Combined effects of using multiple porous cylinders and inclined magnetic field on the performance of hybrid nanoliquid forced convection

Abstract

Effects of combined utilization of inclined magnetic field and multiple porous cylinders on the forced convection in a vented cavity are numerically assessed by using finite element method. Effects of Reynolds number (Re: 200-1000), magnetic field strength (Ha: 0-75), inclination of magnetic field (gamma: 0-90), permeability of the porous cylinders (Da: 10(-4) - 10(-1)) and size of the cylinders (R: 0.04 H-0.15 H) on the fluid flow convective heat transfer performance are studied. The presence of the cylinder and their permeability can be used for controlling the heat transfer. When cylinders at the highest permeability is used, there is 77% additional contribution to the overall thermal performance when lowest and highest Re cases are compared. There is significant contribution of the magnetic field on the suppression of the vortices in the cavity for the case with lower permeability of the cylinders. The magnetic field strength is more effective on the flow field and heat transfer as compared to its inclination. Up to 123% increment in the heat transfer is obtained at the highest strength of magnetic field for the highest permeability of the cylinders while it is only 12% when cylinders with the lowest permeability are used. When variation in the magnetic field inclination is considered, average heat transfer variation up to 19.8% is obtained for the multiple cylinders with the highest permeability. The size of the porous cylinders generally contributes positively to the overall thermal performance. Heat transfer enhancements up to 88% can be obtained by using highest cylinder size as compared to lowest size when the permeability is lowest while it is only 15% for the highest permeability case. The optimum set of parameters at Re = 200 is found as Ha, gamma, Da) = (74.4, 1.3, 10(-5)) and at Re = 1000, it is (Ha, gamma, Da) = (75, 0.35, 10(-5)). Significant variations in the average heat transfer is obtained when optimum case is compared with the parametric study case.