LMGC90 Training session
Trainers: Frédéric Dubois, Rémy Mozul
Inscription: mail to firstname.lastname@example.org
Limited to 20 !
Dates: 01/03/2021 to 05/03/2020
Training sessions will be in French.
- Python basics
- Unix terminal basics
- To learn how to use LMGC90.
- To learn the python pre-processor possibilities to manage large collection of bodies.
- Overview of some advanced possibilities of LMGC90 software.
Due to the global sanitary conditions, the formation will be provided through zoom.
The attendees will receive the connexion link by email within one hour before the start of each session.
It would be appreciated that LMGC90 is installed beforehand (please check How does it work section of the wiki if need be).
In case of problem help will be provided on-line for installation or at least to access LMGC90 through a web API,
This detailed schedule is not decided yet. And the data provided here are provisional and subject to changes.
Each Day: from 9h00 to 12h00 and from 13h30 to 17h00
- Rough presentation of the software
- Introduction of the attendees
- Reminder of Python basics (with training)
- Basic ideas governing the pre-processing of rigids
- Training period
- Reminder of Python for scientific uses
- Computation, post-processing and visualization with rigids
- Training period
- More on rigids
- Some advanced featurers
- Thursday and Friday:
- Deformable modelling
A more detailed list of the different subjects approached would be:
- Introducing round table with the attendees
- Presentation of LMGC90 possibilities
- Presentation of the user version of LMGC90
- Installing the software
- Recall of Python use
- General introduction to the pre-processing tools
- Resolution strategies: the NSCD method
- Details on the input data files and command scripts
- Advanced features
- Discussions on detection algorithms
- Introduction to possibilities to improve computation time
- Round table
- Practical Work:
- use of LMGC90 pre-processor
- use of GMSH
- use of LMGC90 for rigid and deformable bodies
- post-processing and visualization