Non-Linear k-ε-ζ-f model sensitized to rotation for blade turbine internal cooling
The need to study flow and heat transfer in turbine blade cooling design calls to develop appropriate modelling approaches able to return accurate predictions at a reduced computational costs. Here we propose and scrutinize a quadratic version of the well-known k-ε-ζ-f RANS turbulence models, aiming at sensitizing the model to the effect of rotation in configurations mimicking the flow in turbine internal cooling.