Assessment of cement characteristics affecting rheological properties of cement pastes     
Yazarlar (5)
Alı Mardanı Aghabaglou
Türkiye
Murat Kankal
Bursa Uludağ Üniversitesi, Türkiye
Doç. Dr. Sinan NACAR Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Burak Felekoğlu
Türkiye
Kambiz Ramyar
Türkiye
Makale Türü Özgün Makale
Makale Alt Türü SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale
Dergi Adı NEURAL COMPUTING & APPLICATIONS
Dergi ISSN 0941-0643 Wos Dergi Scopus Dergi
Dergi Tarandığı Indeksler SCI-Expanded
Dergi Grubu Q2
Makale Dili İngilizce
Basım Tarihi 10-2021
Cilt No 33
Sayı 19
Sayfalar 12805 / 12826
DOI Numarası 10.1007/s00521-021-05925-8
Makale Linki http://dx.doi.org/10.1007/s00521-021-05925-8
Özet
In this study, the cement-based parameters affecting CEMI portland cements-polycarboxylate ether-based high-range water-reducing (HRWR) admixtures compatibility were investigated. For this purpose, eight CEMI cements and three commercial HRWR admixtures were used. The rheological properties of 112 paste mixtures with different admixture dosages and water/cement (W/C) ratios were determined in accordance with Herschel–Bulkley model. Then after, using the experimental data, proper models were established to predict the dynamic yield stress and final viscosity of the pastes. In addition to cement characteristics (such as fineness, compound composition and equivalent alkali content), water-reducing admixture content and its solid material content as well as water/cement ratio of the pastes were considered as input data. Multivariate adaptive regression splines (MARS) and multiple additive regression trees (MART) methods were used in the models. Besides, artificial neural network (ANN) and conventional regression analysis (CRA) including linear, power, and exponential functions were applied to determine the accuracy of the heuristic regression methods. Three statistical indices, root-mean-square error, mean absolute error, and Nash–Sutcliffe, were used to evaluate the performance of the models. Modeling findings indicated that the model with the lowest error for both of the rheological variables in the testing set is the MART, followed by ANN, MARS, and CRA-Exponential methods. The most effective cement characteristics causing incompatibility, hence detraction of paste rheological properties, in decreasing order, were …
Anahtar Kelimeler
Cementitious systems | Rheological properties | Multivariate adaptive regression splines | Multiple additive regression trees