Computational Study of the Application of Al2O3 Nanofluids in Forced Convection of High-Reynolds Swirling Jets for Engineering Cooling Processes.

Abstract

Numerical modeling of turbulent impinging swirling jets presents significant challenges due to the complex flow dynamics involved. As a result, there is limited literature on the computational modeling of such nanofluid jets, with most existing studies focusing on laminar nanofluid jets or turbulent jets using air or water without nanoparticles. This work presents a computational study of various configurations using Al₂O₃ nanoparticles in submerged, high-Reynolds-number (Re = 35,000) turbulent jets for cooling applications. The analysis explores six nanoparticle volume fractions (0–10%, corresponding to nanofluid Prandtl numbers in the range [7, 14.4]), two nozzle-to-plate distances (H/D = 2 and 4), and multiple swirl numbers (S = 0–0.83). Results indicate that adding nanoparticles consistently enhances forced convection. However, the effects of swirl intensity and nozzle-to-plate distance on heat transfer performance are more complex and non-linear, with some combinations improving heat transfer while others diminish it, depending on the configuration.