Browsing by Author "Ozturk, AU"

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    Effects of Admixture Type and Dosage on Microstructural and Mechanical Properties of Cement Mortars
    Ozturk, AU; Baradan, B
    Effects of admixture type and dosage have been investigated in the scope of this study. The influence of incorporation of chemical admixtures at different dosages on the development of pore structure of cement mortars has also been investigated. A delay on the development rate of strength by incorporation of chemical admixtures at early ages has been determined. The highest strength values were obtained for the cement mortars prepared by naphthalene sulphonate based chemical admixture. The strength values of specimens prepared with overdosage were lower than those of control specimens. Therefore, setting time and flow values were investigated related to admixture dosage and type. Increase in dosage of admixtures results in an increase of setting time and flow values. The pore structure development was given by time and dosage. Maximum pore area ratio values are determined for cement mortars prepared with overdosage. Pore area ratio values decrease by time, as compressive strength values increase.
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    Microstructure - macro property model proposal
    Ozturk, AU; Onal, O; Baradan, B
    A relationship between the microstructure formation and compressive strength of cement mortars has been established within this study. Microstructure properties such as pore area ratio, total pore length, total dendrite length and average roundness of pore phases were determined by microstructural investigations. In addition, the hydrated part area, calcium hydroxide phase area and unhydrated part area ratios were calculated based on image analysis. Six parameters (pore area ratio, total pore length, total dendrite length, average roundness, hydrated part area ratio and unhydrated part area ratio) were correlated to the compressive strength values of different mixtures. Multiple linear regression investigations indicated that determination of only two parameters (total dendrite length and hydrated part area ratio) is sufficient enough to represent the relationship of microstructural formation-compressive strength confidently. This analysis indicates that the connected channel system of pore phase is more effective on strength than the amount of pore phase.
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    Identification of water/cement ratio of cement pastes, basing on the microstructure image analysis data and using artificial neural network
    Ozturk, AU; Onal, O
    Artificial Neural Network (ANN) analysis has been established to forecast the Water/Cement (w/c) ratio values of cement pastes by using image analysis techniques in the scope of this study. W/c ratio values have reasonably great effects on the performance of cement based structural members. The service life or ultimate performances such as strength and durability characteristics are strongly affected by w/c ratios of cementitious materials. In this study, the relationship between microstructural phases such as unhydrated cement part, hydration products, capillary porosity, and w/c ratios predicted by ANN analysis, has been established. The predicted values are compared with estimated values obtained by proposed method in the literature. The study indicated that, using a contemporary data analysis technique, which is capable of searching nonlinear relationships more thoroughly, would result in more realistic prediction of the w/c ratios compared to the proposed method.
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    Effectiveness of micro phases on water/cement ratio
    Ozturk, AU
    Multiple linear regression (MLR) analysis has been performed to determine the effects of microstructural phases formed during hydration period of cement pastes to forecast their water/cement ratios. Image analysis methods have been used to determine the properties of microstructural phases in order to predict water/cement (w/c) ratio of cement pastes. Water/cement ratio has a great effect on strength and durability characteristics of cement-based structural members in their service life. In this study, the relationship between microstructural phases such as anhydrated cement part, hydration products, capillary porosity, and w/c ratios predicted by MLR analysis, has been established. The predicted values are compared with estimated values obtained by proposed method in the literature. MLR model indicates that volumetric ratios of microstructural phases in cement paste are effective in predicting w/c ratios of cement pastes.
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    Abrasion Resistance and Mechanical Properties of Waste-Glass-Fiber-Reinforced Roller-compacted Concrete
    Yildizel, SA; Timur, O; Ozturk, AU
    The potential use of waste glass fibers in roller-compacted concrete (RCC) was investigated with the aim to improve its performance and reduce environmental effects. The research was focused on the abrasion resistance and compressive and flexural strengths of the reinforced concrete relative to those of reference mixes without fibers. The freeze-thaw resistance of RCC mixes was also examined. It was found that the use of waste glass fibers at a rate of 2 % increased the abrasion resistance of the RCC mixes considerably.
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    Numerical analysis on corrosion resistance of mild steel structures
    Erdem, RT; Seker, S; Ozturk, AU; Gucuyen, E
    Corrosion resistances of mild steel specimens according to artificial neural network (ANN) analysis were investigated in the scope of this study. Corrosion rate values were taken into numerical analysis as a result of experimental studies under corrosive aggressive media. Mild steel specimens were selected according to the section type varieties such as box, tube and cornier. All steel specimens were subjected to the aggressive media formed using sodium chloride (NaCl with 99.8 % purity) solutions with 3.5, 5.0 and 7.0 % ratios per one liter distilled water and only distilled water. The reduction in corrosion rate has been observed and considered according to some corrosion loss respects. Corrosion rate prediction models were established between corrosion rate and parameters such as mass loss obtained by experimental studies using ANN. ANNs are computing systems that simulate the biological neural systems of the human brain. In this study, ANN analysis was generated to predict the corrosion rate values after experimental studies. Experimental and predicted values were compared by each other and it is seen that a strong relationship was established between them.
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    ESTIMATION OF COMPRESSIVE STRENGTH OF CEMENT MORTARS
    Erdem, RT; Ozturk, AU; Gücüyen, E
    Due to several advantages of cementitious materials especially mortars, they are widely used in construction works. It is important to determine the mechanical properties of cementitious materials to understand their behavior under different effects. In this study, Artificial Neural Networks (ANN) analysis is used to predict the 7 and 28 days compression strength values of cement mortars. Physical-mechanical properties such as flow, setting time and compressive strength of cement mortars incorporating of different chemical admixtures such as air-entraining admixture (HS), naphthalene sulfonate based (SPNS) and modified polymer (SPMP) based admixtures have been determined. The aim of the usage of combinations of air-entraining admixture with two different based superplasticizers is to form different inner structure affecting on compressive strength. All admixtures are used with three different ratios by cement weight and one of them is for overdosage effect. ANN analysis has been performed to predict the compression strength values after 7 and 28 days, in correlation with experimental part of the study. According to this view, 28 sets have been prepared with different combination of admixtures. At early ages, HS015-SPNS2.0 series had the lowest strength whereas the highest compressive strength at 28 days were obtained for HS005-SPMP0.8 series. Obtained compression strength values after 7 and 28 days have also been predicted by ANN analysis. It is stated that the established ANN model indicates a great capacity to predict the compressive strength values in the end.
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    Early age corrosion of mild steel in aggressive media
    Ozturk, AU; Gucuyen, E; Erdem, RT; Seker, S
    Effects of the time of holding, type of section, and concentration of the solution on the early age corrosion of mild steel are studied. Section types for steel specimens were box, tube, and corner. They were subjected to 3.5%, 5.0%, and 7.0% NaCl solutions. It was established that the concentration of the solution affects the corrosion until reaching the saturation value.
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    INFLUENCE OF THE AIR-ENTRAINING ADMIXTURE WITH DIFFERENT SUPERPLASTICIZERS ON THE FREEZE-THAW RESISTANCE OF CEMENT MORTARS
    Ozturk, AU; Erdem, RT
    Compatibility of different based superplasticizers with air-entraining admixture has been investigated. Physical and mechanical properties such as flow, setting time and compressive strength of cement mortars incorporating an air-entraining admixture (HS) with naphthalene sulfonate (SPNS) and modified polymer (SPMP) based admixtures have been determined. Also, the effects of their combinations on the freeze-thaw resistance of cement mortars have been determined. All admixtures are used with three different ratios and one of them is for overdosage effect. Results indicate that cement mortars having lowest early strength values are mortars incorporating 1.5% SPMP and 2.0% SPNS by mass of cement. The most effective series for the ultimate highest strength values were series with 0.05 % HS and 0.8 % SPMP. The freeze-thaw resistances of cement mortars were investigated for 50, 100, 150 and 200 freeze-thaw cycles. Indeed, the most effective series for freeze-thaw resistance were series with 0.05 % HS and 0.8 % SPMP.
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    Prediction of effects of microstructural phases using generalized regression neural network
    Ozturk, AU; Turan, ME
    In the scope of this study, microstructure-macroproperty relationship of cement mortars has been established in order to define the effects of microstructural phases on strength. Microstructural studies have been become great issue in materials engineering. Nowadays, to characterize the microstructural phase properties and to improve and modify them are performed by scientist to forecasting and enhancing. According to this objective, cement mortars incorporating with chemical admixtures were prepared to constitute different microstructural graphs. These micrographs were analyzed to determine the amounts of unhydrated cement part, undifferentiated hydrated part and capillary pore phases in the cement mortar sections. Afterwards, the amounts of these microstructural phases were related to strength values of each cement mortar specimen. The relationship was established by using generalized regression neural network analysis. (C) 2011 Elsevier Ltd. All rights reserved.