Ozturk A.U.Onal O.2024-07-222024-07-22201319763808http://akademikarsiv.cbu.edu.tr:4000/handle/123456789/17295Artificial 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. © 2013 Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg.EnglishCementsCompressive strengthHydrationImage analysisMicrostructureBackscattered electron imagingCementitious materialsData analysis techniquesImage analysis techniquesMicrostructural phasisNon-linear relationshipspastePerformance of cementNeural networksArticle10.1007/s12205-013-0156-9