Stochastic model updating for assembled structures with bolted joints using a Bayesian method

Zhang, Yong, Zhao, Yan and Ouyang, Huajiang ORCID: 0000-0003-0312-0326 (2022) Stochastic model updating for assembled structures with bolted joints using a Bayesian method. ENGINEERING OPTIMIZATION, 54 (11). pp. 1919-1937.

Text Stochastic Updating final.docx - Author Accepted Manuscript Download (863kB)

Abstract

An efficient model-updating method based on Bayesian power spectral sensitivity analysis is proposed to update the uncertain parameters of assembled structures. The dynamic equations of bolted assembled structures are derived using the substructure component model synthesis technique. The posteriori probability density function of uncertain parameters of bolted joints is established by the Bayesian method, where the negative logarithmic likelihood function is taken as the objective function to be optimized. To improve the efficiency of the stochastic model-updating process, the pseudo-excitation method is introduced to derive analytically the expressions of the gradient vector and the Hessian matrix for optimization. The proposed method is evaluated in the stochastic model updating of an assembled structure consisting of three beams. Then, it is applied to model updating of the simplified model of a rocket. The numerical results demonstrate that this approach can significantly reduce the computational cost and ensure computational accuracy.

Item Type:	Article
Uncontrolled Keywords:	Stochastic model updating, Bayesian inference, pseudo-excitation method, substructuring, bolted assembly
Divisions:	Faculty of Science and Engineering > School of Engineering
Depositing User:	Symplectic Admin
Date Deposited:	13 Sep 2021 07:38
Last Modified:	18 Jan 2023 21:28
DOI:	10.1080/0305215X.2021.1965136
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3136838