• Journal of the Korea Concrete Institute
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• v.24 no.3
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• pp.225-232
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• 2012

This paper presents the test results on the shear performance of large-size reinforced concrete beams using recycled fine aggregate to evaluate its applicability to structural concrete. The performance of these beams is compared to that of similar beams casted with natural coarse and fine aggregates. All of the beam specimens without shear reinforcement had $400mm{\times}600mm$ rectangular cross section and a shear span ratio (a/d) of 5.0. Five concrete mixtures with different replacement levels of recycled fine aggregates (0, 30, 60, 70 and 100%) were used to obtain a nominal concrete compressive strength of 28MPa. The test results of load-deflection curve, shear deformation, diagonal cracking load, crack pattern, ultimate shear strength, and failure mode are examined and compared. In addition, code and empirical equations from KCI, JSCE, CSA, Zsutty, and MCFT were considered to evaluate the applicability of these equations for predicting shear strength of reinforced concrete beam with recycled fine aggregate. The results showed that the overall shear behavior of reinforced concrete beams incorporating less than 60% recycled fine aggregate was comparable with that of conventional concrete beam. The MCFT gave good prediction and other code equations were conservative in predicting the shear strength of the tested beams. The beam specimens with replacement of 70 and 100% of natural fine aggregates by recycled fine aggregates showed different failure mode than other tested beams.

• Proceedings of the Korea Concrete Institute Conference
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• 1997.10a
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• pp.603-608
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• 1997

Studies on the second-order analysis of reinforced concrete columns have been chiefly dealt with symmetric section under uniaxial loading. In practical situations, however, columns are subjected to biaxial loadings. Therefore, for more accurate prediction of the behavior of concrete columns under biaxial loading, the interaction between bending moments of major and minor axes should be considered. Recently Kim & Lee proposed a numerical method of predicting the behavior of concrete columns under biaxial loading. In this paper, to investigate the behavior of concrete columns under biaxial loading and verify the validity of proposed method, a series of test were carried out for sixteen tied reinforced columns with 100${\times}$100mm square and 200${\times}$100mm rectangular sections under various loading conditions. The length of columns was 1,300mm and the concrete strength was 28MPa. The boundary conditions at the both ends were hinged and end eccentricities were equal(400mm). Proposed numerical analyses applied to the test piece were performed to predict behavior of concrete columns with square and rectangular sections under various loading conditions. Test results were also compared with those using the moment magnifier method in ACI code. The test results showed that the moment magnifier method is conservative.

• Steel and Composite Structures
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• v.48 no.5
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• pp.531-545
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• 2023

Composite dowels are implemented as a powerful alternative to headed studs for the efficient combination of Ultra High-Performance Concrete (UHPC) with high-strength steel in novel composite structures. They are required to provide sufficient shear resistance and ensure the transmission of tensile forces in the composite connection in order to prevent lifting of the concrete slab. In this paper, the load bearing capacity of puzzle-shaped and clothoidal-shaped dowels encased in UHPC specimen were investigated based on validated experimental test data. Considering the influence of the embedment depth and the spacing width of shear dowels, the characteristics of UHPC square plate on the load bearing capacity of composite structure, 240 numeric models have been constructed and analyzed. Three artificial intelligence approaches have been implemented to learn the discipline from collected experimental data and then make prediction, which includes Artificial Neural Network-Particle Swarm Optimization (ANN-PSO), Adaptive Neuro-Fuzzy Inference System (ANFIS) and an Extreme Learning Machine (ELM). Among the factors, the embedment depth of composite dowel is proved to be the most influential parameter on the load bearing capacity. Furthermore, the results of the prediction models reveal that ELM is capable to achieve more accurate prediction.

• Journal of the Korea Concrete Institute
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• v.15 no.4
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• pp.513-521
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• 2003

Existing tests results have shown that confining the concrete compression region with closed stirrups improves the ductility and load-carrying capacity of beams. However, only few researchers have attempted to utilize the beneficial effects of the presence of these stirrups in design. This paper presents the result of experimental studies on the load-deflection behavior and the strengthening effect of laterally confined structural high-strength concrete beam members in which confinement stirrups have been introduced into the compression regions. Fifteen tests were conducted on full-scale beam specimens having concrete compressive strength of 41 MPa and 61 MPa. Different spacing of stirrups(0.25∼1.0d) and amount of tension steel($0.55{\sim}0.7{\rho}_b$) as major variables were investigated. And also, this study present an appropriate shear equation for decision of ultimate failure modes of high-strength concrete beams according to stirrup spacing. The equation is based on interaction between shear strength and displacement ductility. Prediction of failure mode from presented method and comparison with test results are also presenteded

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4A
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• pp.537-548
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• 2008

Recently, the prestressed unbonded concrete structures are increasingly being built. The mechanical behavior of prestressed concrete beams with unbonded tendon is different from that of normal bonded PSC beams in that the increment of tendon stress was derived by whole member behavior. The purpose of the present paper is therefore to evaluate the flexural behavior and to propose the equation of ultimate tendon stress by performing static flexural test according to span/depth, concrete compression strength, reinforcement ratio and the effect of existing bonded tendon. From experimental results, for cracking, yielding and ultimate load, the effect of reinforcement ratio was more effective than concrete compression strength, and the beams having high strength concrete had a good performance than having low concrete, but there was no difference between high strength and low strength. And as L/dp was larger, test beams had a long region of ductility. This means that unbonded tendon has a large contribution after reinforcement yielding. Especially, the equation of ACI-318 was not match with test results and had no correlations. After analysis of test results, the equation of ultimate unbonded tendon stress without slip was proposed, and the proposed equation was well matched with test results. So the proposed equation in this paper will be a effective basis for the evaluation of unbonded tendons without slip, analysis and design.

• Structural Engineering and Mechanics
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• v.70 no.5
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• pp.639-647
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• 2019

The performance of precast concrete structures is greatly influenced by the behaviour of beam-to-column connections. A single connection may be required to transfer several loads simultaneously so each one of those loads must be considered in the design. A good connection combines practicality and economy, which requires an understanding of several factors; including strength, serviceability, erection and economics. This research work focuses on the performance aspect of a specific type of beam-to-column connection using partly hidden corbel in precast concrete structures. In this study, the results of experimental assessment of the proposed beam-to-column connection in precast concrete frames was used. The purpose of this research is to develop and apply the Extreme Learning Machine (ELM) for moment-rotation prediction of precast beam-to-column connections. The ELM results are compared with genetic programming (GP) and artificial neural network (ANN). The reliability of the computational models was accessed based on simulation results and using several statistical indicators.

• Steel and Composite Structures
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• v.44 no.3
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• pp.309-324
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• 2022

The post-fire elastic stiffness and performance of concrete-filled steel tube (CFST) columns containing recycled aggregate concrete (RAC) has rarely been addressed, particularly in terms of material properties. This study was conducted with the aim of assessing the modulus of elasticity of recycled aggregate concrete-filled steel tube (RACFST) stub columns following thermal loading. The test data were employed to model and assess the elastic modulus of circular RACFST stub columns subjected to axial loading after exposure to elevated temperatures. The length/diameter ratio of the specimens was less than three to prevent the sensitivity of overall buckling for the stub columns. The gene expression programming (GEP) method was employed for the model development. The GEP model was derived based on a comprehensive experimental database of heated and non-heated RACFST stub columns that have been properly gathered from the open literature. In this study, by using specifications of 149 specimens, the variables were the steel section ratio, applied temperature, yielding strength of steel, compressive strength of plain concrete, and elastic modulus of steel tube and concrete core (RAC). Moreover, parametric and sensitivity analyses were also performed to determine the contribution of different effective parameters to the post-fire elastic modulus. Additionally, comparisons and verification of the effectiveness of the proposed model were made between the values obtained from the GEP model and the formulas proposed by different researchers. Through the analyses and comparisons of the developed model against formulas available in the literature, the acceptable accuracy of the model for predicting the post-fire modulus of elasticity of circular RACFST stub columns was seen.

• Computers and Concrete
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• v.24 no.2
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• pp.159-172
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• 2019

This paper presents an investigation into the flexural behavior of reinforced concrete (RC) beams retrofitted by ultra-high performance fiber-reinforced concrete (UHPFRC) layers. The experimental study has been conducted in two parts. In the first part, four methods of retrofitting with UHPFRC layers in both the up and down sides of the beams have been proposed and their efficiency in the bonding of the normal concrete and ultra-high performance fiber-reinforced concrete has been discussed. The results showed that using the grooving method and the pre-casted UHPFRC layers in comparison with the sandblasting method and the cast-in-place UHPFRC layers leads to increase the load carrying capacity and the energy absorption capacity and causes high bond strength between two concretes. In the second part of the experimental study, the tests have been conducted on the beams with single UHPFRC layer in the down side and in the up side, using the effective retrofitting method chosen from the first part. The results are compared with those of non-retrofitted beam and the results of the first part of experimental study. The results showed that the retrofitted beam with two UHPFRC layers in the up and down sides has the highest energy absorption and load carrying capacity. A finite element analysis was applied to prediction the flexural behavior of the composite beams. A good agreement was achieved between the finite element and experimental results. Finally, a parametric study was carried out on full-scale retrofitted beams. The results indicated that in all retrofitted beams with UHPFRC in single and two sides, increasing of the UHPFRC layer thickness causes the load carrying capacity to be increased. Also, increases of the normal concrete compressive strength improved the cracking load of the beams.

• Journal of the Korean Society of Hazard Mitigation
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• v.3 no.4 s.11
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• pp.119-129
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• 2003

Concrete and steel are essential structural materials in the construction. But, concrete, different from steel, consists of many materials and is affected by many factors such as properties of materials, site environmental situations, and skill of constructors. Concrete have two kinds of properties, immediately knowing properties such as slump, air contents and time dependent one like strength. Therefore, concrete mixes depend on experiences of experts. However, at point of time using High Performance Concrete, new method is wanted because of more ingredients like mineral and chemical admixtures and lack of data. Artificial Neural Networks(ANN) are a mimic models of human brain to solve a complex nonlinear problem. They are powerful pattern recognizers and classifiers, also their computing abilities have been proven in the fields of prediction, estimation and pattern recognition. Here, among them, the back propagation network and radial basis function network ate used. Compositions of high-performance concrete mixes are eight components(water, cement, fine aggregate, coarse aggregate, fly ash, silica fume, superplasticizer and air-entrainer). Compressive strength, slump, and air contents are measured. The results show that neural networks are proper tools to minimize the uncertainties of the design of concrete mixtures.

• Structural Engineering and Mechanics
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• v.70 no.1
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• pp.13-31
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• 2019

A nonlinear finite element model (FEM) using ATENA-3D software to simulate the axially compressive behavior of circular steel tube confined concrete (CSTCC) columns infilled with ultra high performance concrete (UHPC) was presented in this paper. Some modifications to the material type "CC3DNonlinCementitious2User" of UHPC without and with the incorporation of steel fibers (UHPFRC) in compression and tension were adopted in FEM. The predictions of utimate strength and axial load versus axial strain curves obtained from FEM were in a good agreement with the test results of eighteen tested columns. Based on the results of FEM, the load distribution on the steel tube and the concrete core was derived for each modeled column. Furthermore, the effect of bonding between the steel tube and the concrete core was clarified by the change of friction coefficient in the material type "CC3DInterface" in FEM. The numerical results revealed that the increase in the friction coefficient leads to a greater contribution from the steel tube, a decrease in the ultimate load and an increase in the magnitude of the loss of load capacity. By comparing the results of FEM with experimental results, the appropriate friction coefficient between the steel tube and the concrete core was defined as 0.3 to 0.6. In addition to the numerical evaluation, eighteen analytical models for confined concrete in the literature were used to predict the peak confined strength to assess their suitability. To cope with CSTCC stub and intermediate columns, the equations for estimating the lateral confining stress and the equations for considering the slenderness in the selected models were proposed. It was found that all selected models except for EC2 (2004) gave a very good prediction. Among them, the model of Bing et al. (2001) was the best predictor.