A novel approach in modelling of concrete made with recycled aggregates

•Design of optimum level of RCA that can be used in new concrete is an important problem.•Experimental and numerical studies is proposed to find the optimum level of RCA.•Experimental data is measured and fed into framework of automated neural network.•Neural network model fits the properties of RCA accurately is validated by experiments.•Compressive and splitting strength of RCA closely matches the experimental results.

The adhered old mortar paste of recycled concrete aggregates (RCA) plays an important role in production of new concrete with RCA and has positive environmental impacts. A larger number of research papers are available on the properties of concrete where different percentage of natural aggregates (NA) is being replaced by RCA. The outcomes of those research papers have shown that if the good quality of certain percentage (up to 30-50%) RCA is used; the properties of new concrete don't change when it is compared with concrete made from 100% NA. However, the properties of RCA vary significantly from its source to source. Therefore, it is very important to know the optimum level of RCA that can be used in new concrete. This paper conducted experimental and numerical studies to reveal the probable relationship between the parameters such as percentage of RCA replacement, water to cement ratio, aggregate to cement ratio, percentage of air content in the concrete mix and relate them to the mechanical strength of RCA concrete. Finally, automated neural network search (ANNS) analysis was applied to predict the mechanical strength of RCA concrete when other parameters were used as the inputs of the model. It is observed that proposed relation predicts the compressive and splitting strength of RCA concrete that closely matches the experimental results.