Heat transfer enhancement and optimization of flat-tube multilouvered fin compact heat exchangers with delta-winglet vortex generators

Surrogate-based optimization procedure is used to maximize the heat transfer of multilouvered fin compact heat exchangers with delta-winglet vortex generators (DWL). Five input parameters, such as louver angle and DWL angles of attack and positions, were chosen. The heat transfer enhancement performance of two distinct geometries, GEO1 and GEO2, with two rows of delta-winglets were considered on this research. Reynolds numbers of 120 and 240, based on hydraulic diameter, were investigated. The surrogate-based optimization procedure uses the NSGA-II (Non-Dominated Sorting Genetic Algorithm) combined with artificial neural networks. Compared with the respective baseline geometry (louvered fin without DWLs), the results showed that GEO1 optimized solutions increased the heat transfer by 21.27% and 23.52% with associated pressure loss increase of 24.66% and 36.67% for the lower and the higher Reynolds numbers, respectively. For GEO2 optimized solutions, the heat transfer was increased by 13.48% and 15.67% with an increase of the pressure drop by 20.33% and 23.70%, for the lower and the higher Reynolds numbers, respectively. The optimized solutions showed that heat transfer behind the second row of delta-winglets are as high as that behind the first row, for both Reynolds numbers. The flow patterns and heat transfer characteristics from optimized solutions presented some particular behavior, differently from the findings when louvered fin and DWLs are applied separately.