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| MECA0027-1 | Structural and multidisciplinary optimization
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| Duration : | 30h Th, 30h Pr |
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| Number of credits : |
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| Lecturer : | Pierre Duysinx, Patricia Tossings |
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Language(s) of instruction :
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| French language |
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Organisation and examination :
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| Teaching in the first semester, review in January |
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Course contents :
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| 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
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Learning outcomes of the course :
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| 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 or to choose efficient formulations and optimization algorithms to solve their own problems using commercial tools. |
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Prerequisites and co-requisites/ Recommended optional programme components :
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- Functional analysis of real functions
- Matrix algebra
- Matlab programming (basic level)
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Planned learning activities and teaching methods :
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- Exercises
- Supervised computer works
- Computer project (2 students/group) : equivalent to 12h
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Mode of delivery (face-to-face ; distance-learning) :
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| Live presentation |
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Recommended or required readings :
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| Copy of slides available on line on the web site of Automotive Engineering Labs. www.ingveh.ulg.ac.be
Notes of Prof. Fleury edited by La Centrale des Cours:
Optimisation des Structures: Théorie
Optimisation des Structures: Exercices
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
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Assessment methods and criteria :
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| Exam in January:
- Oral theory exam
- Written exam of exercices (with open books)
- Report of supervised computer works
- Computer work: Report evaluation and its oral presentation
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Work placement(s) :
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Organizational remarks :
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| The lectures are given on Thursday morning (8:30-12:30) during fall semester (September 15 - December 15). Exam in January. |
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Contacts :
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| 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
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| Items online : |
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| Lecture notes available on line |
| Lecture notes available on line on www.ingveh.ulg.ac.be |
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