Determination of the Optimum Stability Conditions in Al2O3 Nanofluids with Artificial Neural Networks
Yazarlar (4)
Fevzi Şahin Ondokuz Mayıs Üniversitesi, Türkiye
Dr. Öğr. Üyesi Murat KAPUSUZ Sinop Üniversitesi, Türkiye
Prof. Dr. Lütfü Namlı Ondokuz Mayıs Üniversitesi, Türkiye
Prof. Dr. Hakan Özcan Ondokuz Mayıs Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | International Journal of Thermophysics (Q3) | ||
| Dergi ISSN | 0195-928X Dergi Bilgileri (2020) | ||
| Dergi Tarandığı Indeksler | SCI | ||
| Makale Dili | Türkçe | Basım Tarihi | 01-2020 |
| Cilt / Sayı / Sayfa | 41 / 5 / 1–20 | DOI | 10.1007/s10765-020-02625-8 |
| Makale Linki | http://dx.doi.org/10.1007/s10765-020-02625-8 | ||
| UAK Araştırma Alanları |
Makine Mühendisliği
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| Özet |
| In this study, the optimum stability conditions in Al2O3 nanofluids were determined by utilizing artificial neural networks (ANN). First of all, nanofluids used in the experimental study were prepared by synthesizing Al2O3 nanoparticles and mobile brand oil as a base fluid, which is used as a heat transfer fluid in the industry. To ensure stability, the nanoparticles were synthesized in the oil by adding the specified acid and base solutions. The sedimentation method was applied to measure the stability after ultrasonic mixing stage of nanofluids which determined as Al2O3 nanoparticles 1 %, 2 %, and 3 % by mass. Periodic sedimentation measurements were continued for 36 h. Optimum conditions were obtained using the successful models. Experiments were repeated for optimum conditions, and the consistency of the model and agreement with the experimental system were observed. According to the findings, the … |
| Anahtar Kelimeler |
| Artificial neural networks (ANN) | Nanofluids | Sedimentation method | Stability |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 6 |
| Scopus | 6 |
| Google Scholar | 8 |