Czech

4

doc. Ing. Tomáš Návrat, Ph.D.

Institute of Solid Mechanics, Mechatronics and Biomechanics

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

Graded course-unit credit. Conditions: written test (basic terms), semester project.
Active participation in exercises is necessary. Organization of lectures is specified by the teacher at the beginning of semester.

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

Programme N-IMB-P: Engineering Mechanics and Biomechanics, Master's
specialization BIO: Biomechanics, compulsory

Programme C-AKR-P: , Lifelong learning
specialization CLS: , elective

Programme N-IMB-P: Engineering Mechanics and Biomechanics, Master's
specialization IME: Engineering Mechanics, compulsory

26 hours, optionally

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).