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Impact of an effective Prandtl number model and across mass transport phenomenon on the γAI2O3 nanofluid flow inside a channel

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  • Saba, Fitnat
  • Ahmed, Naveed
  • Khan, Umar
  • Mohyud-Din, Syed Tauseef

Abstract

In this article, the flow of water-γAI2O3 and ethylene glycol–γAI2O3 nanofluids have been considered inside a channel, whose permeable lower wall is also bilaterally stretchable. In order to attain a balanced across mass transport (AMT) phenomena, the fluid has been injected from the upper wall of the channel. Moreover, the heat transport mechanism along with nonlinear thermal radiative effects have also been studied in detail. Experimental based models for physical and thermal properties as well as the effective Prandtl number, for γAI2O3 nanofluid, have been considered in this study. In addition, a novel technique of Galerkin-based Legendre wavelet method has been presented to find the numerical solution of the transformed set of equations. The impact of various active parameters on the velocity along with temperature and heat transport mechanism are deliberated through the graphs. It has been observed that the ethylene glycol–γAI2O3 nanofluid exhibit lower temperature values. Moreover, the presence of effective Prandtl number appreciably contribute in diffusing the heat, for both water-γAI2O3 and ethylene glycol–γAI2O3 nanofluids, at the lower boundary of the channel

Suggested Citation

  • Saba, Fitnat & Ahmed, Naveed & Khan, Umar & Mohyud-Din, Syed Tauseef, 2019. "Impact of an effective Prandtl number model and across mass transport phenomenon on the γAI2O3 nanofluid flow inside a channel," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    • Handle: RePEc:eee:phsmap:v:526:y:2019:i:c:s0378437119306636
    DOI: 10.1016/j.physa.2019.121083
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    Cited by:

    1. Aly, Abdelraheem M. & Raizah, Z.A.S., 2020. "Incompressible smoothed particle hydrodynamics simulation of natural convection in a nanofluid-filled complex wavy porous cavity with inner solid particles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    2. Xiaohong, Dai & Huajiang, Chen & Bagherzadeh, Seyed Amin & Shayan, Masoud & Akbari, Mohammad, 2020. "Statistical estimation the thermal conductivity of MWCNTs-SiO2/Water-EG nanofluid using the ridge regression method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).

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