Prediction of self-compacting concrete strength using artificial neural networks

Despite the widespread use of self-compacting concrete (SCC) in construction in the last decades, there is not yet a robust quantitative method, available in the literature, which can reliably predict their strength based on the mix components. This is mainly due to the highly non-linear behaviour exhibited by the compressive strength in relation to the components of the concrete mixtures. In the present paper, the application of artificial neural networks (ANNs) to predict the mechanical characteristics of SCC has been investigated. Specifically, ANN models for the prediction of the 28-days compressive strength of admixture-based self-compacting concrete (based on experimental data available in the literature) are presented. The comparison of the derived results with experimental findings demonstrates the promising potential of using back propagation neural networks for the reliable and robust approximation of the compressive strength of self-compacting concrete.