Experimental and ANN-based optimization of thermal and hydraulic performance in a hexagonal honeycomb structure
Yazarlar (3)
Prof. Dr. Adnan Berber Selçuk Üniversitesi, Türkiye
Doç. Dr. Cuma Ali Yılmaz Selçuk Üniversitesi, Türkiye
Doç. Dr. Mehmet GÜRDAL Kastamonu Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | International Journal of Thermal Sciences (Q1) | ||
| Dergi ISSN | 1290-0729 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | Ingilizce | Basım Tarihi | 01-2026 |
| Cilt / Sayı / Sayfa | 220 / 1 / 110374– | DOI | 10.1016/j.ijthermalsci.2025.110374 |
| Makale Linki | https://doi.org/10.1016/j.ijthermalsci.2025.110374 | ||
| UAK Araştırma Alanları |
Isı Transferi
Akışkanlar Mekaniği
Termodinamik
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| 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 |
| ANN | Forced heat convection | Hexagonal honeycomb | Machine learning | Turbulent flow |
Science Direct
Experimental and ANN-based optimization of thermal and hydraulic performance in a hexagonal honeycomb structure
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 2 |
| Scopus | 2 |
| Google Scholar | 2 |