scholarly journals Influence Factors for the Shear Strength of Exterior and Interior Reinforced Concrete Beam-column Joints

2016 ◽  
Vol 142 ◽  
pp. 63-70 ◽  
Author(s):  
Minh Tung Tran
2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
De-Cheng Feng ◽  
Bo Fu

In this paper, an intelligent modeling approach is presented to predict the shear strength of the internal reinforced concrete (RC) beam-column joints and used to analyze the sensitivity of the influence factors on the shear strength. The proposed approach is established based on the famous boosting-family ensemble machine learning (ML) algorithms, i.e., gradient boosting regression tree (GBRT), which generates a strong predictive model by integrating several weak predictors, which are obtained by the well-known individual ML algorithms, e.g., DT, ANN, and SVM. The strong model is boosted as each weak predictor has its own weight in the final combination according to the performance. Compared with the conventional mechanical-driven shear strength models, e.g., the well-known modified compression field theory (MCFT), the proposed model can avoid the complicated derivation process of shear mechanism and calibration of the involved empirical parameters; thus, it provides a more convenient, fast, and robust alternative way for predicting the shear strength of the internal RC joints. To train and test the GBRT model, a total of 86 internal RC joint specimens are collected from the literatures, and four traditional ML models and the MCFT model are also employed as comparisons. The results indicate that the GBRT model is superior to both the traditional ML models and MCFT model, as its degree-of-fitting is the highest and the predicting dispersion is the lowest. Finally, the model is used to investigate the influences of different parameters on the shear strength of the internal RC joint, and the sensitivity and importance of the corresponding parameters are obtained.


2017 ◽  
Author(s):  
Rodolfo Giacomim Mendes de Andrade ◽  
Magno Teixeira Mota ◽  
Michèle Schubert Pfeil ◽  
Romildo Dias Toledo Filho ◽  
Ronaldo Carvalho Battista ◽  
...  

Materials ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1014 ◽  
Author(s):  
Yafei Ma ◽  
Baoyong Lu ◽  
Zhongzhao Guo ◽  
Lei Wang ◽  
Hailong Chen ◽  
...  

Shear strength is a widely investigated parameter for reinforced concrete structures. The corrosion of reinforcement results in shear strength reduction. Corrosion has become one of the main deterioration factors in reinforced concrete beam. This paper proposes a shear strength model for beams with inclined bars based on a limit equilibrium method. The proposed model can be applied to both corroded and uncorroded reinforced concrete beams. Besides the tensile strength of longitudinal steel bars, the shear capacity provided by the concrete on the top of the diagonal crack, the tensile force of the shear steel at the diagonal crack, the degradation of the cross-sectional area and strength of the reinforcements induced by corrosion are all considered. An experimental work on two groups accelerated corroded beams was performed. Good agreements were found between the proposed theoretical predictions and experimental observations.


2018 ◽  
Vol 30 (5) ◽  
pp. 543-551
Author(s):  
Dong-Hee Son ◽  
Joo-Hong Chung ◽  
Dong-Hoon Jwa ◽  
Joog-Min Lee ◽  
Chang-Sik Choi

2018 ◽  
Vol 188 ◽  
pp. 1234-1248 ◽  
Author(s):  
Zhao-Hui Lu ◽  
Hai Li ◽  
Wengui Li ◽  
Yan-Gang Zhao ◽  
Wenkui Dong

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