BSE-based dispersion quantification of carbon fibres in cementitious composite through FCM-CA approach

Micro-engineered cementitious composite requires a quantitative evaluation of the phase dispersion state. In the application of the carbon fibre enhanced cementitious composite, the excellent electrical conductivity of the fibre network has been utilized for structural monitoring and internal heat generation. The dispersion state of carbon fibres significantly influences the performance of the functional application. However, it is challenging to evaluate the fibre dispersion with a quantitative consideration of the spatial arrangement. In this paper, an image-based approach is proposed to evaluate the spatial dispersion of carbon fibres in the cementitious composite. The independently programmed approach integrates fuzzy c-mean (FCM) clustering, random sequential addition simulation and originally developed cellular automata (CA). Quantification of fibre dispersion is performed with the nearest-neighbour analysis on the backscattered electron (BSE) images of the fibre-cement composite. Further investigation is conducted with the proposed approach, BSE images, electrical resistivity, compressive strength and flexural strength. Mechanical and chemical mixing techniques are applied during the sample preparation to investigate the dispersion behaviour in different systems. The evaluation results in a quantitative pattern of the dispersion coefficient within the range from 0.44 to 0.48. The dispersion and electrical resistivity results demonstrate that a well-distributed conductive network is formed with up to 6.5 min of mechanically controlled mixing. A negative correlation between the dispersion coefficient and the electrical resistivity is found in the form of the second-order power law. The microscale arrangement of fibre dispersion minorly influences compressive and flexural strength, but significantly influences the electrical function. Electrical evaluation of fibre dispersion confronts inconsistency in the chemical mixing system. (C) 2020 Elsevier Ltd. All rights reserved.