Prediction of mechanical and electrical properties of carbon fibre-reinforced self-sensing cementitious composites

Abstract

The transmission of signal values in self-sensing concrete allows us to precisely locate damaged structures and prevent disasters. Currently, there are over ten functional materials used in self-sensing concrete applications. Carbon fibre (CF) is a well-known functional material that has been extensively studied for its reproducibility and accuracy in self-sensing concrete experiments. In contrast, this study is based on finite element modelling to rapidly predict the impact of the functional filler material, CF, on concrete performance. This paper simulates the mechanical and piezoresistive properties of concrete with unsized and desized short-cut CFs at lengths of 3, 6, and 12 mm. Four different weight ratios were considered for each type of CF. The results indicate that the inclusion of CF increases compressive strength by approximately 2 MPa, while flexural strength can increase by up to 39%, with the unsized 6 mm fibres performing best at a concentration of 0.7 wt%. In the piezoresistive model, the higher fractional change in resistivity between 0 and 2 MPa is attributed to the formation of a conductive circuit. The predicted trends in mechanical strength and resistance variation align well with experimental observations. Therefore, this proposed model holds the potential to aid in the development of design strategies aimed at fine-tuning the microstructure of these self-sensitive materials to enhance performance and facilitate the design and application of carbon fibres in cementitious composites.