Daniel Arndt - Interdisciplinary Center for Scientific Computing
Daniel Arndt

 
Contact

Dr. Daniel Arndt
Interdisciplinary Center for Scientific Computing (IWR)
Im Neuenheimer Feld 205
Room 1.412
69120 Heidelberg
Germany
 
Tel: +49 (0)6221-54 14538
E-Mail http://www.mathsim.eu/~darndt

 
Compact Course deal.II

Lecturer Daniel Arndt
Class data: LSF MÜSLI
Date 09.04.2018-13.04.2018, 09:00-16:00
Room Mathematikon (INF 205), PC-Pool SW 1
deal.II-Logo

 
Summary

deal.II is a free, open source library to solve partial differential equations using the finite element method. The aim of this course is to provide an introduction into this framework. After this course, students should be able to implement suitably easy problems in deal.II.

The course will take place in the PC-Pool SW 1 with a preinstalled deal.II version. Since you will need your own installation for your final project, it is recommended to install deal.II on your own notebook. For using amandus, you will need to use a developer version. Instructions for installing can be found here. Files used in the course can be found here.


 
Target group

Students of mathematics (BSc, MSc, PhD) as well as students of scientific computing (MSc, PhD).


 
Prior Knowledge

Basic knowledge of FEM and C++ is required.


 
Participation

The number of participants is limited to 25 students. Please register via MÜSLI (or e-mail containing subject of study, semester and academic degree). Preferrably, also state subjects of interest for the course and a problem you want to solve using deal.II in separate e-mail.

For the successful completion of the final project (project summary, short presentation) 6 CP are awarded.


 
Topics

We will loosely follow the following outline
  1. Short introduction to FEM and deal.II
  2. Creating and refining meshes. Setting up finite element spaces.
  3. A first Poisson solver
  4. A multilevel Poisson solver with discontinuous Galerkin methods
  5. Meshworker
  6. Mixed finite elements
  7. Time-dependent problems
  8. Eigenvalue problems
  9. Exploring error estimation and adaptive refinement
  10. Parallelization (MPI)

 
Project Summary

  • The project summary has to be written using doxygen or LaTeX.
  • Code has to be suitably commented.

 
Sources