Assessment of Effect of Flux Scheme and Turbulence Model on Blade-to-blade Calculations

Document Type : Regular Article

Authors

1 Department of Mechanical Engineering, Middle East Technical University, Ankara, Çankaya, 06800, Turkey

2 Department of Aeronautical Engineering, University of Turkish Aeronautical Association, Ankara, Etimesgut, 06790, Turkey

Abstract

Today, due to advances in computing power, Reynolds Averaged Navier-Stokes (RANS) solvers are widely preferred for quasi-three-dimensional (Q3D) blade-to-blade analysis. This study investigates the performance of different flux calculation methods and turbulence models with a density-based RANS solver (Numeca®) in blade-to-blade analysis. A block-structured mesh topology is used to create a solution grid around the airfoil. Spatial discretization is performed in the pitchwise direction to represent the quasi three-dimensional flow, while only one computational cell is used in the radial direction to simulate the flow through the Q3D cascade. The computational grid around the airfoil is created with the Autogrid® tool using the block mesh topology. For the convective flow calculations, both the central and upwind methods available in Numeca® are applied separately. The Baldwin Lomax (BL), Spalart Allmaras (SA), Shear Stress Transport (SST), Explicit Algebraic Reynolds Stress Model (EARSM) and k-ε (KEPS) turbulence models are used for the turbulent shear stress calculations. In order to evaluate the aerodynamic performance of the spatial discretization methods and turbulence models, the isentropic Mach distribution on the airfoil surface, the total pressure loss and the exit flow angle behind the blade are compared with the experimental data of six test cases. In the compressor cases, the Spalart-Allmaras turbulence model with the Central scheme gives the best results in terms of average loss prediction, while no turbulence model is superior to the other in terms of exit angle prediction. On the turbine side, EARSM and KEPS give better performance in terms of loss prediction for the low Reynolds case compared to others, while the Spalart-Allmaras turbulence model is better for the high Reynolds cases.

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