Fragility analysis for performance-based blast design of RC columns artificial neural network

被引:17
作者
Zhang, Xuejie [1 ,2 ]
Li, Zhong-Xian [2 ]
Shi, Yanchao [2 ]
Wu, Chengqing [3 ]
Li, Jun [3 ]
机构
[1] Tianjin Chengjian Univ, Tianjin Key Lab Civil Struct Protect & Reinforcem, Tianjin 300384, Peoples R China
[2] Tianjin Univ, Key Lab Coast Civil Struct Safety, Minist Educ, Tianjin 300350, Peoples R China
[3] Univ Technol Sydney, Sch Civil & Environm Engn, Sydney, NSW 2007, Australia
基金
中国国家自然科学基金;
关键词
Performance-based blast design; Fragility analysis; FRP-strengthened column; Artificial neural network; RESISTANT OFFSHORE TOPSIDES; PRESSURE-IMPULSE DIAGRAMS; CONCRETE WALL PANELS; RELIABILITY-ANALYSIS; RISK-ASSESSMENT; LOAD VARIABILITY; TENSILE-STRENGTH; DAMAGE; PREDICTION; BUILDINGS;
D O I
10.1016/j.jobe.2022.104364
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In this paper, fragility analysis for performance-based blast design of FRP-strengthened RC columns is carried out. The blast intensity levels, performance levels and performance objectives of the RC columns are defined. A simplified probabilistic risk assessment framework incorporating the performance-based design concept and fragility analysis is established. Since fragility analysis is the most important but time-consuming process of probabilistic assessment risk, an artificial neural network (ANN) based fragility analysis framework is proposed to improve its computational efficiency. Based on the rapid fragility analysis method, fragility curves of several typical RC columns with or without FRP strengthening are calculated to analyze their damage probabilities. This study provides avenues for engineers to estimate the failure probabilities of RC columns with or without FRP strengthening under blast loads and make decisions quickly.
引用
收藏
页数:20
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