Synergistic experimental and ANN-based prediction of mechanical properties of basalt fiber reinforced high-strength concrete

Abstract

This research focuses on how basalt macrofibers and microfibres affect the durability and Mechanical properties of M60 high-strength concrete. Compressive, split tensile, flexural strength, and acid resistance tests were employed to assess the performance of fiber-reinforced concrete at various fibre volume fractions. The findings demonstrate that the addition basalt fibres greatly enhanced the overall behaviour of concrete compared with the conventional control mix. The greatest compressive strengths were attained at a fibre dosage of 0.75%, reaching 68.42 MPa for microfibres and 63.86 MPa for macrofibres, compared to 58.81 MPa for conventional concrete. Additionally, split tensile strength increased as the fibre content increased to 0.75%, beyond which a slight reduction was observed, likely due to reduced matrix uniformity. Flexural performance showed substantial enhancement, with peak values of 8.78 and 7.88 MPa for microfibre- and macrofibre-reinforced concrete, respectively, demonstrating improved crack resistance and ductile behaviour. Durability evaluation through acid resistance testing revealed comparable performance at the optimum fibre dosage, although a marginal increase in weight loss was observed at higher fibre contents. Microstructural investigations confirmed effective fibre–matrix interaction and crack-bridging mechanisms, while XRD analysis verified the presence of stable crystalline phases that contributed to matrix integrity. Overall, basalt fibre reinforcement enhanced strength, toughness and durability characteristics of concrete. Furthermore, the experimental dataset was integrated with a model of an artificial neural network that accomplished high prediction accuracy. To validate and extend the predictive capability, additional Machine learning approaches were used, and strong agreement was shown with the experimental observations.