Surrogate-based optimization of the attack and inclination angles of a delta winglet pair vortex generator in turbulent channel flow

Abstract

Vortex generators (VGs) have been extensively studied and utilized in multifunctional heat exchangers/reactors due to their remarkable ability to create coherent flow structures and streamwise vortices. These characteristics significantly enhance the mixing and heat transfer performance in laminar and turbulent flow regimes. With the advancement of computational power, VG shape optimization has become feasible, leading to the discovery of various optimized shapes in the literature for different Reynolds numbers. In this paper, the response surface polynomial method is employed as a surrogate model to optimize the angle of attack and inclination angle of a delta winglet VG at a Reynolds number of 4,600. The potential applications of these optimized designs are diverse, particularly in scenarios that require cooling or heating. Some examples include photovoltaic (PV) panel cooling, waste heat recovery in hybrid PV/solar water heating systems, energy-efficient HVAC systems, and thermal management in electric vehicles. To achieve this objective, Computational Fluid Dynamics (CFD) simulations are conducted to compute the thermal performance factor of each VG design at various values of attack and inclination angles. By enhancing mixing and heat transfer capabilities, this design can have a substantial impact on various renewable energy applications, contributing to a greener and more sustainable future. The highest thermal enhancement factor of 1.15 is found to be achieved for an inclination angle of −45° and an angle of attack of 35°. This means that optimized VG enhances heat transfer by 15% compared to empty channel flow, while maintaining the same pumping power.