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Research Papers

Steady/Unsteady Reynolds-Averaged Navier–Stokes and Large Eddy Simulations of a Turbine Blade at High Subsonic Outlet Mach Number

[+] Author and Article Information
Thomas Léonard

SAFRAN – Turbomeca,
DT/MD/MO,
Bordes Cedex 1 64511, France

Laurent Y. M. Gicquel, Nicolas Gourdain

CERFACS,
Computational Fluid Dynamics Team,
42 Avenue G. Coriolis,
Toulouse Cedex 1 31057, France

Florent Duchaine

CERFACS,
Computational Fluid Dynamics Team,
42 Avenue G. Coriolis,
Toulouse Cedex 1 31057, France
e-mail: florent.duchaine@cerfacs.fr

Sensitivity to the exit boundary condition treatment and relative position from the blade trailing edge has been specifically studied. The current results provide the best solution as discussed in a dedicated article under review.

Without points inside the viscous sublayer (i.e., y+ < 1) and without appropriate functions, the k–ω turbulence model cannot be guaranteed to predict the isentropic Mach number.

The spectral analysis relies on a time series of 3 ms obtained for a numerical and experimental probes located at x/cax = 0.933 and pictured in Fig. 16(g). Note that this duration corresponds approximately to 20 cycles of the wake shedding.

Corresponding to a converged simulation for RANS and a temporal integration of 10 ms for LES (note that around 40 ms are needed to pass the transient phase).

1Corresponding author.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received October 12, 2010; final manuscript received August 26, 2014; published online October 28, 2014. Assoc. Editor: Beth Wisler.

J. Turbomach 137(4), 041001 (Oct 28, 2014) (10 pages) Paper No: TURBO-10-1188; doi: 10.1115/1.4028493 History: Received October 12, 2010; Revised August 26, 2014

Reynolds-averaged Navier–Stokes (RANS), unsteady RANS (URANS), and large eddy simulation (LES) numerical approaches are clear candidates for the understanding of turbine blade flows. For such blades, the flow unsteady nature appears critical in certain situations and URANS or LES should provide more physical understanding as illustrated here for a laboratory high outlet subsonic Mach blade specifically designed to ease numerical validation. Although RANS offers good estimates of the mean isentropic Mach number and boundary layer thickness, LES and URANS are the only approaches that reproduce the trailing edge flow. URANS predicts the mean trailing edge wake but only LES offers a detailed view of the flow. Indeed, LESs identify flow phenomena in agreement with the experiment, with sound waves emitted from the trailing edge separation point that propagate upstream and interact with the lower blade suction side.

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References

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Figures

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Fig. 1

Blade design (a) as experimentally studied by Refs. [9] and [10] and (b) expected flow features and available measurement stations [9,10]

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Fig. 2

Conceptual representation of the turbulent information to be supplied in (a) RANS or URANS and (b) LES in the context of a turbulent isotropic flow

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Fig. 3

Computational domain retained for all RANS, URANS, and LES predictions

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Fig. 4

Typical mesh topology used for RANS, URANS, and LES

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Fig. 5

Norm of the density gradient as obtained by use of (a) RANS, (b) URANS, (c) LES at given instants, and (d) a direct view at the trailing edge flow dynamics as seen in the experiment [9,10]

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Fig. 6

Temporal mean solution as obtained by use of (a) URANS and (b) LES. Note that both results can be directly compared to Fig. 5(a).

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Fig. 7

Mean isentropic Mach distribution along the blade wall predicted numerically and measured in the experiment

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Fig. 8

Mean pressure distribution along the blade trailing edge as predicted numerically and measured in the experiment

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Fig. 9

Temporal evolution of the axial velocity component in the wake of the blade

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Fig. 10

Mesh point distribution for the (a) structured and (b) unstructured meshes

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Fig. 11

Typical snapshot of the density gradient obtained with the block-structured meshes: (a) H1 and (b) H2

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Fig. 12

Typical snapshot of the density gradient obtained with the unstructured meshes: (a) T1, (b) T2, and (c) T3

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Fig. 13

Mean isentropic Mach distribution along the blade wall and as a function of the mesh resolution: (a) structured and (b) unstructured meshes

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Fig. 14

Mean boundary layer profiles as a function of the mesh resolution: (a) and (b) structured and (c) and (d) unstructured meshes. The two sides of the blade are presented: (a) and (c) for the suction side and (b) and (d) for the pressure side.

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Fig. 15

Mean trailing edge pressure profile as a function of the mesh resolution: (a) structured and (b) unstructured meshes

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Fig. 16

Unsteady pressure signal comparisons as issued by structured and unstructured LES at positions along the blade wall

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