Novel parametric reduced order model for aeroengine blade dynamics
Novel parametric reduced order model for aeroengine blade dynamics
The work introduces a novel reduced order model (ROM) technique to describe the dynamic behavior of turbofan aeroengine blades. We introduce an equivalent 3D frame model to describe the coupled flexural/torsional mode shapes, with their relevant natural frequencies and associated modal masses. The frame configurations are identified through a structural identification approach based on a simulated annealing algorithm with stochastic tunneling. The cost functions are constituted by linear combinations of relative errors associated to the resonance frequencies, the individual modal assurance criteria (MAC), and on either overall static or modal masses. When static masses are considered the optimized 3D frame can represent the blade dynamic behavior with an 8% error on the MAC, a 1% error on the associated modal frequencies and a 1% error on the overall static mass. When using modal masses in the cost function the performance of the ROM is similar, but the overall error increases to 7%. The approach proposed in this paper is considerably more accurate than state-of-the-art blade ROMs based on traditional Timoshenko beams, and provides excellent accuracy at reduced computational time when compared against high fidelity FE models. A sensitivity analysis shows that the proposed model can adequately predict the global trends of the variations of the natural frequencies when lumped masses are used for mistuning analysis. The proposed ROM also follows extremely closely the sensitivity of the high fidelity finite element models when the material parameters are used in the sensitivity.
235-253
Yuan, J.
4bcf9ce8-3af4-4009-9cd0-067521894797
Allegri, G.
8dd43a78-5f53-472f-853a-1b2fd7b129e4
Scarpa, F.
684472c3-1a28-478a-a388-5fd896986c1d
Rajasekaran, R.
c5f6d9b9-8517-49e1-afc5-5830d2d1390d
Patsias, S.
e7e4a982-00c2-4025-ba71-32c101489b7c
October 2015
Yuan, J.
4bcf9ce8-3af4-4009-9cd0-067521894797
Allegri, G.
8dd43a78-5f53-472f-853a-1b2fd7b129e4
Scarpa, F.
684472c3-1a28-478a-a388-5fd896986c1d
Rajasekaran, R.
c5f6d9b9-8517-49e1-afc5-5830d2d1390d
Patsias, S.
e7e4a982-00c2-4025-ba71-32c101489b7c
Yuan, J., Allegri, G., Scarpa, F., Rajasekaran, R. and Patsias, S.
(2015)
Novel parametric reduced order model for aeroengine blade dynamics.
Mechanical Systems and Signal Processing, 62-63, .
(doi:10.1016/j.ymssp.2015.02.015).
Abstract
The work introduces a novel reduced order model (ROM) technique to describe the dynamic behavior of turbofan aeroengine blades. We introduce an equivalent 3D frame model to describe the coupled flexural/torsional mode shapes, with their relevant natural frequencies and associated modal masses. The frame configurations are identified through a structural identification approach based on a simulated annealing algorithm with stochastic tunneling. The cost functions are constituted by linear combinations of relative errors associated to the resonance frequencies, the individual modal assurance criteria (MAC), and on either overall static or modal masses. When static masses are considered the optimized 3D frame can represent the blade dynamic behavior with an 8% error on the MAC, a 1% error on the associated modal frequencies and a 1% error on the overall static mass. When using modal masses in the cost function the performance of the ROM is similar, but the overall error increases to 7%. The approach proposed in this paper is considerably more accurate than state-of-the-art blade ROMs based on traditional Timoshenko beams, and provides excellent accuracy at reduced computational time when compared against high fidelity FE models. A sensitivity analysis shows that the proposed model can adequately predict the global trends of the variations of the natural frequencies when lumped masses are used for mistuning analysis. The proposed ROM also follows extremely closely the sensitivity of the high fidelity finite element models when the material parameters are used in the sensitivity.
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Accepted/In Press date: 15 February 2015
e-pub ahead of print date: 3 May 2015
Published date: October 2015
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Local EPrints ID: 479124
URI: http://eprints.soton.ac.uk/id/eprint/479124
ISSN: 0888-3270
PURE UUID: 724ff74e-a27e-4d1a-bcbf-89c09f0c015a
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Date deposited: 20 Jul 2023 16:36
Last modified: 17 Mar 2024 04:20
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Author:
J. Yuan
Author:
G. Allegri
Author:
F. Scarpa
Author:
R. Rajasekaran
Author:
S. Patsias
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