Estimation of forced heat convection in a rectangular channel with curved-winglet vortex generator: A machine learning approach
Yazarlar (2)
Prof. Dr. Adnan Berber 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 | Thermal Science and Engineering Progress (Q1) | ||
| Dergi ISSN | 2451-9049 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI | ||
| Makale Dili | Türkçe | Basım Tarihi | 01-2023 |
| Cilt / Sayı / Sayfa | 37 / 1 / 101563–0 | DOI | 10.1016/j.tsep.2022.101563 |
| Makale Linki | http://dx.doi.org/10.1016/j.tsep.2022.101563 | ||
| UAK Araştırma Alanları |
Isı Transferi
Termodinamik
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| Özet |
| There are a limited number of studies in the literature on the effect of curved fins on heat transfer. In this study, the effect of novel fin geometry and angle of attack of winglet (α = 30°, 60°, and 90°) on heat convection is estimated using a machine learning method. Airflow in the rectangular channel is investigated under constant heat flux (q''=100 W/m2) and turbulence regime (5683 ≤ Re ≤ 17049) by experimental studies. Improvements in heat transfer are observed at different temperature values (T = 30 °C, 50 °C and 70 °C) of the plate on which the blades were attached. In order to investigate the effect of input parameters on the prediction accuracy, an artificial neural network structure consisting of curved fin angle, Reynolds number and heater plate temperature parameters is preferred. Heat transfer is estimated by feedforward backpropagation (FFBP) and multi-layer perceptron (MLP) neural network algorithm … |
| Anahtar Kelimeler |
| Artificial neural network | Forced convection | Heat transfer | Turbulent flow | Winglet |
Science Direct
Estimation of forced heat convection in a rectangular channel with curved-winglet vortex generator: A machine learning approach
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 18 |
| Scopus | 21 |
| Google Scholar | 27 |