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Research Papers

Prediction of Transition and Losses in Compressor Cascades Using Large-Eddy Simulation

[+] Author and Article Information
Gorazd Medic

United Technologies Research Center,
411 Silver Lane,
East Hartford, CT 06108
e-mail: medicg@utrc.utc.com

Vicky Zhang

United Technologies Research
Center (China) Ltd.,
Room 3502,
35/F, Kerry Parkside Office,
1155 Fang Dian Road,
Pudong New Area,
Shanghai 201204, China
e-mail: zhangw3@utrc.utc.com

Guolei Wang

United Technologies Research
Center (China) Ltd.,
Room 3502,
35/F, Kerry Parkside Office,
1155 Fang Dian Road,
Pudong New Area,
Shanghai 201204, China
e-mail: wanggl@utrc.utc.com

Jongwook Joo

United Technologies Research Center,
411 Silver Lane,
East Hartford, CT 06108
e-mail: jooj@utrc.utc.com

Om P. Sharma

United Technologies Research Center,
411 Silver Lane,
East Hartford, CT 06108
e-mail: sharmaop@utrc.utc.com

1Corresponding author.

2Present address: Envision Energy Limited, SOHO Zhongshan Plaza, 1065 West Zhongshan Road, Shanghai 200051, China.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received March 20, 2015; final manuscript received April 19, 2016; published online June 1, 2016. Assoc. Editor: Graham Pullan.

J. Turbomach 138(12), 121001 (Jun 01, 2016) (9 pages) Paper No: TURBO-15-1054; doi: 10.1115/1.4033514 History: Received March 20, 2015; Revised April 19, 2016

In the 1950s, NACA conducted a series of low-speed cascade experiments investigating the performance of NACA 65-series compressor cascades with tests covering multiple airfoils of varying camber and with variations in solidity and air inlet angle. Most of the configurations show transition via laminar separation—both on suction and pressure side—characterized by a relatively flat region in pressure distribution, while turbulent reattachment is characterized by a rapid pressure recovery just downstream of the separated region. In the current study, wall-resolved large-eddy simulation (LES) has been used to predict transition via laminar separation in such compressor configurations as well as the resulting airfoil losses. Six different cascades with local diffusion factor varying from 0.14 to 0.56 (NACA 65-010, 65-410, 65-(12)10, 65-(15)10, 65-(18)10, and 65-(21)10 cascades) were analyzed at design conditions. In addition, the loss bucket for various angles of attack off-design conditions has been computed for the NACA 65-(18)10 cascade. Chord-based Reynolds number for all the experiments considered here was held at 250,000. This allows sufficient grid resolution in these LES analyses at an acceptable computational cost, i.e., up to 20,000 CPU hours per case. Detailed comparisons to test data are presented in the form of surface pressure coefficient, drag coefficient, losses, and momentum thickness ratio. The results show that LES is capable of capturing transition via laminar separation relatively well for most of the cases, and consequently, may constitute a predictive tool for assessing losses of different compressor airfoils.

Copyright © 2016 by ASME
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References

Figures

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Fig. 1

Computational domain used for NACA65 compressor cascades

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Fig. 2

Detail of computational grid for NACA 65-(18)10 cascade at inlet angle of 45 deg

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Fig. 3

Grid resolution in plus units for NACA 65-(18)10 cascade at inlet angle of 45 deg

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Fig. 4

Isosurfaces of Q = |Ω|2 − |S|2, colored by pressure, indicating Kelvin–Helmholtz instabilities that lead from laminar separation to transition to turbulence (NACA 65-18-10 cascade at inlet angle of 45 deg)

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Fig. 5

Instantaneous spanwise velocity (top) and time-averaged streamlines with static pressure contours (bottom) for NACA 65-(18)10 cascade at inlet angle of 45 deg

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Fig. 6

Time-averaged surface skin-friction coefficient from LES computations for NACA 65-(18)10 cascade at inlet angle of 45 deg; the results are also included from fully turbulent and manually tripped RANS with k–omega model

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Fig. 7

Cp comparison to data for NACA65-010 (a), NACA65-410 (b), and NACA65-(12)10 (c) cascades at design conditions

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Fig. 8

Cp comparison to data for NACA65-(18)10 (a), NACA65-(15)10 (b), and NACA65-(21)10 (c) cascades at design conditions

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Fig. 9

Comparison of computed momentum thickness ratio against local diffusion factor at reference incidence angle for low-speed cascade data of NACA 65-(A10)10 blades—using LES

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Fig. 10

Comparison of computed momentum thickness ratio against local diffusion factor at reference incidence angle for low-speed cascade data of NACA 65-(A10)10 blades—using fully turbulent RANS and by manually tripping turbulence model in RANS simulations

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Fig. 11

Comparison of Cp to data for NACA65-(18)10 cascadeat design conditions as computed by using manual tripping with k–omega RANS turbulence model and with Langtry–Menter transition model with SST RANS turbulence model

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Fig. 12

Cp comparison illustrating turbulent reattachment prediction with WALE, Vreman, and dynamic Smagorinsky SGS models for NACA 65-(18)10 cascade at inlet angle of 45 deg

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Fig. 13

Instantaneous spanwise velocity distribution for NACA65-(18)10 cascade at inlet angles of 37 deg (a) and 54 deg (b)

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Fig. 14

Cp comparison to data for NACA65-(18)10 cascade at off-design conditions—inlet angles of 37 (a), 41 (b), and 45 (c) deg

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Fig. 15

Cp comparison to data for NACA65-(18)10 cascade at off-design conditions—inlet angles of 47 (a), 51 (b), and 54 (c) deg

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Fig. 16

Cd comparison to data for NACA65-(18)10 cascade at off-design conditions

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