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Numerical Modelling of Electrical Engineering Problems 1 - NMNV461

Title:	Numerické modelování problémů elektrotechniky 1
Guaranteed by:	Department of Numerical Mathematics (32-KNM)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2014 to 2014
Semester:	winter
E-Credits:	3
Hours per week, examination:	winter s.:2/0, Ex [HT]
Capacity:	unlimited
Min. number of students:	unlimited
4EU+:	no
Virtual mobility / capacity:	no
State of the course:	taught
Language:	Czech
Teaching methods:	full-time
Teaching methods:	full-time

Guarantor:	doc. RNDr. Tomáš Vejchodský, Ph.D.
Class:	M Mgr. NVM M Mgr. NVM > Povinně volitelné
Classification:	Mathematics > Numerical Analysis
Incompatibility :	NMOD023
Interchangeability :	NMOD023
Is co-requisite for:	NMNV462
Is interchangeable with:	NMOD023

Opinion survey results Examination dates Schedule Noticeboard

Annotation -

Last update: T_KNM (13.04.2015)

Numerical solutions should always be accompanied by a posteriori error estimates. Besides the qualitative information about the error, they enable to find the spatial distribution of the error and optimize the computation by adaptive techniques. The course provides an overview of techniques for a posteriori error estimates and compares their properties.

Aim of the course -

Last update: T_KNM (07.04.2015)

Students will get an overview about the techniques of the a posteriori error estimation for the elliptic and parabolic partial differential equations.

Literature - Czech

Last update: T_KNM (07.04.2015)

Ainsworth, M.; Oden, J.T.: A posteriori error estimation in finite element analysis. Wiley, New York, 2000.

Bangerth, W.; Rannacher, R.: Adaptive finite element methods for differential equations. Birkhäuser Verlag, Basel, 2003.

Verfürth, R.: A posteriori error estimation techniques for finite element methods. Oxford University Press, Oxford, 2013.

Syllabus -

Last update: doc. RNDr. Václav Kučera, Ph.D. (15.01.2019)

Numerical solution can hardly be reliable if we do not know how inaccurate it is. A posteriori error estimates provide the information about the size of the error and therefore they should supplement all numerical solutions. Besides this, the a posteriori error estimates enable to find the spatial distribution of the error among the computational domain and optimize the computation by adaptive techniques. This course offers an overview of techniques for a posteriori error estimation. In particular, it covers explicit and implicit residual estimates, hierarchical estimates, estimates based on the postprocessing and goal oriented estimates. (The complementary estimates are covered by the course NMNV464: A posteriori numerical analysis by the equilibrated fluxes.) Based on the example of Poisson equation discretized by the finite element method, we will explain individual techniques and prove their properties.