Mechanical Engineering

Description

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Innovation in product design and manufacturing has become a major driver for industrial competitiveness and profitablity in recent years. As enabling technologies become more easily accessible, engineers are faced with increasing demands for designing and producing more complex mechanical devices to serve the needs of the society.

Next generation engineering products will be 'smart' with many functionalities; they will be made of new materials; they will increase energy efficiency and reduce environmental impact; they will vary in size from nano to mega scales; and they will be more closely integrated with information processing systems. Also as mechanical systems are becoming increasingly complex to analyze and expensive to experiment, more emphasis will have to be placed on computer aided analysis, design, verification and manufacturing.

Our research program in mechanical engineering responds to these trends and focuses on basic research related to materials science and process engineering, product design, and information integrated manufacturing processes. In doing so applications to different physical processes are studied (e.g. energy systems, bioengineering, metal forming, polymer processing, discrete part manufacturing to name a few).

Research Areas

* Computer Aided Numerical Control (CNC) Systems and Machine Tools


* Automation and Mechatronics


* Composite Materials Manufacturing


* Human and Machine Haptics (Biomechanics, Robotics)


* Multi-Scale Experimental and Computational Mechanics of Materials


* Vibrations and Structural Dynamics


* Modelling and Design of Micro/Macro Systems


* Computational Materials Science (Polymers, Biomaterials, Shape Memory Alloys)


* Computational Fluid Dynamics


* Thermal and Bio/Micro Fluidic Systems


* Micro-Nano Fabrication

Contents

Course Descriptions
CMSE 501 Introduction to Computational Science

An introduction to methods and software tools used in scientific computing. Software development, data abstraction and the concept of object oriented programming. Hands-on exploration of some of the principal modern software tools of computational science including computing environments, symbolic computing, numerical libraries and software repositories. An introduction to high performance computing and parallel programming.

ECOE 510 Computer Graphics

Theory and practice of 3D computer graphics. Topics covered include graphics systems and models; geometric representations and transformations; graphics programming; input and interaction; viewing and projections; compositing and blending; illumination and color models; shading; texture mapping; animation; rendering and implementation; hierarchical and object-oriented modeling; scene graphs; 3D reconstruction and modeling.

Prerequisite: COMP 202 or consent of the instructor.

ECOE 521 Photonics and Lasers

Review of electromagnetism; electromagnetic nature of light, radiation, geometrical optics, Gaussian beams, transformation of Gaussian beams; electromagnetic modes of an optical resonator, interaction of light with matter, classical theory of absorption and dispersion, broadening processes, Rayleigh scattering, quantum theory of spontaneous and stimulated emission, optical amplification, theory of laser oscillation, examples of laser systems, Q switching and mode locking of lasers.

Prerequisite: ELEC 206 or consent of the instructor.

ECOE 522 Micro-opto-electro-mechanical Systems

Introduction to microsystems and micro-electro-mechanical-systems (MEMS) and their integration with optics; microfabrication and process integration; MEMS modeling and design; actuator and sensor design; mechanical structure design; optical system design basics; packaging; optical MEMS application case studies; scanning systems (Retinal Scanning Displays, Barcode scanners); projection display systems (DMD and GLV); infrared imaging cameras; optical switching for telecommunications.

Prerequisite: ELEC 321 or consent of the instructor.

ECOE 554 Machine Learning

An introduction to the fields of machine learning and data mining from a statistical perspective. Machine learning is the study of computer algorithms that improve automatically through experience. Vast amounts of data generated in many fields from biology to finance to linguistics makes a good understanding of the tools and techniques of machine learning indispensable. Topics covered include regression, classification, kernel methods, model assessment and selection, boosting, neural networks, support vector machines, nearest neighbors, and supervised learning.

Prerequisite: Consent of the instructor.

ECOE 570 Bioinformatics and Algorithms in Computational Biology

Algorithms, models, representations, and databases for collecting and analyzing biological data to draw inferences. Overview of available molecular biological databases. Sequence analysis, alignment, database similarity searches. Phylogenetic trees. Discovering patterns in protein sequences and structures. Protein 3D structure prediction: homology modeling, protein folding, representation for macromolecules, simulation methods. Protein-protein interaction networks, regulatory networks, models and databases for signaling networks, data mining for signaling networks.

INDR 501 Optimization Models and Algorithms

Convex analysis, optimality conditions, linear programming model formulation, simplex method, duality, dual simplex method, sensitivity analysis; assignment, transportation, and transshipment problems.

Prerequisite: Consent of the instructor.

INDR 505 Manufacturing Systems

This course will cover the basic concepts and techniques in hierarchical design, planning, and control of manufacturing systems. Topics include assembly lines, general serial systems, group technology and cellular manufacturing, flexible manufacturing systems, facility layout, material handling systems and warehousing.

Prerequisite: Consent of the instructor.

INDR 508 Discrete Event Simulation

Topics on distribution fitting and generating random numbers and random varieties will be covered as well as the statistical analysis of simulation output, including some well-known analysis methods and variance reduction techniques. Recent developments in the area will also be discussed.

Prerequisite: INDR 503 or consent of the instructor.

INDR 510 Mathematical Statistics

Review of descriptive statistics, important population statistics and their distributions. Point estimation, estimation methods and minimum-variance unbiased estimators. Testing hypothesis, Neyman-Pearson lemma and likelihood ratio tests. Estimation and testing in linear regression modes. Analysis of variance models. Non-parametric statistics methods. Bayesian testing and analysis.

Prerequisite: INDR 252 or consent of the instructor.

INDR 551 Advanced Optimization Methods

Combinatorial optimization, structure of integer programs, pure integer and mixed integer programming problems, branch and bound methods, cutting plane and polyhedral approach, convexity, local and global optima, Newton-type, and conjugate gradient methods for unconstrained optimization, Karush-Kuhn-Tucker conditions for optimality, algorithms for constrained nonlinear programming problems, applications in combinatorial and nonlinear optimization.

Prerequisite: INDR 501 or consent of the instructor.

INDR 560 Large Scale Optimization

Methods for the solution of complex real world problems modeled as large-scale linear, nonlinear and stochastic programming, network optimization and discrete optimization problems. Solution methods include Decomposition Methods: Bender's, Dantzig-Wolfe, Lagrangian Methods; Meta-heuristics: Local search, simulated annealing, tabu search, genetic algorithms; Constraint Programming. Applications in transportation and logistics planning, pattern classification and image processing, data mining, design of structures, scheduling in large systems, supply-chain management, financial engineering, and telecommunications systems planning.

Prerequisite: INDR 501 or consent of the instructor.

INDR 564 Dynamic Programming

Theory and practice of dynamic programming, sequential decision making over time; the optimal value function and Bellman's functional equation for finite and infinite horizon problems; Introduction of solution techniques: policy iteration, value iteration, and linear programming; General stochastic formulations, Markov decision processes; application of dynamic programming to network flow, resource allocation, inventory control, equipment replacement, scheduling and queueing control.

Prerequisite: INDR 501 and INDR 503 or consent of the instructor.

INDR 572 Reliability Theory

Basic concepts and definitions of system reliability. Series, parallel, k-out-of n systems. Structure functions, coherent systems, min-path and min-cut representations. System reliability assessment and computing reliability bounds. Parametric families of distributions, classes of life distributions and their properties. Shock and wear models. Maintenance, replacement and repair models. Current issues on stochastic modeling of hardware and software reliability.

Prerequisite: INDR 503 or consent of the instructor.

Math 503 Applied Mathematics

Review of Linear Algebra and Vector Fields: Vector Spaces, Eigenvalue Problems, Quadratic Forms, Divergence Theorem and Stokes Theorem. Sturm-Liouville Theory and Orthogonal Polynomials, Methods of Solution of Boundary Value Problems for the Laplace Equation, Diffusion Equation and the Wave Equation. Elements of Variational Calculus.

Math 504 Numerical Methods I

Review of Linear Algebra: linear spaces, orthogonal matrices, norms of vectors and matrices, singular value decomposition. Projectors, QR Factorization Algorithms, Least Squares, Conditioning and Condition Numbers, Floating Point Representation, Stability, Conditioning and Stability of Least Squares, Conditioning and Stability Analysis of Linear Systems of Equations.

Math 506 Numerical Methods II

Numerical Solution of Functional Equations, the Cauchy Problem and Boundary Value Problems for Ordinary Differential Equations. Introduction to the Approximation Theory of One Variable Functions. Finite - difference Methods for Elementary Partial Differential Equations. Monte Carlo Method and Applications.

MASE 501 (1,5 credits) Structure of Materials

Structure of materials; atomic structure and bonding, crystalline solids, symmetry, lattice and unit cell, determination of crystal structures; imperfections, defects in metals, vacancies, substitutional and interstitial impurities, dislocation defects in ionic solids.

MASE 502 (1,5 credits) Electrical & Optical Properties of Materials

Electrical properties of materials, band theory of solids, electrical conductivity, metals, semiconductors, and dielectrics; magnetic phenomena, ferromagnetism and diamagnetism, superconductors; optical properties of materials, refractive index, dispersion, absorption and emission of light, nonlinear optical properties, second- and third-order susceptibilities, Raman effect.

MASE 503 Thermodynamics & Kinetics

Classical thermodynamics: enthalpy, entropy, free energies, equilibria; introduction to statistical thermodynamics to describe the properties of materials; kinetic processes; diffusion of mass, heat, energy; fundamentals of rate processes in materials, kinetics of transformations.

MASE 504 (1,5 credits) Thermal Properties of Materials

Thermal properties of metals, polymers, ceramics and composites in relation to their structure & morphology; change in microstructural mechanisms and macroscopic behaviour with temperature; crystallization, melting & glass transition.

MASE 505 (1,5 credits) Mechanical Properties of Materials

Mechanical properties of metals, polymers, ceramics and composites in relation to their structure & morphology; stress-strain behaviour; elastic deformation, yielding, plastic flow; viscoelasticity; strengthening mechanisms, fracture, fatigue, creep.

MASE 506 Synthesis, Characterization & Processing of Materials

Experimental projects in the laboratory including topics from polymer synthesis & processing, composite materials, inorganic material/ceramic processing, metal processing, optical properties, electrical & magnetic properties, interfacial properties.

MASE 510 Synthetic Polymer Chemistry

Introduction to polymers (nomenclature, tacticity, molecular weight, physical state, properties & applications); Synthesis of polymers and macromolecular structures: step growth polymerization, chain growth polymerization; polymer reactions.

Prerequisite: Consent of the instructor.

MASE 511 Introduction to Polymer Science

Differences between the small molecules and macromolecules, thermosets and thermoplastics, and structure-property relationships in polymers. Introduces main polymer families. Also discusses supramolecular structures, blends, composites and IPNs.

Prerequisite: Consent of the instructor.

MASE 522 Vibrational Spectroscopy

Molecular symmetry, group theory, reducible and irreducible representation, character tables, introduction to vibrational spectroscopy, Raman effect, infrared absorption, selection rules, pure rotational spectroscopy, normal modes, prediction and interpretation of the vibrational spectra of polyatomic species.

MASE 530 Materials Behaviour

Materials behavior using phenomenological and microstructure-based approaches. Topics include plasticity, fracture, fatigue and micromechanics.

MASE 532 Statistical Mechanics of Polymers

Statistical mechanics of the single chain, configurational averages, polymer solution statistics and thermodynamics, dilute and concentrated polymer solutions, the bulk state of polymers, critical phenomena and phase equilibria; numerical techniques for polymeric systems.

MASE 534 Rubber Elasticity

Classical theories of rubber elasticity, elasticity of the single chain, intermolecular effects, effects of entanglements, relationships between stress and strain, swelling of networks, critical phenomena and phase transitions in gels, thermoelastic behavior of elastomers, computational aspects.

MASE 536 Multicomponent Polymeric Materials

Block and segmented copolymers, polymer blends and composites; design, preparation, properties and applications of multicomponent polymeric materials; phase separation in polymeric systems; structure-morphology-property relations in multicomponent polymers.

Prerequisite: CHEM 410 and MASE 510 and MASE 511

MASE 538 Intermolecular and Surface Forces

Intermolecular forces which govern self-organization of biological and synthetic nanostructures. Thermodynamic aspects of strong (covalent and coulomb interactions) and weak forces (dipolar, hydrogen bonding). Self-assembling systems: micelles, bilayers, and biological membranes. Computer simulations for "hands-on" experience with nanostructures.

Prerequisites: CHEM 301 or consent of the instructor.

MASE 540 Surface & Interface Properties of Materials

Fundamental physico-chemical concepts of surface and interface science; interaction forces in interfacial systems; surface thermodynamics, structure and composition, physisorption and chemisorption; fluid interfaces; colloids; amphiphilic systems; interfaces in polymeric systems & polymer composites; liquid coating processes.

MASE 542 Biomaterials

Materials for biomedical applications; synthetic polymers, metals and composite materials as biomaterials; biopolymers, dendrimers, hydrogels, polyelectrolytes, drug delivery systems, implants, tissue grafts, dental materials, ophthalmic materials, surgical materials, imaging materials.

Prerequisite: At least one semester of organic chemistry or consent of the instructor.

MASE 544 Nanoparticle Science and Technology

Size related properties of nanoparticles; synthetic strategies, main characterization tools, challenges and solutions, surface functionalization, technological applications and current trends.

Prerequisite: Consent of the instructor.

MASE 550 Optical and Laser Spectroscopy

Interaction of electromagnetic radiation with atoms and molecules, rotational spectroscopy, vibrational spectroscopy, electronic spectroscopy, spectroscopic instrumentation, lasers as spectroscopic light sources, fundamentals of lasers, nonlinear optical spectroscopy, laser Raman spectroscopy.

Prerequisite: Consent of the instructor.

MASE 570 Micro and Nanofabrication

Fabrication and characterization techniques for micro and nano electro mechanical systems, MEMS & NEMS (including: microlithography; wet & dry etching techniques; physical & chemical vapor deposition processes; electroplating; bonding; focused ion beams; top-down approaches - electron-beam lithography, SPM, soft lithography - ; bottom-up techniques based on self-assembly). Semiconductor nanotechnology. Nanotubes & nanowires. Biological systems. Molecular electronics.

Prerequisite: MECH 202 or consent of the instructor.

MASE 571 Semiconductor Processing Methods

Introduction, material properties, crystal growth, epitaxy, ion implantation, cleaning, wet etching, photolithography, non-optical lithography, plasma processing, dry etching, metal deposition, diagnostic techniques.

MECH 590 Seminar

A series of lectures given by faculty or outside speakers. Participating students must also make presentations during the semester.

MECH 596 Ph.D. Thesis

Independent research towards Ph.D. degree.

TEAC 500 Teaching Experience

Provides hands-on teaching experience to graduate students in undergraduate courses. Reinforces students' understanding of basic concepts and allows them to communicate and apply their knowledge of the subject matter.

ENGL 500 Graduate Writing

This is a writing course specifically designed to improve academic writing skills as well as critical reading and thinking. The course objectives will be met through extensive reading, writing and discussion both in and out of class. Student performance will be assessed and graded by Satisfactory/Unsatisfactory.

Requirements

Items listed below are only for applicant's information.
All the applicants should apply through ONLINE APPLICATION PPROGRAM.

* Application Form
* Personal and Educational Background Information (CV)
* 3 Recommendation Letters
* TOEFL , IELTS or UDS&KPDS Requirement (for those whose native language is not English) * New Internet Based: Minimum Score 80
* Computer Based: Minimum Score 213
* Paper Based: Minimum Score 550
* IELTS: Minimum Score 6,5
* UDS / KPDS: 87
* ALES scores (required for all Turkish nationals)
* GRE scores (required from foreign students; optional for Turkish students)


* Official transcripts from all the universities attended
* Statement of Purpose
* Areas of Interest

English Language Requirements

Funding

Scholarship

Students admitted with a BS/BA degree will have the following offer:
* Tuition waiver (33,500 TL/year) plus 1,150 TL monthly stipend, housing. The monthly stipend increases to 1,600 TL after the student passes the PhD qualifier.



Students admitted with a MS/MA degree will have the following offer:
* Tuition waiver (33,500 TL/year) plus 1, 400 TL monthly stipend. The monthly stipend increases to 1,600 TL after the student passes the PhD qualifier.



Additional Benefits:
* All students receive a laptop computer and private health insurance.


* Students with successful standing receive travel funds to attend scientific conferences and meetings.


* PhD students with higher GPA degrees may be offered super scholarship up to 2,500 TL .


* Students who receive their stipend from other sources (like TÜBITAK scholarships or externally funded research grants and projects) are eligible for the following benefits provided by the university:



* Research Award: 1,300 TL


* Free Housing: This includes all costs except telephone expenses.


* Research Award for PhD students: 2,000 TL/year after they pass the qualifier.