Distribution-free stochastic model updating of dynamic systems with parameter dependencies

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Autoren

Externe Organisationen

  • University of Strathclyde
  • The University of Liverpool
  • Tongji University
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OriginalspracheEnglisch
Aufsatznummer102227
FachzeitschriftStructural safety
Jahrgang97
PublikationsstatusVeröffentlicht - Juli 2022

Abstract

This work proposes a distribution-free stochastic model updating framework to calibrate the joint probabilistic distribution of the multivariate correlated parameters. In this framework, the marginal distributions are defined as the staircase density functions and the correlation structure is described by the Gaussian copula function. The first four moments of the staircase density functions and the correlation coefficients are updated by an approximate Bayesian computation, in which the Bhattacharyya distance-based metric is proposed to define an approximate likelihood that is capable of capturing the stochastic discrepancy between model outputs and observations. The feasibility of the framework is demonstrated on two illustrative examples and a followed engineering application to the updating of a nonlinear dynamic system using observed time signals. The results demonstrate the capability of the proposed updating procedure in the very challenging condition where the prior knowledge about the distribution of the parameters is extremely limited (i.e., no information on the marginal distribution families and correlation structure is available).

ASJC Scopus Sachgebiete

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Distribution-free stochastic model updating of dynamic systems with parameter dependencies. / Kitahara, Masaru; Bi, Sifeng; Broggi, Matteo et al.
in: Structural safety, Jahrgang 97, 102227, 07.2022.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Kitahara M, Bi S, Broggi M, Beer M. Distribution-free stochastic model updating of dynamic systems with parameter dependencies. Structural safety. 2022 Jul;97:102227. doi: 10.1016/j.strusafe.2022.102227
Kitahara, Masaru ; Bi, Sifeng ; Broggi, Matteo et al. / Distribution-free stochastic model updating of dynamic systems with parameter dependencies. in: Structural safety. 2022 ; Jahrgang 97.
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AU - Kitahara, Masaru

AU - Bi, Sifeng

AU - Broggi, Matteo

AU - Beer, Michael

N1 - Funding Information: The first author acknowledges the support of the Deutsche Forschungsgemensschaft (DFG, German Research Foundation) — SFB1463-434502799.

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AB - This work proposes a distribution-free stochastic model updating framework to calibrate the joint probabilistic distribution of the multivariate correlated parameters. In this framework, the marginal distributions are defined as the staircase density functions and the correlation structure is described by the Gaussian copula function. The first four moments of the staircase density functions and the correlation coefficients are updated by an approximate Bayesian computation, in which the Bhattacharyya distance-based metric is proposed to define an approximate likelihood that is capable of capturing the stochastic discrepancy between model outputs and observations. The feasibility of the framework is demonstrated on two illustrative examples and a followed engineering application to the updating of a nonlinear dynamic system using observed time signals. The results demonstrate the capability of the proposed updating procedure in the very challenging condition where the prior knowledge about the distribution of the parameters is extremely limited (i.e., no information on the marginal distribution families and correlation structure is available).

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KW - Bhattacharyya distance

KW - Gaussian copula function

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