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Computer Solutions of Continuum Physics Problems - NMMO403

Title:	Počítačové řešení úloh fyziky kontinua
Guaranteed by:	Mathematical Institute of Charles University (32-MUUK)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2016 to 2017
Semester:	summer
E-Credits:	5
Hours per week, examination:	summer s.:2/2, C+Ex [HT]
Capacity:	unlimited
Min. number of students:	unlimited
4EU+:	no
Virtual mobility / capacity:	no
State of the course:	taught
Language:	Czech, English
Teaching methods:	full-time
Teaching methods:	full-time
Additional information:	http://www.karlin.mff.cuni.cz/~hron/NMMO403/

Guarantor:	RNDr. Jaroslav Hron, Ph.D.
Class:	M Mgr. MOD M Mgr. MOD > Povinné M Mgr. NVM M Mgr. NVM > Volitelné
Classification:	Mathematics > Mathematical Modeling in Physics, Numerical Analysis
Incompatibility :	NMOD041
Interchangeability :	NMOD041
Is interchangeable with:	NMOD041

Opinion survey results Examination dates Schedule Noticeboard

Annotation -

Last update: Mgr. Dalibor Šmíd, Ph.D. (11.05.2023)

The goal of the course is to introduce students to modern methods for numerical solution of systems of partial differential equations obtained by mathematical modeling of continuum mechanics problems (heat transfer, fluid flow, elastic deformation, etc.). The course includes overview of the basic commercial software for numerical computation (Matlab, Femlab) and its application to solution of PDEs. Further overview and practical use of the basic numerical libraries (Blas, Lapack, Petsc, etc. ), finite element libraries (Feat, Featflow) and libraries for paralel computation (MPI, OpenMP).

Literature - Czech

Last update: RNDr. Jaroslav Hron, Ph.D. (15.05.2017)

[1] A. Logg, K.-A. Mardal, G. Wells, eds., Automated Solution of Differential Equations by the Finite Element Method, Lecture Notes in Computational Science and Engineering. (2012).

[2] K. Eriksson, D. Estep, P. Hansbo, C. Johnson, Computational Differential Equations, 1996.

[3] D. Goldberg, What every computer scientist should know about floating-point arithmetic, ACM Computing Surveys. 23 (1991) 5-48.

Syllabus -

Last update: RNDr. Jaroslav Hron, Ph.D. (12.01.2022)

Solving a partial differential equation by finite element method using

FEniCS.

Introduction to Python language

Overview of the basic components for finite element solution of

partial differential equations: domain description and discretization,

basis function implementation (parametric, non-parametric finite

elements), boundary condition implementation, efficient linear system

assembly, solution of large, sparse linear systems (direct,

preconditioned iterative, multigrid methods)

Nonlinear problems, fixed point method, Newton method

Example applications: the Poisson equation, the convection-diffusion-reaction equation, the heat transfer equation, the Navier--Stokes

equation, the elastic deformation equation, multi-phase flows, the levelset method