A physically based semi-empirical model for secondary loss in throughflow analysis based on corner flow mechanism

Corner separation and stall are important phenomena in axial compressors, significantly impacting loading capacity, efficiency, and stall margin. However, most existing loss model systems, applied by two-dimensional (2D) throughflow analysis for compressor preliminary design, highly rely on empirical models to predict secondary loss. These models may produce misleading results under strong three-dimensional (3D) corner flow conditions. In this paper, a physically based semi-empirical model based on corner flow mechanism is proposed for throughflow analysis, which accounts for both the magnitude and spanwise distribution of secondary loss. Secondary loss is decomposed into three components by physically decoupling different flow structures. These components are modeled mainly through simulating the formation of the corner vortex and analyzing the influences of critical factors. The new model is validated employing numerical simulation and experimental data of subsonic linear cascades with various geometric and aerodynamic configurations. Results indicate that the proposed model reduces the prediction errors of secondary loss by over 60%, compared to conventional models. It additionally captures the sharp increase in loss during the transition from corner separation to stall and the variation of spanwise distribution form caused by secondary flow. The introduction of physical mechanism provides a more solid theoretical foundation for secondary loss prediction, beneficial to the accuracy of 2D throughflow calculation and giving designers better guidance at the preliminary stages of design.

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Publication Details

Journal
Physics of Fluids
Published
2025-04-01
DOI
https://doi.org/10.1063/5.0264304
Citations
2
Primary Topic
Fluid Dynamics and Turbulent Flows
Type
article
Field-Weighted Citation Impact
2.67

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article

A physically based semi-empirical model for secondary loss in throughflow analysis based on corner flow mechanism

Baojie Liu, Xianjun Yu, Guangfeng An, Xiang Yan et al.
2 citations
Physics of Fluids
Fluid Dynamics and Turbulent Flows
2.67
article

A physically based semi-empirical model for secondary loss in throughflow analysis based on corner flow mechanism

Baojie Liu, Xianjun Yu, Guangfeng An, Xiang Yan, Ruoyu Wang
article en
2 citations

Abstract

Corner separation and stall are important phenomena in axial compressors, significantly impacting loading capacity, efficiency, and stall margin. However, most existing loss model systems, applied by two-dimensional (2D) throughflow analysis for compressor preliminary design, highly rely on empirical models to predict secondary loss. These models may produce misleading results under strong three-dimensional (3D) corner flow conditions. In this paper, a physically based semi-empirical model based on corner flow mechanism is proposed for throughflow analysis, which accounts for both the magnitude and spanwise distribution of secondary loss. Secondary loss is decomposed into three components by physically decoupling different flow structures. These components are modeled mainly through simulating the formation of the corner vortex and analyzing the influences of critical factors. The new model is validated employing numerical simulation and experimental data of subsonic linear cascades with various geometric and aerodynamic configurations. Results indicate that the proposed model reduces the prediction errors of secondary loss by over 60%, compared to conventional models. It additionally captures the sharp increase in loss during the transition from corner separation to stall and the variation of spanwise distribution form caused by secondary flow. The introduction of physical mechanism provides a more solid theoretical foundation for secondary loss prediction, beneficial to the accuracy of 2D throughflow calculation and giving designers better guidance at the preliminary stages of design.

Physics of FluidsVol. 37(4)
Beihang University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 13%
Fluid Dynamics and Turbulent Flows
2.67
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