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Aydin Shishegaran


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Journal of Zhejiang University SCIENCE A 2021 Vol.22 No.6 P.441-466


Prediction of the load-carrying capacity of reinforced concrete connections under post-earthquake fire

Author(s):  Aydin Shishegaran, Mehdi Moradi, Mohammad Ali Naghsh, Behnam Karami, Arshia Shishegaran

Affiliation(s):  School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran; more

Corresponding email(s):   aydin_shishegaran@civileng.iust.ac.ir

Key Words:  Reinforced concrete connection (RCC), Post-earthquake fire (PEF), Surrogate models, Load-carrying capacity, Gene expression programming (GEP), Ensemble model

Aydin Shishegaran, Mehdi Moradi, Mohammad Ali Naghsh, Behnam Karami, Arshia Shishegaran. Prediction of the load-carrying capacity of reinforced concrete connections under post-earthquake fire[J]. Journal of Zhejiang University Science A, 2021, 22(6): 441-466.

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author="Aydin Shishegaran, Mehdi Moradi, Mohammad Ali Naghsh, Behnam Karami, Arshia Shishegaran",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Prediction of the load-carrying capacity of reinforced concrete connections under post-earthquake fire
%A Aydin Shishegaran
%A Mehdi Moradi
%A Mohammad Ali Naghsh
%A Behnam Karami
%A Arshia Shishegaran
%J Journal of Zhejiang University SCIENCE A
%V 22
%N 6
%P 441-466
%@ 1673-565X
%D 2021
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2000268

T1 - Prediction of the load-carrying capacity of reinforced concrete connections under post-earthquake fire
A1 - Aydin Shishegaran
A1 - Mehdi Moradi
A1 - Mohammad Ali Naghsh
A1 - Behnam Karami
A1 - Arshia Shishegaran
J0 - Journal of Zhejiang University Science A
VL - 22
IS - 6
SP - 441
EP - 466
%@ 1673-565X
Y1 - 2021
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A2000268

Finding out the most effective parameters relating to the resistance of reinforced concrete connections (RCCs) is an important topic in structural engineering. In this study, first, a finite element (FE) model is developed for simulating the performance of RCCs under post-earthquake fire (PEF). Then surrogate models, including multiple linear regression (MLR), multiple natural logarithm (Ln) equation regression (MLnER), gene expression programming (GEP), and an ensemble model, are used to predict the remaining load-carrying capacity of an RCC under PEF. The statistical parameters, error terms, and a novel statistical table are used to evaluate and compare the accuracy of each surrogate model. According to the results, the ratio of the longitudinal reinforcement bars of the column (RLC) has a significant effect on the resistance of an RCC under PEF. Increasing the value of this parameter from 1% to 8% can increase the residual load-carrying capacity of an RCC under PEF by 492.2% when the RCC is exposed to fire at a temperature of 1000 °C. Moreover, based on the results, the ensemble model can predict the residual load-carrying capacity with suitable accuracy. A safety factor of 1.55 should be applied to the results obtained from the ensemble model.


创新点:1. 本文评估了几个参数对RCC行为的影响(在此之前没有相关研究),同时也评估了几个设计参数的影响.2. 通过使用替代模型(比如基因表达式编程(GEP))预测了RCC的承载能力.
方法:1. 使用有限元方法开发132个具有各种设计参数的模型.2. 采用回归模型、GEP和集成模型等替代模型预测多个设计参数对RCC承载能力的影响.
结论:1. 温度从25 °C提高到600 °C和1000 °C,可导致RCC的承载能力分别降低25%和75%以上.2. 提高RCC耐火性的最有效参数是柱的纵向钢筋(RLC).将RLC从1%增加到8%,RCC在不同温度下的承载能力提高了234.8%~492.9%.3. 提高混凝土的抗压强度可略微增加RCC在震后火灾(PEF)下的剩余承载能力;该影响在高温情况下更为明显,因为高温时钢材的力学性能下降迅速.4. 集成模型为预测PEF情况下RCC剩余承载能力的最佳模型.


Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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