• Steel and Composite Structures
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• v.51 no.5
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• pp.529-543
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• 2024

The bonding efficacy of steel I-section embedded in metakaolin-fly ash-based geopolymer concrete (MK-FA-GC) was investigated in this study. Push-out tests were conducted on nine column specimens to evaluate the influence of compressive strength of concrete, embedded length of steel I-section, thickness of concrete cover, and stirrup ratio on the bond performance. Failure patterns, load-slip relationships, bond strength, and distribution of bond stress among the specimens were analyzed. The characteristic bond strength of geopolymer concrete (GC) increased with higher compressive strength, longer embedded steel section length, thicker concrete cover, and larger stirrup ratio. Empirical formulas for bond strength at the loading end were derived based on experimental data and a bond-slip constructive model for steel-reinforced MK-FA-GC was proposed. The calculated bond-slip curves showed good agreement with experimental results. Furthermore, numerical simulations using ABAQUS software were performed on column specimens by incorporating the suggested bond-slip relationship into connector elements to simulate the interface behavior between MK-FA-GC and the steel section. The simulation results showed a good correlation with the experimental findings.

• Computers and Concrete
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• v.29 no.6
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• pp.433-444
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• 2022

Concrete's compressive strength is widely studied in order to understand many qualities and the grade of the concrete mixture. Conventional civil engineering tests involve time and resources consuming laboratory operations which results in the deterioration of concrete samples. Proposing efficient non-destructive models for the prediction of concrete compressive strength will certainly yield advancements in concrete studies. In this study, the efficiency of using radial basis function neural network (RBFNN) which is not common in this field, is studied for the concrete compressive strength prediction. Complementary studies with back propagation neural network (BPNN), which is commonly used in this field, have also been carried out in order to verify the efficiency of RBFNN for compressive strength prediction. A total of 13 input parameters, including novel ones such as cement's and fly ash's compositional information, have been employed in the prediction models with RBFNN and BPNN since all these parameters are known to influence concrete strength. Three different train: test ratios were tested with both models, while different hidden neurons, epochs, and spread values were introduced to determine the optimum parameters for yielding the best prediction results. Prediction results obtained by RBFNN are observed to yield satisfactory high correlation coefficients and satisfactory low mean square error values when compared to the results in the previous studies, indicating the efficiency of the proposed model.

• Structural Engineering and Mechanics
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• v.53 no.6
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• pp.1183-1200
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• 2015

Reinforcement corrosion can cause serious safety deterioration to aging concrete structures exposed in aggressive environments. This paper presents an approach for reliability analyses of deteriorating reinforced concrete structures affected by reinforcement corrosion on the basis of the representative symptoms identified during the deterioration process. The concrete cracking growth and rebar bond strength evolution due to reinforcement corrosion are chosen as key symptoms for the performance deterioration of concrete structures. The crack width at concrete cover surface largely depends on the corrosion penetration of rebar due to the expansive rust layer at the bond interface generated by reinforcement corrosion. The bond strength of rebar in the concrete correlates well with concrete crack width and decays steadily with crack width growth. The estimates of cracking development and bond strength deterioration are examined by experimental data available from various sources, and then matched with symptom-based lifetime Weibull model. The symptom reliability and remaining useful life are predicted from the predictive lifetime Weibull model for deteriorating concrete structures. Finally, a numerical example is provided to demonstrate the applicability of the proposed approach for forecasting the performance of concrete structures subject to reinforcement corrosion. The results show that the corrosion rate has significant impact on the reliability associated with serviceability and load bearing capacity of reinforced concrete structures during their service life.

• KCI Concrete Journal
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• v.13 no.1
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• pp.19-25
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• 2001

Based on the orthotropic hypoelasticity formulation, a constitutive material model of concrete taking account of triaxial stress state is presented. In this model, the ultimate strength surface of concrete in triaxial stress space is described by the Hsieh's four-parameter surface. On the other hand, the different ultimate strength surface of concrete in strain space is proposed in order to account for increasing ductility in high confinement pressure. Compressive ascending and descending behavior of concrete is considered. Concrete cracking behavior is considered as a smeared crack model, and after cracking, the tensile strain-softening behavior and the shear mechanism of cracked concrete are considered. The proposed constitutive model of concrete is compared with some results obtained from tests under the states of uniaxial, biaxial, and triaxial stresses. In triaxial compressive tests, the peak compressive stress from the predicted results agrees well with the experimental results, and ductility response under high confining pressure matches well the experimental result. The reinforcing bars embedded in concrete are considered as an isoparametric line element which could be easily incorporated into the isoparametric solid element of concrete, and the average stress - average strain relationship of the bar embedded in concrete is considered. From numerical examples for a reinforced concrete simple beam and a structural beam type member, the stress state of concrete in the vicinity of talc critical region is investigated.

• Earthquakes and Structures
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• v.7 no.5
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• pp.647-665
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• 2014

Squat reinforced concrete walls require enough shear strength in order to promote flexural yielding, which creates the need for designers of an accurate method for strength prediction. In many cases, especially for existing buildings, strength estimates might be insufficient when more accurate analyses are needed, such as pushover analysis. In this case, estimates of load versus displacement are required for building modeling. A model is developed that predicts the shear load versus shear deformation of squat reinforced concrete walls by means of a panel formulation. In order to provide a simple, design-oriented tool, the formulation considers the wall as a single element, which presents an average strain and stress field for the entire wall. Simple material constitutive laws for concrete and steel are used. The developed models can be divided into two categories: (i) rotating-angle and (ii) fixed-angle models. In the first case, the principal stress/strain direction rotates for each drift increment. This situation is addressed by prescribing the average normal strain of the panel. The formation of a crack, which can be interpreted as a fixed principal strain direction is imposed on the second formulation via calibration of the principal stress/strain direction obtained from the rotating-angle model at a cracking stage. Two alternatives are selected for the cracking point: fcr and 0.5fcr (post-peak). In terms of shear capacity, the model results are compared with an experimental database indicating that the fixed-angle models yield good results. The overall response (load-displacement) is also reasonable well predicted for specimens with diagonal compression failure.

• Journal of the Regional Association of Architectural Institute of Korea
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• v.20 no.6
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• pp.17-23
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• 2018

The purpose of this study is to suggest 100MPa class ultra high strength concrete mix design model applying neural network theory, in order to minimize an effort wasted by trials and errors method until now. Mix design model was applied to each of the 70 data using binary binder, ternary binder and quaternary binder. Then being repeatedly applied to back-propagation algorithm in neural network model, optimized connection weight was gained. The completed mix design model was proved, by analyzing and comparing to value predicted from mix design model and value measured from actual compressive strength test. According to the results of this study, more accurate value could be gained through the mix design model, if error rate decreases with the test condition and environment. Also if content of water and binder, slump flow, and air content of concrete apply to mix design model, more accurate and resonable mix design could be gained.

• Computers and Concrete
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• v.33 no.6
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• pp.643-658
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• 2024

To date, shell-solid and fibre element model analysis are the most commonly used methods to investigate the seismic performance of concrete-filled steel tube (CFST) bridge piers. However, most existing research does not consider the loss of bearing capacity caused by the fracture of the outer steel tube. To fill this knowledge gap, a refined finite element (FE) model considering the ductile damage of steel tubes and the behaviour of infilled concrete with cracks is established and verified against experimental results of unidirectional, bidirectional cyclic loading tests and pseudo-dynamic loading tests. In addition, a parametric study is conducted to investigate the seismic performance of CFST bridge piers with different concrete strength, steel strength, axial compression ratio, slenderness ratio and infilled concrete height using the proposed model. The validation shows that the proposed refined FE model can effectively simulate the residual displacement of CFST bridge piers subjected to highintensity earthquakes. The parametric analysis indicates that CFST piers hold sufficient strength reserves and sound deformation capacity and, thus, possess excellent application prospects for bridge construction in high-intensity areas.

• Earthquakes and Structures
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• v.9 no.6
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• pp.1233-1250
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• 2015

The behavior of reinforced concrete (RC) columns made from high strength materials was investigated experimentally. Six high-strength concrete specimen columns (1:4 scale), which included three with high-strength transverse reinforcing bars and three with normal-strength transverse reinforcement, were tested under double curvature bending load. The effects of yielding strength and ratio of transverse reinforcement on the cracking patterns, hysteretic response, shear strength, ductility, strength reduction, energy dissipation and strain of reinforcement were studied. The test results indicated that all specimens failed in splitting failure, and specimens with high-strength transverse reinforcement exhibited better seismic performance than those with normal-strength transverse reinforcement. It also demonstrated that the strength of high-strength lateral reinforcing bars was fully utilized at the ultimate displacements. Shear strength formula of short concrete columns, which experienced a splitting failure, was proposed based on the Chinese concrete code. To enhance the applicability of the model, it was corroborated with 47 short concrete columns selected from the literature available. The results indicated that, the proposed method can give better predictions of shear strength for short columns that experienced a splitting failure than other shear strength models of ACI 318 and Chinese concrete codes.

• Computers and Concrete
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• v.29 no.5
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• pp.303-321
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• 2022

The current design equations for predicting the torsional capacity of RC members underestimate the torsional strength of under-reinforced members and overestimate the torsional strength of over-reinforced members. This is because the design equations consider only the yield strength of torsional reinforcement and the cross-sectional properties of members in determining the torsional capacity. This paper presents an analytical model to predict the thickness of shear flow path in RC beams subjected to pure torsion. The analytical model assumes that torsional reinforcement resists torsional moment with a sufficient deformation capacity until concrete fails by crushing. The ACI 318 code is modified by applying analytical results from the proposed model such as the average stress of torsional reinforcement and the effective gross area enclosed by the shear flow path. Comparison of the calculated and observed torsional strengths of existing 129 test beams showed good agreement. Two design variables related to the compressive strength of concrete in the proposed model are approximated for design application. The accuracy of the ACI 318 code for the over-reinforced test beams improved somewhat with the use of the approximations for the average stresses of reinforcements and the effective gross area enclosed by the shear flow path.

• International Journal of Highway Engineering
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• v.6 no.1 s.19
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• pp.37-45
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• 2004

The characteristics of concrete strength and fracture parameters of recycled aggregate concrete were investigated to apply to the concrete pavements. As the results, the early strength of recycled aggregate concrete showed to be lower than that of natural coarse aggregate concrete, whereas strength at 28 days showed to be similar. Young's modulus of recycled aggregate concrete was lower than that of natural coarse aggregate concrete due to the difference of aggregate strength. And recycled aggregate concrete contained with ground granulated blast furnace slag seemed to have an effect of strength increasing. The critical stress intensity factor of recycled aggregate concrete at the early age was increased, and converged to be similar, compared to natural aggregate concrete at later age. The reliability of two-parameter fracture model was identified by the good correlation between the theoretical value computed by P-CMOD relationship and experimental results for Young's modulus and tensile strength.