Multi-objective genetic optimization of the heat transfer for tube inserted with porous media

This work is aimed at determining the best configurations of porous media inserted in a tube to achieve the excellent performance of fluid flow and heat transfer. Both geometry parameters and property parameters are the variables to be optimized. In order to evaluate the performance of tube, two conflicting objectives, Nusselt number Nu and friction factor f, are simultaneously considered. In the optimization process, computational fluid dynamics (CFD) and multi-objective genetic algorithm are coupled to obtain the numerical solutions of two-dimensional calculation model and Pareto front composed of non-inferior solutions. Besides, an attempt of utilizing limited resources is made by applying the penalty function instead of adding or modifying governing equations to restrain the flow resistance. Subsequently, technique for order preference by similarity to an ideal solution (TOPSIS) is employed to help decision makers determine the best alternative from the Pareto front. The results selected by TOPSIS are compared with the alternative which has the maximum Nusselt number. It is found that TOPSIS is effective to balance deferent objectives and determine compromise parameters.