Finite Element Model Updating of a High‐Rise Building Based on Measured Seismic Response Data from the 2021 Yangbi Earthquake

ABSTRACT Finite element model updating (FEMU) is essential for improving the accuracy of structural simulations, particularly in seismic analysis of high‐rise buildings. This study focuses on updating the finite element model of a high‐rise structure based on seismic response data recorded during the M6.4 Yangbi earthquake in Dali, Yunnan Province, China, on May 21, 2021. A structural seismic response monitoring array was deployed in the building, capturing valuable data that reflects the building's dynamic characteristics under actual seismic loads. To enhance the accuracy of the model update, intelligent optimization algorithms were applied, including particle swarm optimization (PSO), ant colony optimization (ACO), fish swarm algorithm (FSA), and artificial bee colony (ABC). Additionally, a response surface model was constructed to reduce computational costs and improve efficiency. The study further explores the influence of key structural parameters—such as elastic modulus and moment of inertia—on model performance through sensitivity analysis and response surface modeling. The results demonstrate that the intelligent optimization algorithms successfully improved the accuracy of the finite element model, with average errors below 1.5% for all tested algorithms. Evolutionary algorithms, particularly PSO and ACO, showed superior performance in reducing discrepancies between simulated and observed data, enhancing the model's predictive capability. The findings underscore the significance of integrating seismic response data with intelligent optimization techniques for robust structural model updating, contributing to more reliable performance‐based earthquake engineering (PBEE) practices.