Research Papers: Flows in Complex Systems

Comparative Studies of RANS Versus Large Eddy Simulation for Fan–Intake Interaction

[+] Author and Article Information
Yunfei Ma

Department of Engineering,
University of Cambridge,
Cambridge CB2 1PZ, UK
e-mail: ym324@cam.ac.uk

Nagabhushana Rao Vadlamani

Department of Aerospace Engineering,
Indian Institute of Technology (IIT) Madras,
Chennai 600036, India
e-mail: nrv@iitm.ac.in

Jiahuan Cui

School of Aeronautics and Astronautics,
ZJU-UIUC Institute,
Zhejiang University,
Haining 310007, China
e-mail: jiahuancui@intl.zju.edu.cn

Paul Tucker

Department of Engineering,
University of Cambridge,
Cambridge CB2 1PZ, UK
e-mail: pgt23@cam.ac.uk

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received April 23, 2018; final manuscript received September 3, 2018; published online October 5, 2018. Assoc. Editor: Riccardo Mereu.

J. Fluids Eng 141(3), 031106 (Oct 05, 2018) (13 pages) Paper No: FE-18-1286; doi: 10.1115/1.4041393 History: Received April 23, 2018; Revised September 03, 2018

The present research applied a mixed-fidelity approach to examine the fan–intake interaction. Flow separation induced by a distortion generator (DG) is either resolved using large eddy simulation (LES) or modeled using the standard k–ω model, Spalart–Allmaras (SA) model, etc. The immersed boundary method with smeared geometry (immersed boundary method with smeared geometry (IBMSG)) is employed to represent the effect of the fan and a wide range of test cases is studied by varying the (a) height of the DG and (b) proximity of the fan to the DG. Comparisons are drawn between the LES and the Reynolds-averaged Navier–Stokes (RANS) approaches with/without the fan effect. It is found that in the “absence of fan,” the discrepancies between RANS and LES are significant within the separation and reattachment region due to the well-known limitations of the standard RANS models. “With the fan installed,” the deviation between RANS and LES decreases substantially. It becomes minimal when the fan is closest to the DG. It implies that with an installed fan, the inaccuracies of the turbulence model are mitigated by the strong flow acceleration at the casing due to the fan. More precisely, the mass flow redistribution due to the fan has a dominant primary effect on the final predictions and the effect of turbulence model becomes secondary, thereby suggesting that high fidelity eddy resolving simulations provide marginal improvements to the accuracy for the installed cases, particularly for the short intake–fan strategies with fan getting closer to intake lip.

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Grahic Jump Location
Fig. 1

Parametric studies with varying ((b), (c), and (e)) heights of distortion generator ((b), (d), and (f)) fan-location. Nomenclature given here for each case will be followed throughout the paper.

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Fig. 2

Computational setup and boundary conditions of the Darmstadt rotor

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Fig. 3

Performance map of the Darmstadt rotor at 65% rotating speed (SC: smooth casing, B120: 120 deg beam)

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Fig. 4

Circumferential variation of total pressure distribution for 65% speed, monitored at (a) rotor inlet, (b) rotor outlet, and (c) stator outlet

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Fig. 5

Radial variation of mass flux at x = 4.5H, using IBMSG and geometry resolved approach. Fan placed at location 0.

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Fig. 6

Mesh sensitivity study from LES showing the radial variation of (a) velocity and (b) TKE at x = 4.5H, for the case duct H without

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Fig. 7

Carpet plots comparing the (a) velocity profiles and (b) TKE profiles between RANS and LES for the case duct, H (without fan)

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Fig. 8

Comparison of TKE profiles obtained from LES against the RANS (with frozen velocity field from LES), for the case duct H without fan

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Fig. 9

Radial variation of mass flux with and without fan

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Fig. 10

Carpet plot showing the velocity profiles with and without fan. Locus of inflection points is also overlaid. Dash-dotted line corresponds to fan leading edge location.

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Fig. 11

Carpet plots comparing velocity profiles predicted by RANS against LES for a given distortion generator of height, H and varying fan locations: cases (a) Loc 0, (b) Loc 1, and (c) Loc 2

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Fig. 12

Radial distributions of (a) total pressure ratio, (b) acceleration parameter, and (c) angle of incidence predicted by RANS and LES at x = 4.5H. Cases compared for same beam height, H and varying fan location: Loc0, Loc1, Loc2. Test case without fan (duct, H) is also shown.

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Fig. 13

Carpet plots comparing the velocity profiles predicted by RANS and LES for a given fan-location Loc0 and varying beam heights (a) H, (b) H/2, and (c) H/4

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Fig. 14

Radial distributions of (a) total pressure ratio, (b) acceleration parameter, and (c) angle of incidence predicted by RANS and LES at x = 4.5H. Cases compared for same fan location, Loc0 and varying beam heights: H, H/2, H/4.

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Fig. 15

Variation of maximum discrepancy in d theta (typically observed at the casing) with acceleration parameter for all the test cases with varying fan locations and beam heights

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Fig. 16

Carpet plot comparing the prediction of TKE from LES against kω SST model for case Loc0, H

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Fig. 17

Carpet plot showing LES predictions of (a) velocity profiles and (b) TKE profiles at two different Reynolds numbers for case Loc0, H



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