4.7 Article

Analysis of hybrid nanofluid and surface corrugation in the laminar convective flow through an encapsulated PCM filled vertical cylinder and POD-based modeling

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijheatmasstransfer.2021.121623

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Hybrid nanofluid; PCM; POD; Corrugation; Finite element method

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In this study, numerical simulations were used to investigate the performance assessment of a PCM filled three-dimensional vertical cylinder under the combined effects of surface corrugation and presence of binary nanoparticles in the heat transfer fluid. Results showed that thermal transport features are enhanced and charging time is reduced for higher values of Reynolds number and solid volume fraction of the binary mixture in the heat transfer fluid.
In the present work, performance assessment of a PCM filled three dimensional vertical cylinder is con-ducted under the combined effects of surface corrugation and presence of binary nanoparticles in the heat transfer fluid. The numerical simulation is performed by using finite element method with varying values of Reynolds number (100 <= Re <= 750 ), number (1 <= N <= 8) and height (H/10 <= h <= H/2 ) of rect-angular type corrugation form and volume fraction of particles (0 <= phi <= 0.02) in unsteady configuration. Thermal transport features are enhanced while charging time is reduced for higher values of Reynolds number, solid volume fraction of the binary mixture in the heat transfer fluid. Complete charging time is reduced by 57 % with increase of Reynolds number from 100 to 750 while it is reduced by 23 % when nanofluid at the highest solid volume fraction is used instead of water. However, the corrugation param-eters have reverse effects on the charging process. A computational framework for reconstruction of heat transfer fluid and PCM temperatures for the unsteady parametric configuration in the computational do-main is offered by utilizing proper orthogonal decomposition (POD) technique with 25 modes for heat transfer fluid and 75 modes for PCM. (C) 2021 Elsevier Ltd. All rights reserved.

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