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Artificial neural network and numerical predictions on flow and heat transfer characteristics for buoyancy-driven flows in regard to dilatant fluids

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Abstract

The objective of present study is to carry out an unsteady numerical analysis to investigate the buoyancy-driven flows in a square enclosure containing an inner circular cylinder. The square enclosure is filled with dilatant fluids commonly known as shear thickening fluids. The inner circular cylinder is placed at the center of the square enclosure. The effects of Prandtl number (10, 100 and 1000) and Rayleigh number (103 to 106) on heat transfer characteristics are reported. The power-law index (n) varied from 1.0–1.6 where n = 1 corresponds to the Newtonian fluid. The heat transfer characteristics are almost insignificant to the change in Prandtl number. The flow and heat transfer characteristics diminished in square enclosure when filled with dilatant fluid in comparison to the Newtonian fluid. The present study demonstrates the adequacy of incorporating artificial neural network model in estimating the heat transfer characteristics.

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Abbreviations

D,R :

Diameter and radius of circular cylinder

L :

Enclosure length

m :

Consistency index

n :

Power-law index

〈Nu〉:

Time-averaged local Nusselt number

P :

Dimensionless pressure, \(P = {{{L^2}p} \over {\rho {\alpha ^2}}}\)

T :

Temperature

t :

Time

U,V :

Dimensionless velocities in x and y directions, \(U = {{Lu} \over \alpha },\,\,V = {{Lv} \over \alpha }\)

X, Y :

Dimensionless coordinates in x and y directions, \(X = {x \over L},\,\,Y = {y \over L}\)

η :

Effective viscosity, Ns/m2

ϕ :

Angle of internal cylinder

θ :

Dimensionless temperature, \(\theta = {{T - {T_c}} \over {{T_h} - {T_c}}}\)

τ :

\(\tau = {{t\alpha } \over {{L^2}}}\)

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Acknowledgments

This study was financially supported by the “2021 Post-Doc Development Program of Pusan National University” and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1A5A8083201).

Author information

Authors and Affiliations

  1. Rolls-Royce and Pusan National University Technology Centre in Thermal Management, Jang Jeon 2-Dong, Geum Jeong Gu, Busan, 609-735, Korea

    Sudhanshu Pandey & Young Min Seo

  2. School of Mechanical Engineering, Changwon National University, 20, Changwondaehak-ro, Uichang-gu, Changwon, 51140, Korea

    Yong Gap Park

  3. School of Mechanical Engineering, Pusan National University, 2, Busandaehak-ro 63beon-gil, Geumjeong-gu, Busan, 46241, Korea

    Man Yeong Ha

Authors
  1. Sudhanshu Pandey
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  2. Yong Gap Park
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  3. Young Min Seo
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  4. Man Yeong Ha
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Corresponding authors

Correspondence to Young Min Seo or Man Yeong Ha.

Additional information

Sudhanshu Pandey received his M.S. degree from Indian Institute of Technology Madras, India in 2016, and Ph.D. from Pusan National University, Korea in 2021. Dr. Pandey is currently a Postdoctoral Researcher at Rolls-Royce and Pusan National University Technology Centre in Thermal Management in Busan, Korea. His research interests are focused on natural convection, non-Newtonian fluids and computational fluid dynamics.

Young Min Seo received his Undergraduate degree from Pusan National University, South Korea in 2013, his Ph.D. degree from Pusan National University, Korea in 2019. Dr. Seo is currently a Post-doctoral Researcher at Rolls-Royce and Pusan National University Technology Centre in Thermal Management in Busan, Korea. His research interests are focused on natural convection, finite volume method and computational fluid dynamics.

Man Yeong Ha received his B.S. degree from Pusan National University, Korea, in 1981, M.S. degree, in 1983, from Korea Advanced Institute of Science and Technology, Korea, and Ph.D. degree from Pennsylvania State University, USA in 1990. Dr. Ha is currently a Professor at the School of Mechanical Engineering at Pusan National University in Busan, Korea. He served as an Editor of the Journal of Mechanical Science and Technology. He is a member of Honorary Editorial Advisory Board of the International Journal of Heat and Mass Transfer. His research interests are focused on thermal management, computational fluid dynamics, and micro/nano fluidics.

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Pandey, S., Park, Y.G., Seo, Y.M. et al. Artificial neural network and numerical predictions on flow and heat transfer characteristics for buoyancy-driven flows in regard to dilatant fluids. J Mech Sci Technol 35, 4775–4784 (2021). https://doi.org/10.1007/s12206-021-0943-z

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  • DOI: https://doi.org/10.1007/s12206-021-0943-z

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