Prediction of heat transfer distribution induced by the variation in vertical location of circular cylinder on Rayleigh-Bénard convection using artificial neural network

•Flow and thermal fields of Rayleigh-Bénard convection (RBC) in a rectangular channel with an internal circular cylinder.•The Rayleigh number and the vertical distance significantly influence the flow and thermal characteristics within the channel.•An artificial neural network (ANN) model is used to...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	International journal of mechanical sciences Ročník 209; s. 106701
Hlavní autori:	Seo, Young Min, Pandey, Sudhanshu, Lee, Hyeon Uk, Choi, Changyoung, Park, Yong Gap, Ha, Man Yeong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.11.2021
Predmet:	Artificial neural network Heat transfer performance Irreversibility Rayleigh-Bénard convection Supervised learning algorithm Vertical distance Rayleigh-Bénard convection Heat transfer performance Vertical distance Irreversibility Artificial neural network Supervised learning algorithm
ISSN:	0020-7403, 1879-2162
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Popis
Shrnutí:	•Flow and thermal fields of Rayleigh-Bénard convection (RBC) in a rectangular channel with an internal circular cylinder.•The Rayleigh number and the vertical distance significantly influence the flow and thermal characteristics within the channel.•An artificial neural network (ANN) model is used to predict the distribution of local Nusselt number.•The results show that the ANN model can precisely predict the correlation between the input and output parameters with lesser computational time and cost compared to the DNS. The present study investigates the flow and thermal fields of Rayleigh-Bénard convection (RBC) in a rectangular channel with an internal circular cylinder. The parameters considered are Rayleigh number (104≤Ra≤106), Prandtl number (Pr = 0.7), and irreversibility distribution ratio (φ = 1). The vertical distance (δ) in the range of -0.2 ≤ δ ≤ 0.2 is the major simulation parameter in present study. The results are analyzed based on the iso-surface of temperature, vortical structure with orthogonal enstrophy distribution, and entropy generations. Additionally, Nusselt number (Nu) and Bejan number (Be) are obtained to analyze the heat transfer characteristics and irreversibility, respectively. The Rayleigh number and the vertical distance significantly influence the flow and thermal characteristics within the channel. Besides, an artificial neural network (ANN) model is used to predict the distribution of local Nusselt number. The performance of present ANN model is evaluated by comparing the tendency and quantitative values with the direct numerical simulation (DNS) results. The results show that the ANN model used in this study can precisely predict the correlation between the input parameters and output parameter with lesser computational time and cost compared to the DNS. [Display omitted]
ISSN:	0020-7403 1879-2162
DOI:	10.1016/j.ijmecsci.2021.106701