This study proposes a density-based solver, dbturb, developed within the OpenFOAM framework to numerically predict film cooling performance under flow conditions characterized by significant temperature and density variations. Under such conditions, conventional pressure-based RANS solvers often suffer from reduced accuracy and numerical instability. In contrast, dbturb enhances predictive robustness by directly solving density, momentum, and energy conservation equations. Low-Mach- number corrections were incorporated into the HLLC and flux schemes, and boundary stability was ensured through a characteristic-based pressure extrapolation method to improve accuracy in low-Mach-number regimes. Numerical simulations were conducted on a flat plate model with a 7-7-7 fan-shaped film cooling hole under blowing ratios of 0.5, 1.0, and 2.0. The simulation results were compared with experimental data and those obtained from the commercial solver ANSYS CFX. The solver successfully captured qualitative features such as coolant dispersion and thermal protection, as well as key flow structures, including downstream coolant spreading and the formation of counter-rotating vortex pairing(CRVP) with increasing blowing ratio. Furthermore, dbturb demonstrated superior accuracy over CFX in predicting both the lateral and area-averaged distributions of adiabatic film cooling effectiveness. These findings suggest that dbturb is reliable for simulating film cooling flows dominated by density variations. These results confirm that dbturb has achieved a level of reliability and accuracy suitable for film cooling flow simulations.
Hong et al. (Mon,) studied this question.