Research Papers

Hybrid LES Approach for Practical Turbomachinery Flows—Part I: Hierarchy and Example Simulations

[+] Author and Article Information
Paul Tucker1

Department of Engineering, Whittle Laboratory, University of Cambridge, CB3 0DY, Cambridge, United Kingdom

Simon Eastwood, Christian Klostermeier, Richard Jefferson-Loveday, James Tyacke, Yan Liu

Department of Engineering, Whittle Laboratory, University of Cambridge, CB3 0DY, Cambridge, United Kingdom


Corresponding author.

J. Turbomach 134(2), 021023 (Jul 07, 2011) (10 pages) doi:10.1115/1.4003061 History: Received July 02, 2010; Revised July 30, 2010; Published July 07, 2011; Online July 07, 2011

Unlike Reynolds-averaged Navier–Stokes (RANS) models that need calibration for different flow classes, LES (where larger turbulent structures are resolved by the grid and smaller modeled in a fashion reminiscent of RANS) offers the opportunity to resolve geometry dependent turbulence as found in complex internal flows—albeit at substantially higher computational cost. Based on the results for a broad range of studies involving different numerical schemes, large eddy simulation (LES) models and grid topologies, an LES hierarchy and hybrid LES related approach is proposed. With the latter, away from walls, no LES model is used, giving what can be termed numerical LES (NLES). This is relatively computationally efficient and makes use of the dissipation present in practical industrial computational fluid dynamics (CFD) programs. Near walls, RANS modeling is used to cover over numerous small structures, the LES resolution of which is generally intractable with current computational power. The linking of the RANS and NLES zones through a Hamilton–Jacobi equation is advocated. The RANS-NLES hybridization makes further sense for compressible flow solvers, where, as the Mach number tends to zero at walls, excessive dissipation can occur. The hybrid strategy is used to predict flow over a rib roughened surface and a jet impinging on a convex surface. These cases are important for blade cooling and show encouraging results. Further results are presented in a companion paper.

Copyright © 2012 by American Society of Mechanical Engineers
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Figure 8

Variation of amplitude and phase error with M for a subcritical T-S wave

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Figure 9

Industrial turbomachinery LES hierarchy

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Figure 10

Potential blending of distance function between RANS and NLES region

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Figure 11

Schematic of the ribbed channel configuration

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Figure 12

Heat transfer along a ribbed channel for different RANS models

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Figure 13

Mid x-y plane particle paths: (a) from instantaneous flow and (b) from time-averaged flow

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Figure 14

Local Nu distributions (dashed line hybrid NLES-RANS, О measurements)

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Figure 15

Estimation of κ−5/3 region: (a) energy spectra based on R and (b) R-field contours

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Figure 1

Grid requirements against Rec for y+<100 and y+>100 (after Piomelli and Balaras (17))

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Figure 2

LES grid requirements in different zones for a medium-sized gas turbine (after Mayle (22))

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Figure 3

Sensitivity to LES model and numerical scheme for homogeneous decaying turbulence: (a) solution for different LES models and (b) solutions for a different numerical parameter settings

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Figure 4

Peak shear stress in a shear layer for hybrid RANS-NLES and different Ti

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Figure 5

Law of the wall for under-resolved LES grids

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Figure 6

Decay of cross-stream velocity perturbation for a subcritical T-S wave

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Figure 7

Control volume form for poorly performing grid

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Figure 16

Schematic of the jet impingement onto a concave hemisphere

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Figure 17

Time-averaged distributions on concave surface (dashed line NLES-RANS, О measurements): ((a) and (b)) radial variation of wall pressure coefficient and ((c) and (d)) radial distribution of Nu

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Figure 18

Vorticity magnitude contours for jet impingement onto a concave surface




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