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Research Papers

Hybrid RANS/LES Simulation of Corner Stall in a Linear Compressor Cascade

[+] Author and Article Information
Guoping Xia

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

Gorazd Medic

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

Thomas J. Praisner

Pratt and Whitney,
United Technologies Corporation,
400 Main Street,
East Hartford, CT 06108
e-mail: thomas.praisner@pw.utc.com

1Corresponding author.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received September 26, 2017; final manuscript received October 23, 2017; published online July 26, 2018. Editor: Kenneth Hall.

J. Turbomach 140(8), 081004 (Jul 26, 2018) (11 pages) Paper No: TURBO-17-1177; doi: 10.1115/1.4040113 History: Received September 26, 2017; Revised October 23, 2017

Current design-cycle Reynolds-averaged Navier–Stokes (RANS) based computational fluid dynamics (CFD) methods have the tendency to over-predict corner-stall events for axial-flow compressors operating at off-design conditions. This shortcoming has been demonstrated even in simple single-row cascade configurations. Here we report on the application of hybrid RANS/large eddy simulation (LES), or detached eddy simulation (DES), for simulating the corner-stall data from the linear compressor cascade work conducted at Ecole Centrale de Lyon. This benchmark data set provides detailed loss information while also revealing a bimodal behavior of the separation which, not surprisingly, is also not well modeled by RANS. The hybrid RANS/LES results presented here predict bimodal behavior similar to the data only when special treatment is adopted to resolve the leading-edge endwall region where the horseshoe vortex (HV) forms. The (HV) is shown to be unstable, which produces the bimodal instability. The DES simulation without special treatment or refinement in the HV region fails to predict the bimodal instability, and thus the bimodal behavior of the separation. This, in turn, causes a gross over-prediction in the scale of the corner-stall. The HV region is found to be unstable with rolling of the tertiary vortex (TV) over the secondary vortex and merging with the primary HV. With these flow dynamics realized in the DES simulations, the corner stall characteristics are found to be in better agreement with the experimental data, as compared to RANS and standard DES approaches.

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Figures

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Fig. 1

Ecole Centrale de Lyon cascade's diffusion parameter and stall indicator using the method of Lei et al. [6]

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Fig. 2

Schematic representation of the structure of horseshoe vortex. Courtesy of Praisner and Smith [14].

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Fig. 3

Temporal sequence of laser-illuminated particle visualizations of horseshoe vortex dynamics. Courtesy of Praisner and Smith [14].

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Fig. 10

Integral total pressure loss comparison at different measurement stations. EXP and LES from Gao [8].

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Fig. 9

Spanwise total pressure loss comparison at 0.363ca downstream of the trailing edge, EXP from Gao [8]

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Fig. 8

Total pressure loss comparison. First row at 0.363ca, second row at 0.635ca, and third row at 0.907ca downstream of the trailing edge. EXP and LES from Gao [8].

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Fig. 7

Total pressure loss comparison. First row at 0.363ca, second row at 0.635ca, and third row at 0.907ca downstream of the trailing edge. Experimental (EXP) and LES from Gao [8].

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Fig. 6

Delayed DES blending function fd (grid 2)

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Fig. 5

Grids in DDES simulations

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Fig. 4

Experiment setup and measurement stations, courtesy of Gao [8]

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Fig. 11

Averaged total pressure loss in grid-1 and grid-2 at 50 mm above the bottom wall, or z/h = 0.135

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Fig. 12

Averaged total pressure loss in grid-1 and grid-2 at 110 mm above the bottom wall, or z/h = 0.297

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Fig. 13

Static pressure coefficient at 50 mm above the bottom wall, or z/h = 0.135

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Fig. 14

Static pressure coefficient at 110 mm above the bottom wall, or z/h = 0.297

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Fig. 15

Instantaneous vorticity magnitude contours at 6 mm above the bottom wall in grid 1

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Fig. 16

Instantaneous vorticity magnitude contours at 6 mm above the bottom wall in grid 2

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Fig. 17

Instantaneous flow field visualization in the experiment, courtesy of Zambonini et al. [11]

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Fig. 18

Instantaneous Q iso-surfaces in grid-2 DDES solution, colored by modeled turbulence kinetic energy

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Fig. 19

Instantaneous leading edge flow behavior showing the unsteady flow along the leg of horseshoe vortex

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Fig. 20

Histograms of u velocities in points A and B, denoted in the top plot

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Fig. 21

Instantaneous Q iso-surfaces in grid-1 DDES solution, colored by modeled turbulence kinetic energy

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Fig. 22

Instantaneous leading edge horseshoe vortex in grid-2 simulation

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