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Research Papers: Gas Turbines: Structures and Dynamics

Mistuning Effects on Aero-elastic Stability of Axial Compressor Rotor Blades

[+] Author and Article Information
Yanrong Wang

Collaborative Innovation Center
for Advanced Aero-Engine,
School of Energy and Power Engineering,
Beihang University,
37 Xueyuan Road, Haidian District,
Beijing 100191, China
e-mail: yrwang@buaa.edu.cn

Zhizhong Fu

Collaborative Innovation Center
for Advanced Aero-Engine,
School of Energy and Power Engineering,
Beihang University,
37 Xueyuan Road, Haidian District,
Beijing 100191, China
e-mail: buaaxiaochuang@163.com

Xianghua Jiang

Collaborative Innovation Center
for Advanced Aero-Engine,
School of Energy and Power Engineering,
Beihang University,
37 Xueyuan Road, Haidian District,
Beijing 100191, China
e-mail: jxh@buaa.edu.cn

Aimei Tian

School of Astronautics,
Beijing University of Aeronautics and Astronautics,
37 Xueyuan Road, Haidian District,
Beijing 100191, China
e-mail: amtian@buaa.edu.cn

1Corresponding author.

Contributed by the Structures and Dynamics Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received February 13, 2015; final manuscript received March 18, 2015; published online May 6, 2015. Editor: David Wisler.

J. Eng. Gas Turbines Power 137(10), 102504 (Oct 01, 2015) (12 pages) Paper No: GTP-15-1045; doi: 10.1115/1.4030280 History: Received February 13, 2015; Revised March 18, 2015; Online May 06, 2015

The mistuning effects on the aero-elastic stability of axial compressor rotor blades have been investigated by employing aero-elastic eigenvalue method. An axial compressor rotor suffered from flutter failure has been analyzed with four intentional mistuning patterns and their sensitivities to random mistuning. Through a comparison of four intentional mistuning patterns, the mistuning mechanism of improving aero-elastic stability may be understood from the combining effects of frequency offset and the destruction of periodicity by the introduction of mistuning. Increasing the amount of alternate mistuning cannot provide any additional improving effects on the aero-elastic stability when the mistuning amount reaches a critical value. However, the further mistuning effects can be obtained by placing several groups (isolation zone) with additional frequency offset relative to the alternately mistuned system. The random mistuning can always improve the aero-elastic stability of the tuned system. However, for the intentionally mistuned system, the inclusion of random mistuning with a small level may weaken the improving effects of intentional mistuning and even makes the system unstable.

Copyright © 2015 by ASME
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References

Petrov, E. P., 2011, “Reduction of Forced Response Levels for Bladed Disks by Mistuning: Overview of the Phenomenon,” ASME J. Gas Turbines Power, 133(7), p. 072501. [CrossRef]
Castanier, M. P., and Pierre, C., 2006, “Modeling and Analysis of Mistuned Bladed Disk Vibration: Status and Emerging Directions,” J. Propul. Power, 22(2), pp. 384–396. [CrossRef]
Yang, M. T., and Griffin, J. H., 2001, “A Reduced-Order Model of Mistuning Using a Subset of Nominal System Modes,” ASME J. Gas Turbines Power, 123(4), pp. 893–900. [CrossRef]
Lim, S.-H., Bladh, R., Castanier, M. P., and Pierre, C., 2007, “Compact, Generalized Component Mode Mistuning Representation for Modeling Bladed Disk Vibration,” AIAA J., 45(9), pp. 2285–2298. [CrossRef]
Martel, C., and Corral, R., 2009, “Asymptotic Description of Maximum Mistuning Amplification of Bladed Disk Forced Response,” ASME J. Gas Turbines Power, 131(2), p. 022506. [CrossRef]
Whitehead, D. S., 1966, “Effect of Mistuning on the Vibration of Turbo-Machine Blades Induced by Wakes,” J. Mech. Eng. Sci., 8(1), pp. 15–21. [CrossRef]
Zhai, Y., Bladh, R., and Dyverfeldt, G., 2012, “Aeroelastic Stability Assessment of an Industrial Compressor Blade Including Mistuning Effects,” ASME J. Turbomach., 134(6), p. 060903. [CrossRef]
Bendiksen, O. O., 1984, “Flutter of Mistuned Turbomachinery Rotors,” ASME J. Gas Turbines Power, 106(1), pp. 25–33. [CrossRef]
Crawley, E. F., 1988, “Aeroelastic Formulation for Tuned and Mistuned Rotors,” Structural Dynamics and Aeroelasticity (AGARD Manual on Aeroelasticity in Axial-Flow Turbines, Vol. 2), AGARD-AG-298, AGARD, Neuilly sur Seine, France, Chap. 19.
Kielb, R. E., Feiner, D. M., Griffin, J. H., and Miyakozawa, T., 2004, “Flutter of Mistuned Bladed Disks and Blisks With Aerodynamic and FMM Structural Coupling,” ASME Paper No. GT2004-54315 [CrossRef].
Hanamura, Y., Tanaka, H., and Yamaguchi, K., 1980, “A Simplified Method to Measure Unsteady Forces Acting on the Vibrating Blades in Cascade,” Bull. JSME, 23(180), pp. 880–887. [CrossRef]
Choi, Y. S., Gottfried, D. A., and Fleeter, S., 2010, “Resonant Response of Mistuned Bladed Disks Including Aerodynamic Damping Effects,” J. Propul. Power, 26(1), pp. 16–24. [CrossRef]
Hsu, K., and Hoyniak, D., 2011, “A Fast Influence Coefficient Method for Linearized Flutter and Forced-Response Analysis,” AIAA Paper No. 2011-229. [CrossRef]
Fu, Z. Z., Wang, Y. R., Jiang, X. H., and Wei, D. S., 2015, “Tip Clearance Effects on Aero-Elastic Stability of Axial Compressor Blades,” ASME J. Gas Turbines Power, 137(1), p. 012501. [CrossRef]
Zhang, X., Wang, Y., and Xu, K., 2013, “Mechanisms and Key Parameters for Compressor Blade Stall Flutter,” ASME J. Turbomach., 135(2), p. 024501. [CrossRef]
Zhang, X. W., Wang, Y. R., and Xu, K. N., 2011, “Flutter Prediction in Turbomachinery With Energy Method,” Proc. Inst. Mech. Eng., Part G, 225(9), pp. 995–1002. [CrossRef]
Song, Z. H., 1993, Typical Failure Analysis of Aeroengine and Its Components, Beijing University of Aeronautics and Astronautics Press, Beijing (in Chinese).
Zhang, X. W., 2011, “Numerical Prediction Method for Aeroelastic Stability of Blades in Turbomachines,” Ph.D. thesis, Beijing University of Aeronautics and Astronautics, Beijing (in Chinese).

Figures

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Fig. 1

The sketch of blade cascade

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Fig. 2

9-passage fluid model

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Fig. 3

The curve of pressure at point 1 versus time

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Fig. 4

Aerodynamic force amplitude contours of different passage models: (a) pressure surface of 5-passage model, (b) suction surface of 5-passage model, (c) pressure surface of 7-passage model, (d) suction surface of 7-passage model, (e) pressure surface of 9-passage model, and (f) suction surface of 9-passage model

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Fig. 5

The obtained aerodynamic influence coefficients from different fluid models: (a) amplitude and (b) phase angle

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Fig. 6

AMDR of different passage models and energy method

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Fig. 7

The eigenvalue distribution of tuned system

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Fig. 8

Four intentional mistuning patterns: (a) mistuning 1, (b) mistuning 2, (c) mistuning 3, and (d) mistuning 4

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Fig. 9

Pattern of 1B frequency difference arrangement for mistuning 4

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Fig. 10

Variations of real parts of the maximum and minimum eigenvalue versus mistuning amount for alternate pattern

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Fig. 11

Eigenvalue distributions of tuned and mistuned systems

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Fig. 12

Distribution of frequency offset for the base system with 1.5% mistuning amount

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Fig. 13

One percent frequency offset of isolation zone relative to the base system: (a) 1 isolation zone, (b) 2 isolation zones, (c) 3 isolation zones, (d) 4 isolation zones, and (e) 5 isolation zones

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Fig. 14

Effects of isolation zone number on aero-elastic eigenvalues. (a) The maximum real part of eigenvalues and (b) the minimum real part of eigenvalues.

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Fig. 15

Effects of frequency offset of isolation zone on eigenvalues for the AMIZ mistuned system with 3 isolation zones. (a) The maximum real part of eigenvalues and (b) the minimum real part of eigenvalues.

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Fig. 16

Flutter probability of randomly mistuned system: (a) 10,000 simulations at each standard deviation level and (b) 100,000 simulations at each standard deviation level

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Fig. 17

Probability density distribution of the maximum real part of eigenvalues for intentionally mistuned systems: (a) mistuning 1, (b) mistuning 2, (c) mistuning 3, and (d) mistuning 4

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