Improving turbulence modeling for gas turbine blades: A novel approach to address flow transition and stagnation point anomalies

Abstract

Accurate prediction of temperature and Heat Transfer Coefficient (HTC) distributions over gas turbine blades is crucial for the design process and life assessment of these components. Numerical studies of flow over gas turbine blades face significant challenges in accurately simulating two complex phenomena: (1) the transition of flow from laminar to turbulent, and (2) stagnation point flow at the leading edge. Many turbulence models tend to overpredict the temperature on turbine blades, leading to incorrect identification of hot-spot regions and, consequently, erroneous estimations of blade life. This paper investigates the performance of various turbulence models in simulating flow and heat transfer over gas turbine vanes. The study includes three full turbulence models, i.e., Spalart-Allmaras (SA), Shear Stress Transport $k-\omega$ (SST-kw), and $v^2-f$ (V2F), as well as two transitional models, i.e., Transition SST (Trans-SST) and $k-k_L-\omega$ (k-kl-w). Simulation results indicate that the $v^2-f$, Trans-SST, and $k-k_L-\omega$ models can detect flow transition. However, the transition length and onset location predicted by the Trans-SST and $k-k_L-\omega$ models do not align with experimental data. Conversely, the $v^2-f$ model suffers from over-predictions at the leading edge due to stagnation point anomaly. To address these issues and due to capacities of the V2F model, this study proposes two modifications to enhance the performance of the V2F model. First, the production term of turbulent kinetic energy is redefined to mitigate the stagnation point anomaly. Second, the model is recalibrated to improve the prediction of flow transition. The new model, named the Production Modified V2F (PMV2F) model, shows promising results in predicting temperature and heat transfer coefficients.