Identification of water/cement ratio of cement pastes, basing on the microstructure image analysis data and using artificial neural network
dc.contributor.author | Ozturk, AU | |
dc.contributor.author | Onal, O | |
dc.date.accessioned | 2024-07-18T11:54:12Z | |
dc.date.available | 2024-07-18T11:54:12Z | |
dc.description.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. | |
dc.identifier.issn | 1226-7988 | |
dc.identifier.other | 1976-3808 | |
dc.identifier.uri | http://akademikarsiv.cbu.edu.tr:4000/handle/123456789/6173 | |
dc.language.iso | English | |
dc.publisher | KOREAN SOCIETY OF CIVIL ENGINEERS-KSCE | |
dc.subject | PREDICTION | |
dc.subject | STRENGTH | |
dc.title | Identification of water/cement ratio of cement pastes, basing on the microstructure image analysis data and using artificial neural network | |
dc.type | Article |