Course detail

Simulation Tools and Techniques

FIT-SNTAcad. year: 2019/2020

Theory of modelling and simulation, DEVS (Discrete Event System Specification) formalism. Simulation systems, their design and implementation. Algorithms used for simulation control, introduction to 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. Introduction to model validation and verification. Simulation experiment control. Simulation results analysis and visualization overview. 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 methods.

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

Not applicable.

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

Within this course, attendance on the lectures is not monitored.
The knowledge of students is examined by the projects and
by the final exam. The minimal number of points which
can be obtained from the final exam is 30. Otherwise,
no points will be assigned to a student.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Cellier, F., Kofman, E.: Continuous System Simulation, Springer, 2006, ISBN: 978-0-387-26102-7
Fujimoto, R.: Parallel and Distribution Simulation Systems, John Wiley & Sons, 1999, ISBN:0471183830
Chopard, B.: Cellular Automata Modelling od Physical Systems, Cambridge University Press, 1998, ISBN:0-521-67345-3
Law, A., Kelton, D.: Simulation Modelling and Analysis, McGraw-Hill, 2000, ISBN 0-07-100803-9
Nutaro, J.: Building Software for Simulation: Theory and Algorithms, with Applications in C++. John Wiley & Sons, 2011, ISBN-13: 978-0470414699
Ross, S.: Simulation, Academic Press, 2002, ISBN 0-12-598053-1
Slides available online at WWW page.
Zeigler, B., Praehofer, H., Kim, T.: Theory of Modelling and Simulation, second edition, Academic Press, 2000, ISBN 0-12-778455-1
Zeigler B., Praehofer H., Kim T.: Theory of Modelling and Simulation, 2nd edition, Academic Press, 2000

Classification of course in study plans

  • Programme IT-MSC-2 Master's

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

  • Programme MITAI Master's

    specialization NVER , 0 year of study, summer semester, compulsory
    specialization NBIO , 0 year of study, summer semester, elective
    specialization NSEN , 0 year of study, summer semester, elective
    specialization NVIZ , 0 year of study, summer semester, elective
    specialization NGRI , 0 year of study, summer semester, elective
    specialization NISD , 0 year of study, summer semester, elective
    specialization NSEC , 0 year of study, summer semester, elective
    specialization NCPS , 0 year of study, summer semester, elective
    specialization NHPC , 0 year of study, summer semester, elective
    specialization NNET , 0 year of study, summer semester, elective
    specialization NMAL , 0 year of study, summer semester, elective
    specialization NIDE , 0 year of study, summer semester, elective
    specialization NEMB , 0 year of study, summer semester, elective
    specialization NSPE , 0 year of study, summer semester, elective
    specialization NADE , 0 year of study, summer semester, elective
    specialization NMAT , 0 year of study, summer semester, elective
    specialization NISY , 0 year of study, summer semester, compulsory

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

Dr. Ing. Petr Peringer

Syllabus

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

Project

13 hod., compulsory

Teacher / Lecturer

Ing. Martin Hrubý, Ph.D.

Syllabus

  • Individual solution of specified simulation problem, or extending of given simulation system to allow the use of new modelling methods.