Comparative study of hybrid and nanofluid flows amidst two rotating disks with thermal stratification: Statistical and numerical approaches

The flow of nanofluids is of great importance because of their substantial industrial usage and alluring heat transfer capabilities. Recently, an innovative notion namely “hybrid nanofluid” has replaced the customary nanofluid flows to further enhance the heat transfer capabilities. We in this envis...

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Veröffentlicht in:Case studies in thermal engineering 2021-12, Vol.28, p.101596, Article 101596
Hauptverfasser: Ramzan, Muhammad, Mehmood, Tahir, Alotaibi, Hammad, Ghazwani, Hassan Ali S., Muhammad, Taseer
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Sprache:eng
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Zusammenfassung:The flow of nanofluids is of great importance because of their substantial industrial usage and alluring heat transfer capabilities. Recently, an innovative notion namely “hybrid nanofluid” has replaced the customary nanofluid flows to further enhance the heat transfer capabilities. We in this envisaged mathematical model are heading in the same direction and are intended to present a comparative analysis of the heat transfer competence of two time-dependent fluid models namely; hybrid nanofluid (Copper–Iron Oxide, Manganese- Zinc ferrite/Diathermic oil) (Cu-Fe2O4, Mn-ZnFe2O4/DO) and simple nanofluid (Mn-ZnFe2O4/DO) flows amidst two rotating disks in a porous media with Darcy-Forchheimer effect. The subject flows are assisted by the thermal stratification with nonlinear radiation effects. A blend of numerical “bvp4c” and statistical “Response Surface Method (RSM)” approaches is utilized to analyze the envisioned mathematical model. Tabulated and graphical depiction of the outcomes is given to comprehend their appraisal. It is comprehended that the radiation and thermal stratification parameters possess differing trends for the fluid temperature profile. Furthermore, it is observed that the parameter estimation and significance indicate both skin friction coefficient models are similar. The fitted model for skin friction and Nusselt number are the best fit where the normality assumption is satisfied.
ISSN:2214-157X
2214-157X
DOI:10.1016/j.csite.2021.101596