This study investigates turbulent slot jet impingement using the generalized k-𝜔 (GEKO) turbulence model, calibrated with a set of optimal coefficients, to analyze flow dynamics and heat transfer under stationary and moving wall conditions. The effects of varying the surface-to-jet velocity ratio and Reynolds number on flow topology, vortical structures, and convective heat transfer are examined. As plate velocity increases, secondary vortices form, trapping warmer fluid near the surface, reducing local heat transfer, and shifting the Nusselt peak downstream. Additionally, wall-scaled velocity profiles show a return to canonical linear and logarithmic behavior as the jet develops downstream, consistent with the law of the wall. A regression-based correlation is developed to quantify the nonlinear dependence of the average Nusselt number on the surface-to-jet velocity ratio, demonstrating strong predictive performance across a wide range of Reynolds numbers.

Investigation of Secondary Vortex Effect in Slot Jet Impingement Heat Transfer Using a Generalized Two-Equation Turbulence Model

D'ADDIO Rossella
;
MEZZACAPO Antonio;DE STEFANO Giuliano
2026

Abstract

This study investigates turbulent slot jet impingement using the generalized k-𝜔 (GEKO) turbulence model, calibrated with a set of optimal coefficients, to analyze flow dynamics and heat transfer under stationary and moving wall conditions. The effects of varying the surface-to-jet velocity ratio and Reynolds number on flow topology, vortical structures, and convective heat transfer are examined. As plate velocity increases, secondary vortices form, trapping warmer fluid near the surface, reducing local heat transfer, and shifting the Nusselt peak downstream. Additionally, wall-scaled velocity profiles show a return to canonical linear and logarithmic behavior as the jet develops downstream, consistent with the law of the wall. A regression-based correlation is developed to quantify the nonlinear dependence of the average Nusselt number on the surface-to-jet velocity ratio, demonstrating strong predictive performance across a wide range of Reynolds numbers.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/601986
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