Research Papers

Impact of Wall Temperature on Heat Transfer Coefficient and Aerodynamics for Three-Dimensional Turbine Blade Passage

[+] Author and Article Information
Roberto Maffulli

Turbomachinery Department,
Von Karman Institute for Fluid Dynamics,
Chaussée de Waterloo 72,
Rhode St Genese 1640, Belgium
e-mail: maffulli@vki.ac.be

Li He

Osney Thermofluids Laboratory,
Department of Engineering Science,
University of Oxford,
Osney Mead,
Oxford OX2 0ES, UK
e-mail: li.he@eng.ox.ac.uk

1Corresponding author.

Contributed by the Heat Transfer Division of ASME for publication in the JOURNAL OF THERMAL SCIENCE AND ENGINEERING APPLICATIONS. Manuscript received March 21, 2016; final manuscript received February 5, 2017; published online April 19, 2017. Assoc. Editor: Ting Wang.

J. Thermal Sci. Eng. Appl 9(4), 041002 (Apr 19, 2017) (12 pages) Paper No: TSEA-16-1073; doi: 10.1115/1.4036012 History: Received March 21, 2016; Revised February 05, 2017

The present work is aimed to examine how the heat transfer coefficient (HTC) and main three-dimensional (3D) passage aerodynamic features may be affected by a nonadiabatic wall temperature condition. A systematic computational study has been first carried out for a 3D nozzle guide vane (NGV) passage. The impacts of wall temperature on the secondary flows, trailing edge shock waves, and the passage flow capacity are discussed, underlining the connection and interactions between the wall temperature and the external aerodynamics of the 3D passage. The local discrepancies in HTC in these 3D flow regions can be as high as 30–40% when comparing low and high temperature ratio cases. The effort is then directed to a new three-point nonlinear correction method. The benefit of the three-point method in reducing errors in HTC is clearly demonstrated. A further study illustrates that the new method also offers much enhanced robustness in the wall heat flux scaling, particularly relevant when the wall thermal condition is also shown to influence the laminar–turbulent transition exhibited by two well-established transition models adopted in the present work.

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Fig. 1

Schematics of the linear and nonlinear dependency of heat transfer with Tw: (a) linear variation of q˙ with Tw and (b) nonlinear variation of q˙ with Tw

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Fig. 7

Mesh dependency study. Total pressure field (Pa) downstream of the trailing edge.

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Fig. 6

Mesh dependency study. Surface heat flux (W/m2) for the two mesh densities.

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Fig. 5

(q˙/q˙ref) for 50% span section: comparison of CFD with experimental data

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Fig. 4

Mis for 50% span section: comparison of CFD with experimental data

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Fig. 3

Grid used for the performed calculations: (a) computational grid: laminar region highlighted and (b) grid detail: trailing edge-hub

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Fig. 2

Computational domain

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Fig. 8

Midspan HTC distribution for the three analyzed temperature differences

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Fig. 9

HTC dependency on TR, 50% span cut

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Fig. 10

HTC dependency on TR, on the vane pressure side

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Fig. 19

Wall heat transfer (W/m2) for TR = 0.6, direct CFD (center), conventional two-point method (left), and new three-point method (right)

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Fig. 11

HTC dependency on TR, on the vane suction side

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Fig. 12

HTC dependency on TR, on the shroud endwall

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Fig. 13

HTC dependency on TR, on the hub endwall

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Fig. 14

Suction-side shock position for the quasi-adiabatic (TR = 0.99) and cooled (TR = 0.7) case

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Fig. 15

Streamlines at suction side–endwalls corners for quasi-adiabatic (TR = 0.99) and cooled (TR = 0.7) case

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Fig. 16

Wall shear stress direction on suction side for quasi-adiabatic (TR = 0.99) and cooled (TR = 0.7) case

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Fig. 17

Wall shear stress magnitude on suction side for quasi-adiabatic (TR = 0.99) and cooled (TR = 0.7) case

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Fig. 18

Density contours at TE cut plane for quasi-adiabatic (TR = 0.99) and cooled (TR = 0.7) case

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Fig. 20

Prediction error comparison between the two-point and three-point

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Fig. 21

(q˙/q˙ref) (Eq. (3)) for TR = 0.8 and 0.6 using the k–kl–ω transition model

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Fig. 22

(q˙/q˙ref) (Eq. (3)) for TR = 0.8 and 0.6 using the transitional SST model

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Fig. 23

HTC plots for TR = 0.6 for k–kl–ω transition model, obtained using the traditional two-point method of Eq. (5)

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Fig. 24

Comparison of the new three-point method and the conventional two-point method for a transitional case using the k–kl–ω transition model



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