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Research Papers: Flows in Complex Systems

Assessment of Transition Modeling and Compressibility Effects in a Linear Cascade of Turbine Nozzle Guide Vanes

[+] Author and Article Information
Silvia Ravelli

Department of Engineering and
Applied Sciences,
University of Bergamo,
Marconi Street 5,
Dalmine 24044, Italy
e-mail: silvia.ravelli@unibg.it

Giovanna Barigozzi

Department of Engineering and
Applied Sciences,
University of Bergamo,
Marconi Street 5,
Dalmine 24044, Italy
e-mail: giovanna.barigozzi@unibg.it

Ernesto Casartelli

Lucerne University of Applied Sciences
and Arts (HSLU),
Technik & Architektur,
Technikumstrasse 21,
Horw 6048, Switzerland
e-mail: ernesto.casartelli@hslu.ch

Luca Mangani

Lucerne University of Applied Sciences
and Arts (HSLU),
Technik & Architektur,
Technikumstrasse 21,
Horw 6048, Switzerland
e-mail: luca.mangani@hslu.ch

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received October 5, 2016; final manuscript received November 23, 2016; published online March 16, 2017. Assoc. Editor: Kwang-Yong Kim.

J. Fluids Eng 139(5), 051104 (Mar 16, 2017) (13 pages) Paper No: FE-16-1656; doi: 10.1115/1.4035462 History: Received October 05, 2016; Revised November 23, 2016

The flow field in a linear cascade of highly loaded turbine nozzle guide vanes (NGVs) has been numerically investigated at low and high-subsonic regime, i.e., exit isentropic Mach number of M2is = 0.2 and 0.6, respectively. Extensive experimental data are available for an accurate assessment of the numerical procedure. Aerodynamic measurements include not only vane loading and pressure drop in the wake but also local flow features such as boundary layer behavior along both pressure and suction sides of the vane, as well as secondary flow structures downstream of the trailing edge (TE). Simulations were performed by using two computational fluid dynamics (CFD) codes, a commercial one and an open-source based in-house code. Besides computations with the well-established shear-stress transport (SST) k–ω turbulence model assuming fully turbulent flow, transition models were taken into account in the present study. The original version of the γ–Reθ model of Menter was employed. Suluksna–Juntasaro correlations for transition length (Flenght) and transition onset (Fonset) were also tested. The main goal was to establish essential ingredients for reasonable computational predictions of the cascade aerodynamic behavior, under both incompressible and compressible regime. This study showed that transition modeling should be coupled with accurate profiles of inlet velocity and turbulence intensity to get a chance to properly quantify aerodynamic losses via CFD method. However, additional weaknesses of the transition modeling have been put forward when increasing the outlet Mach number.

Copyright © 2017 by ASME
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References

Figures

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Fig. 2

Inlet boundary layer profile (X/cax = −1.6)

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Fig. 3

View of the structured grid

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Fig. 4

Contours of y+ on vane surface, at M2is = 0.6

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Fig. 5

Inlet freestream turbulence profiles

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Fig. 6

Normalized profile Mis distributions at low Mach number (M2is = 0.2)

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Fig. 7

Normalized profile Mis distributions at high Mach number (M2is = 0.6)

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Fig. 8

Predicted skin friction coefficient distributions at M2is values of 0.2 and 0.6

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Fig. 9

Acceleration parameter

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Fig. 10

Blade-to-blade Mach number distribution at M2is = 0.2

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Fig. 11

Contours of intermittency at M2is = 0.2

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Fig. 12

Profile of Reθc at M2is = 0.2

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Fig. 13

Predicted and measured boundary layer profiles along the vane SS at M2is = 0.2

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Fig. 14

Predicted and measured boundary layer profiles along the vane PS at M2is = 0.2

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Fig. 15

Contours of intermittency at M2is = 0.6

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Fig. 16

Profile of Reθc at M2is = 0.6

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Fig. 17

Predicted and measured boundary layer profiles along the vane SS (left) and PS (right) at M2is = 0.6

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Fig. 18

Predicted and measured normalized total pressure loss profile at M2is values of 0.2 (left) and 0.6 (right), X/cax = 1.53

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Fig. 19

Predicted and measured contours of kinetic energy loss coefficient ζ at X/cax = 1.53 and M2is = 0.2

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Fig. 20

Predicted and measured contours of kinetic energy loss coefficient ζ at X/cax = 1.53 and M2is = 0.6

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Fig. 21

SS flow visualizations at M2is values of 0.2 (left) and 0.6 (right)

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Fig. 22

SS contours of computed skin friction coefficient cf at M2is values of 0.2 (left) and 0.6 (right)

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