9600-1008/01 – Mathematical Modelling (MAM)

Gurantor departmentIT4InnovationsCredits6
Subject guarantorprof. Ing. Tomáš Kozubek, Ph.D.Subject version guarantorprof. Ing. Tomáš Kozubek, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Year1Semestersummer
Study languageCzech
Year of introduction2016/2017Year of cancellation
Intended for the facultiesUSPIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
KOZ75 prof. Ing. Tomáš Kozubek, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2

Subject aims expressed by acquired skills and competences

Upon the successful completion of the course, students will be able to: Actively use new terms in the field of mathematical modelling, which are essential for understanding modern computational method. Discretize, solve, and analyze errors of selected mathematical model. Choose and apply suitable discreet method for numerical solutions of mathematical models.

Teaching methods

Lectures
Tutorials
Project work

Summary

Compulsory literature:

1. M. Meerschaert, Mathematical Modeling, ISBN-13: 978-0123869128. 2. N. Kapur, Mathematical Modelling, New Age International, 1988, 259 pages. 3. Kozubek, T., Brzobohatý, T., Hapla, V., Jarošová, M., Markopoulos, A. Lineární algebra s Matlabem, VŠB-TU Ostrava 2012, http://mi21.vsb.cz/modul/linearni-algebra-s-matlabem.

Recommended literature:

1. Reddy, J. N. An introduction to the finite element method. 2nd Edition. McGraw-Hill, 1993. 2. Blaheta, R. Matematické modelování a metoda konečných prvků, VŠB-TU Ostrava 2012, http://mi21.vsb.cz/modul/matematicke-modelovani-metoda-konecnych-prvku-numericke-metody-2

Way of continuous check of knowledge in the course of semester

E-learning

Další požadavky na studenta

No other requirements.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1. Introduction to Mathematical Modelling. 2. Stationary Problem (String/Membrane Deflection), Discretization using the Finite Difference Method, Direct Solvers, Error Analysis, and Visualization of Results. 3. Non-stationary Problem (Heat Transfer, Diffusion), Discretization using the Finite Difference Method, Iterative Solvers, Error Analysis, and Visualization of Results. 4. Non-linear Heat Transfer Problem, Solution (Linearization) using Newton’s Method. 5. Signal and Image Analysis using FFT, FFT Efficient Algorithms, practical examples.

Conditions for subject completion

Full-time form (validity from: 2016/2017 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 30 (30) 15
                Test Written test 15  0
                Projekt Project 15  0
        Examination Examination 70 (70) 21
                Písemná část Written examination 40  20
                Ústní zkouška Oral examination 30  0
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2018/2019 (N2658) Computational Sciences (2612T078) Computational Sciences P Czech Ostrava 1 Compulsory study plan
2017/2018 (N2658) Computational Sciences (2612T078) Computational Sciences P Czech Ostrava 1 Compulsory study plan
2016/2017 (N2658) Computational Sciences (2612T078) Computational Sciences P Czech Ostrava 1 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner