Python-based machine learning estimation of thermo-hydraulic performance along varying nanoparticle shape, nanofluid and tube configuration
Yazarlar (4)
Dr. Öğr. Üyesi Emrehan Gürsoy Recep Tayyip Erdoğan Üniversitesi, Türkiye
Dr. Öğr. Üyesi Muhammed TAN Kastamonu Üniversitesi, Türkiye
Doç. Dr. Mehmet GÜRDAL Kastamonu Üniversitesi, Türkiye
Doç. Dr. Yücel ÇETİNCEVİZ Kastamonu Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Advances in Engineering Software (Q1) | ||
| Dergi ISSN | 0965-9978 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2025 |
| Cilt / Sayı / Sayfa | 199 / 1 / 103814–0 | DOI | 10.1016/j.advengsoft.2024.103814 |
| Makale Linki | https://doi.org/10.1016/j.advengsoft.2024.103814 | ||
| Özet |
| In this research article, a Python-based machine learning model prediction study was conducted based on the study results obtained from sudden expansion tubes containing different expansion angles, dimpled fin structures and nanofluids, whose thermo-hydraulic performance was previously examined. In the study, Artificial Neural Network and Ridge reg... |
| Anahtar Kelimeler |
| CFD | Forced convection | Machine learning | Nanofluid | Python | Various dimpled fins |
Science Direct
Python-based machine learning estimation of thermo-hydraulic performance along varying nanoparticle shape, nanofluid and tube configuration
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 4 |
| Scopus | 4 |
| Google Scholar | 5 |