Title:

Simulation Tools and Techniques

Code:SNT
Ac.Year:2009/2010
Term:Summer
Study plans:
ProgramBranchYearDuty
IT-MSC-2MBI1stCompulsory-Elective - group I
IT-MSC-2MBS-Compulsory-Elective - group B
IT-MSC-2MGM-Compulsory-Elective - group M
IT-MSC-2MGM.2ndElective
IT-MSC-2MIN1stCompulsory
IT-MSC-2MIN.1stCompulsory
IT-MSC-2MIS-Elective
IT-MSC-2MIS.-Elective
IT-MSC-2MMI2ndCompulsory-Elective - group M
IT-MSC-2MMM1stCompulsory-Elective - group M
IT-MSC-2MPS-Elective
IT-MSC-2MPV1stCompulsory-Elective - group C
IT-MSC-2MSK-Elective
Language:Czech
Public info:http://www.fit.vutbr.cz/study/courses/SNT/public/
Credits:5
Completion:accreditation+exam (written&verbal)
Type of
instruction:
Hour/semLecturesSem. ExercisesLab. exercisesComp. exercisesOther
Hours:3900013
 ExaminationTestsExercisesLaboratoriesOther
Points:7000030
Guarantee:Češka Milan, prof. RNDr., CSc., 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
 
Learning objectives:
Students will be introduced to design and implementation principles of simulation systems. Further, the methods and techniques for modelling 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, 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. Modelling 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.
Knowledge and skills required for the course:
Basic knowledge of modelling, simulation, algorithms, and numerical mathematics.
Subject specific learning outcomes and competences:
The basics of modelling 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 techniques
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. 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.
Syllabus - others, projects and individual work of students:
  1. Individual solution of specified simulation problem, or extending of given simulation system to allow the use of new modelling methods.
Fundamental literature:
  1. Fishwick, P.: Simulation Model Design and Execution, Prentice Hall, 1995, ISBN 0-13-098609-7
  2. Law, A., Kelton, D.: Simulation Modelling and Analysis, McGraw-Hill, 2000, ISBN 0-07-100803-9
  3. Zeigler, B., Praehofer, H., Kim, T.: Theory of Modelling and Simulation, second edition, Academic Press, 2000, ISBN 0-12-778455-1
  4. Ross, S.: Simulation, Academic Press, 2002, ISBN 0-12-598053-1
  5. Cellier, F., Kofman, E.: Continuous System Simulation, Springer, 2006, ISBN: 978-0-387-26102-7
  6. Fujimoto, R.: Parallel and Distribution Simulation Systems, John Wiley & Sons, 1999, ISBN:0471183830
  7. Chopard, B.: Cellular Automata Modelling od Physical Systems, Cambridge University Press, 1998, ISBN:0-521-67345-3
Study literature:
  1. Rábová Z. a kol.: Modelování a simulace, VUT Brno, 1992, ISBN 80-214-0480-9
  2. Cellier, F., Kofman, E.: Continuous System Simulation, Springer, 2006, ISBN: 978-0-387-26102-7
  3. Fishwick, P.: Simulation Model Design and Execution, Prentice Hall, 1995, ISBN 0-13-098609-7
  4. Zeigler B., Praehofer H., Kim T.: Theory of Modelling and Simulation, 2nd edition, Academic Press, 2000
  5. Slides available online at WWW page.
Controlled instruction:
Within this course, attadance 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.