Computer simulation

Higher education teachers: Karer Gorazd
Credits: 12
Semester: summer, summer
Subject code: 64133M

Subject description


  • Enrollment in the study year.

Content (Syllabus outline):

Introduction, the classification on the continuous and discrete modeling and simulation.Continuous modeling and simulation. Theoretical modeling, the equilibrium laws. Examples from specific areas - electrical, mechanical and hydraulic systems and their analogy. Description of the typical linear model for a proportional, integrating and differential type. Computer support for modeling: Matlab: the possibilities to describe models, transformations. Object-oriented approach to modeling: the standard for the description of Modelica models, standard library, using the Dymola Modelica environment.Tools for continuous simulation. Division, properties. Simulation using a basic configuration of the Matlab environment. Advanced simulation options using Matlab Simulink: nonlinearity, submodels, masking, S functions. Experimenting with the help of a simulation model: parameterization, linearization, computation of steady state, optimization.Simulation with general purpose programming languages. The concept of digital simulation. Numerical problems: integration, algebraic loop.Simulation of discrete event systems. Basic concepts of probability and random variables, distribution laws. Generating random numbers. Monte Carlo simulation method. Queuing systems. Basic configurations. Analysis by means of simulation. Showing typical cases using appropriate tools: GPSS + Proof animation, Matlab + SimEvents BlockSet.

Objectives and competences:

  • to demonstrate the field of computer simulation in an interesting way through a number of cases
  • to present the process of theoretical modeling with equilibrium laws
  • to provide computer support for modeling,
  • to learn in detail the structure and capabilities of simulation tools,
  • to learn discrete event simulation systems and the use of appropriate tools.

Intended learning outcomes:

Advanced knowledge of modeling, simulation and use of computer tools

Learning and teaching methods:

Lectures and laboratory work

Study materials

  • D. Matko, B. Zupančič, R. Karba, Simulation and Modelling of Continuous Systems - A Case Study Approach, Prentice Hall, London, 1992
  • F.E. Cellier, Continuous System Modeling, Springer - Verlag, NY, USA, 1991.
  • F.E. Cellier, E. Kofman, Continuous System Simulation, Springer Science+Business Media, Inc., NY, USA, 2006
  • P. Fritzson, Principles of Object Oriented Modeling and Simulation with Modelica 2.1, IEEE Press, John Wiley&Sons, Inc., Publication, USA, 2004
  • S. Raczynski, Modeling and Simulation, John Wiley & Sons, Ltd., England, 2006

Study in which the course is carried out

  • 2 year - 1st cycle - Multimedia
  • 3 year - 1st cycle - Multimedia