Multiobjective geometry optimization of microchannel heat exchanger using real-coded genetic algorithm

In this paper, a multiobjective optimization of the structure of a flat-tubed microchannel heat exchanger is performed to reduce its volume and fan power at a specified capacity. Design variables include tube height, tube width, tube length, fin height, and fin pitch. A weight-based, real-coded genetic algorithm is implemented to optimize the design variables within their specified range of dimensions. To further improve the numerical simulations of the microchannel heat exchanger performance, correlations for the air-side Nusselt number, friction factor, and fin efficiency are developed and validated. In the optimization, the Pareto optimal fronts are obtained by varying weights of the two conflicting objectives. A reference microchannel heat exchanger operating at different capacities is optimized. Results show that the volume and fan power of the reference microchannel heat exchanger can be reduced by up to 45% and 51% respectively, depending on the weighting factor selected. The optimization approach of this study provides the optimal solutions at the given domain of geometric parameter dimensions.

Automated summary

This paper investigates the multiobjective optimization of a flat-tubed microchannel heat exchanger to reduce its volume and fan power. By implementing a weight-based genetic algorithm and developing correlations for performance evaluations, significant reductions in volume and fan power were achieved by optimizing design variables.