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Influence of nanoparticle shapes on natural convection flow with heat and mass transfer rates of nanofluids with fractional derivative

机译:Influence of nanoparticle shapes on natural convection flow with heat and mass transfer rates of nanofluids with fractional derivative

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摘要

Nanofluids are gaining extensive attention due to their thermo‐physical properties in technological and industrial fields for controlling the effects of heat transfer. Classical nanofluid studies are generally confined to models described by partial differential equations of an integer order where the memory effect and hereditary properties of materials are neglected. In order to overcome these downsides, the present work focuses on studying nanofluids with fractional derivative formed by differential equations with Caputo time derivatives that provides memory effect on nanofluid characteristics. Also, investigation on natural convective flow, heat, and mass transfer of nanofluids formed by different base fluids with different shapes of copper nanoparticles past an infinite vertical plate with radiation effect is carried out. The governing fractional differential equations are solved by employing Laplace transform technique with suitable boundary conditions. The different base fluids—water (H2O), SA:sodium alginate (C6H9Na O7), and EG:ethylene glycol (C2H6O2) and different shapes of nanoparticles—blade, brick, platelet, and cylinder are considered for the study. The exact solutions are obtained for the temperature, concentration, and velocity distributions and the respective Nusselt number, Sherwood number, and skin‐friction coefficient. The influence of non‐dimensional parameters provides physical interpretations of temperature, concentration, and velocity fields, Nusselt number, Sherwood number, and skin friction in detail with the help of graphical representations. From the results, it is found that nanofluid with water‐based blade‐shaped nanoparticle exhibits more velocity and temperature distributions. Also, strengthen of fluid flow, temperature, and concentration of nanofluids are inversely correlate with fractional order derivatives.

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