TY - JOUR
T1 - Mechanical properties prediction of injection molded short/long carbon fiber reinforced polymer composites using micro X-ray computed tomography
AU - Pei, Shenli
AU - Wang, Kaifeng
AU - Li, Jingjing
AU - Li, Yang
AU - Zeng, Danielle
AU - Su, Xuming
AU - Xiao, Xianghui
AU - Yang, Hui
N1 - Publisher Copyright:
© 2019
PY - 2020/3
Y1 - 2020/3
N2 - This paper addresses the challenge of reconstructing nonuniformly orientated fiber-reinforced polymer composites (FRPs) with three-dimensional (3D) geometric complexity, especially for fibers with curvatures, and proposes a framework using micro X-ray computed tomography (μXCT) images to quantify the fiber characteristics in 3D space for elastic modulus prediction. The FRP microstructure is first obtained from the μXCT images. Then, the fiber centerlines are efficiently extracted with the proposed fiber reconstruction algorithm, i.e., iterative template matching, and the 3D coordinates of the fiber centerlines are adopted for quantitative characterization of the fiber morphology. Finally, Young's modulus is predicted using the Halpin-Tsai model and laminate analogy approach, and the fiber configuration averaging method with the consideration of the fiber morphology. The new framework is demonstrated on both injection-molded short and long carbon fiber-reinforced polymer composites, whose fiber morphology and predicted mechanical properties are validated through previous pyrolysis and quasi-static tensile tests, respectively.
AB - This paper addresses the challenge of reconstructing nonuniformly orientated fiber-reinforced polymer composites (FRPs) with three-dimensional (3D) geometric complexity, especially for fibers with curvatures, and proposes a framework using micro X-ray computed tomography (μXCT) images to quantify the fiber characteristics in 3D space for elastic modulus prediction. The FRP microstructure is first obtained from the μXCT images. Then, the fiber centerlines are efficiently extracted with the proposed fiber reconstruction algorithm, i.e., iterative template matching, and the 3D coordinates of the fiber centerlines are adopted for quantitative characterization of the fiber morphology. Finally, Young's modulus is predicted using the Halpin-Tsai model and laminate analogy approach, and the fiber configuration averaging method with the consideration of the fiber morphology. The new framework is demonstrated on both injection-molded short and long carbon fiber-reinforced polymer composites, whose fiber morphology and predicted mechanical properties are validated through previous pyrolysis and quasi-static tensile tests, respectively.
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U2 - 10.1016/j.compositesa.2019.105732
DO - 10.1016/j.compositesa.2019.105732
M3 - Article
AN - SCOPUS:85076750059
SN - 1359-835X
VL - 130
JO - Composites Part A: Applied Science and Manufacturing
JF - Composites Part A: Applied Science and Manufacturing
M1 - 105732
ER -