Investigating the effect of nanoparticle on thermo-economic optimization of fin and tube heat exchanger

Abstract

In this paper, the effects of Al2O3 nanoparticles suspended in the water-based fluid on the thermo-economic properties of a fin and tube heat exchanger are studied using fast and elitism nondominated sorting genetic algorithm. Nine design parameters are selected as design parameters, and the total annual cost and effectiveness are considered as the two objective functions. First, the effect of nanoparticle on the total annual cost versus effectiveness is obtained at different cold side mass flow rates, and the results are compared with the base fluid. The results show that nanoparticles have a significant influence on the total annual cost and effectiveness in a lower cold side mass flow rates. Next, the heat exchanger volume versus effectiveness for the optimum points is measured at different cold side mass flow rates. It is demonstrated that, adding Al2O3 nanoparticle to the base fluid for the fixed value of effectiveness, decreases the heat exchanger volume, and this reduction is more significant in the lower mass flow rates. The pressure drop and total heat transfer surface area versus effectiveness for the optimum points are also obtained with and without nanoparticle. An increase in the tube side pressure drop is revealed in the nanofluid. In addition, due to the increase in the overall heat transfer coefficient, the lower heat transfer surface area is required for the fixed value of effectiveness. Finally, variations of objective functions versus particle volumetric concentration for five typical optimum points are estimated. It is concluded that an optimal value for the volumetric concentration can be obtained, in which the effectiveness is highest.