概率逻辑
地震灾害
增量动力分析
脆弱性
结构工程
模块化设计
强度(物理)
无筋砌体房屋
标量(数学)
非线性系统
工程类
地震分析
计算机科学
砖石建筑
土木工程
数学
几何学
化学
物理
量子力学
操作系统
物理化学
人工智能
作者
Ali Bigdeli,Amirhossein Emamikoupaei,Konstantinos Daniel Tsavdaridis
标识
DOI:10.1016/j.jobe.2023.105916
摘要
Establishing suitable probabilistic seismic demand models (PSDMs) is a key part of the probabilistic performance-based method. Intensity measures (IMs) are used as a connection between earthquake hazard and seismic response in performance-based earthquake engineering. This study identifies the optimal intensity measures (IMs) of probabilistic seismic demand models for steel Modular Building Systems (MBSs) subjected to near-field earthquake ground motions. It is achieved by performing a Cloud analysis utilizing two sets of near-field ground motions: 72 pulse-like and 120 non-pulse-like ground motions. The nonlinear time history analysis is carried out using a finite-element model of a 6-story mid-rise MBS. For this aim, a total of 36 scalar intensity measures were collected. Based on a large number of regression analyses between the IMs and Engineering Demand Parameters for the studied MBS, the selected IMs were evaluated on several criteria, including correlation, efficiency, practicality, sufficiency, and proficiency. Finally, in the framework of PSDMs, different fragility curves and seismic demand hazard curves were generated for the studied MBS.
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