| Yazarlar (3) |
|
Selçuk Üniversitesi, Türkiye |
|
|
Doç. Dr. Mehmet GÜRDAL
Kastamonu Üniversitesi, Türkiye |
| Özet |
| This study uses an experimental and machine learning-based approach to investigate the effects of hexagonal honeycomb structures on forced convection heat transfer. The research addresses the lack of comprehensive studies on hexagonal geometries' thermal and hydraulic performance under varying flow and current conditions. This study's novelty lies in integrating experimental and machine learning methods to optimize heat transfer and friction characteristics, contributing to the efficient design of heat exchangers for industrial applications. An experimental setup with a turbulent flow regime and aluminum honeycomb heat exchangers was employed. The system parameters, including Nusselt number (Nu) and friction factor (f), were analyzed for various honeycomb geometry rates (0.26, 0.56, and 0.80), airflow velocities (10, 15, and 20 m/s), and electrical currents (50, 100, 150, 200, and 250 A). The data were … |
| Anahtar Kelimeler |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | International Journal of Thermal Sciences |
| Dergi ISSN | 1290-0729 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI |
| Dergi Grubu | Q1 |
| Makale Dili | İngilizce |
| Basım Tarihi | 01-2025 |
| Makale Linki | https://www.sciencedirect.com/journal/international-journal-of-thermal-sciences |