• Advances in nano research
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• v.11 no.6
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• pp.595-606
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• 2021

This paper conducted mainly for forecasting the behavior of the shear connectors in steel-concrete composite beams based on the different factors. The main goal was to analyze the influence of variable parameters on the shear strength of C-shaped and L-shaped angle shear connectors. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data in order to select the most influential factors for the mentioned shear strength forecasting. Five inputs are considered: height, length, thickness of shear connectors together with concrete strength and respective slip of the shear connectors after testing. The ANFIS process for variable selection was also implemented in order to detect the predominant factors affecting the forecasting of the shear strength of C-shaped and L-shaped angle shear connectors. The results show that the forecasting methodology developed in this research is useful for enhancing the multiple performances characterizing in the shear strength prediction of C and L shaped angle shear connectors analyzing.

• Structural Engineering and Mechanics
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• v.58 no.3
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• pp.475-514
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• 2016

Various models have been proposed by several researchers for predicting the exterior RC beam-column joint shear strength. Most of these models were calibrated and verified with some limited experimental database. From the models it has been identified that the joint shear strength majorly depends on ten governing parameters. In the present paper, detailed investigation of twelve analytical models for predicting shear strength of exterior beam-column joint has been carried out. The study shows the effect of each governing parameter on joint shear strength predicted by various models. It has been observed that the consensus on effect of few of the governing parameters amongst the considered analytical models has not been attained. Moreover, the predicted joint strength by different models varies significantly. Further, the prediction of joint shear strength by these analytical models has also been compared with a set of 200 experimental results from the literature. It has been observed that none of the twelve models are capable of predicting joint shear strength with sufficient accuracy for the complete range of experimental results. The research community has to reconsider the effect of each parameters based on larger set of test results and new improved analytical models should be proposed.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.05a
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• pp.367-370
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• 2005

This study is to propose a truss model which is able to reasonably predict the shear strength of reinforced concrete (RC) members with high-strength materials. The shear strengths of 107 RC test beams with high-strength steel bars reported in the technical literatures were compared to those obtained from proposed model, TATM, and existing truss models. The shear strength of reinforced concrete beams obtained from test was better predicted by TATM than other truss models. Also, the theoretical results by TATM were almost constant regardless of yield strengths and steel ratios of tension and shear reinforcements.

• Proceedings of the Korea Concrete Institute Conference
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• 1998.04b
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• pp.463-468
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• 1998

This paper presents the shear behavior in reinforced normal and high-strength concrete beams with Belite cement due to the increase of concrete compressive strength. The shear tests were conducted on thirty two beam specimens having concrete compressive strengths of 350 and 600kg/$\textrm{cm}^2$. The major experimental variables are compressive strength of concrete, shear span to depth ratio, and shear reinforcement ratio. The shear responses as to each variable are discussed in terms of shear capacity. The comparison of prediction equations with test results is also presented.

• Proceedings of the Korea Concrete Institute Conference
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• 2001.05a
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• pp.69-74
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• 2001

Steel plate or fiber composite plate are mainly used in externally bonding method. Shear strengthening by externally bonding method is to confirm shear safety and to avoid brittle failure. In case of strengthening by externally bonding method, a failure of structure occurs frequently due to delamination between strengthening plate and concrete. Therefore, it is important to consider the delamination in the strengthening design. The objective of this study is to propose a modified shear strength evaluation by considering the delamination. The delamination criteria of strengthening plate is established by the ultimate strain and shear stress. And shear strength of RC beams is proposed in terms of the delamination criteria. The proposed shear strength is compared with test results and verified through the comparison.

• Journal of the Korea Concrete Institute
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• v.12 no.5
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• pp.101-110
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• 2000

A practical approach of calculating the ultimate strength of composite beams with unreinforced web opning is proposed through shear behavioral tests. In this method, the slab shear contribution at the opening is calculated as the smaller value of the pullout capacity of shear connector at the high moment end and the one way shear capacity of slab. A simple interaction equation is used to predict the ultimate strength under simultaneous bending moment and shear force. Strength prediction by the proposed method is compared with previous test results and the predictions by other analytical methods. The comparison shows that the proposed method predicts the ultimate capacity with resonable accuracy.

• Steel and Composite Structures
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• v.38 no.4
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• pp.431-445
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• 2021

This paper presents experiments and theoretical analysis on shear behavior of eight concrete-encased square concrete-filled steel tube (CECFST) specimens and three traditional reinforced concrete (RC) specimens. A total of 11 specimens with the test parameters including the shear span-to-depth ratio, steel tube size and studs arrangement were tested to explore the shear performance of CECFST specimens. The failure mode, shear capacity and displacement ductility were thoroughly evaluated. The test results indicated that all the test specimens failed in shear, and the CECFST specimens enhanced by the interior CFST core exhibited higher shear capacity and better ductility performance than that of the RC specimens. When the other parameters were the same, the larger steel tube size, the smaller shear span-to-depth ratio and the existence of studs could lead to the more satisfactory shear behavior. Then, based on the compatible truss-arch model, a set of formulas were developed to analytically predict the shear strength of the CECFST members by considering the compatibility of deformation between the truss part, arch part and the steel tube. Compared with the calculated results based on several current design specifications, the proposed formulas could get more accurate prediction.

• Magazine of the Korea Concrete Institute
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• v.6 no.6
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• pp.190-198
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• 1994

Th~s paper presents the shear behavior in reinforced normal, medium and high strength con crete beams due to the Increase of concrete compressive strength. Twelve shear tests were con ducted on full scale beam speclrnerls havmg concrete compressive stlengths of 360, 670 and 873kg/$cm^2$. Different amounts of shear reinforcement as a variable were investigated according to ACI 318 89. The shear responses are discussed in terms of the shear capacity. the ductility and the reserved strength. The prediction and comparison with the test results are also presented.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.18 no.2
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• pp.201-211
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• 2005

Due to the complex mechanism and various parameters that affect shear behavior of reinforced concrete (RC) members, models on shear tend to be complex and difficult to utilize for design of structural members, and empirical relationships formulated with limited test data often work lot members having a specific range of influencing parameters on shear. As an alternative approach tot solving this problem, artificial neural networks have been suggested by some researchers. In this paper, artificial neural networks were used to predict shear strengths of RC beams without shear reinforcement. Especially, a large database that consists of shear test results of 398 RC members without shear reinforcement was used for artificial neural network analysis. Three well known approaches for shear strength of RC members, ACI 318-02 shear provision, Zsutiy's equation, and Okamura's relationship, are also evaluated with test results in the shear database and compared with neural network approach. While ACI 318-02 provided inaccurate predictions for RC members without shear reinforcement, the empirical equations by Zsutty and Okamura provided more improved prediction of Shear strength than ACI 318-02. The artificial neural networks, however provided the best prediction of shear strengths of RC beams without shear reinforcement that was closest to test results.

• Computers and Concrete
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• v.14 no.4
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• pp.479-501
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• 2014

This paper presents the improvement of the EC-2 and EHE-08 shear strength formulations for concrete beams with shear reinforcement. The employed method is based on the genetic programming (GP) technique, which is configured to generate symbolic regression from a set of experimental data by considering the interactions among precision, accuracy, safety and simplicity. The size effect and the influence of the amount of shear reinforcement are examined. To develop and verify the models, 257 experimental tests on concrete beams from the literature are used. Three expressions of considerable simplicity, which significantly improve the shear strength prediction with respect to the formulations of the different studied codes, are proposed.