Faculty of Information Technology, BUT

Course details

Simulation Tools and Techniques

SNT Acad. year 2018/2019 Summer semester 5 credits

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.

Guarantor

Deputy Guarantor

Peringer Petr, Dr. Ing. (DITS FIT BUT)

Language of instruction

Czech

Completion

Credit+Examination (written+oral)

Time span

39 hrs lectures, 13 hrs projects

Assessment points

70 exam, 30 projects

Department

Lecturer

Peringer Petr, Dr. Ing. (DITS FIT BUT)

Instructor

Subject specific learning outcomes and competences

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

Generic learning outcomes and competences

Creation of simulation tools, models, and practical use of simulation methods.

Learning objectives

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.

Why is the course taught

The course overviews methods usable for modelling, simulation, and other areas (like computer games, system optimization, etc.).

Prerequisite kwnowledge and skills

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

Study literature

  • Cellier, F., Kofman, E.: Continuous System Simulation, Springer, 2006, ISBN: 978-0-387-26102-7
  • Zeigler B., Praehofer H., Kim T.: Theory of Modelling and Simulation, 2nd edition, Academic Press, 2000
  • Slides available online at WWW page.

Fundamental literature

  • 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 0-12-598053-1
  • 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
  • Nutaro, J.: Building Software for Simulation: Theory and Algorithms, with Applications in C++. John Wiley & Sons, 2011, ISBN-13: 978-0470414699

Syllabus of lectures

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

Syllabus - others, projects and individual work of students

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

Controlled instruction

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.


Exam prerequisites

At least half of the points for each project.

Schedule

DayTypeWeeksRoomStartEndLect.grpGroupsInfo
Tueexam2019-05-28 E104 14:0015:50 1MIT 2MIT 1. oprava
Tueexam2019-05-07 D102 15:0016:50 1MIT 2MIT řádná
Wedexam2019-06-05 E104 17:0018:50 1MIT 2MIT 2. oprava
Thulecturelectures D0206 17:0019:50 1MIT 2MIT MIN xx

Course inclusion in study plans

  • Programme IT-MSC-2, field MBI, any year of study, Compulsory-Elective group I
  • Programme IT-MSC-2, field MBS, any year of study, Compulsory-Elective group B
  • Programme IT-MSC-2, field MGM, MMI, MMM, any year of study, Compulsory-Elective group M
  • Programme IT-MSC-2, field MIN, 1st year of study, Compulsory
  • Programme IT-MSC-2, field MIS, MSK, any year of study, Elective
  • Programme IT-MSC-2, field MPV, any year of study, Compulsory-Elective group C
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