TY - JOUR
T1 - Anisotropic analysis of fibrous and woven materials part 1
T2 - Estimation of local orientation
AU - Semeraro, Federico
AU - Ferguson, Joseph C.
AU - Panerai, Francesco
AU - King, Robert J.
AU - Mansour, Nagi N.
N1 - Funding Information:
This work was supported by the NASA Entry System Modeling project (Dr. Michael D. Barnhardt, Project Manager; Dr. Aaron M. Brandis, Principal Investigator). This research used resources of the Advanced Light Source, which is a DOE Office of Science User Facility under contract No. DE-AC02-05CH11231 . The authors would like to acknowledge Sergio F. Izquierdo and Arnaud P. Borner for the review of the manuscript. F. Panerai was in part supported by the Air Force Office of Scientific Research under award number FA9559-19-1-0050 (Dr. Ivett Leyva, Program Officer).
Funding Information:
This work was supported by the NASA Entry System Modeling project (Dr. Michael D. Barnhardt, Project Manager; Dr. Aaron M. Brandis, Principal Investigator). This research used resources of the Advanced Light Source, which is a DOE Office of Science User Facility under contract No. DE-AC02-05CH11231. The authors would like to acknowledge Sergio F. Izquierdo and Arnaud P. Borner for the review of the manuscript. F. Panerai was in part supported by the Air Force Office of Scientific Research under award number FA9559-19-1-0050 (Dr. Ivett Leyva, Program Officer).
Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - 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.
AB - 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.
KW - Computed tomography
KW - Fiber orientation
KW - Material modeling
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U2 - 10.1016/j.commatsci.2020.109631
DO - 10.1016/j.commatsci.2020.109631
M3 - Article
AN - SCOPUS:85081676396
SN - 0927-0256
VL - 178
JO - Computational Materials Science
JF - Computational Materials Science
M1 - 109631
ER -