Identification of water/cement ratio of cement pastes, basing on the microstructure image analysis data and using artificial neural network
No Thumbnail Available
Date
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Artificial Neural Network (ANN) analysis has been established to forecast the Water/Cement (w/c) ratio values of cement pastes by using image analysis techniques in the scope of this study. W/c ratio values have reasonably great effects on the performance of cement based structural members. The service life or ultimate performances such as strength and durability characteristics are strongly affected by w/c ratios of cementitious materials. In this study, the relationship between microstructural phases such as unhydrated cement part, hydration products, capillary porosity, and w/c ratios predicted by ANN analysis, has been established. The predicted values are compared with estimated values obtained by proposed method in the literature. The study indicated that, using a contemporary data analysis technique, which is capable of searching nonlinear relationships more thoroughly, would result in more realistic prediction of the w/c ratios compared to the proposed method.