Course detail

Modelling in Engineering Practice

FSI-RMVAcad. year: 2020/2021

The course offers an overview of basic knowledge in these fields: theory of systems, structure of the world of technology, theory of modelling, theory of experiment, design of technical objects, theory of statistical data processing, theory of failures and limit states, theory of deterministic chaos, theory of synergetics. It offers a possibility of a comprehensive view of technical life of technical objects.

Language of instruction

Czech

Number of ECTS credits

4

Mode of study

Not applicable.

Guarantor

doc. Ing. Tomáš Návrat, Ph.D.

Department

Institute of Solid Mechanics, Mechatronics and Biomechanics (ÚMTMB)

Learning outcomes of the course unit

Knowledge on structures, properties and behaviour of various systems, above all technical, on approaches and methods of solving stress-strain, stability and reliability problems of these systems, especially by computational and experimental modelling with application of statistical methods. Basic knowledge on deterministic chaos in behaviour of non-linear dynamic systems.
Students will get abilities of correct and pragmatic formulation of problems concerning technical systems, basic knowledge on the "art of modelling", on effective exploitation of various types of modelling in solving problems, and the ability of investigation of all processes in systems in the sense of the possibility of a deterministic and stochastic chaos.

Prerequisites

Knowledge of previous courses in Mechanics (Statics, Kinematics, Dynamics), basics in programming recommended.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

The course is taught through lectures explaining the basic principles and theory of the discipline.

Assesment methods and criteria linked to learning outcomes

Graded course-unit credit. Conditions: written test (basic terms), semester project.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

The aim of the course is to learn a system approach for the solution of engineering tasks using computational and experimental modelling.

Specification of controlled education, way of implementation and compensation for absences

Active participation in exercises is necessary. Organization of lectures is specified by the teacher at the beginning of semester.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Dhillon, B. S. Creativity for Engineers. World Scientific Publishing Company, 2006-02-06. 204 p. ISBN: 9812565299. (EN)
Janíček, P.: Systémové pojetí vybraných oborů pro techniky, 2006 (CS)
Wright I.V. Design methods in engineering and product design. McGraw-Hill, 1998 - Počet stran: 285 (EN)

Recommended reading

Janíček, P.: Ondráček. E.: Řešení problémů modelování, (skriptum), 1995. (CS)

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme N-IMB-P Master's

    specialization IME , 1 year of study, winter semester, compulsory
    specialization BIO , 1 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

prof. Ing. Přemysl Janíček, DrSc.
doc. Ing. Tomáš Návrat, Ph.D.

Syllabus

1. Science and engineering revolution in midway last century. Paradigm of holism in the problem solving. General system theory and system engineering.
2. Beginning and advancement of system approach. Forming of system methodology like methodology aided of Theory of systems. System approach (attributes of system approach).
3. System thinking, system branches, system algorithm - system conception. Specifics of hard, soft and mixed systems.
4. System terminology - definition of basic system terms.
5. Continuation of system terminology.
6. Problem situation, problem, scenario of causal problem solving. Hard and soft system - specificity of problem solution.
7. System concept of experiment.
8. System concept of modelling.
9. System concept of calculation modelling (classical, simulation, optimization, identification of objects, identification of systems.
10. System concept of limit states.
11. System concept of mathematical statistic.
12. Principles of chaos theory.
13. Principles of self-organization theory (synergism in first and second sense).

Elearning

eLearning: currently opened course