Browsing by Author "Yildizel S."
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Scopus Cost optimization of mortars containing different pigments and their freeze-thaw resistance properties(2016-01-01) Yildizel S.; Kaplan G.; Öztürk A.Nowadays, it is common to use colored concrete or mortar in prefabricated concrete and reinforced concrete construction elements. Within the scope of this study, colored mortars were obtained with the addition of brown, yellow, black, and red pigments into the white cement. Those mixtures are examined for their compressive strength, unit weight, water absorption, and freeze-thaw resistance. Subsequent to comparison of these properties, a cost optimization has been conducted in order to compare pigment costs. The outcomes showed that the pore structure in architectural mortar applications plays an important role in terms of durability. And cost optimization results show that light colored minerals can be used instead of white cements.Scopus Glass fibre reinforced concrete rebound optimization(2017-01-01) Yildizel S.; Yiǧit M.; Kaplan G.Glass fibre reinforced concrete placement technique generates losses due to rebound effects of the already sprayed concrete particles. Rebounded concrete amount cause a significant difference between the initial mix design and emplaced mix compositions. Apart from the structural differences, it comes with a cost increase which was resulted by the splashed concrete amount. Many factors such as viscosity and quantity of mixes dominate this rebound amount in sprayed glass fibre reinforced concrete applications depending on production technologies and processes; however, this research focuses on the spray distance and the angle of the spray gun which mainly effects the rebound amount in glass fibre reinforced concrete production. This paper aims to understand the required angle and distance for glass fibre reinforced concrete mixes having on-site plastic viscosity values. Glass fibre reinforced mixtures were also modelled with a finite element method based software and, the analysis results were compared with production line results. Results of the analysis and on-site studies showed a decisive correlation between, discharge distance, discharge angle and the viscosity of the concrete.Scopus Prediction of Skid Resistance Value of Glass Fiber-Reinforced Tiling Materials(2017-01-01) Yildizel S.; Tuskan Y.; Kaplan G.This research focuses on the use of adaptive artificial neural network system for evaluating the skid resistance value (British Pendulum Number; BPN) of the glass fiber-reinforced tiling materials. During the creation of the neural model, four main factors were considered: fiber, calcium carbonate content, sand blasting, and polishing properties of the specimens. The model was trained, tested, and compared with the on-site test results. As per the comparison of the outcomes of the study, the analysis and on-site test results showed that there is a great potential for the prediction of BPN of glass fiber-reinforced tiling materials by using developed neural system.