Micro‐mesoscopic analysis of 3D void formation and evolution in CFRP composite using high‐resolution x‐ray microtomography

Author:

Peng Yunfei1,Li Maojun1ORCID,Yang Xujing1

Affiliation:

1. State Key Laboratory of Advanced Design and Manufacture for Vehicle Body Hunan University Changsha Hunan China

Abstract

AbstractVoid defect is prevalent during the composite manufacturing process and may reduce the mechanical properties of composite structures, while limited information about three‐dimensional void distribution and evolution can be found due to the difficulties in void observation. In this work, void defects at different positions were detected and analyzed using x‐ray microtomography (XRM), and the random forest algorithm was implemented for segmenting components of CFRP samples. Results showed a trend of gradual rising porosity in the axial direction, with an increase of ~250% of porosity at the outlet of resin injection compared to the one at the inlet during the composite manufacturing process. The voids mainly featured with microscale between carbon fibers, with less distribution between fiber bundles and resin‐rich zones. Void defects achieved aggregation at the middle position of manufactured laminate, which is probably related to pressure interception. In the axial direction, the proportion of large‐diameter voids gradually increased, and a large volume of connected voids appeared near the outlet. Due to the shear deformation of resin and fiber and the pressure gradient effect, most of the voids showed stripe shape. The spatial orientation of voids was predominantly along the direction of resin flow and fluctuated due to fiber curl.Highlights 3D void characteristics in CFRP were studied using the XRM technique. Void formation and the effects of fibers on void morphology were analyzed. Dynamic void transport mechanisms during CFRP manufacturing were studied. Location and morphology of voids are helpful for CFRP damage modeling. The effective partitioning of CFRP was achieved using a random forest algorithm.

Funder

National Natural Science Foundation of China

Publisher

Wiley

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