Mathematics 5 (M)
FAST-NAA021Acad. year: 2020/2021
Introduction to numerical mathematics, namely interpolation and approximations of functions, numerical differentiation and quadrature, analysis of algebraic and differential equations and their systems.
Institute of Mathematics and Descriptive Geometry (MAT)
Learning outcomes of the course unit
Following the aim of the course, students will receive the basic orientaion in numerical and statistical methods needed in material engineering and in related engineering applications.
Basic courses of mathematics for bachelor students, MATLAB programming (as in the recommended course at MAT FCE).
Recommended optional programme components
Recommended or required reading
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Language of instruction
1. Errors in numerical calculations. Linear spaces and operators, fixed point theorems. Iterative methods for the analysis of nonlinear algebraic and selected further equations.
2. Iterative and coupled methods for the analysis of linear algebraic equations, relaxation methods, method of conjugated gradients.
3. Multiplicative decomposition of matrices. Numerical evaluation of eigenvalues and eigenvectors of matrices and of inverse matrices, algorithms for special matrices.
4. Condition numbers of systems of linear equations. Least squares method, pseudoinverse matrices.
5. Generalizations of methods from 3. and 4. to the analysis of systems of nonlinear equations.
6. Lagrange and Hermite interpolation of functions of 1 variable, namely polynoms and splines.
7. Approximation of functions of 1 variable using the least squares methos: linear and nonlinear approach.
8. Approximation of function of more variables.
9. Numerical differentiation. Finite difference method for the analysis of selected initial and boundary problems for ordinary differential equations.
10. Numerical quadrature. Finite element method for the analysis of selected initial and boundary problems for ordinary differential equations.
11. Time-dependent problems. Time discretization: Euler methods, Cranka-Nicholson method, Runge-Kutta methods, Newmark method.
12. Generalization of 9. and 10. for pro partial differential equations of evolution, e.g. heat transfer equations, fluid flow equations and equations of dynamics of building structures.
13. Sensitivity and inverse problems. Identification of uncertain material parameters from known measurement results. Selected engineering application, due to other courses.
Students will obtain the basic knowledge of numerical mathematics, probability and statistics, applied to technical problems, especially from material engineering.
Specification of controlled education, way of implementation and compensation for absences
Extent and forms are specified by guarantor’s regulation updated for every academic year.
Classification of course in study plans
- Programme NPC-SIM Master's, 1. year of study, winter semester, 4 credits, compulsory