Browsing by Author "Bayraktar, Emin"

Now showing 1 - 11 of 11

Citation - Scopus: 1
Analytical Solutions of Model Problems for Large-Deformation Micromorphic Approach To Gradient Plasticity
(Mdpi, 2021) Aslan, Ozgur; Bayraktar, Emin
The objective of this work is to present analytical solutions for several 2D model problems to demonstrate the unique plastic fields generated by the implementation of micromorphic approach for gradient plasticity. The approach is presented for finite deformations and several macroscopic and nonstandard microscopic boundary conditions are applied to a gliding plate to illustrate the capability to predict the size effects and inhomogeneous plastic fields promoted by the gradient terms. The constitutive behavior of the material undergoing plastic deformation is analyzed for softening, hardening and perfect plastic response and corresponding solutions are provided. The analytical solutions are also shown to match with the numerical results obtained by implementing a user element subroutine (UEL) to the commercial finite element software Abaqus/Standard.
Citation - WoS: 4
Citation - Scopus: 5
Assessing Cast Aluminum Alloys With Computed Tomography Defect Metrics: a Gurson Porous Plasticity Approach
(Mdpi, 2023) Gul, Armagan; Aslan, Ozgur; Kayali, Eyuep Sabri; Bayraktar, Emin
Aluminum alloys have inherent tendencies to produce casting defects caused by alloying or metal melt flow inside the mold. The traditional detection method for these defects includes reduced pressure tests, which assess metal quality in a destructive manner. This leaves a gap between metal quality assessments and tensile test correlations. Computed tomography (CT) scans offer crucial assistance in evaluating the internal quality of castings without damaging the structure. This provides a valuable opportunity to couple mechanical tests with numerical methods such as finite element analysis to predict the mechanical performance of the alloy. The present study aims to evaluate the internal quality of cast aluminum alloys using CT scans and to correlate the defect metrics obtained from CT scans with mechanical test results. The Gurson-type material model and finite element methodology have been used to validate the correlation studies. Therefore, we propose a more holistic approach to predicting the behavior of metals by coupling damage models with CT scans and mechanical tests. The study investigates several CT metrics such as the defect volume, total defect surface, biggest defect surface, and projected area of defects. The conclusion reveals that CT scans provide crucial assistance in evaluating the internal quality of castings, and CT defect metrics can be used to build correlations between mechanical tests and CT evaluations. The study also suggests that the concept of adjusted representative material yield parameter (ARMY) or computed representative material yield parameter (CRMY) can be used to correlate CT metrics with mechanical strength in cast materials and parts for a given aluminum alloy. Overall, the study proposes a more comprehensive methodology to assess the quality of cast aluminum alloys and couple the quality to mechanical performance.
Citation - WoS: 1
Citation - Scopus: 1
Classification of Different Recycled Rubber-Epoxy Composite Based on Their Hardness Using Laser-Induced Breakdown Spectroscopy (libs) With Comparison Machine Learning Algorithms
(Mdpi, 2023) Yilmaz, Vadi Su; Yılmaz, Vadi Su; Eseller, Kemal Efe; Aslan, Ozgur; Aslan, Özgür; Bayraktar, Emin; Eseller, Kemal Efe; Yılmaz, Vadi Su; Aslan, Özgür; Eseller, Kemal Efe; Electrical-Electronics Engineering; Department of Electrical & Electronics Engineering; Mechanical Engineering; Electrical-Electronics Engineering; Mechanical Engineering; Department of Electrical & Electronics Engineering
This paper aims toward the successful detection of harmful materials in a substance by integrating machine learning (ML) into laser-induced breakdown spectroscopy (LIBS). LIBS is used to distinguish five different synthetic polymers where eight different heavy material contents are also detected by LIBS. Each material intensity-wavelength graph is obtained and the dataset is constructed for classification by a machine learning (ML) algorithm. Seven popular machine learning algorithms are applied to the dataset which include eight different substances with their wavelength-intensity value. Machine learning algorithms are used to train the dataset, results are discussed and which classification algorithm is appropriate for this dataset is determined.
A Coupled Modelling and Simulation Approach to Electromagnetic Sheet Metal Forming
(Taylor & Francis Ltd, 2025) Aslan, Ozgur; Kabakci, Gamze Cakir; Sait, Ferit; Camalan, Caner; Baranoglu, Besim; Bayraktar, Emin
This study presents a coupled numerical and experimental investigation of electromagnetic forming (EMF) for aluminium sheets. A custom simulation framework is developed in ABAQUS/Standard using user-defined material (UMAT) and load (DLOAD) subroutines. The magnetic pressure exerted on the workpiece is computed through a finite difference-based solution of Maxwell's equations and applied to the mechanical solver. The mechanical response of the material is modelled using a strain-rate-sensitive plasticity law calibrated for aluminium 7075-O. Experimental forming trials are performed using a custom-built EMF setup, and the results are compared with numerical predictions to validate the model. The comparison shows strong agreement in deformation profiles, confirming the predictive capability of the proposed simulation strategy. This work offers a reliable computational tool for optimising EMF processes and provides insights into material behaviour under high strain rate electromagnetic loading.
Development of Ni-Al Composites Reinforced With Recycled Aa7075+aa1050 and Ceramics Produced by the Sintering Plus Forging Process
(Springer international Publishing Ag, 2024) Gatamorta, Fabio; Klinkova, Olga; Aslan, Ozgur; Miskioglu, Ibrahim; Bayraktar, Emin
In this study, the microstructural formation and static/cyclic compression behavior of "Ni-Al+AA7075 +AA1050"-based composites reinforced with ceramics (TiC-TiB2) have been evaluated. It is aimed at creating a new design to be an alternative to traditional alloys/composites used in the aeronautical industry. These composites are generally produced using a combined method that we call "sinter + forging processes". The static and dynamic properties and also the microstructure (including the distribution of reinforcement elements) are evaluated in detail.
Citation - WoS: 2
Citation - Scopus: 2
An Investigation of Recycled Rubber Composites Reinforced With Micro Glass Bubbles: an Experimental and Numerical Approach
(Taylor & Francis Ltd, 2024) Kabakci, Gamze Cakir; Bayraktar, Emin; Aslan, Ozgur
Recycled rubber is widely used for its lightweight and cost-effective properties but often has limited mechanical strength, restricting its applications. This study enhances the mechanical performance of devulcanised recycled rubber by reinforcing it with micro glass bubbles (GBs) featuring a density of 0.65 g/cm(3) and an elastic modulus of 3.5 GPa, offering a high strength-to-density ratio. Uniaxial compression tests were conducted on samples with GB volume fractions of 5%, 10%, and 15%. Results were validated through finite element analysis (FEA) in ABAQUS/Standard, incorporating randomised GB distributions. A 2D representative volume element (RVE) with randomly distributed GBs was modelled, applying periodic boundary conditions to simplify the composite into an equivalent homogeneous material. Numerical simulations assessed the effects of GB diameters (30, 40, and 50 mu m) and inclusion size ranges (20-50 mu m and 10-60 mu m), finding minimal impact on results. The RVE, sized at 238 mu m, accurately represented macroscale composite behaviour. Stress-strain behaviour was analysed using average stress and strain tensors. The strong agreement between experimental and numerical results validates the proposed method, demonstrating its accuracy in predicting the mechanical behaviour of the reinforced composite material.
Citation - WoS: 5
Citation - Scopus: 5
A Large-Deformation Gradient Damage Model for Single Crystals Based on Microdamage Theory
(Mdpi, 2020) Aslan, Ozgur; Bayraktar, Emin
This work aims at the unification of the thermodynamically consistent representation of the micromorphic theory and the microdamage approach for the purpose of modeling crack growth and damage regularization in crystalline solids. In contrast to the thermodynamical representation of the microdamage theory, micromorphic contribution to flow resistance is defined in a dual fashion as energetic and dissipative in character, in order to bring certain clarity and consistency to the modeling aspects. The approach is further extended for large deformations and numerically implemented in a commercial finite element software. Specific numerical model problems are presented in order to demonstrate the ability of the approach to regularize anisotropic damage fields for large deformations and eliminate mesh dependency.
Citation - WoS: 2
Citation - Scopus: 2
Lifetime Prediction of Single Crystal Nickel-Based Superalloys
(Mdpi, 2025) Kasar, Cagatay; Kaftancioglu, Utku; Bayraktar, Emin; Aslan, Ozgur
Single crystal nickel-based superalloys are extensively used in turbine blade applications due to their superior creep resistance compared to their polycrystalline counterparts. With the high creep resistance, high cycle fatigue (HCF) and low cycle fatigue (LCF) become primary failure mechanisms for such applications. This study investigates the fatigue life prediction of CMSX-4 using a combination of crystal plasticity and lifetime assessment models. The constitutive crystal plasticity model simulates the anisotropic, rate-dependent deformation behavior of CMSX-4, while the modified Chaboche damage model is used for lifetime assessment, focusing on cleavage stresses on active slip planes to include anisotropy. Both qualitative and quantitative data obtained from HCF experiments on single crystal superalloys with notched geometry were used for validation of the model. Furthermore, artificial neural networks (ANNs) were employed to enhance the accuracy of lifetime predictions across varying temperatures by analyzing the fatigue curves obtained from the damage model. The integration of crystal plasticity, damage mechanics, and ANNs resulted in an accurate prediction of fatigue life and crack initiation points under complex loading conditions of single crystals superalloys.
Citation - WoS: 10
Citation - Scopus: 16
A Review on Analysis of Reinforced Recycled Rubber Composites
(Mdpi, 2022) Kabakci, Gamze Cakir; Aslan, Ozgur; Bayraktar, Emin
Rubber recycling attracts considerable attention by a variety of industries around the world due to shrinking resources, increasing cost of raw materials, growing awareness of sustainable development, and environmental issues. Recycled rubber is commonly used in aeronautic, automotive, and transportation industries. In this study, recycled rubber composites designed with different reinforcements in the literature are scrutinized by means of toughening mechanisms, mechanical and physical properties, as well as microstructural and fracture surface analysis. Microscale reinforcements (glass bubbles, alumina fiber, etc.) and nanoscale reinforcements (nanosilica, graphene nanoplatelets, etc.) utilized as reinforcements in rubber composites are thoroughly reviewed. The general mechanical properties reported by previous studies, such as tensile, compressive, and flexural strength, are investigated with the main goal of optimizing the amount of reinforcement used. The majority of the studies on recycled rubber composites show that recycled rubber reinforced with microscale particles leads to the development of physical and mechanical properties of the structures and also provides low-cost and lightweight composites for several application areas. Moreover, recycled rubber containing composites can be suitable for applications where high toughness and high resistance to impact are desirable. The present review aims to demonstrate research on reinforced recycled rubber composites in the literature and prospective outcomes.
Static and Fatigue Behaviour of Recycled Thinsheet "ti-Al Based Composites Produced by Hot Forging Diffusion Process
(Springer international Publishing Ag, 2024) Zambelis, Georges; Gatamorta, Fabio; Aslan, Ozgur; Miskioglu, Ibrahim; Bayraktar, Emin
Within the framework of the common research project, the mechanical properties and fatigue behaviour of recycled thin sheet Ti-Al-based composites reinforced with atomized scrap aluminium (AA7075) and Nb elements have been evaluated. All the thin sheet sandwich structures were produced by the hot forging process, which is a semi-solid-forming process similar to partial melting hot forging. The effect of the chemical bonds during the production of these multifunctional sandwich composite structures was analysed using 3-point bending tests under static and dynamic (fatigue) loading conditions. Additional tensile tests have been carried out to evaluate the mating effect. Interface and microstructure of these composites have also been evaluated using scanning electron microscopy.
Citation - WoS: 9
Citation - Scopus: 10
Toughening Mechanism Analysis of Recycled Rubber-Based Composites Reinforced With Glass Bubbles, Glass Fibers and Alumina Fibers
(Mdpi, 2021) Kabakci, Gamze Cakir; Aslan, Ozgur; Bayraktar, Emin
Recycling of materials attracts considerable attention around the world due to environmental and economic concerns. Recycled rubber is one of the most commonly used recyclable materials in a number of industries, including automotive and aeronautic because of their low weight and cost efficiency. In this research, devulcanized recycled rubber-based composites are designed with glass bubble microsphere, short glass fiber, aluminum chip and fine gamma alumina fiber (gamma-Al2O3) reinforcements. After the determination of the reinforcements with matrix, bending strength and fracture characteristics of the composite are investigated by three-point bending (3PB) tests. Halpin-Tsai homogenization model is adapted to the rubber-based composites to estimate the moduli of the composites. Furthermore, the relevant toughening mechanisms for the most suitable reinforcements are analyzed and stress intensity factor, K-Ic and critical energy release rate, G(Ic) in mode I are determined by 3PB test with single edge notch specimens. In addition, 3PB tests are simulated by finite element analysis and the results are compared with the experimental results. Microstructural and fracture surfaces analysis are carried out by means of scanning electron microscopy (SEM). Mechanical test results show that the reinforcement with glass bubbles, aluminum oxide ceramic fibers and aluminum chips generally increase the fracture toughness of the composites.