Influence mechanism of lightweight aggregate on concrete impermeability: prediction by ANN

Abstract

The influence of lightweight aggregate (LWA) on concrete impermeability is complex, varying according to LWA type, water–cement ratio and curing age. A convenient, quick method to predict impermeability of lightweight concrete is needed. To investigate the influencing mechanism, the microstructure of LWA and the interfacial transition zone are observed, and the water absorbing/releasing character of LWA in cement paste is studied. Chloride diffusion coefficients of concrete with different LWAs and water–cement ratios are also tested at different ages. LWA is found to have both an advantageous and disadvantageous influence on concrete impermeability. Based on 108 experimental datasets collected, an artificial neural network (ANN) model is applied to predict the influence of LWA on chloride diffusivity of concrete. The model is developed, trained and tested using a multi-layer back-propagation method. The predicted values are then compared with actual test results; the average relative error of prediction is found to be 4·14% and coefficient of determination (R2) is 0·97. These results indicate that the developed model has successfully learned the relationship between the different input and output parameters, and can predict the chloride diffusivity with accuracy adequate for practical design purposes. The ANN procedure provides guidelines to select the appropriate LWA for the required chloride diffusivity of concrete, reducing trial and error attempts, and saving both cost and time.