Abstract
The direct tensile resistance of strain-hardening steel-fibre-reinforced concrete (SHSFRC) was experimentally investigated and modelled. Three steel fibre types (twisted, hooked and smooth fibres) and three matrices with different compressive strengths (28 MPa (M1), 84 MPa (M2) and 180 MPa (M3)) were investigated in both single-fibre pull-out tests and direct tensile tests. A model based on machine learning was developed to predict the tensile resistance of the SHSFRCs. The experimental results showed that the twisted fibres not only exhibited the highest pull-out resistance but also the greatest tensile resistance in M1 and M2, whereas smooth fibres achieved the same results in M3. The predicted outcomes showed that the proposed model had high efficiency and accuracy in estimating the tensile resistance of SHSFRC, with a correlation coefficient of 0.951.
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