Turbulence Modelling for Complex Flows in Turbomachinery

Abstract

This research aims to contribute the efforts of reducing the predictive uncertainties of Computational Fluid Dynamics (CFD) so that it can be a more reliable tool for modelling complex flows in turbomachinery. To achieve this goal, a three-dimensional (3D) flow phenomenon that embodies many key features of turbomachinery flows, that is, the corner separation flow often found in axial compressor stators, is selected as the research object. Based on the understanding of the underlying physics of this complex flow, the RANS turbulence closure models and a hybrid RANS-LES method are developed and extended. The improved RANS and hybrid RANS-LES models are shown to be able to predict the corner separation flows with significantly improved accuracy, and are expected to be applicable to other types of flows driven by the similar physical mechanisms as those of the corner separation flows. The commonly used RANS turbulence models (namely Spalart-Allmaras (SA) and Menter’s Shear Stress Transport (SST) models) have been found to overpredict the size of corner separation. The physical reason is partly attributed to the underestimation of turbulence mixing between the main flow and the endwall boundary layer. This makes the endwall boundary layer unable to withstand the bulk adverse pressure gradient, and in turn leads to its premature separation near the endwall. The flow characteristics within the compressor stator cascade are then studied to facilitate understanding the physical mechanisms that drive the formation of 3D flow structures, and the physical reasons that lead to the RANS modelling uncertainties. The source terms in the SA and SST models that control mixing are identified and modified, in order to increasing the mixing process and strengthening the endwall flow. The modified turbulence models are validated to give better predictions of the extent of corner separation under various operating conditions. Further, the results of an investigation into the effects of explicit non-linear turbulence modelling on anisotropic turbulence flows are presented. In compressors, the flow is subject to 3D shear and the effects due to turbulence anisotropy shall not be ignored. It is found that increasing the Reynolds stress anisotropy within the corner region contributes to counter-rotating streamwise vortices being generated in the corner region. This leads to the higher-momentum fluid in the main flow passage being entrained into the corner region and thus enhances mixing between the corner flow and the main flow. The flow within the corner region is energized and thus is more resistant to separation. Although the proposed modifications can predict corner separations with significantly better accuracy, the results are still subject to the limitations of RANS in capturing separated flows. To further reduce the modelling uncertainties, the hybrid RANS-LES method is resorted to allow for at least some larger scales of turbulence being resolved in the regions where RANS does not work well. In this thesis, an effort is presented towards a high-fidelity hybrid RANS-LES simulation for 3D complex separated flows. The hybrid RANS-LES method is developed to resolve turbulence where necessary, while avoiding the higher cost of performing large eddy simulation (LES) everywhere. That is, reasonably modelling the near-wall turbulence behaviour in the hybrid RANS-LES context by proposing a physical-based RANS-LES blending function. The suggested future work is presented in the final chapter, which outlines the necessity of investigation into the turbulence anisotropic effects on the tip-leakage flow modelling, and the potential applicability of the proposed model variants in the prediction of the blockage due to corner separation in the multi-stage environment.