Self-sensing and piezoresistive performance of carbon fibre textile-reinforced cementitious composites under tensile loading

• A novel self-sensing technique monitored cracking behaviour, textile-matrix debonding, and cover spalling. • Single- and multiple-sensor techniques captured global and local TRC behaviour, enabling precise crack quantification and localisation. • Optimal piezoresistive performance was analysed based on reinforcement orientation and matrix type. • A constitutive relationship was proposed between the fractional change in resistance and applied tensile strain. This paper introduces an advanced self-sensing technique for two-dimensional carbon fibre textile-reinforced concrete (TRC) under monotonic tensile loading to monitor cracking behaviour, textile-matrix bond performance, fibre slippage, and cover spalling. The study employs single-sensor and multiple-sensor techniques to capture both global and local TRC behaviours, including crack quantification and location. It examines the conductive mechanism and evaluates piezoresistive performance in elastic and post-elastic regimes. Results demonstrated that the single-sensor technique provided comprehensive monitoring, while the multi-sensor approach improved crack detection. The conductive mechanism, driven by the carbon fibre network, exhibited dynamic changes with mechanical deformation, with the fractional change in measured resistance ( Δ R / R O ) varying based on reinforcement orientation. Optimal performance was associated with higher-quality matrices and specific reinforcement orientations. The Δ R / R O behaviour was linear within the elastic regime until the first crack, with significant drops at each crack location and exponential decay in the post-elastic regime. In the crack widening and failure stages, the Δ R / R O plateaued and exhibited partially reversible behaviour, indicating plastic deformations. The extent of the Δ R / R O drop was correlated with the degree of debonding at the sensor terminals. This work offered an effective technique for TRC monitoring and laid a foundation for future research in this area.