Flow and irreversible mechanism of pure and hybridized non-Newtonian nanofluids through elastic surfaces with melting effects

Author:

Hashim 1,Rehman Sohail2,Akermi Mehdi3,Nasr Samia4

Affiliation:

1. Department of Mathematics & Statistics, The University of Haripur , 22620 , Haripur , Pakistan

2. Department of Mathematics, Islamia College , Peshawar , 25000 , Pakistan

3. Department of Physics, College of Science, Jazan University , P.O. Box 114 , Jazan 45142 , Kingdom of Saudi Arabia

4. Department of Chemistry, Abha, King Khalid University , P.O. Box 9004 , Abha 61413 , Saudi Arabia

Abstract

Abstract The significance of nanofluid research in nanotechnology, pharmaceutical, drug delivery, food preparation, and chemotherapy employing single- and two-phase nanofluid models has drawn the attention of researchers. The Tiwari–Das model does not capture the diffusion and random movement of nanoparticles (NPs) when they are injected into complex functional fluids. In order to fix the peculiar behavior of NPs, more complex models like the Buongiorno model are coupled with the single-phase model. To examine the heat-mass transfer attributes of nanofluids, a single- and two-phase mixture model is coupled for the first time. The effect of hybrid NPs on the hemodynamic properties of the blood flow through a stretched surface with interface slip in the neighborhood of the stagnation point is examined. Due to their significance in medicinal uses and nominal toxicity, blood is loaded with zinc–iron ( ZnO F e 2 O 3 ) {\rm{ZnO}}\left-{\rm{F}}{{\rm{e}}}_{2}{{\rm{O}}}_{3}) NPs. However, blood is speculated to have the hematocrit viscosity of the Powell–Eyring fluid. The single-phase model predicts an improvement in heat transport due to an increased volumetric friction of NPs, while the two-phase models provide closer estimates of heat-mass transfer due to Brownian and thermophoretic phenomena. Entropy evaluation predicts the details of irreversibility. The mathematical structures are effectively solved with a Runge–Kutta fourth-order algorithm along with a shooting mechanism. The Eyring–Powell parameters decrease the drag coefficient and mass/thermal transport rate. A higher estimation of the slip, material, and magnetic parameters decreases the flow behavior. The Bejan number increases with the diffusion parameter and decreases as the magnetic and Brinkman numbers increase. The effect of iron oxide ( F e 2 O 3 ) \left({\rm{F}}{{\rm{e}}}_{2}{{\rm{O}}}_{3}) is observed to be dominant.

Publisher

Walter de Gruyter GmbH

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