Mechanical properties prediction of injection molded short/long carbon fiber reinforced polymer composites using micro X-ray computed tomography

Shenli Pei, Kaifeng Wang, Jingjing Li, Yang Li, Danielle Zeng, Xuming Su, Xianghui Xiao, Hui Yang

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article number105732
JournalComposites Part A: Applied Science and Manufacturing
Volume130
DOIs
StatePublished - Mar 2020

All Science Journal Classification (ASJC) codes

  • Ceramics and Composites
  • Mechanics of Materials

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