Surrogate-assisted finite element model updating for detecting scour depths in a continuous bridge

Yi He, Judy P. Yang*, Jie Yu

*此作品的通信作者

研究成果: Article同行評審

2 引文 斯高帕斯(Scopus)

摘要

In this study, the Kriging surrogate-assisted method is proposed to improve the computational efficiency in finite element model updating (FEMU) based scour depth detection for the first time. Unlike the conventional methods of FEMU that update the structural parameters by the frequency surrogate models, the proposed method further takes the mode shapes into account by constructing the modal assurance criterion (MAC) surrogate models. The bi-objective functions of the frequency discrepancies and MAC values are directly optimized by the nondominated sorting genetic algorithm II to circumvent the specification of weighting factors as required in single-objective optimization. The preferred solution is selected from the nondominated solutions by the criterion of minimum distance from the equilibrium point. As the sensitivity analysis indicates that the transverse vibration modes are sensitive to the bridge scour, the transverse mode shapes measured on the bridge piers are adopted in scour detection. The illustrative examples show that the proposed method can greatly reduce the computational time with a competitive estimation of the scour depth vector. The parametric study further demonstrates the ability of the proposed method to yield satisfactory results even using the modal parameters of the first two modes with three measurement points.

原文English
文章編號101996
期刊Journal of Computational Science
69
DOIs
出版狀態Published - 5月 2023

指紋

深入研究「Surrogate-assisted finite element model updating for detecting scour depths in a continuous bridge」主題。共同形成了獨特的指紋。

引用此