Early estimation of 28-day compressive strength of mortars using regression and neural network-based models
Yazarlar (2)
Öğr. Gör. Okay YILDIZ
Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Doç. Dr. Şahin SÖZEN
Tokat Gaziosmanpaşa Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
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| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | CONSTRUCTION AND BUILDING MATERIALS |
| Dergi ISSN | 0950-0618 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Dergi Grubu | Q1 |
| Makale Dili | İngilizce |
| Basım Tarihi | 10-2023 |
| Cilt No | 400 |
| Sayı | 132789 |
| DOI Numarası | 10.1016/j.conbuildmat.2023.132789 |
| Makale Linki | https://www.sciencedirect.com/science/article/pii/S0950061823025059?dgcid=author |
| Özet |
| Concrete, the most commonly used construction material, presents a challenge in determining its compressive strength (CS) after 28 days of manufacture. This study aims to predict the compressive strength of conventionally cured (CC) mortar specimens using data from accelerated microwave-cured (MC) specimens. Two hundred and seventy-six specimens with different mixes and admixtures were divided into two groups: one half was subjected to MC and the other to CC. The CSs of the CC specimens were determined after 28 days, while the MC specimens were subjected to additional tests such as ultrasonics pulse velocity and three-point bending after microwave curing. Regression and artificial neural network models (ANN) were developed using the obtained data. While the data of the specimens subjected to MC were used as independent variables of the developed models, the compressive strength of the … |
| Anahtar Kelimeler |
| ANN | CS | Microwave curing method | Modeling | MARS |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| WoS | 4 |
| Google Scholar | 6 |