The effect of nanoparticles on multi-objective optimization of a shell and tube heat exchanger

Effect of different nanoparticle on thermo-economic optimization of a shell and tube heat exchanger (STHE) is investigated in this paper. Aluminum oxide (Al2O3) and silicon dioxide (SiO2) are used as nanoparticles. Thermal modeling by "ε-NTU" method and multi-objective optimization using genetic algorithm is used to increase effectiveness and reduce total annual cost. Tube arrangement, tube diameter, tube pitch ratio, tube length in each pass, tube number, baffle spacing ratio, baffle cut ratio, cold stream flow allocation, tube pass number and particles volumetric concentration are considered as ten design parameters. The results as a set of solutions (Pareto optimal front) is displayed. The results showed that efficiency and total annual cost improved in the case with nanoparticles. For example, 4.174% and 2.028%, improvement in the effectiveness are find respectively for aluminum oxide and silicon oxide compared with base fluid and for a fixed value of annual cost=5000 $/year. Furthermore, the effect of nanoparticle on some of heat exchanger specifications is studied and results are reported.