Speaker
Description
Predictions from computer models are now extensively in industrial studies, to complement, or even sometimes replace, field experiments. Such numerical experiments have key advantages, such as reduced costs, and added flexibility. However, they raise the question of assessing the validity of computer model predictions, with respect to the physical phenomena they seek to reproduce. This is the goal of verification, validation and uncertainty quantification (VVUQ), a process whose development is an active field of research in applied mathematics. The goal of this talk is to present the different objectives and challenges of VVUQ, as well as a generic workflow that can be applied to virtually any uncertainty quantification problem. We then discuss software libraries that implement this methodology, as well as open problems and perspectives.