Research Papers

Prediction of Ingress Through Turbine Rim Seals—Part I: Externally Induced Ingress

[+] Author and Article Information
J. Michael Owen

Department of Mechanical Engineering, University of Bath, Bath BA2 7AY, UKensjmo@bath.ac.uk

Kunyuan Zhou

School of Jet Propulsion, Beihang University, Beijing 100191, China

Oliver Pountney, Mike Wilson, Gary Lock

Department of Mechanical Engineering, University of Bath, Bath BA2 7AY, UK

J. Turbomach 134(3), 031012 (Jul 15, 2011) (13 pages) doi:10.1115/1.4003070 History: Received July 14, 2010; Revised July 22, 2010; Published July 15, 2011; Online July 15, 2011

Rotationally induced (RI) ingress is caused by the negative pressure (relative to the external air) inside the wheel-space of a gas turbine; this negative pressure, which is created by the rotating flow in the wheel-space, drives the ingestion of hot gas through the rim seals. Externally induced (EI) ingress is caused by the circumferential distribution of pressure created by the blades and vanes in the turbine annulus: Ingress occurs in those regions where the external pressure is higher than that in the wheel-space, and egress occurs where it is lower. Although EI ingress is the dominant mechanism for hot-gas ingestion in engines, there are some conditions in which RI ingress has an influence: This is referred to as combined ingress (CI). In Part I of this two-part paper, values of the sealing effectiveness (obtained using the incompressible orifice equations developed for EI ingress in an earlier paper) are compared with published experimental data and with the results obtained using 3D steady compressible computational fluid dynamics (CFD). Acceptable limits of the incompressible-flow assumption are quantified for the orifice model; For the CFD, even though the Mach number in the annulus reaches approximately 0.65, it is shown that the incompressible orifice equations are still valid. The results confirm that EI ingress is caused predominantly by the magnitude of the peak-to-trough circumferential difference of pressure in the annulus; the shape of the pressure distribution is of secondary importance for the prediction of ingress. A simple equation, derived from the orifice model, provides a very good correlation of the computed values of effectiveness. Using this correlation, it is possible to estimate the minimum sealing flow rate to prevent ingress without the need to know anything about the pressure distribution in the annulus; this makes the orifice model a powerful tool for rim-seal design.

Copyright © 2012 by American Society of Mechanical Engineers
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Figure 1

Typical rim-sealing arrangement used in gas turbines. (a) High-pressure turbine stage. (b) Schematic of rim sea and wheel-space.

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Figure 2

Simplified diagram of ingress and egress through an axial-clearance rim seal

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Figure 3

Variation of Cw,min with Cp,max(11) (symbols represent experimental data; lines correspond to correlations)

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Figure 4

Schematic of orifice model (1)

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Figure 5

Effect of Cd,i/Cd,e on variation of ε with Cw,o predicted by orifice model (2). Solid line, EI ingress; dashed line, RI ingress.

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Figure 6

Variation of f, the pressure shape factor, with θ, the angular location in the annulus, based on data of Johnson (12): (a) Conf and (b) Conf 1c

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Figure 7

Variation of ε, the sealing effectiveness, with Φo, where Φo=Cw,o/2πGc Reϕ (symbols represent corners of envelope of experimental data given by Johnson (12)): (a) Conf 1a and (b) Conf 1c

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Figure 8

Illustration of computational geometry (not to scale)

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Figure 9

Computational mesh with detail of generic vane profile and clearance region for “thin-seal” model

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Figure 10

Computed flow structure and concentration inside wheel-space: Reϕ/106=1.03, Cw,o/104=1.69: (a) flow structure and (b) concentration contours

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Figure 11

Comparison between computed and theoretical variation of effectiveness with nondimensional sealing flow rate for Reϕ=1.03×106, Gc=0.01. (Φo=Cw,o/2πGc Reϕ and Γc=Cd,i/Cd,e=0.35 is the optimum value for the saw-tooth model.)

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Figure 12

Contours of ΔCp computed inside annulus for Φo=0

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Figure 13

Computed variation of pressure shape factor f with θ inside annulus at x=0.93, y=0

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Figure 14

Circumferential distribution of pressure and radial velocity for saw-tooth model (2): (a) circumferential distribution of p1 and p2, and (b) circumferential distribution of Vr

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Figure 15

Contours of nondimensional pressure g computed inside annulus for Φo=0. (Dotted line corresponds to contour of g∗=0.332.)

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Figure 16

Close-up of contours of ΔCp computed near seal clearance for Φo=0. (Dotted line corresponds to locus of g∗=0.332.)





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