An intelligent model for the prediction of the depth of the wear of cementitious composite modified with high-calcium fly ash

Abstract

Although the application of cementitious composite with high-calcium fly ash is a popular trend, no research has been reported on the prediction of its depth of wear. Taking into account current knowledge, examining this property involves destructive and costly laboratory tests using special devices (e.g. the rotating-cutter method). Thus, in these investigations an intelligent model for the prediction of the depth of wear of cementitious composite modified with high-calcium fly ash was developed. The developed model is based on the proportions of the components of a concrete mix. The authors presented the possibility of using artificial intelligence to predict the depth of wear by applying an artificial neural network with suitable architecture and a learning algorithm. Results showed a satisfactory precision of the new intelligent model for predicting the depth of wear with high accuracy when compared to the rotating-cutter method. The developed model can potentially assist in the design of high-calcium fly ash cementitious composite with increased durability.