Response surface methodology-based multi-objective grey relation optimization for impinging jet cooling with Al2O3/water nanofluid on a curved surface

Abstract

In this study, a modelling procedure is followed to simultaneously optimize the heat transfer and entropy generation performance in the impinging jet flow on a convex surface. For this optimization study, numerical results of laminar nanofluid flow (Al2O3/water) having two different particle shape (blade and cylindrical) were used as inputs and optimum Nusselt number and total entropy generation parameters were obtained by using RSM-based multi-objective grey relation analysis. Different nanofluid volume fractions, target distance/nozzle diameter ratio (H/B) and Reynolds numbers were evaluated for the analysis. Each control variable has three levels except for the particle shape (blade and cylindrical). In total, forty CFD analyses have been performed based on these variables and the findings obtained by the RSM-based multi-objective grey relation analysis reveal that geometric differences and nanofluid properties have a considerable impact on the performance of jet impingement cooling. The results show that the H/B ratio has the greatest impact on heat transfer enhancement and entropy generation improvement on convex surface at laminar flow conditions. As a result of the optimization, the highest Nu number and the lowest entropy generation obtained by grey relation analysis were found to be 4.383 and 9.06 x 10(-4) kj/kg K, respectively, for blade-shaped alumina nanofluid at H/B = 2.