Digital simulations are increasily used for modeling physic, chemical or biologic, but also economic or financial systems. They help limit risk and avoid the real experience side (car crash tests). They can in different steps of an industrial or economic project: during design of the pre-project, during optimization of the final project, and during validation of the achieved project.
This raises the question of how much confidence we can have in the predictions and decisions from such simulations. various uncertainty sources exist: incertainties on some physic parameters, on environmental conditions, on manufacturing errors, on relevent or neglected phenomenon and their modeling.
The aim of this course is to present mathematic methods allowing the modeling, indentification and analysis of uncertainties in digital simulations.
- Teaching coordinator: Garnier Josselin
- Teaching coordinator: Le Maitre Olivier
- Teaching coordinator: Lelievre Tony
- Teaching coordinator: Rey Clément