Artificial Neural Network Estimation of the Effect of Varying Curing Conditions and Cement Type on Hardened Concrete Properties
Yazarlar (4)
Doç. Dr. Gökhan Kaplan Kastamonu Üniversitesi, Türkiye
Hasbi Yaprak
Kastamonu Üniversitesi, Türkiye
Kastamonu Üniversitesi, Türkiye
Doç. Dr. Selçuk MEMİŞ Kastamonu Üniversitesi, Türkiye
Abdoslam Alnkaa
Kastamonu Üniversitesi, Türkiye
Kastamonu Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | Buildings | ||
| Dergi ISSN | 2075-5309 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | ESCI | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2019 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 03-01-2019 |
| Cilt / Sayı / Sayfa | 9 / 1 / 10–0 | DOI | 10.3390/buildings9010010 |
| Makale Linki | https://www.mdpi.com/2075-5309/9/1/10 | ||
| UAK Araştırma Alanları |
Yapı ve Malzemeleri
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| Özet |
| The use of mineral admixtures and industrial waste as a replacement for Portland cement is recognized widely for its energy efficiency along with reduced CO2 emissions. The use of materials such as fly ash, blast-furnace slag or limestone powder in concrete production makes this process a sustainable one. This study explored a number of hardened concrete properties, such as compressive strength, ultrasonic pulse velocity, dynamic elasticity modulus, water absorption and depth of penetration under varying curing conditions having produced concrete samples using Portland cement (PC), slag cement (SC) and limestone cement (LC). The samples were produced at 0.63 and 0.70 w/c (water/cement) ratios. Hardened concrete samples were then cured under three conditions, namely standard (W), open air (A) and sealed plastic bag (B). Although it was found that the early-age strength of slag cement was lower, it was improved significantly on 90th day. In terms of the effect of curing conditions on compressive strength, cure W offered the highest compressive strength, as expected, while cure A offered slightly lower compressive strength levels. An increase in the w/c ratio was found to have a negative impact on pozzolanic reactions, which resulted in poor hardened concrete properties. Furthermore, carbonation effect was found to have positive effects on some of the concrete properties, and it was observed to have improved the depth of water penetration. Moreover, it was possible to estimate the compressive strength with high precision using artificial neural networks (ANN). The values of the slopes of the regression lines for training, validating … |
| Anahtar Kelimeler |
| Artificial neural networks | Curing | Portland limestone cement | Slag cement | W/C |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 20 |
| Scopus | 23 |
| Google Scholar | 30 |