Characterization of carbon fiber distribution in cement-based composites by Computed Tomography

Carbon-fiber-reinforced cement-based composites (CFRC) have been considered as an innovatively functional civil engineering material for self-monitoring buildings, snow-melting pavement and smart pavement. However, the distribution of carbon fiber can significantly influence the performance of CFRC, especially their mechanical and electrical properties. The main purpose of this research is to explore the effect of carbon fiber distribution on mechanical and electrical properties of CFRC. For this purpose, the components in consecutive slices of Computed Tomography (CT) images were identified and segmented by using their grayscale thresholds. The typical morphology of each component in micro-graph of fracture surface was classified. The classification was used to verify the results identified by their grayscale in CT images. Indexes of planar distribution (Pd), spatial distribution (Sd) and volume factor were designed and calculated using 3D reconstruction model of the specimen. The resistivity, bending strength, bending fracture energy and compressive strength of specimens with different carbon fiber contents were tested. Finally, the grey entropy correlation analysis (GECA) was conducted to determine the effect of fiber distribution on the performances of CFRC. Results showed that four components contained in CFRC are the sub-mm pores, highly clustered area, clustered area and fiber sparse area. The volume fractions of pores (VP), highly clustered area (VH), and clustered area (VC) increase with the increase of carbon fiber content while the sparse area (VS) shows the opposite trend. The Pd and Sd increase with the increase of carbon fiber content. Sd has greater influence on the bending strength and toughness of CFRC. Volume factor plays a more important role on compressive strength and electrical resistivity of CFRC.