scholarly journals Modelling catastrophic degradation of flexural-dominated RC columns at ultimate displacements based on fibre beam-column model

2021 ◽  
pp. 103476
Author(s):  
Lei Li ◽  
Wentao Wang ◽  
Pengpeng Shi
Keyword(s):  
2017 ◽  
Vol 34 (4) ◽  
pp. 393
Author(s):  
Zhixiang Chen ◽  
Shunqun Li ◽  
Jinhong Xia ◽  
Kai Wang ◽  
Chao Gui

2019 ◽  
Vol 23 (5) ◽  
pp. 2158-2174 ◽  
Author(s):  
He Zhang ◽  
Pingzhou Cao ◽  
Kai Wu ◽  
Chao Xu ◽  
Lijian Ren

2021 ◽  
Vol 11 (9) ◽  
pp. 4043
Author(s):  
Aleksandar Landović ◽  
Miroslav Bešević

Experimental research on axially compressed columns made from reinforced concrete (RC) and RC columns strengthened with a steel jacket and additional fill concrete is presented in this paper. A premade squared cross-section RC column was placed inside a steel tube, and then the space between the column and the tube was filled with additional concrete. A total of fourteen stub axially compressed columns, including nine strengthened specimens and five plain reinforced concrete specimens, were experimentally tested. The main parameter that was varied in the experiment was the compressive strength of the filler concrete. Three different concrete compression strength classes were used. Test results showed that all three cross-section parts (the core column, the fill, and the steel jacket) worked together in the force-carrying process through all load levels, even if only the basic RC column was loaded. The strengthened columns exhibited pronounced ductile behavior compared to the plain RC columns. The influence of the test parameters on the axial compressive strength was investigated. In addition, the specimen failure modes, strain development, and load vs. deformation relations were registered. The applicability of three different design codes to predict the axial bearing capacity of the strengthened columns was also investigated.


2020 ◽  
Vol 24 (6) ◽  
pp. 04020063
Author(s):  
Anh Duc Mai ◽  
M. Neaz Sheikh ◽  
Kento Yamakado ◽  
Muhammad N. S. Hadi

2021 ◽  
Vol 231 ◽  
pp. 111809
Author(s):  
Yangxi Zhang ◽  
Mingke Deng ◽  
Tong Li ◽  
Zhifang Dong
Keyword(s):  

2021 ◽  
pp. 113717
Author(s):  
Marta Del Zoppo ◽  
Costantino Menna ◽  
Marco Di Ludovico ◽  
Domenico Asprone ◽  
Andrea Prota

2020 ◽  
Vol 37 (7) ◽  
pp. 2517-2537
Author(s):  
Mostafa Rezvani Sharif ◽  
Seyed Mohammad Reza Sadri Tabaei Zavareh

Purpose The shear strength of reinforced concrete (RC) columns under cyclic lateral loading is a crucial concern, particularly, in the seismic design of RC structures. Considering the costly procedure of testing methods for measuring the real value of the shear strength factor and the existence of several parameters impacting the system behavior, numerical modeling techniques have been very much appreciated by engineers and researchers. This study aims to propose a new model for estimation of the shear strength of cyclically loaded circular RC columns through a robust computational intelligence approach, namely, linear genetic programming (LGP). Design/methodology/approach LGP is a data-driven self-adaptive algorithm recently used for classification, pattern recognition and numerical modeling of engineering problems. A reliable database consisting of 64 experimental data is collected for the development of shear strength LGP models here. The obtained models are evaluated from both engineering and accuracy perspectives by means of several indicators and supplementary studies and the optimal model is presented for further purposes. Additionally, the capability of LGP is examined to be used as an alternative approach for the numerical analysis of engineering problems. Findings A new predictive model is proposed for the estimation of the shear strength of cyclically loaded circular RC columns using the LGP approach. To demonstrate the capability of the proposed model, the analysis results are compared to those obtained by some well-known models recommended in the existing literature. The results confirm the potential of the LGP approach for numerical analysis of engineering problems in addition to the fact that the obtained LGP model outperforms existing models in estimation and predictability. Originality/value This paper mainly represents the capability of the LGP approach as a robust alternative approach among existing analytical and numerical methods for modeling and analysis of relevant engineering approximation and estimation problems. The authors are confident that the shear strength model proposed can be used for design and pre-design aims. The authors also declare that they have no conflict of interest.


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