Background: Achieving a nanofluid with optimal thermal conductivity and viscosity is
one of the main problems of applications of nanofluids in industries.
Methods: There are experimental and theoretical methods to reach an applicable nanofluids with
mentioned characteristics. Surely, experimental methods are not optimal in time and cost($) aspects.
So, in the present study multi-objective optimization of nanofluids ND-Co3O4 is done to find the
optimal solid volume fraction for having maximum thermal conductivity and minimum viscosity.
The response surface methodology (RSM) is used to model target functions using empirical data.
The improved non- dominated sorting method and multi-objective particle swarm optimization are
used as powerful tools for optimization. In order to implement the optimization process, the obtained
target function model is joined to multi-objective particle swarm algorithm and it is used in each step
of the target function evaluation.
Results: The obtained results of these two algorithms are presented in the form of Pareto front. Also,
a comparison between them is provided. According to the optimal results, MOPSO has a better performance
that the other one.
Conclusion: It will be shown that the highest thermal conductivity and the lowest viscosity occur at
the maximum temperature. By investigating obtained optimum results, the optimal point with highest
thermal conductivity and lowest viscosity was found at about 60 °C and 0.1 to 0.11 of solid volume