Abstract
This paper investigates heat and mass transfer in a hybrid nanofluid flow impinging upon a cylindrical bluff-body embedded in porous media and featuring homogenous and heterogeneous chemical reactions. The analysis includes mixed convection and local thermal non-equilibrium in the porous medium as well as Soret and Dufour effects. Assuming single-phase mixture, a laminar flow of Al2O3-Cu-water (Aluminium oxide-Copper-water) hybrid nanofluid is considered and coupled transport processes are simulated computationally. Due to the significant complexity of this problem, containing a large number of variables, conventional approaches to parametric study struggle to provide meaningful outcomes. As a remedy, the simulation data are fed into an artificial neural network to estimate the target responses. This shows that the volume fraction of nanoparticles, interfacial area of the porous medium and mixed convection parameter, are of primary importance. It is also observed that small variation in the volume fraction of nanoparticles can considerably alter the response of thermal and solutal domains. Further, it is shown that the parameters affecting the thermal process can modify the problem chemically. In particular, raising the volume fraction of nanoparticles enhances the production of chemical species. Furthermore, particle swarm optimization is applied to predict correlations for Nusselt and Sherwood numbers through a systematic identification of the most influential parameters. The current study clearly demonstrates the advantages of using the estimator algorithms to understand and predict the behaviours of complex thermo-chemical and solutal systems.
Highlights
The rapidly growing concerns on environmental pollutions and global warming [1,2], have motivated many attempts to improve the efficiency of transport processes
The forced convection of Al2O3–CuO–water hybrid nanofluid in a cylinder filled with porous medium was conducted by Aminian et al [22]
The hybrid nanofluid is assumed to be a mixture of various volume fractions of Cu nanoparticles into the Al2O3-water nanofluid with fixed value of φ1 = 0.1%
Summary
The rapidly growing concerns on environmental pollutions and global warming [1,2], have motivated many attempts to improve the efficiency of transport processes. Blending nanoparticles with the base working fluid has been demonstrated to be an effective way of boosting thermal conductivity and results in improved heat transfer [6]. The forced convection of Al2O3–CuO–water hybrid nanofluid in a cylinder filled with porous medium was conducted by Aminian et al [22] These authors reported that declining Darcy number intensifies the heat transfer rate, while it poses an adverse effect on the pressure drop. Stagnation-point flows over a permeable stretching sheet in a nanofluid flow [25], porous medium [26,27,28] and by considering radiation and mixed convection heat transfer [24] have been already studied. Particle swarm optimization (PSO) method is applied to precisely extract correlations for Nusselt and Sherwood numbers [36,37]
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