Abstract
Fatigue failure is a major problem in pavement layers. When using non-conventional aggregate as a replacement for natural stone aggregate, the probability of pavement distress is high. The fatigue behaviour of asphalt concrete with crushed brick aggregate (CBA) reinforced with polypropylene fibre (PPF) was analysed in this study. Two different aggregate types were used with four different PPF contents. The CBA asphalt mixes performed better against fatigue failure when reinforced with PPF. An effort to predict the fatigue life was also carried out. The prediction of the fatigue life of asphalt concrete is a challenging task due to the complexity of variables involved. Two different fatigue prediction models for PPF-reinforced asphalt concrete with CBA were compared. Regression-based predictions and artificial neural network (ANN) model predictions were studied, with models based on the initial strain and the initial dissipated energy. To compare the models, 12 fatigue beam replicas with four different PPF percentages and two different aggregate groups were tested. The ANN models showed better performance when compared with the regression models, where the initial strain and dissipated energy were found to have a strong influence on the fatigue life properties.
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