Abstract

Masonry has been used extensively in civil engineering for centuries. However, various factors can reduce its performance over time. To extend its life and increase its load-bearing capacity, it needs to be reinforced. Strengthening with composite materials, in particular with Textile-Reinforced Cementitious (TRC) matrix composites, has proven to be effective. However, the assessment of the load transfer between TRC and masonry, as well as between matrix and textile at the core of the TRC remains a significant scientific challenge for optimal reinforcement. In this context, this paper aims to contribute to the understanding of the load transfer mechanisms at these interfaces, particularly for shear behaviour.To this end, this study investigates the reinforcement of masonry using TRC. Six different configurations of TRC-to-masonry prisms were subjected to single-lap shear bond tests: two types of textile reinforcements, two types of matrices and two reinforcement ratios. These six configurations were instrumented by distributed fibre optic sensors in the core of the TRC. These sensors measured the mechanical strains of the matrix and textile in the core of TRC with millimetric spatial resolution. From these strains, the local shear stresses and bond behaviour of the textile-to-matrix and TRC-to-masonry interfaces were experimentally quantified, assessed and analysed. A decreasing parabolic trend of these shear stresses along the effective length was obtained before the appearance of cracks, while cracks considerably modify this trend.The contributions of the matrix and the textile to the interface shear stresses were assessed. Before cracking, the contribution of the matrix prevails, while after cracking, the contribution of the textile is predominant. The shear stresses over the TRC thickness were also quantified and analysed. The debonding at the textile-to-matrix interface was tracked and analysed before, during and after crack propagation in TRC. The results obtained confirm that this debonding evolution can be predicted by pull-out tests.

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