The University of Southampton
University of Southampton Institutional Repository

Stochastic component mode synthesis

Stochastic component mode synthesis
Stochastic component mode synthesis
In this paper, a stochastic component mode synthesis method is developed for the dynamic analysis of large-scale structures with parameter uncertainties. The main idea is to represent each component displacement using a subspace spanned by a set of stochastic basis vectors in the same fashion as in stochastic reduced basis methods [1, 2]. These vectors represent however stochastic modes in contrast to the deterministic modes used in conventional substructuring methods [3]. The Craig-Bampton reduction procedure is used for illustration. A truncated set of stochastic fixed-free modes and a complete set of stochastic constraint modes are used to generate reduced matrices for each component. These are then coupled together through necessary compatibility constraints to form the global system matrices.
The advantage of using stochastic component modes is that the Bubnov-Galerkin scheme can be applied for the computation of undetermined coefficients in the reduced approximation. Explicit expressions can be obtained for the responses in terms of the random parameters. Therefore the statistical moments of responses can be efficiently computed. The method is applied to a test case problem. Results obtained are compared with the traditional Craig-Bampton method, the first-order Taylor series and Monte Carlo Simulation benchmark results. We will refer to the proposed method as ROBUST or Reduced Order By Using Stochastic Techniques.
Bah, Mamadou T.
b5cd0f47-016f-485c-8293-5f6bf8a7ef1a
Nair, Prasanth B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Bhaskar, Atul
d4122e7c-5bf3-415f-9846-5b0fed645f3e
Keane, Andy J.
26d7fa33-5415-4910-89d8-fb3620413def
Bah, Mamadou T.
b5cd0f47-016f-485c-8293-5f6bf8a7ef1a
Nair, Prasanth B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Bhaskar, Atul
d4122e7c-5bf3-415f-9846-5b0fed645f3e
Keane, Andy J.
26d7fa33-5415-4910-89d8-fb3620413def

Bah, Mamadou T., Nair, Prasanth B., Bhaskar, Atul and Keane, Andy J. (2003) Stochastic component mode synthesis. 44th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Norfolk, USA. 06 - 09 Apr 2003. 11 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

In this paper, a stochastic component mode synthesis method is developed for the dynamic analysis of large-scale structures with parameter uncertainties. The main idea is to represent each component displacement using a subspace spanned by a set of stochastic basis vectors in the same fashion as in stochastic reduced basis methods [1, 2]. These vectors represent however stochastic modes in contrast to the deterministic modes used in conventional substructuring methods [3]. The Craig-Bampton reduction procedure is used for illustration. A truncated set of stochastic fixed-free modes and a complete set of stochastic constraint modes are used to generate reduced matrices for each component. These are then coupled together through necessary compatibility constraints to form the global system matrices.
The advantage of using stochastic component modes is that the Bubnov-Galerkin scheme can be applied for the computation of undetermined coefficients in the reduced approximation. Explicit expressions can be obtained for the responses in terms of the random parameters. Therefore the statistical moments of responses can be efficiently computed. The method is applied to a test case problem. Results obtained are compared with the traditional Craig-Bampton method, the first-order Taylor series and Monte Carlo Simulation benchmark results. We will refer to the proposed method as ROBUST or Reduced Order By Using Stochastic Techniques.

Text
bah_03.pdf - Accepted Manuscript
Download (2MB)

More information

Published date: 2003
Additional Information: AIAA 2003-1750 SKU: TPM.O.663 - MSDM2003
Venue - Dates: 44th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Norfolk, USA, 2003-04-06 - 2003-04-09

Identifiers

Local EPrints ID: 23529
URI: http://eprints.soton.ac.uk/id/eprint/23529
PURE UUID: 9420bd9f-fc0f-4e39-9317-1aa6ff43d8be
ORCID for Andy J. Keane: ORCID iD orcid.org/0000-0001-7993-1569

Catalogue record

Date deposited: 01 Jun 2006
Last modified: 26 Jul 2022 01:35

Export record

Contributors

Author: Mamadou T. Bah
Author: Prasanth B. Nair
Author: Atul Bhaskar
Author: Andy J. Keane ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×