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سال چهاردهم شماره 2 (تابستان 1400)

In high-rise concrete buildings, the external grid consists of a reinforced concrete shell, which has a large number of openings and is resistant to gravity and lateral loads. In this paper, the effect of opening distribution on reinforced concrete external grid is studied. For this purpose, high-rise reinforced concrete structures of 20, 30, 40 and 50 floors with external grid and in three different modes of opening in the external grid are considered. In model 1 (base model), the openings are regularly distributed in the external grid of the building, but in Model 2, the openings are concentrated in the middle of the grid funds and in Model 3, the openings are concentrated in the corners of the external grid. Selective parameters for estimating the optimal opening location in the external grid of high-rise reinforced concrete buildings are the lateral displacement of the floor and the drift index of each floor. Also, in order to determine the optimal location of the core, the percentage of shear absorption and moment due to the seismic force between the core and the external grid is investigated. The results showed that in buildings with low aspect ratio, the best position of the opening is the regular distribution of openings in the external grid, but in buildings with higher aspect ratio, the best location of the opening is in the middle parts of the external grid.

The use of concrete in special structures always faces challenges in implementation. By increasing the amount of cement to increase the compressive strength, the thermal gradient between the surface and the center of the concrete due to hydration heat will lead to an increase in thermal stress. On the other hand, due to the highly congested rebars in massive structural members of reinforced concrete such as columns of high-rise structures, the use of self-compacting concrete will facilitate the implementation and therefore understanding the thermal behavior of concrete and comparing it with ordinary concrete can be a good ground for studying crack risk. In this paper, the evaluation of thermal and mechanical properties affected by the application of high strength self-compacting mass concrete regime with three ratios of water to cement ratio and two cement content has been done in the form of twelve mixed designs. The results show that self-compacting concrete in addition to better mechanical properties on the surface and core of high strength mass concrete had different and more suitable thermal regime compared to ordinary concrete. Its lower strain and higher stress conversion time reduces thermal stress and ultimately reduces the risk of cracking up to thirty-six percent.

Concrete pavement bears dynamic loads and is exposed to destructive environmental effects. Abrasion resistance is one of the items that will be very effective in increasing the durability of concrete pavement. The abrasion resistance of concrete is more effective and drier under the influence of compressive strength, concrete surface curing technique, type of setting, curing, aggregate properties and test conditions. Today the factors affecting the wear and durability of concrete procedures, is of particular importance, so this study evaluates the strategies affecting the performance of compressive strength and Abrasion and durability of pavement concrete. A total of thirty cylindrical samples were created, with approximately half of them being used for Dorry wear evaluations. The type and of minerals type and constituents of stone materials has a direct effect on the abrasion resistance of roller concrete, so that increasing the abrasion resistance of stone materials increases the abrasion resistance of concrete. Of all the aggregates used in this research, aggregate No. 3 prepared from Choghart mine, tectonic block 1, has the highest wear resistance and compressive strength, which is very suitable for use in places where roller concrete pavement is exposed to wear and stress. The results of friction resistance are suitable for all samples and aggregates No. 4 and 3 showed the highest friction resistance on wet surfaces. The findings also show that Dorry wear test results with a dependence coefficient of 80% in roller concrete pavement is dependent on the wear of aggregates.

This study is aimed to examine the effect of Forta and polypropylene fibers on compressive behavior, modulus of elasticity, deformation, crack growth pattern, and absorbing energy of concrete materials. The laboratory specimens were made as cylindrical samples of 150 mm height and 100 mm diameter in two groups and 7 mix designs. Group A consists of two mix designs with 0.1 and 0.15 percentages of macrostetic fibers (Forta) with a water to cement ratio of 0.4. Group B specimens include three mixing designs with 0.2, 0.3 and 0.35 percentages of microsatellite fibers (Polypropylene) and with a water to cement ratio of 0.5. Digital Images Correlation (DIC) method has been used for measurement of displacements and strains in concrete specimens while finite element analysis (Abaqus software) has been used for the validation. The obtained results show that the absorbing energy is directly related to the amount of fiber used in the test. The fibers have a controlling effect on the cracks of the specimens so that they reduce the depth and the length of cracks. However, it should be noted that the number of cracks increased. The use of polypropylene fibers as reinforcing material reduced the compressive strength of the concrete specimens while it increased the ductility of specimens.

Today, concrete is regarded as one of the main materials in the construction industry, but besides its advantages, it is brittle and fragile and its tensile strength is lower than compressive strength. Due to the development of science and technology, the use of metal, polymer, glass and natural fibers in the construction industry is considered as an effective step in eliminating the poor tensile strength of ordinary concrete. Thus, in this research, the effect of steel and macro synthetic fibers on the behavioral model of concrete and mechanical properties (compressive and tensile strength, modulus of elasticity) and durability (electrical resistance, water permeability of concrete) have been investigated. Hence, in this research, 10 mixing designs with three different types of fibers, including steel, macro synthetic, polyolefin, and polypropylene fibers with 0.5, 1, 1.5 vol% were tested, and the results show that the steel fibers have no considerable effect on the compressive strength at a percentage higher than 0.5 and significantly increase the tensile strength and reduce the electrical resistance. The macro synthetic fibers of polyolefin and polypropylene have insignificant effect on compressive strength and even reduced compressive strength at high percentages and have a positive effect on tensile strength, electrical resistance, and water permeability, and the fibers can be used to increase the area under the stress-strain curve.

Self-compacting concrete (SCC) has more plastic viscosity and less yield strength due to using more fillers and superplasticizers. In order to achieve performance SCC, in addition to rheology, it is necessary to improve the mechanical properties and durability of concrete. Therefore, the amount of cement should be increased or cement replacement materials should be used. This increases the cost of one cubic meter of concrete and reduces the tendency to use it. In this research, by making 20 mixes of performance SCC, mechanical properties were determined by performing tests of compressive strength, tensile strength and elasticity modulus, and durability properties by tests of water penetration depth, rapid chloride penetration and sulfate resistance. Basically, the degree of technical desirability of concretes was determined. Also, by examining the cost price of one cubic meter of concrete, the economic and technical-economic desirabilities of the concretes were calculated. The results showed that the application of pozzolans in performance SCC reduced the technical desirability due to mechanical properties about 40%, but the technical desirability due to durability increased significantly, so that at the age of 91 days, about 5 times has become more. Accordingly, the final factor of technical desirability in SC mixtures of research is at least 26% and at most 250% more than the reference concrete. Due to the higher price of pozzolanic materials than cement, with the increase in the replacement rate of pozzolans, the economic desirability factor decreased to more than 50%, but the technical-economic desirability factor improved to about 60%.

Many concrete structures have been damaged due to natural disasters such as earthquake, wind, or corrosive fatigue. Therefore, the use of new technologies to modernize and improve these structures is important. Fiber reinforced polymer (CFRP) composites are widely used in retrofit and strengthening of reinforced concrete (RC) structures. FRP composites are applicable for strengthening various structural elements including beams, columns and plane elements such as floor slabs and shear walls. In this paper, the effect of surface preparation on concrete beams with carbon fabrics has been investigated. 8 Reinforced concrete beams were made by composite fibers and a concrete sample beam in the laboratory and tested for four-point bending loading Took. The experimental and Theoretical results of the proposed method have been presented in which the preparation in sandblasting, in addition to increasing the flexural strength, delayed the early detachment in the beams tested. It was also observed that the bending capacity in the beam increased with a 45.9% CFRP reinforcement layer and CFRP reinforcement layer 64.8% higher than that of the sample beam

According to recent research reports on the parameters involved in the retrofitting and reliability analysis of the concrete slabs connected to columns, Monte Carlo simulation has been introduced as a suitable method. However, a large number of analyzes are required to simulate the probability of failure. This, increases the volume of computations required. In the present study, a useful method is introduced to determine the effect of statistical parameters of random design variables on the probability of failure of slab connection. All the proposed relations are proved analytically and while providing a numerical example, the efficiency of these relations is clarified. The proposed method is based on radial basis function neural networks on the way to replace the analysis in the Monte Carlo method and reduce the computational volume. Therefore, with a combination of neural networks and Monte Carlo method, a new method is presented in the analysis of the reliability of slabs without shear steel. Sensitivity analysis is also presented to assess the effective parameters in the reliability analysis of punch design. Column dimensions, concrete compressive strength, live load, slab flexural reinforcement and slab thickness are evaluated as probabilistic design variables using both European Code (EC 2004) and American Concrete Institute relations (ACI 318_11). The results of validation in the proposed method indicate that the combined method of Monte Carlo and neural network with radial basis functions has an appropriate speed and sufficient accuracy. Also, a comparison of the results of the two codes, shows that EC2 (2004) offers a more economical design than the ACI. The reason for this is to consider the effect of flexural reinforcement on the punch capacity. Sensitivity analysis results show that although in both codes, the thickness of the slab has the greatest effect on the probability of connection failure, but in European code, the percentage of flexural steel has as similar effect as column dimensions and compressive strength of concrete effect. In the relations of ACI, after the thickness of the slab, only the compressive strength of concrete will have a significant effect on the probability of failure. Therefore, it can be concluded that although the flexural reinforcement provides the flexural strength of the slab, but also increases the punch shear strength of the slab by reducing the slab rotation. In general, the proposed method can be used in reviewing other design criteria, especially in credibility analysis and proper retrofitting of structures, due to the reduction of computational volume and appropriate accuracy.

Reactive powder concrete (RPC) is a type of ultra-high performance concrete (UHPC) with a high cementitious materials content. Coarse aggregates are removed in RPCs and ultra-fine powder materials such as silica sand, silica fume and pozzolans are used to provide a homogeneous concrete with excellent microstructure. In this study, the effect of limestone powder on the physical and mechanical properties of reactive powder concrete has been investigated. Limestone powder was replaced with different percentages of silica sand, and compressive strength, flexural strength, shrinkage, and water absorption percentage of samples were measured at 7, 28, and 90 days of age. Experimental results showed that the 28-day compressive strength of this concrete was greater than 100 MPa and the physical and mechanical properties of the concrete were improved by increasing the amount of stone powder The mixture containing 54% replacement of limestone powder had the highest compressive strength and the lowest water absorption. Also, replacing silica sand with limestone powder increases shrinkage due to drying and reduces the Autogenous shrinkage of reactive powder concrete.

Nowadays, intelligent methods inspired from nature are implemented to resolve complex problems, there are very popular too. The most common one is artificial neural network; they are capable to collect huge amount of complex information through experiments and tests. With increasing population and a rise in construction and also due to limited resources and consumable materials, demand for hot rolled earthquake-resistant materials in the construction industry has increased. The purpose of this research, by considering concrete mix design parameters as input, the Static neural network and Time-series modeling to predict the compressive strength of concrete will be used. Mixing fly ash and silica fume various designs with different percentages (1%, 5%, 7%, 10%, 12%, 15%, 18%) and mixed with silica fume, fly ashes identical percentages (% 1% 1% 3 and 3%, 5% and 5%, 7% and 7%, 9% and 9%, 10% and 10%) as a percentage of the weight of cement, to evaluate the performance of the models in question were applied. It turned out that neural network models for predicting time series with 5 neurons performance concrete compressive strength is accurate and reliable.