Faculty of Information Technology, BUT

Course details

Modelling and Simulation

IMS Acad. year 2017/2018 Winter semester 5 credits

Introduction to modelling and simulation concepts. System analysis and classification. Abstract and simulation models. Continuous, discrete, and combined models. Heterogeneous models. Using Petri nets in simulation. Pseudorandom number generation and testing. Queuing systems. Monte Carlo method. Continuous simulation, numerical methods, Modelica language. Simulation experiment control. Visualization and analysis of simulation results.

Guarantor

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

Language of instruction

Czech

Completion

Credit+Examination (written)

Time span

39 hrs lectures, 4 hrs exercises, 9 hrs projects

Assessment points

70 exam, 10 half-term test, 20 projects

Department

Lecturer

Hrubý Martin, Ing., Ph.D. (DITS FIT BUT)
Peringer Petr, Dr. Ing. (DITS FIT BUT)

Instructor

Subject specific learning outcomes and competences

Knowledge of simulation principles. The ability to create simulation models of various types. Basic knowledge of simulation system principles.

Learning objectives

The goal is to introduce students to basic simulation methods and tools for modelling and simulation of continuous, discrete and combined systems.

Prerequisites

Prerequisite kwnowledge and skills

Basic knowledge of numerical mathematics, probability, statistics, and basics of programming.

Study literature

  • Fishwick P.: Simulation Model Design and Execution, PrenticeHall, 1995, ISBN 0-13-098609-7
  • Law A., Kelton D.: Simulation Modelling and Analysis, McGraw-Hill, 1991, ISBN 0-07-100803-9
  • Texts available on course WWW page.

Fundamental literature

  • Fishwick P.: Simulation Model Design and Execution, PrenticeHall, 1995, ISBN 0-13-098609-7
  • Law A., Kelton D.: Simulation Modelling and Analysis, McGraw-Hill, 1991, ISBN 0-07-100803-9
  • Ross, S.: Simulation, Academic Press, 2002, ISBN 0-12-598053-1

Syllabus of lectures

  1. Introduction to modelling and simulation. System analysis, classification of systems. Systems theory basics.
  2. Model classification: conceptual, abstract, and simulation models. Multimodels. Basic methods of model building.
  3. Simulation systems and languages, basic means of model and experiment description. Principles of simulation system implementation.
  4. Generating, transformation, and testing of pseudorandom numbers. Stochastic models, Monte Carlo methods.
  5. Parallel process modelling. Using Petri nets in simulation.
  6. Models o queuing systems. Discrete simulation models.
  7. Time and simulation experiment control, "next-event" algorithm.
  8. Continuous systems modelling. Overview of numerical methods used for continuous simulation. Introduction to Dymola simulation system.
  9. Combined/hybrid simulation. Modelling of digital systems.
  10. Special model classes, models of heterogeneous systems. Model optimization.
  11. Analytical solution of queuing system models.
  12. Cellular automata and simulation.
  13. Checking of model validity, verification of models. Analysis of simulation results. Visualization of simulation results.

Syllabus of numerical exercises

  1. discrete simulation: using Petri nets
  2. continuous simulation: differential equations, block diagrams, examples of models

Syllabus - others, projects and individual work of students

Individual selection of a suitable problem, its analysis, simulation model creation, experimenting with the model, and analysis of results.

Progress assessment

project, midterm exam

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 10 points you can get during the semester

Course inclusion in study plans

  • Programme IT-BC-3, field BIT, 3rd year of study, Compulsory
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