Identification of water/cement ratio of cement pastes, basing on the microstructure image analysis data and using artificial neural network
| dc.contributor.author | Ozturk A.U. | |
| dc.contributor.author | Onal O. | |
| dc.date.accessioned | 2025-04-10T11:14:09Z | |
| dc.date.available | 2025-04-10T11:14:09Z | |
| dc.date.issued | 2013 | |
| 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. © 2013 Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg. | |
| dc.identifier.DOI-ID | 10.1007/s12205-013-0156-9 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.14701/50120 | |
| 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 |