Program Description 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).
Degree Requirements Students
can apply to the Ph.D. programs with a B.S. or M.S. degree. The Ph.D.
degree requires successful completion of 14 courses beyond the B.S.
degree or 7 courses beyond the M.S. degree. All students must pass the
Ph.D. Qualifying Examination in the first year after they have been
admitted to the Ph.D. program. Students are encouraged to begin
research early. Students who have passed the Ph.D. qualifying
examination are assisted in matters pertaining to their thesis research
by a faculty thesis advisory committee. The research advisor serves as
the chair of this committee. The committee meets with the student at
least once each semester. Ph.D. students must submit a satisfactory
written Ph.D. thesis proposal in their second year of study. At the
completion of the Ph.D. research, the students must submit a written
Thesis and pass an oral defense to complete the degree requirements.
Faculty and Research Areas Erdem Alaca ; Mechanical Engineering
Research Areas: Micro and Nanofabrication, MEMS-based Biosensors, Materials Behaviour, Engineering Mechanics
Ipek Basdogan ; Mechanical Engineering
Cagatay Basdogan ; Mechanical Engineering
Research
Areas: Robotics, Mechatronics, Control Systems, Human-Machine
Interfaces, Nanotechnology, Biomechanics, Computer Graphics, and
Virtual Reality
Burak Erman ; Chemical & Biological Engineering
Research Areas: Computational studies of polymers, proteins and complex biological systems
Ismail Lazoglu ; Mechanical Engineering
Research
Areas: Automation and Mechatronics, Computer Aided Design (CAD) /
Engineering (CAE) / Manufacturing (CAM), Dynamic Systems and Control,
Artificial Organs, Development of Medical Assist Systems
Metin Muradoglu ; Mechanical Engineering
Research Areas: Multiphase flows in bio/micro fluid systems, turbulent combustion, scientific computing. Thesis Projects
Mehmet Sayar ; Materials Science and Engineering
Murat Sozer ; Mechanical Engineering
Research Areas: Manufacturing of composite materials; modeling and control of liquid composite molding (LCM) processe
Curriculum Graduate curriculum consists of the following 3-credit courses:
- CMSE 501 Introduction to Computational Science
- CMSE 581 Selected Topics in Computational Chemistry
- CMSE 582 Selected Topics in Computational Physics
- CMSE 583 Selected Topics in Computational Biology
- ECOE 510 Computer Graphics
- ECOE 521 Photonics and Lasers
- ECOE 522 Micro-opto-electro-Mechanical Systems
- ECOE 554 Machine Learning
- ECOE 570 Bioinformatics and Algorithms in Computational Biology
- INDR 501 Optimization Models and Algorithms
- INDR 505 Manufacturing Systems
- INDR 508 Discrete Event Simulation
- INDR 510 Mathematical Statistics
- INDR 551 Advanced Optimization Methods
- INDR 560 Large Scale Optimization
- INDR 564 Dynamic Programming
- INDR 572 Reliability Theory
- MATH 503 Applied Mathematics
- MATH 504 Numerical Methods
- MATH 506 Numerical Methods II
- MASE 501 Structure of Materials(1,5 credits)
- MASE 502 Electrical & Optical Properties of Materials (1,5 credits)
- MASE 503 Thermodynamics & Kinetics
- MASE 504 Thermal Properties of Materials (1,5 credits)
- MASE 505 Mechanical Properties of Materials (1,5 credits)
- MASE 506 Synthesis, Characterization & Processing of Materials (4 credits)
- MASE 510 Synthetic Polymer Chemistry
- MASE 511 Introduction to Polymer Science
- MASE 522 Vibrational Spectroscopy
- MASE 530 Materials Behaviour
- MASE 532 Statistical Mechanics of Polymers
- MASE 534 Rubber Elasticity
- MASE 536 Multicomponent Polymeric Systems
- MASE 538 Intermolecular and Surface Forces
- MASE 540 Surface & Interface Properties of Materials
- MASE 542 Biomaterials
- MASE 544 Nanoparticle Science and Technology
- MASE 550 Optical Spectroscopy of Materials and Devices
- MASE 570 Micro and Nanofabrication
- MASE 571 Semiconductor Processing Methods
Courses
are selected by the students from the above list and from other courses
not listed here in accordance with their areas of specialization and
subject to the approval of their advisors. In addition, each student
has to take a seminar course, MECH 590 Seminar. Students also register
for the thesis course.
- MECH 590 Seminar
- MECH 596 PhD Thesis
- TEAC 500 Teaching Experience
Students
who have TA assignments must take TEAC 500: Teaching Experience during
the semesters of their assignments. Students must also take ENGL 500:
Graduate Writing course.
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.