Robustness
Within the last few years, methods for stochastic analysis and robustness evaluation of FE models have been implemented in LS-OPT. For example, this may provide answers to the following questions:
- What is the probability that a specific failure limit will be exceeded?
- Is the solution robust or will a small change in the input variables render entirely different results?
- What is the relationship between input variable and response (solution) like – random or predictable?
- What is the correlation between variables and responses or among responses?
The objective of this course is to give the participants a comprehensive overview of the practical application of stochastic methods and of robustness analyses with LS-OPT. Moreover, participants will acquire a basic knowledge of statistics and probabilistics, and the methods used in LS-OPT will be discussed.
Content:
- Introduction, Terminology
- Definition dependent variables
- Selection of analysis values
- Statistical distributions: Normal (Gauß), Weibull, Uniform, Lognormal, User defined
- Stochastic methodologies: Monte Carlo analysis, Monte Carlo analysis using Meta-Models
- Confidence intervals
- Ant-Hill Plots
- Separation of deterministic and chaotic responses
- Variance and correlation plots
- Post-Processing in LS-OPT and result interpretation
- Examples
Prior attendance of the "Optimization with LS-OPT" course is recommended.
| Dates | Registration | Calendar | Duration/days | Location | Lecturer | Fee | Language |
| 25.05.2012 | Register |
|
1 | Stuttgart |
Dr. H. Müllerschön
|
450,- EUR | german |
| 23.11.2012 | Register |
|
1 | Stuttgart |
Dr. H. Müllerschön
|
450,- EUR | german |
