Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

151-0840-00L  Principles of FEM-Based Optimization and Robustness Analysis

SemesterSpring Semester 2019
LecturersB. Berisha, P. Hora, N. Manopulo
Periodicityyearly recurring course
Language of instructionEnglish

AbstractThe 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.
ObjectiveReal 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. LS-Dyna to evaluate the mechanical response of a system, and an optimization tool e.g. LS-Opt for the mathematical optimization and robustness analysis.
ContentPrinciples 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 LS-Dyna
- Optimization based on meta modeling techniques
- Introduction into structure optimization
- Introduction into geometry parameterization for shape and topology optimization

Robustness and sensitivity of multiparameter systems

- Introduction into stochastics and robustness of processes
- Sensitivity analysis
- Application examples
Lecture notesyes