Response Surface Model Optimization Algorithm for Structural Assessment Based on Vibration Frequency

Finite element model modification based on response surface method is an effective engineering method that can significantly improve the accuracy of finite element model and structural evaluation. In order to solve the shortcomings of the response surface method based finite element model correction, which exists that the polynomial order selection rule is unknown and the correction result is easily affected by the quality of the optimization target, based on the relationship between the polynomial order and the response surface accuracy and computation amount, a robust estimation algorithm was introduced to optimize the response surface solution process, which improves the reliability of the response surface based model correction. Taking an actual project of a cable‐stayed bridge as an example, the response surface‐based finite element model modification method was adopted to compare the response surface accuracy and computation amount of three kinds of response surface models, namely, second‐mode polynomials, third‐mode polynomials and fourth‐mode polynomials. The optimization results of the robust estimation method were compared with the traditional solution method under the conditions of large fluctuation and small fluctuation of optimization target between finite element index. The results show that with the increase of the polynomial order of the response surface model, the unknown covariates to be solved in the response surface model increase sharply, which increases the computational cost, but the effect of improving the accuracy of the response surface model is limited. When the target frequency fluctuates greatly, compared with the least‐squares method, robust estimation will not transfer the error of the correction result of the order with the large fluctuation of the index difference to the other orders, which ensures the stability of the correction results.

Authors

Institutions

Publication Details

Journal
Shock and Vibration
Published
2025-01-01
DOI
https://doi.org/10.1155/vib/5446251
Citations
5
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
4.77

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Response Surface Model Optimization Algorithm for Structural Assessment Based on Vibration Frequency

Xiaoguang Wang, Shuai Song, Wenhao Zhang, Bin Zhao et al.
5 citations
Shock and Vibration
Structural Health Monitoring Techniques
4.77
article

Response Surface Model Optimization Algorithm for Structural Assessment Based on Vibration Frequency

Xiaoguang Wang, Shuai Song, Wenhao Zhang, Bin Zhao, Miao Ming
article en
5 citations

Abstract

Finite element model modification based on response surface method is an effective engineering method that can significantly improve the accuracy of finite element model and structural evaluation. In order to solve the shortcomings of the response surface method based finite element model correction, which exists that the polynomial order selection rule is unknown and the correction result is easily affected by the quality of the optimization target, based on the relationship between the polynomial order and the response surface accuracy and computation amount, a robust estimation algorithm was introduced to optimize the response surface solution process, which improves the reliability of the response surface based model correction. Taking an actual project of a cable‐stayed bridge as an example, the response surface‐based finite element model modification method was adopted to compare the response surface accuracy and computation amount of three kinds of response surface models, namely, second‐mode polynomials, third‐mode polynomials and fourth‐mode polynomials. The optimization results of the robust estimation method were compared with the traditional solution method under the conditions of large fluctuation and small fluctuation of optimization target between finite element index. The results show that with the increase of the polynomial order of the response surface model, the unknown covariates to be solved in the response surface model increase sharply, which increases the computational cost, but the effect of improving the accuracy of the response surface model is limited. When the target frequency fluctuates greatly, compared with the least‐squares method, robust estimation will not transfer the error of the correction result of the order with the large fluctuation of the index difference to the other orders, which ensures the stability of the correction results.

Shock and VibrationVol. 2025(1)
Qingdao University of Science and Technology (CN), Chang'an University (CN), CCCC Highway Consultants (China) (CN), Qingdao University of Technology (CN)
U.S. Department of Transportation, Key Research and Development Program of Ningxia, Shanxi Provincial Key Research and Development Project
Openalex Percentile: Top 6%
Structural Health Monitoring Techniques
4.77
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.