Prediction of heat transfer for a single round jet impingement using the GEKO turbulence model

Two-dimensional Reynolds-Averaged Navier–Stokes simulations are performed to study a single, round impinging jet heat transfer problem, utilizing the generalized k-omega (GEKO) turbulence model as a benchmark. The simulations are performed at a jet Reynolds number of 23,300 and a nozzle-to-plate distance of 2.0 where a second peak in surface Nusselt number is observed. The effects of the three primary ($C_{sep}$, $C_{mix}$ and $C_{nw}$) and three auxiliary ($C_{bf,l}$, $C_{bf,t}$ and $C_{nw,sub}$) GEKO calibration parameters are investigated. The results indicate that $C_{mix}$ has the most significant impact on the laminar-turbulent transition zone. A deep learning based regression model is developed and trained using the simulation outputs for fast predictions of the heat transfer curve. Using $C_{sep}=1.1$, $C_{mix}=-0.7$, $C_{nw}=2.0$, $C_{nw,sub}=2.25$ and $C_{bf,t}=3.0$ along with laminar-to-turbulent transitional modeling values, provides the best agreement with experimental results from previous studies.