On the multi-objective optimization of finned air-cooling heat exchanger: Nano-fluid effects

This paper is devoted to provide a multi-objective optimization in a finned air-cooling heat exchanger with nanofluids using genetic algorithm. For this reason, two objective functions of exergy efficiency and total cost of the system have been selected for four nanofluidics of Al2O3/H2O, CuO/H2O, Fe3O4/H2O and TiO2/H2O. Energy and exergy analysis are presented considering heat transfer and pressure drop in both air and fluid sides and overall cost of the system is evaluated by computing capital, operating and en-vironmental costs. The genetic algorithm is applied to the different design parameters to generate the Pareto front for each nanofluidics. Optimization procedure is completed using LINMAP method based on the objective functions to maximize the exergy efficiency and minimizing the total annual cost of the system. Results show that for all nanofluidics, despite of positive thermal effect of nanofluid, the negative influence of nanofluidics on the hydro-dynamic characteristics leads to zero concentration of nanofluid in the optimal operating point

Heat exchanger, Multi-objective optimization, Genetic algorithm, Nanofluid