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Research Papers

An Exponential Decay Model for the Deterministic Correlations in Axial Compressors

[+] Author and Article Information
Yangwei Liu

National Key Laboratory of
Science and Technology on
Aero-Engine Aero-Thermodynamics,
School of Energy and Power Engineering,
Beihang University,
Beijing 100191, China;
Collaborative Innovation Center of
Advanced Aero-Engine,
Beihang University,
Beijing 100191, China;
State Key Laboratory of Aerodynamics,
China Aerodynamics Research and
Development Center,
P.O. Box 211,
Mianyang Sichuan 621000, China
e-mail: liuyangwei@126.com

Yumeng Tang

National Key Laboratory of
Science and Technology on
Aero-Engine Aero-Thermodynamics,
School of Energy and Power Engineering,
Beihang University,
Beijing 100191, China
e-mail: 15201120825@163.com

Baojie Liu

National Key Laboratory of
Science and Technology on
Aero-Engine Aero-Thermodynamics,
School of Energy and Power Engineering,
Beihang University,
Beijing 100191, China;
Collaborative Innovation Center of
Advanced Aero-Engine,
Beihang University,
Beijing 100191, China
e-mail: liubj@buaa.edu.cn

Lipeng Lu

National Key Laboratory of
Science and Technology on
Aero-Engine Aero-Thermodynamics,
School of Energy and Power Engineering,
Beihang University,
Beijing 100191, China;
Collaborative Innovation Center of
Advanced Aero-Engine,
Beihang University,
Beijing 100191, China
e-mail: lulp@buaa.edu.cn

1Corresponding authors.

Manuscript received February 17, 2018; final manuscript received August 27, 2018; published online January 16, 2019. Assoc. Editor: Coutier-Delgosha Olivier.

J. Turbomach 141(2), 021005 (Jan 16, 2019) (11 pages) Paper No: TURBO-18-1038; doi: 10.1115/1.4041380 History: Received February 17, 2018; Revised August 27, 2018

The unsteady blade row interaction (UBRI) is inherent and usually has a large effect on performance in multistage axial compressors. The effect could be considered by using the average-passage equation system (APES) in steady-state environment by introducing the deterministic correlations (DC). How to model the DC is the key in APES method. The primary purpose of this study is to develop a DC model for compressor routine design. The APES technique is investigated by using a 3D viscous unsteady and time-averaging Computational fluid dynamics (CFD) flow solver developed in our previous studies. Based on DC characteristics and its effects on time-averaged flow, an exponential decay DC model is proposed and implemented into the developed time-averaging solver. Steady, unsteady, and time-averaging simulations are conducted on the investigation of the UBRI and the DC model in the first transonic stage of NASA 67 and the first two stages of a multistage compressor. The DC distributions and mean flow fields from the DC model are compared with the unsteady simulations. The comparison indicates that the proposed model can take into account the major part of UBRI and provide significant improvements for predicting compressor characteristics and spanwise distributions of flow properties in axial compressors, compared with the steady mixing plane method.

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Figures

Grahic Jump Location
Fig. 1

Illustration of rotor/stator reference frame and spatial-temporal transformation used to define the downstream blade row fluctuating velocity [23]

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Fig. 2

Circumferential averaged ρ¯Vx″Vx″̃: (a) unsteady and (b) model

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Fig. 3

Circumferential averaged ρ¯Vx″H″̃: (a) unsteady and (b) model

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Fig. 4

Circumferential averaged ρ¯Vx″Vx″̃ along chord in the stator passage: (a) 10% span, (b) 50% span, and (c) 90% span

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Fig. 5

Circumferential averaged ρ¯Vx″H″̃ along chord in the stator passage: (a) 10% span, (b) 50% span, and (c) 90% span

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Fig. 6

Adiabatic efficiency of NASA 67

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Fig. 7

Spanwise distribution of total pressure, total temperature, Ma, and entropy at the stator exit: (a) total pressure, (b) total temperature, (c) Ma, and (d) entropy

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Fig. 8

Computational grid: (a) 3D grid, (b) leading edge of the first stator, and (c) trailing edge of the first stator

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Fig. 9

Compressor performance map: (a) total pressure ratio and (b) adiabatic efficiency

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Fig. 10

Instantaneous entropy contours and static pressure lines at 90% span at near peak efficiency condition (a) t = 1/60T, (b) t = 6/60T, (c) t = 11/60T, (d) t = 16/60T, (e) t = 21/60T, and (f) t = 26/60T

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Fig. 11

Circumferential averaged ρ¯Vx″H″̃ at near peak efficiency condition: (a) unsteady and (b) model

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Fig. 12

Circumferential averaged ρ¯Vx″H″̃ along chord in the first stator passage at near peak efficiency condition: (a) 10% span, (b) 50% span, and (c) 90% span

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Fig. 13

Spanwise distribution of total pressure, total temperature, Ma and entropy at the second stator exit at near peak efficiency condition: (a) total pressure, (b) total temperature, (c) Ma, and (d) entropy

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