Conférence Finite Volumes for Complex applications 8
La conférence Finite Volumes for Complex Applications 8 aura lieu du 12 au 16 juin 2017 au centre LILLIAD, Cité scientifique à Villeneuve d'Ascq.
- Date : 12/06/2017 au 16/06/2017
- Lieu : LILLIAD - Cité scientifique - Villeneuve d'Ascq
Objectives of the conference
The finite volume method in its numerous variants is a space discretization technique for partial differential equations based on the fundamental physical principle of conservation. It has been used successfully in many applications including fluid dynamics, magnetohydrodynamics, structural analysis, nuclear physics, and semiconductor theory. Recent decades have brought significant success in the theoretical understanding of the method. Many finite volume methods preserve further qualitative or asymptotic properties including maximum principles, dissipativity, monotone decay of the free energy, or asymptotic stability. Due to these properties, finite volume methods belong to the wider class of compatible discretization methods, which preserve qualitative properties of continuous problems at the discrete level. This structural approach to the discretization of partial differential equations becomes particularly important for multiphysics and multiscale applications.
The goal of the conference is to bring together mathematicians, physicists, and engineers interested in physically motivated discretizations. Contributions to the further advancement of the theoretical understanding of suitable finite volume, finite element, discontinuous Galerkin and other discretization schemes, and the exploration of new application fields for them are welcome.
- Design and analysis of numerical methods
- Preservation of physical properties on the discrete level
- Convergence, stability, a priori and a posteriori error analysis
- Applications at the interface with other disciplines
- HPC, parallel computing
- Industrial applications
- Model reduction and multiscale methods
- High-order methods
- Uncertainty quantification and stochastic problems
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