Course detail

# Mathematics 5 (M)

FAST-CA003Acad. year: 2018/2019

Interpolation and approximation of functions. Numerical solution of algebraic equations and their systems. Numerical derivatives and quadrature. Variance analysis, regression analysis. Numerical solution of stationary and non-stationary boundary and initial problems for differential equations with applications to civil engineering. Direct, sensitivity and inverse problems.

Supervisor

Department

Institute of Mathematics and Descriptive Geometry (MAT)

Learning outcomes of the course unit

The students should understand the basic principles of numerical deterministic and stochastic calculations. They should understand the principle of iteration methods for solving the equation f(x)=0 and systems of linear algebraic equations mastering the calculation algorithms. They should learn how to get the basics of interpolation and approximation of functions to solve practical problems. They should be acquainted with the principles of numerical differentiation to be able to numerically solve boundary problems for ordinary differential equations. They should understand numerical calculations of definite integrals. They should bu also able to apply such knowledge to particular direct, sensitivity and inverse engineering problems.

Prerequisites

Basic knowledge of numerical mathematics, probability and statistics, applied to technical problems.

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Not applicable.

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations - lectures, seminars.

Assesment methods and criteria linked to learning outcomes

Successful completion of the scheduled tests and submission of solutions to problems assigned by the teacher for home work. Unless properly excused, students must attend all the workshops. The result of the semester examination is given by the sum of maximum of 70 points obtained for a written test and a maximum of 30 points from the seminar.

Language of instruction

Czech

Work placements

Not applicable.

Course curriculum

1. Mathematical modelling. Deterministic and stochastic models. Errors in numerice calculations.

2. Lagrangean and Hermitean interpolation of functions. Interpolation functions, especially polynomials and splines.

3. Numerical solution of linear and nonlinear algebraic equations and their systems.

4. Numerical derivatives and quadrature.

5. Formulation and numerical solution of direct problems with differential and integral equations.

6. Finite difference, element and volume methods for stationary problems.

7. Methods of lines and discretization in time (Rothe sequences) for nonstationary problems.

8. Statistical tests, variance analysis, fuzzy models.

9. Linear regression analysis. Least squares method.

10. Nonlinear regression analysis.

11. Sensitivity analysis. Application to uncertainty transfer and estimates of durability of building structures.

12. Inverse analysis. Application to determination of material parameters from experiments.

13. Application to significant engineering problems.

Aims

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 N-P-E-SI (N) Master's
branch M , 1. year of study, winter semester, 4 credits, compulsory

- Programme N-K-C-SI (N) Master's
branch M , 1. year of study, winter semester, 4 credits, compulsory

- Programme N-P-C-SI (N) Master's
branch M , 1. year of study, winter semester, 4 credits, compulsory

#### Type of course unit

Lecture

26 hours, optionally

Teacher / Lecturer

Syllabus

1. Mathematical modelling. Deterministic and stochastic models. Errors in numerice calculations.

2. Lagrangean and Hermitean interpolation of functions. Interpolation functions, especially polynomials and splines.

3. Numerical solution of linear and nonlinear algebraic equations and their systems.

4. Numerical derivatives and quadrature.

5. Formulation and numerical solution of direct problems with differential and integral equations.

6. Finite difference, element and volume methods for stationary problems.

7. Methods of lines and discretization in time (Rothe sequences) for nonstationary problems.

8. Statistical tests, variance analysis, fuzzy models.

9. Linear regression analysis. Least squares method.

10. Nonlinear regression analysis.

11. Sensitivity analysis. Application to uncertainty transfer and estimates of durability of building structures.

12. Inverse analysis. Application to determination of material parameters from experiments.

13. Application to significant engineering problems.

seminars

13 hours, compulsory

Teacher / Lecturer

Syllabus

Follows directly particular lectures:

1. Mathematical modelling. Deterministic and stochastic models. Errors in numerice calculations.

2. Lagrangean and Hermitean interpolation of functions. Interpolation functions, especially polynomials and splines.

3. Numerical solution of linear and nonlinear algebraic equations and their systems.

4. Numerical derivatives and quadrature.

5. Formulation and numerical solution of direct problems with differential and integral equations.

6. Finite difference, element and volume methods for stationary problems.

7. Methods of lines and discretization in time (Rothe sequences) for nonstationary problems.

8. Statistical tests, variance analysis, fuzzy models.

9. Linear regression analysis. Least squares method.

10. Nonlinear regression analysis.

11. Sensitivity analysis. Application to uncertainty transfer and estimates of durability of building structures.

12. Inverse analysis. Application to determination of material parameters from experiments.

13. Application to significant engineering problems.

eLearning

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