Scientific Computing Lab Outlook / State of Research Dr. Miriam Mehl Institut für Informatik Scientific Computing in Computer Science

Grids – Regular Grids 2D complicated geometries  Lab Course CFD

Grids – Adaptive Grids

Grids – Unstructured Grids source: grid generation  Scientific Computing I

More Grids triangular/tetrahedral grids: regular structured adaptive block structured mixed structured/unstructured …

Data Structures i j k data[k][j][i]

Data Structures

 projects / master thesis

Data Structures tetraheder 1tetraheder 2tetraheder 3 face 1face 2face 3face 4face 5 ….. edge 1 edge 2 edge 3 edge 4 ….. vertex 1vertex 2vertex 3 data …..

Discretisation – Finite Differences x x+h x-h

Discretisation – Finite Volumes V

Discretisation – Finite Elements  Scientific Computing I

Discretisation – Finite Elements physically correct basis, FE on adaptive grids  projects, master thesis

Solvers – Adaptive Multigrid  projects, master thesiscc

Solvers – Full Multigrid

Solvers – Krylov Methods solution of PDEs -> minimisation  Scientific Computing II

Solvers – Preconditioning  Scientific Computing II

Implementation/Parallelisation  Lab Course CFD  Parallel Numerics  projects, master thesis

Nonlinear PDEs / Systems of PDEs Navier-Stokes Solver  Lab Course CFD  projects, master thesis Newtons Method  Numerical Analysis I

Multiphysics example: fluid-structure interactions

Multiphysics Fluid Solver Structure Solver job/data data job/data data Coupling  projects, master thesis

Other Models Molecular Dynamics  Scientific Computing II