防灾减灾工程学报2025，Vol.45Issue(2)：295-306,12.DOI:10.13409/j.cnki.jdpme.20231220003
响应面参数筛选与智能算法优化的有限元模型更新
Finite Element Model Updating via Response Surface Parameter Screening and Intelligent Algorithm Optimization
摘要
Abstract
In the current engineering and scientific research,finite element models for large-scale struc-tural optimization face limitations due to high computational costs and complexity.The integration of response surface models has emerged as an effective approach to overcome these challenges,enabling researchers to significantly reduce computational costs while maintaining acceptable accuracy.Howev-er,when fitting response surfaces for complex models,conventional parameter screening methods of-ten lead to reduced accuracy and efficiency,particularly when considering individual variations and the high costs of sensitivity analysis.Focusing on the finite element model of a 26-story frame-shear wall structure,this study integrated two preprocessing steps—single-factor experiments and hill-climbing tests—during response surface construction.These steps aimed to narrow the search space,screen key factors,and provide gradient information,making the construction of the response surface more ac-curate and operable,and providing a reliable foundation for subsequent model processing.By integrat-ing multiple intelligent algorithms,this study completed the model updating and optimization opera-tions for the response surface.The research results showed that the response surface constructed using parameters screened through preprocessing steps maintained consistently low error rates with identifi-cation results when multiple algorithm types were applied.This study provides valuable guidance for future engineering practices and research on related fields,offering a more flexible and universal opti-mization solution for enhancing the accuracy and efficiency of finite element model updating in large-scale structural optimization.关键词
有限元模型/响应面模型/单因素试验/爬坡实验/模型更新Key words
finite element model/response surface model/single-factor experiments/hill climbing tests/model updating分类
建筑与水利引用本文复制引用
吴道奇,杜轲,骆欢,马加路,聂桂波..响应面参数筛选与智能算法优化的有限元模型更新[J].防灾减灾工程学报,2025,45(2):295-306,12.基金项目
中国地震局工程力学研究所基本科研业务费专项项目(2023B07)、黑龙江省自然科学基金杰出青年基金(JQ2022E006)资助 （2023B07）
