Load:

1. komponenta
Lecture type  Total 
Lectures 
45 
* Load is given in academic hour (1 academic hour = 45 minutes)

Description:

COURSE AIMS AND OBJECTIVES: The aim of the course is to introduce classical and modern methods of solving of linear and nonlinear partial differential equations. Finite element and finite volume methods.
COURSE DESCRIPTION AND SYLLABUS:
1. Finite element method. Method is introduced at the elliptic equation first: variational approximation principle, elemetary proof of the LaxMilgram, interpolation problem for the Lagrange interpolation. The interpolation estimates are proved in the Sobolev spaces, which are introduced intuitively. Nonconform approximation onlz in the abstract setting of Strang lemmas. Numerical integration, inverse estimates, AubinNiche lemma, nonhomogeneous boundary conditions and regular triangulations. Condition number of the approximation problem matrix.
2. Mixed finite element method for difusion. BabuškaBrezzi condition. RaviarThomas elements.
3. Parabolic equations. Varijational formulation and apriori estimates explained in a formal procedure. Time discretisation (implicit and explicit) and apriori estimates. Applications: Pironeau's FreeFEM++. Iterative solvers and preconditioning informaly introduced.
4. Finite volume method. Discretization on regular meshes: cellcentred and cellvertex methods. Applications on eliptic and parabolic equations and the covectiondifusion equation. Comparasion with mixed finite element method.
5. During the course at least one nonlinear problem should be solved using the Newton iterations.

Literature:

 A. Quateroni, A. Valli: Numerical Approximation of Partial Differential Equations, Springer Series in Computational Mathematics Vol. 23
 R. Le Veque: Finite volume methods
 P. Knabner, L. Angerman: Numerical methods for elliptic and Parabilic PDEs
 O. Axelsson, V. A. Barker: Finite Element Solution of Boundary Value Problems
 W. Hackbush: Iterative Solutions of Large Sparse System of Equations
 D. Braess: Finite elements, Theory, fast solvers, and applications in solid mechanics, 2nd edition

Prerequisit for:

Enrollment
:
Passed
:
Numerical solution of partial differential equations 1
