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Keine Einordnung ins Vorlesungsverzeichnis vorhanden. Veranstaltung ist aus dem Semester WiSe 2021/22 , Aktuelles Semester: SoSe 2023
Masterseminar: Numerical Methods for Large Scale PDE Problems    Sprache: deutsch    Belegpflicht
Nr.:  106364     Seminar     WiSe 2021/22     2 SWS     keine Übernahme    
   Fachbereich: Fachbereich 10 Mathematik und Informatik    
      Master/Mathematics, PO 20 (88F23)
  Master/Mathematik, PO 10 (88105)
  Master/Mathematik, PO 13 (88105)
   Zugeordnete Lehrperson:   Rave verantwort
   Termin: Donnerstag   10:00  -  12:00    woch
Beginn : 21.10.2021   

The discretization of partial differential equations using finite element or finite volume methods often leads to high-dimensional equation systems that are too large to still be solved efficiently on a single computer. In this seminar we will explore different approaches to overcome this limitation:

Domain decomposition methods use decompositions of the computational domain into smaller subdomains, on which easily solvable sub-problems are formulated. These coupled sub-problems can then be solved in parallel on large compute clusters.

When the problem has multiple spatial or temporal scales, numerical multiscale methods can be used to formulate local cell problems which extract the necessary fine-scale information to then build an effective global macro-scale problem of small dimensions.

Often, the same problem has to be solved repeatedly for varying physical or geometrical parameters. In this case, model order reduction techniques can be used to build a low-dimensional surrogate model, which can be solved quickly for varying parameter values while retaining control over the approximation error.


An organizational meeting for the seminar will be held on Thursday, October 21, 10:00h at the meeting room of the applied maths department (room 120.029, Orléansring 10). The seminar will be held as a block seminar near the end of the semester. Due to the current situation, please contact stephan.rave@uni-muenster.de if you are interested in participating.


Knowledge of a discretization method for elliptic partial differential equations.