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Research Papers

Scale-Resolving Simulations of Bypass Transition in a High-Pressure Turbine Cascade Using a Spectral Element Discontinuous Galerkin Method

[+] Author and Article Information
Anirban Garai

Science and Technology Corporation,
21 Enterprise Parkway, Suite 150,
Hampton, VA 23666

Laslo T. Diosady

Science and Technology Corporation,
21 Enterprise Parkway, Suite 150,
Hampton, VA 23666

Scott M. Murman

NASA Ames Research Center,
M/S 258-1,
Moffett Field, CA 94035

Nateri K. Madavan

NASA Ames Research Center,
M/S 258-2,
Moffett Field, CA 94035
e-mail: nateri.k.madavan@nasa.gov

1Corresponding author.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received September 22, 2017; final manuscript received October 20, 2017; published online December 20, 2017. Editor: Kenneth Hall. The United States Government retains, and by accepting the article for publication, the publisher acknowledges that the United States Government retains, a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for United States government purposes.

J. Turbomach 140(3), 031004 (Dec 20, 2017) (13 pages) Paper No: TURBO-17-1174; doi: 10.1115/1.4038403 History: Received September 22, 2017; Revised October 20, 2017

The application of a new computational capability for accurate and efficient high-fidelity scale-resolving simulations of turbomachinery is presented. The focus is on the prediction of heat transfer and boundary layer characteristics with comparisons to the experiments of Arts et al. (1990, “Aero–Thermal Investigation of a Highly Loaded Transonic Linear Turbine Guide Vane Cascade,” von Karman Institute for Fluid Dynamics, Rhode St. Genese, Belgium, Technical Note No. 174.) for an uncooled, transonic, linear high-pressure turbine (HPT) inlet guide vane cascade that includes the effects of elevated inflow turbulence. The computational capability is based on an entropy-stable, discontinuous Galerkin (DG) spectral element approach that extends to arbitrarily high orders of spatial and temporal accuracy. The suction side of the vane undergoes natural transition for the clean inflow case, while bypass transition mechanisms are observed in the presence of elevated inflow turbulence. The airfoil suction-side boundary layer turbulence characteristics during the transition process thus differ significantly between the two cases. Traditional simulations based on the Reynolds-averaged Navier–Stokes (RANS) fail to predict these transition characteristics. The heat transfer characteristics for the simulations with clean inflow agree well with the experimental data, while the heat transfer characteristics for the bypass transition cases agree well with the experiment when higher inflow turbulence levels are prescribed. The differences between the clean and inflow turbulence cases are also highlighted through a detailed examination of the characteristics of the transitional and turbulent flow fields.

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Figures

Grahic Jump Location
Fig. 2

Computational meshes used in the simulations for (a) clean inflow, (b) baseline grid with 7% inflow turbulence, (c) refined grid with 7% inflow turbulence, and (d) 20% inflow turbulence. The black, red, and blue lines are elemental boundaries for fourth, eighth, and 16th order solutions, respectively.

Grahic Jump Location
Fig. 1

Mean skin friction distribution for clean inflow (solid line with triangles) and 7% inflow turbulence (dashed line with inverted triangles) from our RANS simulations using the kω turbulence model and the γ–Reθ [10] transition model for the experimental configuration of Arts et al. [7]. The dotted vertical lines represent the experimentally observed transition locations.

Grahic Jump Location
Fig. 3

Instantaneous contours at midspan of (i) Mach number, (ii) vorticity magnitude, (iii) surface skin friction, and (iv) Z–momentum at a plane offset by 0.0014C from the airfoil surface for the (a) clean and (b) 7% inflow turbulence simulations

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Fig. 4

Principal axes of the mean strain rate tensor for the 7% inflow turbulence simulation. The black arrows indicate stretching and the green arrows indicate compression.

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Fig. 5

Temporal evolution of the airfoil surface-averaged heat flux for the various numerical simulations. The dashed lines represent the mean heat flux values after the flow attains a stationary state.

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Fig. 6

Instantaneous suction-side heat flux at 1.35τ for the (a) baseline mesh, (b) fine mesh, (c) extended span simulations for 7% inflow turbulence, and (d) 20% inflow turbulence simulations

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Fig. 7

(a) Mean and (b) root-mean-square of the airfoil surface pressure distribution for the clean, 7%, and 20% inflow turbulence simulations. In (a), the lines without symbols denote the scale-resolving simulations and the lines with symbols denote the RANS simulations (triangles for clean inflow, inverted triangles for 7% inflow turbulence).

Grahic Jump Location
Fig. 8

(a) Mean and (b) root-mean-square of the airfoil surface skin friction distribution for the clean, 7%, and 20% inflow turbulence simulations. In (a), the lines without symbols denote the scale-resolving simulations and the lines with symbols denote the RANS simulations (triangles for clean inflow, inverted triangles for 7% inflow turbulence), respectively.

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Fig. 9

(a) Mean and (b) root-mean-square of the airfoil surface heat flux distribution for the clean, 7%, and 20% inflow turbulence simulations

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Fig. 10

(a) Shape factor and (b) Reθ for the suction-side boundary layer. Solid black and dashed red lines denote the clean and 7% inflow simulations, respectively. The lines without and with symbols denote results from the scale-resolving simulations and RANS simulations (triangles for clean inflow, inverted triangles for 7%), respectively.

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Fig. 11

Turbulence intensity contours on the airfoil suction side for the (a) clean and (b) 7% inflow turbulence simulations. The black vertical lines denote the locations of the monitoring stations, and the white line denotes the edge of the boundary layer.

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Fig. 12

Wall normal profiles of (a) mean tangential velocity and (b) turbulence intensity. In (a), the solid black and dashed red lines denote the clean inflow and 7% inflow turbulence simulations, respectively. In (b). the black lines without symbols and the red lines with symbols denote the clean and 7% inflow turbulence simulations, respectively. The solid, dashed, and dotted lines in (b) represent the tangential, wall normal, and spanwise components, respectively. The horizontal tick marks in both figures denote the local edge of the boundary layer.

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Fig. 13

Characteristics of the anisotropic Reynolds stress tensor (Lumley triangles) inside the boundary layer for the (a) clean and (b) 7% inflow turbulence simulations at monitoring stations (i) before transition and (ii) at transition. Note that for the 7% inflow turbulence simulation, a station near the leading edge (up to ≈20δ) is also included.

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Fig. 14

Wall normal profiles of the resolved turbulent kinetic energy budget terms at stations D and E for the clean inflow simulations. Budget terms are normalized by the peak production value at each station.

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Fig. 15

Wall normal profiles of the resolved turbulent kinetic energy budget terms at stations B–E for the 7% inflow turbulence simulations. Budget terms are normalized by the peak production value at each station.

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