Artificial neural network modeling of a deflector in a grooved channel as well as optimization of its effective parameters

One of methods available to increase the rate of heat transfer in channels with parallel plates is making grooves in them. But, the fundamental problem of this method is the formation of stagnation zone in the grooves and as a result formation a zone with low energy transfer. In this paper, the effect of placing curved deflectors (geometries with elliptical forms) in channel on thermal and hydraulic characteristic of the fluid flow- with the aim of directing of the flow into the grooves and as a result increasing the rate of heat transfer in this zone- are investigated and heat transfer coefficient and pressure drop are calculated for different values of Reynolds number and geometrical parameters of the deflector (its small and large radiuses). The results show that the presence of the deflector in the channel significantly increases the heat transfer rate compare to the channel without deflector. Of course, it should be noted that this work also increases the pressure drop. So, finally in order to determine configurations of the deflector causing minimum pressure drop, maximum Nusselt number or a balance between them, optimization algorithm consisting of artificial neural network and multi-objective genetic algorithm was utilized to calculate the optimal values of these parameters.