Title:  Simulation Tools and Techniques 

Code:  SNT 

Ac.Year:  2018/2019 

Sem:  Summer 

Curriculums:  

Language of Instruction:  Czech 

Public info:  http://www.fit.vutbr.cz/study/courses/SNT/public/ 

Credits:  5 

Completion:  credit+exam (written&oral) 

Type of instruction:  Hour/sem  Lectures  Seminar Exercises  Laboratory Exercises  Computer Exercises  Other 

Hours:  39  0  0  0  13 

 Exams  Tests  Exercises  Laboratories  Other 

Points:  70  0  0  0  30 



Guarantor:  Češka Milan, prof. RNDr., CSc. (DITS) 

Deputy guarantor:  Peringer Petr, Dr. Ing. (DITS) 

Lecturer:  Peringer Petr, Dr. Ing. (DITS) 
Instructor:  Hrubý Martin, Ing., Ph.D. (DITS) 

Faculty:  Faculty of Information Technology BUT 

Department:  Department of Intelligent Systems FIT BUT 

Schedule: 

Day  Lesson  Week  Room  Start  End  Lect.Gr.  Groups 

Tue  exam  1. oprava  20190528  E104  14:00  15:50  1MIT 2MIT  
Tue  exam  řádná  20190507  D102  15:00  16:50  1MIT 2MIT  
Wed  exam  2. oprava  20190605  E104  17:00  18:50  1MIT 2MIT  
  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.  Description: 

  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.  Knowledge and skills required for the course: 

  Basic knowledge of modelling, simulation, algorithms, and numerical mathematics.
 Subject specific learning outcomes and competencies: 

  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 competencies: 

  Creation of simulation tools, models, and practical use of simulation methods.
 Why is the course taught: 

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


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


 Law, A., Kelton, D.: Simulation Modelling and Analysis, McGrawHill, 2000, ISBN 0071008039
 Zeigler, B., Praehofer, H., Kim, T.: Theory of Modelling and Simulation, second edition, Academic Press, 2000, ISBN 0127784551
 Ross, S.: Simulation, Academic Press, 2002, ISBN 0125980531
 Cellier, F., Kofman, E.: Continuous System Simulation, Springer, 2006, ISBN: 9780387261027
 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:0521673453
 Nutaro, J.: Building Software for Simulation: Theory and Algorithms,
with Applications in C++. John Wiley & Sons, 2011, ISBN13:
9780470414699
 Study literature: 


 Cellier, F., Kofman, E.: Continuous System Simulation, Springer, 2006, ISBN: 9780387261027
 Zeigler B., Praehofer H., Kim T.: Theory of Modelling and Simulation, 2nd edition, Academic Press, 2000
 Slides available online at WWW page.
 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.
 
