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Research Papers

The Whole Annulus Computations of Particulate Flow and Erosion in an Axial Fan

[+] Author and Article Information
Joan Boulanger

Gas Turbine Laboratory,
Institute for Aerospace Research,
National Research Council Canada (NRC),
Ottawa, Ontario, Canada K1A 0R6

1Corresponding author.

2Currently at: Bombardier Aerospace, St-Laurent, Quebec, Canada H4S 2A9.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received August 6, 2011; final manuscript received September 4, 2011; published online October 31, 2012. Editor: David Wisler.

J. Turbomach 135(1), 011040 (Oct 31, 2012) (8 pages) Paper No: TURBO-11-1177; doi: 10.1115/1.4006564 History: Received August 06, 2011; Revised September 04, 2011

Gas turbine engines operating in a hostile environment, polluted with sand or dust particles, are susceptible to erosion damage, mostly at the front axial fans and compressors. Accurately predicting the erosion pattern and rate due to sand ingestion is one of the major challenges faced by the transportation and power industries. Maintenance costs are scrutinized and intensive research efforts are currently deployed in predictive life assessment tools to minimize the overhaul down time. The conventional prediction methods were usually based on steady-state simulations of gas-phase flows through a single blade passage per blade row to reduce the computational cost. However, the multistage turbomachinery flows are intrinsically subject to unsteadiness, especially due to stator-rotor interactions, which may affect sand particle trajectories even if a one-way coupling method is considered. Furthermore, an unsteady stator-rotor interaction requires a whole-annulus model at great computational cost to avoid simplifications of the geometries or flow physics. To study the effects of the stator-rotor interaction on sand particle trajectories and erosion, an axial fan with inlet guide vanes is investigated, based on the whole annulus computations of both steady and unsteady gas-phase flows, each of which is then followed by a Lagrangian particle tracking step. A numerical algorithm for tracking particles driven by the unsteady gas-phase flow is presented. The comparison of the numerical predictions with the experimental data confirms the validity and necessity of the unsteady computational fluid dynamics (CFD) model in providing adequate predictions of sand erosion in the axial fan.

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References

Figures

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Fig. 1

Comparison of the predicted penetration rate with the data of Eyler [16] (all predictions use the same erosion model from Ahlert [28] but different rebound correlations)

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Fig. 2

Comparison of the predicted penetration rate with the data of Eyler [16] (both predictions use the rebound correlation from Forder et al. [26])

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Fig. 3

Penetration-rate contours and particle trajectories in the elbow (with the erosion model of Ahlert [28] and the rebound model of Forder et al. [26])

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Fig. 4

The axial fan unit from Cranfield University: (a) configuration and surface mesh, and (b) unstructured mesh around the blades and at the interface (mesh size: 2.809 M cells)

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Fig. 5

Comparison of the performance map for the axial fan stage at a rotational speed of 11,300 rpm

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Fig. 6

Computing history of the mass flow rate: (a) averaged mass flow rate versus rotational periods, and (b) instantaneous mass flow rate for the last two periods

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Fig. 7

FFT spectrum of the unsteady mass flow rate at the sliding mesh interface

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Fig. 8

Instantaneous turbulent viscosity contours at the mid-span: (a) t = t0, and (b) t = t0 + Tr/32

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Fig. 9

The computed average erosion rates on the rotor and the IGV blades versus the numbers of computed particles (mid concentration)

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Fig. 10

Tip clearance increase with running time: (a) unsteady model, and (b) steady model

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Fig. 11

Tip chord reduction with running time: (a) unsteady model, and (b) steady model

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Fig. 12

Comparison of the erosion pattern on the rotor blades: (a) photograph of the erosion by experiment [1], and (b) erosion rate predicted with the unsteady model (high concentration)

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Fig. 13

Particle trajectories in the absolute frame of reference at the mid concentration with the unsteady model (the casing wall is removed for clarity)

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Fig. 14

A particle path-line to demonstrate the particle impingement onto the casing and rotor pressure surface, with the unsteady model (impingement points are denoted by black spots)

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