Numerical simulations are increasingly used to model physical, chemical and biological systems, as well as economic and financial systems. They can be used to limit the risks and avoid the costs of real experiments (e.g. car crash tests), or to make predictions about the behavior of these systems (e.g. epidemiological models). They can be used at different stages of an industrial or economic project: during the design of a preliminary project, during optimization of the final project, and during validation of the completed project. This raises the question of how much confidence can be placed in the predictions and decisions resulting from such simulations. Indeed, there are many sources of uncertainty: uncertainties about certain physical parameters, about environmental conditions, about manufacturing errors, about the phenomena taken into account or neglected, and about their modeling.
The aim of this course is to present mathematical methods (essentially probabilistic and statistical) for modeling, characterizing and analyzing uncertainties in numerical simulations.
- Teaching coordinator: Garnier Josselin
- Teaching coordinator: Le Maitre Olivier
- Teaching coordinator: Lelievre Tony
- Teaching coordinator: Rey Clément