures and defects in woven ceramic composites are required for generating high-fidelity geometric models and subsequently probing effects of defects on composite performance. Although X-ray computed tomography (CT) has been shown to provide the requisite information with potentially sub-μm resolution, the technique is inherently limited to probing only small volumes: on the order of a few unit cells of typical weaves. Here, we present an assessment of the efficacy of a complementary 2D technique, based on surface topography mapping via 3-D (three-dimensional) digital image correlation (DIC), with potential for ascertaining long-range features in weaves and defects that cannot be gleaned from CT imaging alone. Upon comparing surfaces reconstructed from CT and DIC data, we find that DIC is capable of resolving surface heights with a root mean square(RMS) error of ∼10 μm (about twice the CT voxel size, 4.4 μm) and a spatial resolution of ∼20 μm over areas of several cm². Achieving this level of resolution requires use of sufficiently small speckles (∼50 μm) and small subset size (∼300 μm) relative to the characteristic tow dimensions (∼1 mm). The error is somewhat higher (about 20 μm) in areas where surface discontinuities or rapid changes in topography exist (e.g., at tow boundaries).