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Invitation: Free Structural and Composite Laminate Optimization Course

Dear all, 

Sabancı University, Composite Technologies Center of Excellence would like to invite you to a short course "STRUCTURAL AND COMPOSITE LAMINATE OPTIMIZATION" offered by Prof. Dr. Zafer Gürdal. Please find attached documents on course description, course syllabus and short bio of Prof. Dr. Zafer Gürdal.  
  • The size of the class is limited to 50 person. Therefore, please send your attendance request with an email to Nuray Tatli (nuraytatli@sabanciuniv.edu). Make sure to receive confirmation before coming to the class. 
  • Please arrive early to the first lecture (9:30). A safety training  will be held upon first arrival to the center. 
  • Lectures are free of charge 
Place: KTMM 3rd floor (Seminar Room)
Address:Sabancı Üniversitesi Kompozit Teknolojileri Mükemmeliyet Merkezi (KTMM), Kordsa Binası-Teknopark, İstanbul Teknoloji Geliştirme Bölgesi, Sanayi Mah. Teknopark Bulvarı No:1/1B, 34906  Pendik / İstanbul-Türkiye
Date: 26.06.2018 Tuesday (First Lecture) 
Time: 10:00-11:20
Language: English

 

*Address:Sabancı Üniversitesi Kompozit Teknolojileri Mükemmeliyet Merkezi (KTMM), Kordsa Binası-Teknopark, İstanbul Teknoloji Geliştirme Bölgesi, Sanayi Mah. Teknopark Bulvarı No:1/1B, 34906  Pendik / İstanbul-Türkiye

*Date: 26.06.2018 Tuesday (First Lecture) 

*Time: 10:00-11:20

*Language: English

STRUCTURAL and Composite Laminate Optimization

 

Instructor:                  Zafer Gürdal
(zgurdal@sc.edu)   
Lectures: T, Th:  10:00-11:20,  Room: Conference Hall-3rd floor Composite Center

Description:                Introduction to optimization concepts in structural design.  Application of techniques of mathematical programming along with matrix structural analysis to optimize trusses, beams, columns, and other structures. Integer Programming and Genetic Algorithms for designs with discrete variables, in particular Composite Laminate Optimization. Sensitivity calculations of structural response. Approximation techniques. Fast reanalysis techniques.

Goals and                    Overall goal of the course is to enable engineers to formulate and solve structural  

Learning Outcomes:   design problems using advances design optimization tools along with advanced structural analysis tools in an efficient and accurate manner.  A major emphasis will be integration of matrix methods of engineering analysis with design optimization tools.  The specific learning outcomes are to be able to:

  • prescribe a given structural design problem into a standard mathematical optimization formulation
  • find a suitable optimization algorithm and structural analysis tool for the solution
  • integrate an optimization tool with structural analysis tools for iterative design
  • implement structural sensitivity analysis for linear, nonlinear, and eigenvalue problems
  • implement approximation concepts for linear and nonlinear structural response
  • perform composite laminate stacking sequence optimization

Textbook:                   Class notes.

References:                 R. T. Haftka and Z. Gürdal, Elements of Structural Optimization, Kluwer Academic Publishers, Boston, 1993.

                                    Z. Gürdal, R.T. Haftka, and P. Hajela, Design and Optimization of Laminated Composite Materi­als, John Wiley & Sons, Inc, New York, NY, 1999.

Required Tool:            Mathematica software will be heavily used throughout the course, and students will benefit from having their own copy in lieu of a textbook.    

Course Topics:            Among the topics to be covered are:

Introduction to Structural Optimization

                                    Review of Unconstrained & Constrained Optimization

                                    Introduction and Review of Matrix Structural Analysis

                                    Karush-Kuhn-Tucker Conditions

                                    Classical Tools in Structural Optimization

                                    Optimization of Truss & Membrane Structures

                                    Integer Programming and Genetic Algorithms

                                    Sensitivity Analysis, Adjoint Method

                                    Sensitivity of Eigenvalue and Nonlinear Problems

                                    Local and Global Approximations

                                    Fast Reanalysis Techniques

                                    Topology Optimization

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