Open AccessInvestigation on heat transfer enhancement in a circular pipe with artificial roughness
Author(s) -
А П Королева,
N V Kuzmenkov,
M S Frantcuzov
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1683/2/022105
Subject(s) - nusselt number , pressure drop , mechanics , heat transfer , turbulence , reynolds number , heat transfer enhancement , transverse plane , computational fluid dynamics , convective heat transfer , materials science , airflow , mechanical engineering , engineering , physics , structural engineering
This paper presents a numerical analysis of convective heat transfer enhancement of transverse ribs in circular tubes. Several CFD simulations are carried out for turbulent airflow to analyze heat transfer and pressure drop provided with transverse rectangular ribs. The rib height and pitch are widely varied along with the flow Reynolds number. The effect of each parameter is examined and discussed. To accurately predict major parameters (Nusselt number, friction factor, and thermal hydraulic performance parameter) a deep neural network is developed, trained, and tested by current CFD data. The result demonstrates that artificial neural network shows better performance compared to other methods of prediction (e.g. power-law approximation) and can offer an economical and powerful approach for modeling optimal heat enhancement parameters.