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Parameter selection and stochastic model updating using perturbation methods with parameter weighting matrix assignment

Parameterisation in stochastic problems is a major issue in real applications. In addition, complexity of test structures (for example, those assembled through laser spot welds) is another challenge. The objective of this paper is two-fold: (1) stochastic uncertainty in two sets of different structu...

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Main Authors: Abu Husain, Nurulakmar, Khodaparast, Hamed Haddad, Ouyang, Huajiang
Format: Article
Published: Elsevier Ltd. 2012
Subjects:
QA Mathematics
Online Access:http://eprints.utm.my/id/eprint/47350/
http://dx.doi.org/10.1016/j.ymssp.2012.04.001
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spelling my.utm.473502019-03-31T08:38:20Z http://eprints.utm.my/id/eprint/47350/ Parameter selection and stochastic model updating using perturbation methods with parameter weighting matrix assignment Abu Husain, Nurulakmar Khodaparast, Hamed Haddad Ouyang, Huajiang QA Mathematics Parameterisation in stochastic problems is a major issue in real applications. In addition, complexity of test structures (for example, those assembled through laser spot welds) is another challenge. The objective of this paper is two-fold: (1) stochastic uncertainty in two sets of different structures (i.e., simple flat plates, and more complicated formed structures) is investigated to observe how updating can be adequately performed using the perturbation method, and (2) stochastic uncertainty in a set of welded structures is studied by using two parameter weighting matrix approaches. Different combinations of parameters are explored in the first part; it is found that geometrical features alone cannot converge the predicted outputs to the measured counterparts, hence material properties must be included in the updating process. In the second part, statistical properties of experimental data are considered and updating parameters are treated as random variables. Two weighting approaches are compared; results from one of the approaches are in very good agreement with the experimental data and excellent correlation between the predicted and measured covariances of the outputs is achieved. It is concluded that proper selection of parameters in solving stochastic updating problems is crucial. Furthermore, appropriate weighting must be used in order to obtain excellent convergence between the predicted mean natural frequencies and their measured data. Elsevier Ltd. 2012 Article PeerReviewed Abu Husain, Nurulakmar and Khodaparast, Hamed Haddad and Ouyang, Huajiang (2012) Parameter selection and stochastic model updating using perturbation methods with parameter weighting matrix assignment. Mechanical Systems And Signal Processing, 32 . pp. 135-152. ISSN 0888-3270 http://dx.doi.org/10.1016/j.ymssp.2012.04.001 DOI:10.1016/j.ymssp.2012.04.001
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA Mathematics
spellingShingle QA Mathematics
Abu Husain, Nurulakmar
Khodaparast, Hamed Haddad
Ouyang, Huajiang
Parameter selection and stochastic model updating using perturbation methods with parameter weighting matrix assignment
description Parameterisation in stochastic problems is a major issue in real applications. In addition, complexity of test structures (for example, those assembled through laser spot welds) is another challenge. The objective of this paper is two-fold: (1) stochastic uncertainty in two sets of different structures (i.e., simple flat plates, and more complicated formed structures) is investigated to observe how updating can be adequately performed using the perturbation method, and (2) stochastic uncertainty in a set of welded structures is studied by using two parameter weighting matrix approaches. Different combinations of parameters are explored in the first part; it is found that geometrical features alone cannot converge the predicted outputs to the measured counterparts, hence material properties must be included in the updating process. In the second part, statistical properties of experimental data are considered and updating parameters are treated as random variables. Two weighting approaches are compared; results from one of the approaches are in very good agreement with the experimental data and excellent correlation between the predicted and measured covariances of the outputs is achieved. It is concluded that proper selection of parameters in solving stochastic updating problems is crucial. Furthermore, appropriate weighting must be used in order to obtain excellent convergence between the predicted mean natural frequencies and their measured data.
format Article
author Abu Husain, Nurulakmar
Khodaparast, Hamed Haddad
Ouyang, Huajiang
author_facet Abu Husain, Nurulakmar
Khodaparast, Hamed Haddad
Ouyang, Huajiang
author_sort Abu Husain, Nurulakmar
title Parameter selection and stochastic model updating using perturbation methods with parameter weighting matrix assignment
title_short Parameter selection and stochastic model updating using perturbation methods with parameter weighting matrix assignment
title_full Parameter selection and stochastic model updating using perturbation methods with parameter weighting matrix assignment
title_fullStr Parameter selection and stochastic model updating using perturbation methods with parameter weighting matrix assignment
title_full_unstemmed Parameter selection and stochastic model updating using perturbation methods with parameter weighting matrix assignment
title_sort parameter selection and stochastic model updating using perturbation methods with parameter weighting matrix assignment
publisher Elsevier Ltd.
publishDate 2012
url http://eprints.utm.my/id/eprint/47350/
http://dx.doi.org/10.1016/j.ymssp.2012.04.001
_version_ 1643652295003471872
score 13.211869

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