Atmospheric reentry - © Inria / Bacchus
The Inria Bordeaux – Sud-Ouest Center is pleased to announce the BOQUSE workshop, organized by the Bacchus research team, in collaboration with the Bordeaux University “Cluster of excellence” (CPU)
- Date : 16/12/2013 to 18/12/2013
- Place : Talence, Inria Bordeaux - Sud-Ouest Centre
- Organiser(s) : Inria and CPU Cluster
Three days to discuss the progress in flows simulation
and more specifically the quantification of the uncertainties in Fluid Mechanics
. This topic has a strong impact in several domains : aerospace
, renewable energies
(geothermal energy, solar energy)
, geophysical flow (hydroelectric dams, tsunami or power plant)
, and so on.
Le workshop, qui prend place au sein du Centre Inria Bordeaux – Sud-Ouest réunit des scientifiques de renommée internationale venus de France, Suisse, Italie, des Pays-Bas ou encore des Etats-Unis… Il se déroulera à travers 3 journées thématiques (invités le matin et exposés-abstracts sélectionnés par les organisateurs l’après-midi) :
- 16th Decembe r : numerical methods and algorithms
- 17th December : applications in Fluid Mechanics, such as turbulence, multiphase flows, hypersonic flow, ...
- 18th December : sensitivity and optimization : interest in using uncertainty quantification for the robust optimization.
Optimization and design in the presence of uncertain operating conditions, material properties and manufacturing tolerances poses a tremendous challenge to the scientific computing community . In many industry-relevant situations the performance metrics depend in a complex, non-linear fashion on those factors and the construction of an accurate representation of this relationship is difficult. In addition to that, the numerical simulation in Fluid Mechanics is far to be predictive because of the presence of numerous sources of uncertainty, in particular in shock-dominated turbulent flows. In this case, the problem is to find an efficient representation of the stochastic solution, when the flow presents some discontinuities, thus producing a shock evolving in the coupled physical/stochastic space. As a consequence, developing efficient numerical techniques for handling uncertainties in fluid-flow problems is very challenging.