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research-article

Effect of RANS Method on the Stall Onset Prediction by an Eigenvalue Approach

[+] Author and Article Information
Zhe Xie

ASME Member, National Key Laboratory of Science and Technology on Aero-Engine Aero-Thermodynamics, School of Energy and Power Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China
xiezhe_buaa@buaa.edu.cn

Yangwei Liu

Associate Professor, National Key Laboratory of Science and Technology on Aero-Engine Aero-Thermodynamics, School of Energy and Power Engineering; Collaborative Innovation Center of Advanced Aero-Engine, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China
liuyangwei@126.com

Xiaohua Liu

School of Aeronautics and Astronautics, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Shanghai 200240, China
Xiaohua-Liu@sjtu.edu.cn

Li-peng Lu

National Key Laboratory of Science and Technology on Aero-Engine Aero-Thermodynamics, School of Energy and Power Engineering; Collaborative Innovation Center of Advanced Aero-Engine, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China
lulp@buaa.edu.cn

Xiaofeng Sun

School of Energy and Power Engineering, Collaborative Innovation Center of Advanced Aero-Engine, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China
sunxf@buaa.edu.cn

1Corresponding author.

ASME doi:10.1115/1.4041362 History: Received April 25, 2018; Revised August 25, 2018

Abstract

The eigenvalue approach is a recently developed compressor stability model used to predict stall onset. In this model, the flow field from a Reynolds-Averaged Navier-Stokes (RANS) simulation provides the basic flow. This paper presents the effect of the RANS methods (including the computational grid, the turbulence model and the spatial discretization scheme) on the eigenvalue and investigates which flow structures that impact the eigenvalue most in the transonic compressor of NASA Rotor 37. Three individual meshes with different grid densities was used to validate the grid independence, and the results indicate that RANS simulation and eigenvalue calculation obtain grid independence at the same grid density. Then the effect of four turbulence models (including Spalart-Allmaras (SA) turbulence model, two different k-e models with the extended wall function model and the Yang-Shih model, and k-? Shear Stress Transport model) and three spatial discretization schemes (the central scheme, the Flux Difference Splitting scheme, and the symmetric total variation diminishing (STVD)) were also studied. Further investigation showed that the SA turbulence model combined with the STVD scheme provided the best stall point prediction, with a relative error of 0.05%. Detailed exploration of the three-dimensional flow field revealed that there were two flow patterns near the blade tip necessary for precisely predicting stall onset: the flow blockage generated by the shockwave-tip leakage vortex interaction, and the trailing edge separation and corresponding wake flow. The effect of the blockage was greater than the effect of the trailing edge flow.

Copyright (c) 2018 by ASME
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