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Research Papers

On the Importance of Engine-Representative Models for Fan Flutter Predictions

[+] Author and Article Information
Sina Stapelfeldt

Vibration University Technology Centre,
Mechanical Engineering Department,
Imperial College London,
London SW7 2AZ, UK
e-mail: sina.stapelfeldt@ic.ac.uk

Mehdi Vahdati

Vibration University Technology Centre,
Mechanical Engineering Department,
Imperial College London,
London SW7 2AZ, UK
e-mail: m.vahdati@ic.ac.uk

1Corresponding author.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received November 7, 2017; final manuscript received November 17, 2017; published online July 26, 2018. Editor: Kenneth Hall.

J. Turbomach 140(8), 081005 (Jul 26, 2018) (10 pages) Paper No: TURBO-17-1209; doi: 10.1115/1.4040110 History: Received November 07, 2017; Revised November 17, 2017

Discrepancies between rig tests and numerical predictions of the flutter boundary for fan blades are usually attributed to the deficiency of computational fluid dynamics (CFD) models for resolving flow at off-design conditions. However, as will be demonstrated in this paper, there are a number of other factors, which can influence the flutter stability of fan blades and lead to differences between measurements and numerical predictions. This research was initiated as a result of inconsistencies between the flutter predictions of two rig fan blades. The numerical results agreed well with rig test data in terms of flutter speed and nodal diameter (ND) for both fans. However, they predicted a significantly higher flutter margin for one of the fans, while measured flutter margins were similar for both blades. A new set of flutter computations including the whole low-pressure system was therefore performed. The new set of computations considered the effects of the acoustic liner and mistuning for both blades. The results of this work indicate that the previous discrepancies between CFD and tests were caused by, first, differences in the effectiveness of the acoustic liner in attenuating the pressure wave created by the blade vibration and second, differences in the level of unintentional mistuning of the two fan blades. In the second part of this research, the effects of blade mis-staggering and inlet temperature on aerodynamic damping were investigated. The data presented in this paper clearly show that manufacturing and environmental uncertainties can play an important role in the flutter stability of a fan blade. They demonstrate that aeroelastic similarity is not necessarily achieved if only aerodynamic properties and the traditional aeroelastic parameters, reduced frequency and mass ratio, are maintained. This emphasizes the importance of engine-representative models, in addition to accurate and validated CFD codes, for the reliable prediction of the flutter boundary.

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References

Lane, F. , 1956, “ System Mode Shapes in the Flutter of Compressor Blade Rows,” J. Aeronaut. Sci., 23(1), pp. 54–66. [CrossRef]
Carta, F. O. , 1967, “ Coupled Blade-Disk-Shroud Flutter Instabilities in Turbojet Engine Rotors,” J. Eng. Power, 89(3), pp. 419–426.
Jeffers, J. , and Meece, C. , 1975, “ F100 Fan Stall Flutter Problem Review and Solution,” J. Aircr., 12(4), pp. 350–357. [CrossRef]
Chi, R. , and Srinivasan, A. , 1985, “ Some Recent Advances in the Understanding and Prediction of Turbomachine Subsonic Stall Flutter,” ASME J. Eng. Gas Turbines Power, 107(2), pp. 408–417. [CrossRef]
Marshall, J. , and Imregun, M. , 1996, “ A Review of Aeroelasticity Methods With Emphasis on Turbomachinery Applications,” J. Fluids Struct., 10(3), pp. 237–267. [CrossRef]
Srinivasan, A. V. , 1997, “ Flutter and Resonant Vibration Characteristics of Engine Blades,” ASME J. Eng. Gas Turbines Power, 119(4), pp. 742–775. [CrossRef]
Khalak, A. , 2002, “ A Framework for Flutter Clearance of Aeroengine Blades,” ASME J. Eng. Gas Turbines Power, 124(4), pp. 1003–1010. [CrossRef]
Isomura, K. , and Giles, M. , 1998, “ A Numerical Study of Flutter in a Transonic Fan,” ASME J. Turbomach., 120(3), pp. 500–507. [CrossRef]
di Mare, L. , Vadati, M. , Mueck, B. , Smith, N. H. , and Birch, N. , 2009, “ Aeroelastic Instability of Fan Blades at High Altitudes,” ASME Paper No. GT2009-60091.
Vahdati, M. , and Cumpsty, N. , 2015, “ Aeroelastic Instability in Transonic Fans,” ASME J. Eng. Gas Turbines Power, 138(2), p. 022604. [CrossRef]
Panovsky, J. , and Kielb, R. E. , 1998, “ A Design Method to Prevent Low Pressure Turbine Blade Flutter,” ASME Paper No. 98-GT-575.
Sayma, A. I. , Vahdati, M. , and Imregun, M. , 2000, “ An Integrated Non Linear Approach for Turbomachinery Forced Response Prediction—Part 1: Formulation,” J. Fluids Struct., 14(1), pp. 87–101. [CrossRef]
Lee, K.-B. , Wilson, M. , and Vahdati, M. , 2016, “ Numerical Study on Aeroelastic Instability for a Low Speed Fan,” ASME Paper No. GT2016-56462.
Salles, L. , and Vahdati, M. , 2016, “ Comparison of Two Numerical Algorithms for Computing the Effects of Mistuning of Fan Flutter,” ASME Paper No. GT2016-57324.
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Figures

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Fig. 1

Typical fan map and the flutter boundary (flutter bite)

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Fig. 3

Comparison of AU3D and measured characteristics at Mtip = 0.91 and Mtip = 0.97 for F1 and F2: (a) fan 1 and (b) fan 2

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Fig. 2

Deflection amplitude in first flap (1F) mode for fan F1 and fan F2

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Fig. 12

Measured mistuning patterns for F1 and F2

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Fig. 6

Streamlines and Mach number for F2 at different speeds and constant exit throttle: (a) Mtip = 0.82, (b) Mtip = 0.84, (c) Mtip = 0.87, and (d) = Mtip = 0.89

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Fig. 5

Streamlines and Mach number for fan F2 at Mtip = 0.91: (a) mref = 0.97, (b) mref = 0.95, (c) mref = 0.93, and (d) mref = 0.91

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Fig. 4

Streamlines and Mach number for fan F1 at Mtip = 0.91: (a) mref = 0.97, (b) mref = 0.95, (c) mref = 0.93, and (d) mref = 0.91

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Fig. 9

Flutter boundary with lined wall for F1 and F2

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Fig. 10

Effects of acoustic liner for F1—damping is plotted for the points along HWL (see Fig. 7)

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Fig. 11

Effects of acoustic liner for F2—damping is plotted for the points along HWL (see Fig. 8)

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Fig. 7

Fan map and flutter boundary for F1

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Fig. 8

Fan map and flutter boundary for F2

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Fig. 13

Predicted flutter boundary for F1 using different amount of mistuning: mistuning 1 ≈ F1 mistuning level, mistuning 2 ≈ F2 mistuning level

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Fig. 14

Speedline and aerodamping (1F/2ND) for symmetric assembly (F1): (a) speedline and (b) aerodamping

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Fig. 15

Mis-stagger pattern

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Fig. 16

Variation of aerodamping with mis-stagger amplitude for random mis-staggering pattern

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Fig. 17

Streamlines on mis-staggered assembly

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Fig. 18

Variation of aerodamping with mis-stagger amplitude for the alternate mis-staggering pattern

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Fig. 19

Streamlines for different mass flow and levels of mistuning: (a) mref = 0.93 ms = 0.2, (b) mref = 0.93 ms = 0.6, (c) mref = 0.95 ms = 0.3, and (d) mref = 0.95 ms = 0.7

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Fig. 20

Unsteady forcing in different nodal diameters for mref = 0.93

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Fig. 22

Removal of temperature dependence through scaling

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Fig. 23

Variation of aero-damping with aero speed for different temperatures (with intake)

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Fig. 21

Variation of aero-damping with vibration frequency for different temperatures (without intake)

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