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Principles of FEM-Based Optimization and Robustness Analysis
Last Updated: 2026-02-05 15:42:01
Abstract
The course provides fundamentals of stochastic simulation and non-linear optimization methods. Methods of non-linear optimizaion for complex mechanical systems will be introduced und applied on real processes. Typical applications of stochastical methods for the prediction of process stability and robustness analysis will be discussed.
Objective
Real systems are, in general, of non-linear nature. Moreover, they are submitted to process parameter variations. In spite of this, most research is performed assuming deterministic boundary conditions, in which all parameters are constant. As a consequence, such research cannot draw conclusions on real system behavior, but only on behavior under singular conditions. Hence, the objective of this course is to give an insight into stochastic simulations and non-linear optimization methods. Students will learn mathematical methods e.g. gradient based and gradient free methods like genetic algorithm, and optimization tools (Matlab Optimization Toolbox) to solve basic optimization and stochastic problems. Furthermore, special attention will be paid to the modeling of engineering problems using a commercial finite element program e.g. ABAQUS to evaluate the mechanical response of a system, and an optimization tool e.g. LS-Opt for the mathematical optimization and robustness analysis.
Content
Principles of nonlinear optimization - Introduction into nonlinear optimization and stochastic process simulation - Principles of nonlinear optimization - Introduction into the design optimization and probabilistic tool LS-Opt - Design of Experiments DoE - Introduction into nonlinear finite element methods Optimization of nonlinear systems - Application: Optimization of simple structures using LS-Opt and ABAQUS - Optimization based on meta modeling techniques - Introduction into structure optimization - Introduction into geometry parametrization for shape and topology optimization Robustness and sensitivity of multiparameter systems - Introduction into stochastics and robustness of processes - Sensitivity analysis - Application examples
General Information
- Language
- English
- Levels
- BSC , DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- written 120 minutes
- Aids
- 1x A4 sheet, double-sided with notes/summary, scientific calculator.
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Principles of FEM-Based Optimization and Robustness Analysis |
|
2 h weekly |
| exercise |
Principles of FEM-Based Optimization and Robustness Analysis
If required, two dates for exercises will be offered.
Bei Bedarf werden zwei Übungstermine angeboten.
|
|
2 h weekly |
Offered In
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Manufacturing Science (Focus Coordinator: Prof. Konrad Wegener To achieve the required 20 credit points for the focus specialization you need to pass all 3 compulsory courses (HS/FS). The other 8 credit points can be achieved from the elective courses.)
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Electives (In the ‘electives’ subcategory, at least two course units must be successfully completed.)
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Mechanics, Materials, Structures (The courses listed in this category “Core Courses” are recommended. Alternative courses can be chosen in agreement with the tutor.)
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Electives (In the ‘electives’ subcategory, at least two course units must be successfully completed.)
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Doctoral Department of Mechanical and Process Engineering (More Information at: )