| TMKT48 |
Design Optimization, 6 ECTS credits.
/Konstruktionsoptimering/
For:
DPU
I
Ii
M
MEC
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Prel. scheduled
hours: 70
Rec. self-study hours: 90
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Area of Education: Technology
Main field of studies: Mechanical Engineering
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Advancement level
(G1, G2, A): A
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Aim:
The course aims at integrating traditional design methodologies with concepts and techniques of modern optimisation theory and practice. In the course the student will learn to create an appropriate mathematical description (a simulation model) of the design problem, to formulate the optimisation problem and finally to use numerical optimisation techniques and computer support tools in order to solve the problem. After the course the student:
- Should understand and be able to describe the function of a set of iterative optimization methods such as Genetic Algorithms, the Complex Method, and gradient methods (Newton methods)
- Should be able to compare and evaluate the suitability of different optimization methods for different problem types.
- Should be able to formulate design problems as mathematical optimization problems.
- Should be able to implement mathematical models of design problems in MATLAB and solve them using numerical optimization methods.
- Should be able to describe how simulation and optimization could be connected.
- Should be able to implement the connection between simulation and optimization in the MATLAB/Simulink environment.
- Should be able to analyze the sensitivity of the obtain optimal solutions.
- Should be able to discuss the plausibility of the results.
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Prerequisites: (valid for students admitted to programmes within which the course is offered)
Introductory courses in mathematics, mechanics, solid mechanics and mechanical engineering design.
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding.
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Organisation:
Lectures, seminars, computer exercises where the methods and techniques thought in the course are applied to real design tasks.
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Course contents:
Optimization in the desing process
Optimization methods: Genetic Algorithms, the Complex method, gradient based methods
Formulation of design problems as optimization problems
Formulation of objective functions
Optimization based on simulation models
Multi-objective optimization
Constraints and penalty functions
Post optimal analysis
Sensitivity analysis
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Course literature:
Scientific articles, compendium.
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Examination: |
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Examination
Design task
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5 ECTS
1 ECTS
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Course language is Swedish/English.
Department offering the course: IEI.
Director of Studies: Mikael Axin
Examiner: Johan Persson
Link to the course homepage at the department
Course Syllabus in Swedish
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