LS-DYNA Compact: LS-OPT Optimization
The use of new materials, such as plastics, composites, foams, fabrics or high-tensile steels, demands the application of highly complex material models.
These material formulations are generally associated with numerous material parameters. The optimization program LS-OPT is ideally suited for identifying these parameters.
In the identification process, an automatic comparison is carried out between the experimental results and the simulation results of LS-DYNA. Thereafter, the error between experiments and simulations is minimized.
In this seminar, a brief introduction to LS-OPT is given with a focus on the application of LS-OPT to determine material parameters.
No prior knowledge about optimization or the application of LS-OPT is required.
The webinar will take place from 9-11 a.m. (CET).
Contents
- Brief introduction to LS-OPT
- The optimization problem for the parameter identification
- Objective function: to minimize deviations between simulations and experiments (least-squares principle)
- Constraints
- Optimization variables
- Normalization and weighting
- Min. / max. formulation: minimizing the maximum deviation
- Graphical User Interface (GUI)
- Simultaneous adaptation of several experiments (e.g. tensile test, shear test and biaxial test)
- Starting LS-DYNA simulations and job control in LS-OPT
- Analysis and evaluation of optimization results
- Live demonstration
Dates | Duration/days | Calendar | Registration | Referee | Language | Location | Fee |
---|---|---|---|---|---|---|---|
14.02.2023, 09:00 - 11:00 | 2 h | Add to calendar | Charlotte Keisser | French | 200 € | ||
03.07.2023, 09:00 - 11:00 | 2 h | Add to calendar | Registration | Charlotte Keisser | English | 200 € | |
21.11.2023, 09:00 - 11:00 | 2 h | Add to calendar | Registration | Charlotte Keisser | English | 200 € |
Lecturers
Katharina Liebold

Dipl.-Math.
Area of expertise:
Optimization
Academic studies:
Mathematics
Charlotte Keisser

Diplôme d’Ingénieur
Area of expertise:
Optmization
Academic studies:
Computer science and applied mathematics