Fatigue characterization of hybrid fibre-reinforced concrete: S-N curve development, Weibull reliability modelling, and effect of variable amplitude loading
Abstract
Fatigue loading is a primary factor governing the durability and service life of structural concrete, necessitating materials with enhanced resistance to cyclic degradation. This study presents a detailed fatigue characterization of concrete prisms incorporating mono and hybrid fibre reinforcements under constant and variable amplitude flexural loading. Seven mixtures were investigated: normal concrete (NC), steel fibre -reinforced concrete (SFRC) at 0.5%, 1.0%, and 1.5% volume fractions, and hybrid steel-polypropylene fibre-reinforced concrete (SF-PPF: 75: 25) in each volume fraction. Fatigue stress levels were decided based static flexural tests. Constant-amplitude fatigue tests were conducted at stress levels of 0.6–0.9 (stress ratio 0.1; 5 Hz), to construct S-N curve. It was observed from the extensive experiments that the synergetic effect of fibre reinforcement significantly improved fatigue performance by enhancing crack-bridging capacity, delaying crack propagation, and improving stiffness retention. Fatigue life decreased with increasing stress levels across all mixes; however, hybrid composites, exhibited substantially extended fatigue life. The S-N relationship was effectively described using the Basquin model, demonstrating strong agreement with experimental results. Probabilistic fatigue behaviour was evaluated using a two-parameter Weibull distribution, indicating reduced scatter and improved reliability for fibre-reinforced concretes compared to NC. Among all mixtures, the 1.5% hybrid fibre mix exhibited the highest fatigue life and improved damage resistance under cyclic loading conditions, whereas the 1.0% hybrid mix demonstrated comparatively lower fatigue-life scatter and better statistical reliability based on Weibull analysis. Overall, the optimal comprehensive performance was achieved through a balanced combination of fatigue durability and reliability characteristics.