Heat transfer optimization of twin turbulent sweeping impinging jets

Abstract

Abstract In this study, a numerical investigation is carried out to reveal the potential of obtaining uniform cooling on a planar surface by impinging jets in a turbulent flow regime using the SST k − ω turbulence model. Twin turbulent sweeping impinging jets (TTSIJ), as an idealization of an array of jets, are considered for heat transfer with the planar target surface. Unlike other studies that focused on a few effective parameters or limited the impinging jets to certain conditions, in this study, a more general investigation is performed to clarify the effects of all influential parameters on heat transfer. To this end, the effects of 8 design variables namely Reynolds number, the jet-to-target distance, the phase shift between the two jets, the frequency of pulsations of jets, the frequency of sweeping motion, the jet-to-jet separation distance, the hydraulic diameter of the nozzles, and the maximum of sweeping angle of the nozzles on Nusselt distribution on the target surface are evaluated. For the purpose of elimination of thermal stress on the target surface, it is attempted to optimize the design variables to reach a uniformly distributed Nusselt number on the target surface for 9 design uniform Nusselt distribution. The optimization of the design variables is performed using artificial neural network (ANN) combined with genetic algorithm (GA) to minimize the discrepancy between the ideally uniform and optimized Nusselt distribution. Results show that within the assumed bounds of the design variables, the applied method is successful in obtaining uniform cooling with the accuracy of more than 98% and 93% in the best and worst situation, respectively.