ANN modelling approach for predicting SCC properties - Research considering Algerian experience. Part III. Effect of mineral admixtures

Abstract

This paper addresses the effect of mineral admixtures on fresh and hardened properties of self compacting concrete (SCC). Artificial neural networks (ANN) and simplex lattice design approach was integrated to predict and evaluate the effect of limestone, marble powder, natural pozzolan and slag on rheological and mechanical properties of SCC evaluated by slump flow, L-Box, V-funnel, sieve segregation test and 28 days compressive strength. The modelling results show an acceptable prediction accuracy of SCC behaviour containing mineral admixtures as substitution of cement especially related to the flow time measured with the V-funnel test and mechanical compressive strength at 28 days.