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Significance of Non‐fourier Flux on a Chemically Reactive Ternary Hybrid Nanofluid Flow (water + Al2O3 + ZnO + Fe3O4) by a Quadratically Radiated Tended Elongating Surface

Zeitschrift für angewandte Mathematik und Mechanik(2022)

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摘要
This study compares the dynamics of dissipative water-alumina-zinc oxide-iron (II, III) oxide ternary hybrid nanofluid (THNF) and water-alumina-zinc oxide binary hybrid nanofluid flows across an inclined surface when quadratic thermal radiation and chemical reaction are important. This report presents the governing equations for the transportation of both dynamics using the thermo-physical properties of water (base fluid), alumina nanoparticles, zinc oxide nanoparticles and iron (II, III) oxide nanoparticles. To analyse heat transmission phenomena, the Cattaneo-Christov heat flux model was added into the energy equation. With proper similarity transformations, flow-driven equations are transformed into nonlinear ordinary differential equations and then solved using the bvp4c solver. Slope of linear regression (SLR) is used to determine the rate at which physical parameters increase or decrease as a result of the influence of relevant factors. It is noticed that, when volume percent of nanoparticles (phi(1)) takes input in the range 0 <=phi 1 <= 0.3$0 \le {\phi _1} \le 0.3$, skin friction coefficient decreases at a rate of 16.548 (in case of THNF) and 14.2018 (in case of binary hybrid nanofluid) per unit value of volume percent of nanoparticles. It is detected that when radiation parameter (Rd)$( {{R_d}} )$ increases, Nusselt number decreases. The decrement rates are observed as 2.9451 (in case of THNF) and 1.15337 (in case of binary hybrid nanofluid) when radiation parameter takes input in the range 0 <= Rd <= 0.3$0 \le {R_d} \le 0.3$. Furthermore, it is noticed that, when chemical reaction parameter (Kr)$( {{K_r}} )$ increases, Sherwood number increases. The increment rates are observed as 0.1259 (in case of THNF) and 1.1263 (in case of binary hybrid nanofluid) when chemical reaction parameter takes input in the range 0 <= Kr <= 0.3$0 \le {K_r} \le 0.3$. There was also good agreement in a validation study between the current and previous results.
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