Study Programmes 2015-2016
MECA0027-1  
Structural and multidisciplinary optimization
Duration :
30h Th, 12h Pr, 18h Proj.
Number of credits :
Master in aerospace engineering (120 ECTS)5
Master in aerospace engineering (120 ECTS)5
Master in electro-mechanical engineering (120 ECTS)5
Master in electro-mechanical engineering (120 ECTS)5
Master in mechanical engineering (120 ECTS)5
Master in physical engineering (120 ECTS)5
Master in physical engineering (120 ECTS)5
Lecturer :
Pierre Duysinx, Patricia Tossings
Language(s) of instruction :
French language
Organisation and examination :
Teaching in the first semester, review in January
Units courses prerequisite and corequisite :
Prerequisite or corequisite units are presented within each program
Course contents :
The primary objective of the course is to present a systematic and critical overview of the various numerical methods available to solve optimization problems.
A second important goal is to familiarize participants with the introduction of optimization concepts into the design process. The basic concepts are illustrated throughout the course by solving simple optimization problems. In addition, several examples of application to real-life design problems are offered to demonstrate the high level of efficiency attained in modern numerical optimization methods. Although most examples are taken in the field of structural optimization, using finite element modeling and analysis, the same principles and methods can be easily applied to other design problems arising in various engineering disciplines.

Content


  • Introduction to Mathematical Programming Theory
  • Algorithms for Unconstrained Optimization: Gradient Methods
  • Line Search Techniques
  • Algorithms for Unconstrained Optimization: Newton and Quasi-Newton Methods
  • Quasi-Unconstrained Optimization
  • Linearly Constrained Minimization
  • General Constrained Optimization: Dual Methods
  • General Constrained Optimization: Transformation Methods
  • Reconciliation of OC and MP
  • Structural approximations
  • CONLIN and MMA
  • Sensitivity Analysis for Finite Element Model
  • Meta heuristic optimization algorithms
  • Introduction to shape optimization
  • Introduction to topology optimization
  • Solving identification problems using numerical optimization methods
Learning outcomes of the course :
At the end of the course the participants will be familiar with the fundamental optimization concepts applied to automatic design process.
They will be able:
  • to develop solution schemes to simple engineering optimization problems related to design or parameter identification (including the development of computer program written in MATLAB language),
  • to choose efficient formulations and optimization algorithms to solve their own problems using commercial tools,
  • to read, understand and take advantage of scientific papers from the field.
Prerequisite knowledge and skills :
  • Functional analysis of real functions
  • Matrix algebra
  • Matlab programming (basic level)
Planned learning activities and teaching methods :
  • Practical work sessions
  • Supervised computer work sessions
Mode of delivery (face-to-face ; distance-learning) :
Live presentation.
Attending 60% of supervised computer work sessions is mendatory.
Recommended or required readings :
Copy of slides available on line on the web site of Automotive Engineering Labs. www.ingveh.ulg.ac.be
Lecture notes of practical work sessions edited by La Centrale des Cours:
All the class notes are in English
Reference books (not mandatory)


  • Programmation mathématique: théorie et algorithmes (Tome 1). M. Minoux. Dunod, Paris, 1983.
  • Foundations of Structural Optimization: A Unified Approach. A.J. Morris. John Wiley & Sons Ltd, 1982
  • Haftka, R.T. and Gürdal, Z., Elements of Structural Optimization, 3rd edition, Springer, 1992
  • J. Nocedal and S. Wright. Numerical Optimization. Springer 2006.
Assessment methods and criteria :
Exam in January:
  • Oral theory exam
  • Report of supervised computer works
  • Computer works: Evaluation of the reports and their oral presentation
Work placement(s) :
Organizational remarks :
The lectures are given on Thursday morning (9:00-12:30) during fall semester (September 15 - December 18).
Exam during January session.
Computer works: deadlines for reports beginning of November and before Christmas.
Contacts :
Pierre Duysinx
  • LTAS-Automotive Engineering
  • Institute de Mécanique B52 0/514
  • Tel 04 366 9194
  • Email: P.Duysinx@ulg.ac.be
Patricia Tossings
  • Mathématiques Générales
  • Institut de Mathématique B37 0/57
  • Tél: 04 366 9373
  • Email. Patricia.Tossings@ulg.ac.be
Items online :
Site web du cours
Course Web site