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Numerical assessment of using sherman-morrison, neumann expansion techniques for stochastic analysis of mistuned bladed disc systems

Numerical assessment of using sherman-morrison, neumann expansion techniques for stochastic analysis of mistuned bladed disc systems
Numerical assessment of using sherman-morrison, neumann expansion techniques for stochastic analysis of mistuned bladed disc systems
The paper presents an assessment about using two classical reduced-order techniques, the Sherman-Morrison-Woodbury (SMW) formula and the Neumann expansion method, to enhance the computational efficiency of the stochastic analysis in mistuned bladed disc systems. The frequency responses of the blades are evaluated for different mistuning patterns via stiffness perturbations. A standard matrix factorization method is used as baseline to benchmark the results obtained from the SMW formula and Neumann expansion methods. The modified SMW algorithm can effectively update the inversion of an uncertainty matrix without the need of separated inversions, however with a limited increase of the computational efficiency. Neumann expansion techniques are shown to significantly decrease the required CPU time, while maintaining a low relative error. The convergence of the Neumann expansion however is not guaranteed when the excitation frequency approaches resonance when the mistuned system has either a low damping or high mistuning level. A scalar-modified Neumann expansion is therefore introduced to improve convergence in the neighbourhood of the resonance frequency.
The American Society of Mechanical Engineers
Yuan, J.
4bcf9ce8-3af4-4009-9cd0-067521894797
Scarpa, F.
684472c3-1a28-478a-a388-5fd896986c1d
Allegri, G.
8dd43a78-5f53-472f-853a-1b2fd7b129e4
Patsias, S.
e7e4a982-00c2-4025-ba71-32c101489b7c
Rajasekaran, R.
c5f6d9b9-8517-49e1-afc5-5830d2d1390d
Yuan, J.
4bcf9ce8-3af4-4009-9cd0-067521894797
Scarpa, F.
684472c3-1a28-478a-a388-5fd896986c1d
Allegri, G.
8dd43a78-5f53-472f-853a-1b2fd7b129e4
Patsias, S.
e7e4a982-00c2-4025-ba71-32c101489b7c
Rajasekaran, R.
c5f6d9b9-8517-49e1-afc5-5830d2d1390d

Yuan, J., Scarpa, F., Allegri, G., Patsias, S. and Rajasekaran, R. (2015) Numerical assessment of using sherman-morrison, neumann expansion techniques for stochastic analysis of mistuned bladed disc systems. In ASME Turbo Expo 2015:: Turbine Technical Conference and Exposition. The American Society of Mechanical Engineers.. (doi:10.1115/GT2015-43188).

Record type: Conference or Workshop Item (Paper)

Abstract

The paper presents an assessment about using two classical reduced-order techniques, the Sherman-Morrison-Woodbury (SMW) formula and the Neumann expansion method, to enhance the computational efficiency of the stochastic analysis in mistuned bladed disc systems. The frequency responses of the blades are evaluated for different mistuning patterns via stiffness perturbations. A standard matrix factorization method is used as baseline to benchmark the results obtained from the SMW formula and Neumann expansion methods. The modified SMW algorithm can effectively update the inversion of an uncertainty matrix without the need of separated inversions, however with a limited increase of the computational efficiency. Neumann expansion techniques are shown to significantly decrease the required CPU time, while maintaining a low relative error. The convergence of the Neumann expansion however is not guaranteed when the excitation frequency approaches resonance when the mistuned system has either a low damping or high mistuning level. A scalar-modified Neumann expansion is therefore introduced to improve convergence in the neighbourhood of the resonance frequency.

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Published date: 12 August 2015

Identifiers

Local EPrints ID: 479395
URI: http://eprints.soton.ac.uk/id/eprint/479395
PURE UUID: 45f50303-19f4-406c-9bdd-c49840ab86cf
ORCID for J. Yuan: ORCID iD orcid.org/0000-0002-2411-8789

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Date deposited: 20 Jul 2023 17:43
Last modified: 17 Mar 2024 04:20

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Contributors

Author: J. Yuan ORCID iD
Author: F. Scarpa
Author: G. Allegri
Author: S. Patsias
Author: R. Rajasekaran

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