Identification of water/cement ratio of cement pastes, basing on the microstructure image analysis data and using artificial neural network

dc.contributor.authorOzturk, AU
dc.contributor.authorOnal, O
dc.date.accessioned2024-07-18T11:54:12Z
dc.date.available2024-07-18T11:54:12Z
dc.description.abstractArtificial 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.
dc.identifier.issn1226-7988
dc.identifier.other1976-3808
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/6173
dc.language.isoEnglish
dc.publisherKOREAN SOCIETY OF CIVIL ENGINEERS-KSCE
dc.subjectPREDICTION
dc.subjectSTRENGTH
dc.titleIdentification of water/cement ratio of cement pastes, basing on the microstructure image analysis data and using artificial neural network
dc.typeArticle

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