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Master Seminar Applied Mathematics - Single View

Basic Information
Type of Course Seminar Long text
Number 106364 Short text
Term WiSe 2021/22 Hours per week in term 2
Expected no. of participants Study Year
Max. participants
Credits Assignment enrollment
Hyperlink
Language german
Dates/Times/Location Group: [no name] iCalendar export for Outlook
  Day Time Frequency Duration Room Room-
plan
Lecturer Status Remarks Cancelled on Max. participants
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Thu. 10:00 to 12:00 weekly from 21.10.2021           
Group [no name]:
 


Responsible Instructor
Responsible Instructor Responsibilities
Rave, Stephan, Dr. responsible
Curriculae
Graduation - Curricula Sem ECTS Bereich Teilgebiet
Master - Mathematics (88 F23 20) -
Master - Mathematik (88 105 10) -
Master - Mathematik (88 105 13) -
Exams / Modules
Number of Exam Module
18004 Vorlesung 2 (mit Studienleistung) - Master Mathematik Version 2013
18003 Vorlesung 2 (ohne Studienleistung) - Master Mathematik Version 2013
22003 Seminar oder Lesekurs - Master Mathematik Version 2013
20004 Seminar - Master Mathematics Version 2020
12002 Seminar - Master Mathematics Version 2020
Assign to Departments
Fachbereich 10 Mathematik und Informatik
Contents
Description

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.

Remarks

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.

Prerequisites

Knowledge of a discretization method for elliptic partial differential equations.


Structure Tree
Lecture not found in this Term. Lecture is in Term WiSe 2021/22 , Currentterm: WiSe 2022/23