Effect of textile configuration and matrix composition on the self-sensing performance of carbon fibre textile-reinforced cementitious composites under flexural loading

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Authors: Amir A.E. Elseady, Yan Zhuge, Xing Ma, Christopher W.K. Chow, Ivan Lee, Junjie Zeng
Cited by: 1
References: 64

Abstract

This study investigates the self-sensing performance of carbon fibre textile-reinforced cementitious composites (TRC) under flexural loading, focusing on the contact resistivity of interfacial junctions in carbon fibre textiles. The combined effects of textile configuration and matrix composition are examined. Two carbon textiles—Type A (5 × 5 mm leno weave with 12 K filaments) and Type B (20 × 20 mm stitch-bonded with 24 K filaments)—were embedded in matrices with and without polypropylene (PP) fibres. Four sensors were strategically placed per specimen to monitor failure modes under four-point bending. Two sensors in shear zones detected potential slippage, while two in constant-moment zones tracked crack propagation. Post-test analysis focused on sensors in the constant-moment zone, with elastic and post-elastic responses quantified via linear and nonlinear regression, respectively. Results show that textile geometry and PP fibre inclusion significantly influence piezoresistive response and textile-matrix interface behaviour. PP fibres reduce gauge factors by 14–38 % and decay rates by 62.9–63.8 %. However, Type B consistently outperforms Type A, exhibiting 6.9–9.7 times higher sensitivity in the elastic stage and 2.5 times slower post-elastic debonding. The stitch-bonded configuration of Type B offers the best performance, balancing superior piezoresistive sensitivity with resistance to textile-matrix interface degradation. These findings support optimised TRC designs for real-time structural health monitoring.

Fields of Study & Subjects

Smart Materials for Construction Masonry and Concrete Structural Analysis Mechanical Behavior of Composites

Publication details

Journal / source
Structures
Publisher
Elsevier BV
Volume
86
Pages
111460–111460
Publication date
24 February 2026
Language
EN