Bergische Universität Wuppertal
Fachbereich Mathematik und Naturwissenschaften
Applied and Computational Mathematics (ACM)

Team
Research
Publications
Teaching


Univ.-Prof. Dr. Matthias Ehrhardt
Prof. Dr. Pavel Petrov
Petr Petrov, M.Sc.

Vorlesung im Sommersemester 2025:

Numerical Analysis and Simulation II:
Partial Differential Equations (PDEs)

(This course will be given in English)


Schedule
 
 Lecture (Pavel Petrov)  Mon, 14:15 - 15:45   Hörsaal  5, Gebäude G.10.07   Date:  weekly, starting April 14  
 Lecture (Matthias Ehrhardt)  Tue, 14:15 - 15:45   Hörsaal  6, Gebäude G.10.06   Date:  weekly, starting April 15 
 Exercise (Petr Petrov)  Thu, 12:15 - 13:45   Hörsaal  7, Gebäude G.10.05   Date:  weekly, starting April 17  

Please also register here in MOODLE!

Consultation Hours for exam:
 Consultation Hours (Ehrhardt)  by appointment   Room  G.13.23   Date:  May, June, July 
 Consultation Hours (Pavel Petrov)  by appointment   Room  G.14.22   Date:  May, June, July 
 Consultation Hours (Petr Petrov)  Mon,  ???    Room  G.13.24   Date:  May, June, July 

ausführliche Gliederung der Vorlesung / detailed Outline of the Course

Übungsblätter, Exercise Sheets

Lösungen, Solutions to Exercises

Content:
Partial differential equations arise frequently in the modeling of physical, chemical, or biological phenomena.

The lecture deals with the numerical solution of partial differential equations and the estimation of the error between continuous and discrete solution. We will first study classical finite difference methods for parabolic and elliptic problems and their modern further development, the so-called compact methods, with respect to consistency, stability and convergence.

After an introduction to the theory of Sobolev spaces, finite element discretizations are developed and analyzed based on the weak solution theory of elliptic boundary value problems. Subsequently, multigrid methods for solving the resulting systems of equations are discussed. The lecture concludes with a brief outline of boundary element methods.

The focus is on the connection of theory, numerical analysis and practical implementation issues by means of programs in an accompanying practical course. The students are familiarized with free software in an integrative way: while most of the programming tasks are implemented with GNU Octave / Scilab , the symbolic software Maxima is used to design a tool which determines the resulting mass and stiffness matrices for a variety of approach and test functions.

Matlab, GNU Octave and Scilab, respectively, are recommended for the implementation of the practical tasks. In addition to the use of dedicated learning software for finite elements (CALFEM) and multigrid methods (MGLab), the use of Matlab PDE Toolbox, NMLibforOctave and Scilab finite element toolbox FreeFEM will be learned.


Topics of the Lecture:

  1. Finite Difference Schemes for parabolische and elliptic PDEs
  2. Introduction to the Theory of Sobolev Spaces
  3. Variational formulation of Boundary Value Problems
  4. The Finite Element Method
  5. Introduction to Multigrid Methods
  6. Boundary Element Methods
  7. Hyperbolic Conservation Laws
Focused Topics of Wave Propagation:
  1. Paraxial equation, Schrödinger equations, respective IBVPs benchmark/analytical solutions
  2. Crank-Nicolson (CN) numerical scheme, stability issues, Perfectly matched layers (PML)
  3. SpiltStep Fourier (SSF) method, implementation, combination with the PML
  4. One-way counterparts of elliptic PDEs (wide-angle parabolic equations), split-step Padé method
  5. General pseudospectral methods for linear and non-linear equations

Target Audience:

Remarks:

Pre-Knowledge:
Analysis I-II, Linear Algebra I-II, Introduction to Numerical Mathematics.
Numerics of ODEs is helpful.

Lecture Notes:

Literature:

detailed references for the lecture


University of Wuppertal
Faculty of Mathematics and Natural Sciences
Department of Mathematics
Applied Mathematics & Numerical Analysis Group

Last modified:   Disclaimer   ehrhardt@math.uni-wuppertal.de