0
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
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Figure 1

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

Grahic Jump Location
Figure 2

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

Grahic Jump Location
Figure 3

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

Grahic Jump Location
Figure 4

Schematic of orifice model (1)

Grahic Jump Location
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.

Grahic Jump Location
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

Grahic Jump Location
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

Grahic Jump Location
Figure 8

Illustration of computational geometry (not to scale)

Grahic Jump Location
Figure 9

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

Grahic Jump Location
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

Grahic Jump Location
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.)

Grahic Jump Location
Figure 12

Contours of ΔCp computed inside annulus for Φo=0

Grahic Jump Location
Figure 13

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

Grahic Jump Location
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

Grahic Jump Location
Figure 15

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

Grahic Jump Location
Figure 16

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

Tables

Errata

Discussions

Related

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In