Browsing by Author "Tuskan Y."

Now showing 1 - 6 of 6
  • No Thumbnail Available
    Item
    Investigations into factors influencing the CBR values of some Aegean sands
    (Sharif University of Technology, 2016) Erzin Y.; Türköz D.; Tuskan Y.; Yilmaz I.
    The California Bearing Ratio (CBR) value of the soils is very important for geotechnical engineering and earth structures. A CBR value is affected by the soil type and different soil properties. With this in view, in this paper, an attempt has been made for investigating the factors that affect the CBR values of some Aegean sands collected from nine different locations in Manisa (Turkey). The sand samples were tested for mineralogy, particle shape and size, and specific gravity. The CBR tests were then performed on these samples at different dry densities to examine the influence of dry density, relative density, water content, and particle shape and size on the CBR value. Multiple Regression Analysis (MRA) was performed to predict the CBR value of the sands by using the experimental results. Moreover, several performance indices, such as coefficient of correlation and variance account for mean absolute error and root mean square error, were calculated to check the prediction capacity of the proposed MR equation. The obtained indices make it clear that the equation derived from the samples used in this study applies well, with an acceptable accuracy, to the CBR estimation at the preliminary stage of site investigations. © 2016 Sharif University of Technology. All rights reserved.
  • No Thumbnail Available
    Item
    Prediction of Skid Resistance Value of Glass Fiber-Reinforced Tiling Materials
    (Hindawi Limited, 2017) Yildizel S.A.; 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. © 2017 Sadik Alper Yildizel et al.
  • No Thumbnail Available
    Item
    Evaluation of Offshore Wind Turbine Tower Dynamics with Numerical Analysis
    (Hindawi Limited, 2018) Dagli B.Y.; Tuskan Y.; Gökkuş Ü.
    A dynamic behaviour of a cylindirical wind tower with variable cross section is investigated under environmental and earthquake forces. The ground acceleration term is represented by a simple cosine function to investigate both normal and parallel components of the earthquake motions located near ground surface. The function of earthquake force is simplified to apply Rayleigh's energy method. Wind forces acting on above the water level and wave forces acting on below this level are utilized in computations considering earthquake effect for entire structure. The wind force is divided into two groups: the force acting on the tower and the forces acting on the rotor nacelle assembly (RNA). The drag and the inertial wave forces are calculated with water particle velocities and accelerations due to linear wave theory. The resulting hydrodynamic wave force on the tower in an unsteady viscous flow is determined using the Morison equation. The displacement function of the physical system in which dynamic analysis is performed by Rayleigh's energy method is obtained by the single degree of freedom (SDOF) model. The equation of motion is solved by the fourth-order Runge-Kutta method. The two-way FSI (fluid-structure interaction) technique was used to determine the accuracy of the numerical analysis. The results of computational fluid dynamics and structural mechanics are coupled in FSI analysis by using ANSYS software. Time-varying lateral displacements and the first natural frequency values which are obtained from Rayleigh's energy method and FSI technique are compared. The results are presented by graphs. It is observed from these graphs that the Rayleigh model can be an alternative way at the prelimanary stage of the structural analysis with acceptable accuracy. © 2018 Begum Yurdanur Dagli et al.
  • No Thumbnail Available
    Item
    The use of neural networks for predicting the factor of safety of soil against liquefaction
    (Sharif University of Technology, 2019) Erzin Y.; Tuskan Y.
    In this paper, the Factor of Safety (FS) values of soilaga instliquefaction was investigated by means of Artificial Neural Network (ANN) and Multiple Regression (MR). To achieve this, two earthquake parameters, namely earthquake magnitude (Mw) and horizontal peak ground acceleration (a m a x ), and six soil properties, namely Standard Penetration Test Number (SPT-N), saturated unit weight (γsat), natural unit weight (γn), Fines Content (FC), the depth of Ground Water Level (GWL), and the depth of the soil (d), varied in the liquefaction analysis; then, the FS value was calculated by the simplified method for each case by using the Excel program developed and utilized in the simulation of the feed-forward ANN model with backpropagation algorithm and the MR model. The FS values predicted by both ANN and MR models were compared with those calculated by the simplified method. In addition, five different performance indices were used to evaluate the predictabilities of the models developed. These performance indices indicated that the ANN models were superior to the MR model in terms of predicting the FS value of the soil. © 2019 Sharif University of Technology. All rights reserved.
  • No Thumbnail Available
    Item
    Evaluation of Sustainable Slope Stability with Anti-Slide Piles Using an Integrated AHP-VIKOR Methodology
    (Multidisciplinary Digital Publishing Institute (MDPI), 2023) Tuskan Y.; Basari E.
    The sustainable design of major civil engineering projects, such as landslide management and slope stability, provides new opportunities for our society regarding the global energy crisis. These sources offer an effective solution to environmental issues and human energy needs. Slope stability, as a critical aspect of ensuring public safety and protection of infrastructure, often leads to disastrous consequences, highlighting the significance of designing effective and sustainable measures to mitigate the risks associated with landslides. Although anti-slide piles have become a widely used method to enhance slope stability, this paper investigates how the Analytic Hierarchy Process (AHP) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methodologies can be combined to achieve a sustainable design for anti-slide piles, simultaneously considering environmental, economic, safety, and technical factors. Through the integration of AHP-VIKOR and a case study, this paper demonstrates an effective approach to prioritizing sustainability in the design process of anti-slide pile systems, evaluating five main criteria—slope stability, sustainability, anti-slide pile capacity, cost, and ease of construction—and five sub-criteria. The proposed methodology is validated through a case study, wherein various design alternatives for anti-slide piles are evaluated based on sustainable requirements. The results indicate that the slope stability criterion has the highest weight of 0.404, followed by anti-slide pile capacity (0.283), sustainability (0.129), and cost (0.146) criteria. The ease of construction has the lowest weight of 0.038. As a result of the evaluations, it has been seen that, if the sustainability criteria are included in the analyses, the anti-slide pile alternatives are determined in the range of ξ = 0.1–0.3 and s/D = 2.0–3.0, compared to the scenarios where only the economic and technical criteria are satisfied. A pile geometry of diameter, D = 1.00 m, is the most sustainable value within the selected pile spacing intervals, meeting the criteria of slope safety, pile capacity, cost, and ease of construction. This hybrid approach allows for a more balanced consideration of a multi-criteria decision, while considering the sustainability aspects of anti-slide pile selection. © 2023 by the authors.
  • No Thumbnail Available
    Item
    Shear Capacity Prediction of Extremely-Loaded Box Culvert on Elastic Soil Using Artificial Neural Network
    (Sakarya University, 2024) Tuskan Y.; Uncu D.Y.
    A box culvert, buried at shallow depths beneath roadways, may experience deflections caused by the dynamic impact of traffic loading and the vertical pressure exerted by the soil fill. A computational model commonly employed used to various engineering issues, including those in geotechnical applications, is the beam-onelastic-foundation model. In this context, the Moment Distribution Method (MDM) must be applied to account for the elastic foundation. To achieve this, the internal forces acting on the ends of both exterior and interior walls are transferred to the beam-like bottom slab of the culvert, which rests on an elastic soil bed. Subsequently, the secondary internal forces are determined by refining the structural parameters, taking into account the characteristics of the elastic soil bed. This study presents the development and application of an Artificial Neural Network (ANN) model to predict the shear capacity of box culverts on elastic soil under traffic loading conditions. The proposed model is trained and validated using a comprehensive database of beam on elastic foundation solutions. The input parameters include the geometrical and mechanical properties of the culvert and the soil, as well as the loading conditions. The results of the ANN model show R2 values of 0.9633 and 0.9581 for the training and testing sets, respectively, indicating the model's excellent accuracy. These findings suggest that the ANN model can reliably predict the shear capacity of culverts. © 2024, Sakarya University. All rights reserved.