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Research Papers: Fundamental Issues and Canonical Flows

Adaptive Detached-Eddy Simulation of Three-Dimensional Diffusers

[+] Author and Article Information
Paul Durbin

Aerospace Engineering,
Iowa State University,
Ames, IA 50011
e-mail: durbin@iastate.edu

Zifei Yin

Aerospace Engineering,
Iowa State University,
Ames, IA 50011
e-mail: zifeiyin@iastate.edu

Elbert Jeyapaul

Mechanical and Aerospace Engineering,
Missouri University of Science and Technology,
Rolla, MO 65409

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received September 25, 2015; final manuscript received June 24, 2016; published online July 13, 2016. Assoc. Editor: Francine Battaglia.

J. Fluids Eng 138(10), 101201 (Jul 13, 2016) (8 pages) Paper No: FE-15-1688; doi: 10.1115/1.4034004 History: Received September 25, 2015; Revised June 24, 2016

An adaptive method for detached-eddy simulation (DES) is tested by simulations of flow in a family of three-dimensional (3D) diffusers. The adaptive method either adjusts the model constant or defaults to a bound if the grid is too coarse. On the present grids, the adaptive method adjusts the model constant over most of the flow, without resorting to the default. Data for the diffuser family were created by wall-resolved, large-eddy simulation (LES), using the dynamic Smagorinsky model, for the purpose of testing turbulence models. The family is a parameterized set of geometries that allows one to test whether the pattern of separation is moving correctly from the top to the side wall as the parameter increases. The adaptive DES model is quite accurate in this regard. It is found to predict the mean velocity accurately, but the pressure coefficient is underpredicted. The latter is due to the onset of separation being slightly earlier in the DES than in the LES.

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Figures

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Fig. 1

Geometry of the diffuser: top and side views. The front and top faces are flared.

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Fig. 2

U velocity contours predicted by LES for the diffuser series, normalized by inflow bulk velocity

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Fig. 3

LES predicted pressure coefficient Cp for the diffuser series

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Fig. 4

LES results for Cp and mean velocity profiles compared to experimental and DNS data. An RANS prediction of Cp is included to illustrate the typical level of inaccuracy. For velocity profiles, dashed lines denote LES while solid lines represent DNS.

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Fig. 5

Diffuser geometry and computational domain for AR=2.5

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Fig. 6

Cp along the centerline of the bottom wall: AR=2.5

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Fig. 7

Secondary velocity magnitude Uy2+Uz2, normalized by inflow bulk velocity, in the recycling region: AR=1

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Fig. 8

Secondary velocity magnitude, normalized by bulk velocity, at x = 0: AR=1

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Fig. 9

(a) Cp along the centerline of the bottom wall for AR=1,  1.5,  2.5, and 4 and (b) comparison of Cp with AR=1

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Fig. 10

Velocity profiles at mid-z locations. Top row: AR=1 and 1.5 and bottom row: AR=2.5 and 4.

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Fig. 11

Velocity profiles at mid-y locations. Top row: AR=1 and  1.5 and bottom row: AR=2.5 and 4.

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Fig. 12

DDES predicted U velocity contours, normalized by inflow bulk velocity

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Fig. 13

Instantaneous and averaged CDES and contours of fd for AR=2.5

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Fig. 14

Instantaneous Q contoured by U velocity component, velocity normalized by inflow bulk velocity

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