Heat transfer enhancement in micro heat exchangers using genetic algorithm based multi-objective optimization

In this study, the optimization of heat transfer in serpentine micro heat exchangers using the genetic algorithm based multi-objective optimization was investigated. The effects of geometric parameters of the serpentine microchannels including curvature radius and straight length between the bends on friction factor (f) and Nusselt number (Nu) were investigated experimentally. As was expected, increasing the heat transfer rate and pressure drop occurs simultaneously, which leads to the more energy required for pumping. Hence, both phenomena should be considered at the same time. The constants of two empirical equations for estimating Nusselt number and friction factor were obtained by the genetic algorithm searching method. The mean relative error of 7.49% and 9.76% were calculated for Nu and f correlation, respectively. These empirical equations were employed in two objective functions for genetic algorithm based multi-objective optimization. The optimum geometrical parameters of the investigated serpentine microchannels which lead to a trade-off between heat transfer and pressure drop were presented.