A covariance based framework for the propagation of correlated uncertainty in frequency based dynamic sub-structuring

Meggitt, JWR ORCID: https://orcid.org/0000-0002-6665-2939 and Moorhouse, AT ORCID: https://orcid.org/0000-0002-4034-1091 2020, 'A covariance based framework for the propagation of correlated uncertainty in frequency based dynamic sub-structuring' , Mechanical Systems and Signal Processing, 136 .

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Abstract

Dynamic sub-structuring (DS) is the procedure by which the passive properties (i.e. frequency response functions) of an assembled structure are predicted from those of its constituent sub-structures. In this paper we are concerned with the propagation of correlated uncertainty through such a prediction. In this work a first-order covariance based propagation framework is derived based on the primal and dual formulations of the sub-structuring problem and the complex bivariate description of FRF uncertainty. The proposed framework is valid also in the case of sub-structure decoupling, since the underlying equations are of an identical form. The present paper extends previous work into a more general framework by accounting for the presence of correlated uncertainty. This is important as recent work has demonstrated that the neglect inter-FRF correlation (i.e. the correlated uncertainty associated with impactbased FRF measurements) can lead to large errors in uncertainty estimates. E�cient algorithms are introduced for implementation of the proposed framework. Results are compared against Monte-Carlo simulations and shown to be in good agreement for both correlated, uncorrelated and mixed uncertainty. These results further illustrate that the neglect of inter-FRF correlation, when physically present, can lead to large over-estimations in the uncertainty of coupled structures. This result justifies use of the proposed framework.

Item Type: Article
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Journal or Publication Title: Mechanical Systems and Signal Processing
Publisher: Elsevier
ISSN: 0888-3270
Related URLs:
Funders: Engineering and Physical Sciences Research Council (EPSRC)
Depositing User: JWR Meggitt
Date Deposited: 20 Nov 2019 09:45
Last Modified: 16 Dec 2019 09:00
URI: http://usir.salford.ac.uk/id/eprint/53119

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