Course detail

Simulation Tools and Techniques

FIT-SNTAcad. year: 2009/2010

Theory of modelling and simulation, DEVS (Discrete Event System Specification) formalism. Simulation systems, their design and implementation. Algorithms used for simulation control, parallel and distributed simulation. Continuous, discrete, and combined simulation: model description methods, simulation tools, numerical methods. Special types of models; corresponding methods, techniques, and tools. Modeling of systems described by partial differential equations. Multimodels. Introduction to model validation and verification. Simulation experiment control. Simulation results analysis and visualization. Simulation system case study.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

prof. RNDr. Milan Češka, CSc.

Department

Department of Intelligent Systems (UITS)

Learning outcomes of the course unit

The basics of modeling and simulation theory. Understanding the principles of simulation system implementation. Knowledge of advanced simulation methods and techniques.

creation of simulation tools, models, and practical use of simulation techniques

Prerequisites

Basic knowledge of modelling, simulation, algorithms, and numerical mathematics.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

At least half of the points for each project.

Course curriculum

  1. Introduction. Theory of modelling and simulation, DEVS formalism.
  2. DEVS simulator.
  3. Simulation systems: classification, principles of design and implementation. Simulation control algorithms. Parallel and distributed simulation.
  4. Continuous simulation: numerical methods, stiff systems, algebraic loops. Dymola simulation system, Modelica language.
  5. Discrete simulation: implementation of events and processes. Queueing systems.
  6. Combined simulation: state events.
  7. Modelling of systems described by partial differential equations. Basics of sensitivity analysis.
  8. Digital systems simulation models and tools.
  9. Cellular automata.
  10. Models of uncertainty, using fuzzy logic in simulation.
  11. Multimodels. Model optimization methods. Qualitative simulation.
  12. Simulation experiment control, simulation results analysis. Introduction to model validation and verification. Visualization methods. User interfaces of simulation systems. Simulation and virtual reality.
  13. Simulation system implementation case study. Examples of simulation models.

Work placements

Not applicable.

Aims

Students will be introduced to design and implementation principles of simulation systems. Further, the methods and techniques for modeling and simulation of various types of models will be presented.

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

There are no checked study.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Fishwick, P.: Simulation Model Design and Execution, Prentice Hall, 1995, ISBN 0-13-098609-7 Law, A., Kelton, D.: Simulation Modelling and Analysis, McGraw-Hill, 2000, ISBN 0-07-100803-9 Zeigler, B., Praehofer, H., Kim, T.: Theory of Modelling and Simulation, second edition, Academic Press, 2000, ISBN 0-12-778455-1 Ross, S.: Simulation, Academic Press, 2002, ISBN 0-12-598053-1Cellier, F., Kofman, E.: Continuous System Simulation, Springer, 2006, ISBN: 978-0-387-26102-7Fujimoto, R.: Parallel and Distribution Simulation Systems, John Wiley & Sons, 1999, ISBN:0471183830Chopard, B.: Cellular Automata Modelling od Physical Systems, Cambridge University Press, 1998, ISBN:0-521-67345-3

Recommended reading

Rábová, Z. a kol.: Modelování a simulace, VUT Brno, 1992, ISBN 80-214-0480-9 Cellier, F., Kofman, E.: Continuous System Simulation, Springer, 2006, ISBN: 978-0-387-26102-7Fishwick, P.: Simulation Model Design and Execution, Prentice Hall, 1995, ISBN 0-13-098609-7Soubor materiálů dostupný na WWW stránce předmětu.

Classification of course in study plans

  • Programme IT-MSC-2 Master's

    branch MBI , 1 year of study, summer semester, compulsory-optional
    branch MBS , 0 year of study, summer semester, compulsory-optional
    branch MGM , 0 year of study, summer semester, compulsory-optional
    branch MGM , 2 year of study, summer semester, elective
    branch MIN , 1 year of study, summer semester, compulsory
    branch MIN , 1 year of study, summer semester, compulsory
    branch MIS , 0 year of study, summer semester, elective
    branch MIS , 0 year of study, summer semester, elective
    branch MMI , 2 year of study, summer semester, compulsory-optional
    branch MMM , 1 year of study, summer semester, compulsory-optional
    branch MPS , 0 year of study, summer semester, elective
    branch MPV , 1 year of study, summer semester, compulsory-optional
    branch MSK , 0 year of study, summer semester, elective

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

prof. RNDr. Milan Češka, CSc.

Syllabus

  1. Introduction. Theory of modelling and simulation, DEVS formalism.
  2. DEVS simulator.
  3. Simulation systems: classification, principles of design and implementation. Simulation control algorithms. Parallel and distributed simulation.
  4. Continuous simulation: numerical methods, stiff systems, algebraic loops. Dymola simulation system, Modelica language.
  5. Discrete simulation: implementation of events and processes. Queueing systems.
  6. Combined simulation: state events.
  7. Modelling of systems described by partial differential equations. Basics of sensitivity analysis.
  8. Digital systems simulation models and tools.
  9. Cellular automata.
  10. Models of uncertainty, using fuzzy logic in simulation.
  11. Multimodels. Model optimization methods. Qualitative simulation.
  12. Simulation experiment control, simulation results analysis. Introduction to model validation and verification. Visualization methods. User interfaces of simulation systems. Simulation and virtual reality.
  13. Simulation system implementation case study. Examples of simulation models.

Project

13 hod., optionally

Teacher / Lecturer

prof. RNDr. Milan Češka, CSc.