Courses

Learn the fundamentals of academic research and ethics.

Explain the application of advanced mathematical methods that can be used in solving engineering problems.

The aim of this course is to enable the students to develop their skills in research, surveys, preparing and making presentations and sharing their their research work and get feedback.

Under the supervision of a faculty member, students will prepare a thesis by conducting research on a topic appropriate to their academic background. The thesis should involve the application or development of techniques used in the Mechanical Engineering programme and should make an original contribution. Graduation candidates must defend their thesis in front of a jury appointed by the programme.

Under the supervision of a faculty member, students will prepare a thesis by conducting research on a topic appropriate to their academic background. The thesis should involve the application or development of techniques used in the Mechanical Engineering programme and should make an original contribution. Graduation candidates must defend their thesis in front of a jury appointed by the programme.

In this course, the students will prepare a project in collaboration with industry. The students will identify an important problem in a company, which is related to the subjects covered in the courses. Then, they will make an extensive literature review on the problem selected.

The aim of this course is to review the structures of industrial robots, to learn and use the mathematical foundations required to describe the three-dimensional motion of robot manipulators, to learn the concepts of straight and inverse kinematics in robot manipulators with different geometries, and to obtain joint velocities.

To learn the approximate solution method for solving the heat conduction problems. To learn the various methods through the finite volume to solve the heat conduction problem. To apply the various numerical method for solving the heat conduction problem. To learn the discretize method in terms of solving heat conduction. Applying various numerical methods to heat conduction problems.

Introduction to thermal system design. Thermodynamic analysis and modelling. Heat transfer, modelling and analysis. Heat transfer and flow applications in thermal system design. Modelling of thermal system elements. Thermoeconomic analysis. Thermoeconomic optimisation.

Energy and energy resources. Introduction to renewable energy sources. Analysis and design of solar energy systems. Wind energy. Wind power plant design. Geothermal energy. Electricity generation from geothermal energy. Geothermal power plant design. Biomass, hydrogen, nuclear energy, wave energy, current energy. Comparison of renewable energy sources and their effects on economy.

Basic concepts. Basic equations of fluid mechanics. Examination of flow equations of motion. Investigation of force and stress concepts. Investigation of incompressible potential flow equations.

Investigation of heat transfer by steady, unsteady and multidimensional conduction in different geometries. Solution methods and integral transformation in heat transfer. Approximation in heat transfer. Equations of motion. Heat transfer by laminar, natural and forced convection. Solution methods; similarity solution methods, perturbation. Turbulent flow and convection heat transfer. Prandtl and Karman theorems. Reynolds, Taylor, Prandtl and Martinelli relations.

Cartesian tensor notation. Strain analysis, stress analysis and equations of equilibrium. Hooke's law. Young's modulus. Plane stress and plane strain. 2-dimensional elasticity problems. Energy principles and examples of applied elasticity.

The fatigue course is for engineers interested in the design and development of machinery and equipment subjected to repeated loads and who have to decide about the fatigue resistance of a structure, machine, or component. Key points about successful fatigue design are mentioned, as well as more modern approaches like total damage or life estimation that consider the importance of counting cycles and the order in which events occur. Sample problems will be solved, and real-life applications will be given. The main aim of the course is to enable the participants to understand how metal fatigue occurs and what methods are available to predict and prevent damage.

The Mechanics of Composite Materials course aims to give information about composite materials and to gain general, experimental, and theoretical information about the mechanical behavior of composite materials.

The aim of this course is to introduce various methods used to obtain equations of motion in dynamical problems and to give students the ability to choose the most appropriate method for solving problems.

Gaining knowledge about AI techniques; Learning knowledge-based systems technology and expert systems; Learning fuzzy modelling approach: fuzzification of an engineering problem, obtaining the solution in the fuzzy wold using fuzzy logic and defuzzification of the solution. Overviewing Genetic Algorithms (GA's) as an optimization technique; Modeling and solving an engineering problem using GA's; Overviewing Artificial Neural Network (ANN) models;; Modeling and solving an engineering problem using ANN.; Overviewing deep learning alorithms. as current form ANN.

Understanding the basics behind linear and nonlinear finite element method. Learning the finite element software; Ansys. Generating the skill for modeling and solving an engineering problem by means of Ansys. Evaluating and interpreting the obtained solutions as an engineer.

This course aims to introduce DOE for its potential to improve product quality and process efficiency. Along with practical examples and case studies, the use of simple graphical tools for data analysis and interpretation will be introduced. This course also provides a framework for Six Sigma training and projects related to design optimization and process performance improvements. The course aims to help practitioners and researchers learn how to apply DOE in their work environment.

Mathematical background and error analysis; source of errors, numerical stability and convergence. Solution of nonlinear equations in one variable; bisection method, Newton's method, beam method, Muller's method. General theory for single-point iteration methods, multiple roots, Brent's algorithm. Principle of contraction transformation, Newton's method for systems of nonlinear equations. Polynomial interpolation theory, Newton divided differences, interpolation error analysis. Hermite interpolation, piecewise polynomial interpolation, Chebyshev interpolation. Cubic splayns, Bezier curves, multidimensional interpolation. Weierstrass theorem, multidimensional Taylor theorem, minimax approximation. Least squares approximation. Numerical differentiation; finite difference formulae, rounding error, extrapolation. General differentiation formula for points of variable length, numerical differentiation with slightly modified data. Numerical integration; compound methods of numerical integration, Simpson's rules, weighted Newton-Cotes and Gauss formulae, Gaussian numerical integration. Peano representations of linear functionals, extrapolation methods, Romberg integration. Numerical calculation of singular integrals, multidimensional numerical integration.

To teach the basics of theory of plasticity. To teach the basic method used in metal forming analysis. To teach the finie element solution method for metal forming applications in Anysys Workbench.

Introduction to energy analysis methods. 2nd law of thermodynamics and entropy concept. Introduction to exergy analysis methods. Investigation of exergy efficiency of engineering systems. Application of exergy analysis method to renewable energy sources (solar energy, geothermal energy, wind energy, biomass energy). Investigation of energy performance of buildings using exergy method. Exergy economic methods. Exergy economic optimisation. 

Stability, Liapunov's second method and its application in control systems design. Variational calculus, maximum principle, dynamic programming and Hamilton Jacobi-Bellman equations. Pontragin's minimum principle, linear-quadratic regulator design, time optimal control systems, singular control problems. Dynamic optimization in control systems for different terminal conditions. Numerical solution methods in optimal control problem.