LS-OPT - Robustness

Course description

This course gives an introduction to the robustness part of the software LS-OPT, which is available to all LS-DYNA users for free. Theory for robustness studies and robust parameter design is covered, as well as some application examples. A significant time of the course is spent on hands on training with the software and how to use it together with LS-DYNA. LS-OPT is designed to be used with essentially any analysis software.

Who is it for

Engineers that would like to learn how to do stochastic analysis such as robustness analysis and robust parameter design using LS-OPT and LS-DYNA. LS-DYNA will be used as the analysis solver and therefore attendees need to have at least a basic knowledge of LS-DYNA and LS-PrePost

Contents

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.

Outline

  • 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 Referee Fee Language
14.09.2017   1 Gothenburg
D. Aspenberg
4000,- SEK english
25.05.2018 Register   1 Linköping
D. Aspenberg
4000,- SEK english