• Steel and Composite Structures
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• v.14 no.3
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• pp.229-242
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• 2013

Corrosion is important reason for the deterioration of the bond between reinforcing steel and the surrounding concrete. Corrosion of the steel mainly depends on its microstructure. Smooth S220, ribbed S420 and S500 grade reinforcing steels were used in the experiments. Samples were subjected to accelerated corrosion. Pullout tests were carried out to evaluate the effects of corrosion on bond strength of the specimens. S500 grade steel which has tempered martensite microstructure showed lower corrosion rate in concrete than S220 and S420 steels which have ferrite+perlite microstructure. S500 grade steel showed highest bond strength among the other steel grades in concrete. Bond strength between reinforcing steel and concrete increased with increase in the strength of steel and concrete. It also depends on whether reinforcing bar is ribbed or not.

• Advances in concrete construction
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• v.1 no.2
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• pp.187-200
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• 2013

The damage level in structures (global scale), elements (intermediate scale) and sections (local scale) can be evaluated using a single parameter called the "Damage Index". Part of the damage attributed to the local scale relates to the damage sustained by the materials of which the section is made. This study investigates the damage of concrete subjected to monotonic compressive loading using four different damage models - one proposed here for the first time and three other well-known models. The analytical results show that the proposed model is promising yet simple and effective for evaluating the damage of concrete. The proposed damage model of concrete with its promising characteristics indicated, appears to be a useful tool in the damage assessment of structures made of concrete.

• Advances in concrete construction
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• v.1 no.2
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• pp.151-162
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• 2013

The performance characteristics of high-strength and high-performance concrete are discussed in this review. Recent developments in the field of high-performance concrete marked a giant step forward in high-tech construction materials with enhanced durability, high compressive strength and high modulus of elasticity particularly for industrial applications. There is a growing awareness that specifications requiring high compressive strength make sense only when there are specific strength design advantages. HPC today employs blended cements that include silica fume, fly ash and ground granulated blast-furnace slag. In typical formulations, these cementitious materials can exceed 25% of the total cement by weight. Silica fume contributes to strength and durability; and fly ash and slag cement to better finish, decreased permeability, and increased resistance to chemical attack. The influences of various mineral admixtures such as fly ash, silica fume, micro silica, slag etc. on the performance of high-strength concrete are discussed.

• Computers and Concrete
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• v.18 no.5
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• pp.1053-1063
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• 2016

As concrete is most usable material in construction industry it's been required to improve its quality. Nowadays, nanotechnology offers the possibility of great advances in construction. For the first time, the nonlinear buckling of straight concrete columns armed with single-walled carbon nanotubes (SWCNTs) resting on foundation is investigated in the present study. The column is modelled with Euler-Bernoulli beam theory. The characteristics of the equivalent composite being determined using the Mori-Tanaka model. The foundation around the column is simulated with spring and shear layer. Employing nonlinear strains-displacements, energy methods and Hamilton's principal, the governing equations are derived. Differential quadrature method (DQM) is used in order to obtain the buckling load of structure. The influences of volume percent of SWCNTs, geometrical parameters, elastic foundation and boundary conditions on the buckling of column are investigated. Numerical results indicate that reinforcing the concrete column with SWCNTs, the structure becomes stiffer and the buckling load increases with respect to concrete column armed with steel.

• Computers and Concrete
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• v.19 no.1
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• pp.33-39
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• 2017

In this study, two types of aggregate were used for making self-compacting concrete. Standard cubic specimens were exposed to different temperatures. Seventy-two standard cylindrical specimens ($150{\times}300mm$) and Seventy-two cubic specimens (150 mm) were tested. Compressive strengths of the manufactured specimens at $23^{\circ}C$ were about 33 MPa to 40 MPa. The variable parameters among the self-compacting concrete specimens were of sand stone type. The specimens were exposed to 23, 100, 200, 400, 600, and $800^{\circ}C$ and their mechanical specifications were controlled. The heated specimens were subjected to the unconfined compression test with a quasi-static loading rate. The corresponding stress-strain curves and modulus of elasticity were compared. The results showed that, at higher temperatures, Scoria aggregate showed less sensitivity than ordinary aggregate. The concrete made with Scoria aggregate exhibited less strain. The heated self-compacting concrete had similar slopes before and after the peak. In fact, increasing heat produced gradual symmetrical stress-strain diagram span.

• Steel and Composite Structures
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• v.29 no.1
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• pp.67-75
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• 2018

High performance concrete (HPC) depends on various parameters such as the type of cement, aggregate and water reducer amount. Generally, the ready concrete company in various regions according to the requirements and costs, mix design of concrete as well as type of cement, aggregates, and, amount of other components will vary as a result of moment decisions or dynamic optimization, though the ideal conditions will be more applicable for the design of mix proportion of concrete. This study aimed to apply dynamic optimization for mix design of HPC; consequently, the objective function, decision variables, input and output variables and constraints are defined and also the proposed dynamic optimization model is validated by experimental results. Results indicate that dynamic optimization objective function can be defined in such a way that the compressive strength or performance of all constraints is simultaneously examined, so changing any of the variables at each step of the process input and output data changes the dynamic of the process which makes concrete mix design formidable.

• Structural Engineering and Mechanics
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• v.74 no.4
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• pp.559-565
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• 2020

This paper intends to progress models to accurately estimate the behavior of fresh concrete under vibration using artificial neural networks (ANNs). To this end, behavior of a full scale precast concrete mold was investigated numerically. Experimental study was carried out under vibration with the use of a computer-based data acquisition system. In this study measurements were taken at three points using two vibrators. Transducers were used to measure time-dependent lateral displacements at these points on mold while both mold is empty and full of fresh concrete. Modeling of empty and full mold was made using ANNs. Benefiting ANNs used in this study for modeling fresh concrete, mold design can be performed. For the modeling of ANNs: Experimental data were divided randomly into two parts such as training set and testing set. Training set was used for ANN's learning stage. And the remaining part was used for testing the ANNs. Finally, ANN modeling was compared with measured data. The comparisons show that the experimental data and ANN results are compatible.

• Structural Engineering and Mechanics
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• v.18 no.1
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• pp.21-40
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• 2004

In this paper, we modify the L-L model (Li et al. 2003) and extend the application of this model to concrete confined by both steel reinforcement and CFRP. Thirty-six concrete cylinders with a dimension of ${\varphi}30{\times}60$ cm were tested to verify the effectiveness of the proposed model. The experimental test results show that different types of steel reinforcement have a great effect on the compressive strength of concrete cylinders confined by steel reinforcement, but the different types of steel reinforcement have very little effect on concrete cylinders confined by both steel reinforcement and CFRP. Compared with the stress-strain curves of confined concrete cylinders, we can conclude that the proposed model can provide more effective prediction than others models.

• Structural Engineering and Mechanics
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• v.16 no.1
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• pp.83-99
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• 2003

The aim of this paper is to develop the ISCOSTFUN (Intelligent System for Prediction of Concrete Strength by Functional Networks) in order to provide in-place strength information of the concrete to facilitate concrete from removal and scheduling for construction. For this purpose, the system is developed using Functional Network (FN) by learning functions instead of weights as in Artificial Neural Networks (ANN). In serial functional network, the functions are trained from enough input-output data and the input for one functional network is the output of the other functional network. Using ISCOSTFUN it is possible to predict early strength as well as 7-day and 28-day strength of concrete. Altogether seven functional networks are used for prediction of strength development. This study shows that ISCOSTFUN using functional network is very efficient for predicting the compressive strength development of concrete and it takes less computer time as compared to well known Back Propagation Neural Network (BPN).

• Computers and Concrete
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• v.17 no.5
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• pp.567-578
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• 2016

As concrete is most usable material in construction industry it's been required to improve its quality. Nowadays, nanotechnology offers the possibility of great advances in construction. For the first time, the nonlinear buckling of straight concrete columns armed with single-walled carbon nanotubes (SWCNTs) resting on foundation is investigated in the present study. The column is modelled with Euler-Bernoulli and Timoshenko beam theories. The characteristics of the equivalent composite being determined using mixture rule. The foundation around the column is simulated with spring and shear layer. Employing nonlinear strains-displacements, energy methods and Hamilton's principal, the governing equations are derived. Differential quadrature method (DQM) is used in order to obtain the buckling load of structure. The influences of volume percent of SWCNTs, geometrical parameters, elastic foundation and boundary conditions on the buckling of column are investigated. Numerical results indicate that reinforcing the concrete column with SWCNTs, the structure becomes stiffer and the buckling load increases with respect to concrete column armed with steel.