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Research Papers: Gas Turbines: Structures and Dynamics

Reduced Order Modeling of a Bladed Rotor With Geometric Mistuning Via Estimated Deviations in Mass and Stiffness Matrices

[+] Author and Article Information
Yasharth Bhartiya

e-mail: yasharth@gmail.com

Alok Sinha

e-mail: axs22@psu.edu
Department of Mechanical and Nuclear Engineering,
The Pennsylvania State University,
University Park, PA 16802

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the Journal of Engineering for Gas Turbines and Power. Manuscript received September 26, 2011; final manuscript received July 26, 2012; published online April 18, 2013. Assoc. Editor: Jaroslaw Szwedowicz.

J. Eng. Gas Turbines Power 135(5), 052501 (Apr 18, 2013) (8 pages) Paper No: GTP-11-1320; doi: 10.1115/1.4007783 History: Received September 26, 2011; Revised July 26, 2012

This paper deals with further development of modified modal domain analysis (MMDA), which is a breakthrough method in the reduced order modeling of a bladed rotor with geometric mistuning. The main focus of this paper is to show that deviations in mass and stiffness matrices due to mistuning, estimated by Taylor series expansions in terms of independent proper orthogonal decomposition variables representing geometric variations of blades, can be used for MMDA. This result has rendered Monte Carlo simulation of the response of a bladed rotor with geometric mistuning to be easy and computationally efficient.

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References

Figures

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Fig. 2

POD features #1 and #2

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Fig. 3

Mistuning pattern for POD 1

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Fig. 4

Deviations in natural frequencies (POD #1 only) represented as percentages of corresponding tuned frequencies

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Fig. 5

Errors (%) in deviations of natural frequencies (POD #1 only)

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Fig. 6

MAC Values for (a) Case 1 (first order approximation) and (b) Case 2 (second order approximation), POD #1 only

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Fig. 7

Mistuning pattern for POD #2

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Fig. 8

Deviations in natural frequencies (two POD features, Case 2) represented as percentages of corresponding tuned frequencies

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Fig. 9

MAC Values for MMDA with 2 POD features (Case 2, second order approximation)

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Fig. 10

Comparison of nondimensional maximum amplitudes from ansys and MMDA using the first order approx. (Case 1) and the second order approx. (Case 2), POD #1 only

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Fig. 11

Comparison of nondimensional maximum amplitudes from ansys and MMDA using first order approx. (Case 1) and second order approx. (Case 2), both POD features

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Fig. 12

Distribution of first natural frequencies

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Fig. 13

Distribution of 24th natural frequencies

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Fig. 14

Distribution of peak maximum amplitudes

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