Anisotropic analysis of fibrous and woven materials part 1: Estimation of local orientation

Abstract

In many material science applications mechanical and thermal properties are often locally anisotropic. As such, a common requirement for high fidelity computational modeling is the knowledge of the local property tensor. In fibrous or woven materials, the properties are known along the direction of the fibers, so it is necessary to know their orientation to correctly align the tensors. In this study, three techniques are investigated for estimating the direction in these microstructures, obtained on Cartesian grids using microtomography as grayscale values: a common image processing technique called structure tensor, a method based on artificial flux, and a novel ray-casting approach. All the methods start by identifying the fibers using a grayscale cutoff. The first technique estimates the fiber direction based on the eigenvector corresponding to the smallest eigenvalue obtained from the grayscale gradients. The second method estimates the orientation as the local steady-state flux vector in a heat transfer simulation with temperature gradients imposed in all three directions. In the third method, rays are created at the center of each solid voxel and travel until the first collision with a material boundary occurs. The local direction vector is estimated based on the travel distance of these rays. The performance of each method is studied by examining their predictions for artificially generated weaves and fibrous materials, whose true local fiber direction is known a priori. The last part of this paper contains fiber orientation simulations for different real world materials scanned with X-ray microtomography, and describes a new workflow for weaves.