建筑结构学报2025，Vol.46Issue(7)：12-21,10.DOI:10.14006/j.jzjgxb.2024.0532
城市区域建筑群震灾分析的统一参数化建模方法
Unified parametric modeling approach for seismic simulation of urban building clusters
摘要
Abstract
In urban seismic resilience analysis,establishing parametric dynamic time-history analysis models is crucial for rapid and accurate assessment of resilience indicators for regional building clusters.However,limited design information,diversity of structural types,and complex parameter calibration pose significant challenges for parametric modeling of existing building stocks.This paper proposed a unified modeling approach applicable to various structural types,which considered bending-shear coupling effects and vertical irregularities without requiring pre-selection of simplified modeling strategies based on building height or structural systems.The method adaptively reflected structural bending-shear coupling deformation characteristics and their participation levels.This unified modeling framework utilized structural periods and particle swarm optimization algorithm to provide a standardized procedure for model parameter calibration,directly yielding the story stiffness matrices and global mass and stiffness matrices for subsequent disaster resilience indicator analysis.Case studies of three real-world structures(multi-story,high-rise,and super high-rise buildings)demonstrate that the proposed method achieves a thousandfold improvement in computational efficiency,while maintaining comparable accuracy to refined finite element simulations,exhibiting superior generalization capability and computational performance.This unified parametric modeling framework provides an efficient novel paradigm for disaster-resilience analysis of large-scale urban building clusters.关键词
城市区域建筑群/抗震韧性/动力时程分析/参数化建模/弯剪耦合模型Key words
urban building clusters/seismic resilience/dynamic time-history analysis/parametric modeling/bending-shear coupled model分类
建筑与水利引用本文复制引用
陈楠,项梦洁,庞云升,许泽坤,陈隽..城市区域建筑群震灾分析的统一参数化建模方法[J].建筑结构学报,2025,46(7):12-21,10.基金项目
"十四五"国家重点研发计划(2023YFC3805800),国家自然科学基金青年科学基金项目(52408556). （2023YFC3805800）
