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- MakaleAçık Erişim2024Scopus SJRQ2Fatigue and tensile behaviour of Ti+TiN+Ti+TiVN multilayer nitride films coated on AZ91 magnesium alloy by closed field unbalanced magnetron sputtering
Alibeyoğlu, Fatih; Karabudak, Filiz; Yeşildal, Ruhi; Balcı, Arif; Efeoğlu, İhsan; Ateş, Onur Kazım
Despite their extensive use in the automotive and aerospace industries, Mg and Mg alloys, which are light metals, exhibit low fatigue and tensile strength. In this study, transition metal-nitride (TMN) multilayer coatings (Ti+TiN+Ti+TiVN) were coated twice on AZ91 Mg alloy using a Confined Field Unbalanced Magnetron Sputtering (CFUBMS) system to increase fatigue and tensile strength. The structural properties of the films were analyzed by using X-ray diffraction (XRD), scanning electron microscope (SEM), and energy dispersive spectrometry (EDS) methods, and the mechanical properties were analyzed by rotating bending fatigue and tensile testing machines. Ti+TiN+Ti+TiVN multilayer nitride surface coatings on AZ91 Mg alloys showed a dense and columnar microstructure and according to XRD results (111) was the preferred orientation with the dominant peak. The fatigue limit value of the AZ91 base material was fixed at 60.46 MPa, while it increased to 68.48 MPa after being coated with multilayer nitride. Along with the multilayer nitride coating, the tensile strength increased from 169.98 MPa to 175.43 MPa. As a result, the multilayer hard nitride coating with low surface roughness, which fills the defects, notches, and voids on the surface of the AZ91 base material, increased the fatigue and tensile strength in parallel. Based on the outcomes of the research, the literature has been enriched with an innovative approach through the enhancement of fatigue and tensile strengths by applying a CFUBMS coating to lightweight metals and alloys, such as AZ91, especially in the transportation industry where lightness and dynamic load resistance are essential.
AtıfScopus4WoS4OpenAlex2İncele - MakaleAçık Erişim2021The investigation of mechanical properties of polypropylene fiber-reinforced composites produced with the use of alternative wastes
Külekçi, Gokhan; Çullu, Mustafa
Various studies on the disposal or storage of the wastes generated due to mining activities have been carried out until today. With the developing technology, the use of alternative products instead of aggregates in Composite and the effect of fiber addition were investigated. The most common of these studies is the bending strength tests on the beam sample. In this study, solid wastes generated by mining operations were used instead of aggregate used in Composite. Beam samples were poured with the dimensions of 40x40x160 mm by adding 4-6 kg/m(3) polypropylene fiber to the mixture obtained by using these solid wastes; then, its effects on ultrasonic pulse velocity test, tensile test, and compressive strength tests were conducted. According to the results of these tests, it was found that the fibers had a positive effect on compressive strength and bending strength. Also, it was found that water absorption rates and densities did not have an effect, while the ultrasonic pulse velocity decreased with increasing fiber content.
AtıfWoS12OpenAlex18TR Dizin4İncele - MakaleAçık Erişim2012Scopus SJRQ1New considerations for empirical estimation of tensile strength of rocks
Gurocak, Zulfu; Solanki, Pranshoo; Alemdag, Selcuk; Zaman, Musharraf M.
In this paper, a combined laboratory and modeling study was conducted to develop a database for predicting tensile strength of rocks. Six hundred eighty six rock samples from 24 different sites throughout eastern Turkey were collected and tested for the development of this database and evaluation of models. A total of 512 samples were used for developing the models and the remaining 174 samples were used as control dataset. The material parameters selected in the development of the models include tensile strength (σ t), point load index (Is (50)), Schmidt rebound number (N) and unit weight (γ). A total of four models, two regression models, namely, simple linear regression and multiple regression, and two feed forward-type artificial neural network (ANN) models, namely, radial basis function network (RBFN) and multi-layer perceptron network (MLPN) are developed. A commercial software, Statistica 8.0, is used to develop these models. The strengths and weaknesses of the developed models were assessed by comparing the predicted σ t values with the experimental values with respect to the R 2 values. Overall, the MLPN model was found to be the best model for the present development and evaluation datasets. As a result of these analyses, an equation was suggested based on ANN model to estimate the tensile strength of rocks.
AtıfScopus58OpenAlex60İncele