Course Title: Modelling and Simulation of Engineering Systems

Part A: Course Overview

Course Title: Modelling and Simulation of Engineering Systems

Credit Points: 12.00


Course Code




Learning Mode

Teaching Period(s)


City Campus


172H School of Engineering


Sem 1 2018

Course Coordinator: Prof Pavel M. Trivailo

Course Coordinator Phone: +61 3 9925 6274

Course Coordinator Email:

Course Coordinator Location: Bundoora East Campus: 251.03.16

Course Coordinator Availability: Email for appointment

Pre-requisite Courses and Assumed Knowledge and Capabilities

  Pre-requisite Courses: None.    Assumed Knowledge and Capabilities: Calculus, Linear Algebra, Differential Equations, Basic Probability and Statistics, Familiarity with Matlab and Simulink.


Course Description

This course examines a variety of engineering system modelling and simulation methods, as well as numerical and computer based solution techniques utilized in industrial and engineering environments. Techniques for finding solutions to these systems include: graphical, algebraic, numerical, state space, simulation and computational processes. Case studies in industry and engineering applications are used to illustrate the techniques and modelling concepts. Examples of simulation and analysis methods will be related to the linear and non-linear, deterministic and non-deterministic systems.

Objectives/Learning Outcomes/Capability Development

Objectives:  The objectives of the course are: 

  • Characterise engineering systems in terms of their essential elements, purpose, parameters, constraints, performance requirements, sub-systems, interconnections and environmental context. 
  • Engineering problem modelling and solving through the relationship between theoretical, mathematical, and computational modelling for predicting and optimizing performance and objective. 
  • Mathematical modelling real world situations related to engineering systems development, prediction and evaluation of outcomes against design criteria. 
  • Develop solutions and extract results from the information generated in the context of the engineering domain to assist engineering decision making. 
  • Interpret the model and apply the results to resolve critical issues in a real world environment. 
  • Develop different models to suit special characteristics of the system being modelled. 

Learning Outcomes  The Learning Outcomes of the course are:  1. Analysis 

  • Ability to model deterministic systems and differentiate between nonlinear and linear models.
  • Ability to numerically simulate linear and non-linear ordinary differential equations and deterministic systems. 
  • Ability to estimate and validate a model based upon input and output data. 
  • Ability to create a model prediction based upon new input and validate the output data. 
  • Ability to comprehend and apply advanced theory-based understanding of engineering fundamentals and specialist bodies of knowledge in the selected discipline area to predict the effect of engineering activities. 
  • Ability to apply underpinning natural, physical and engineering sciences, mathematics, statistics, computer and information sciences to engineering applications. 
2. Research 
  • Ability to plan and execute a substantial research-based assessment tasks, with creativity and initiative in new situations in professional practice and with a high level of personal autonomy and accountability. 
  • Awareness of knowledge development and research directions within the engineering discipline. 
  • Ability to develop creative and innovative solutions to engineering challenges. 
  • Ability to assess, acquire and apply the competencies and resources appropriate to engineering activities. 
  • Ability to demonstrate professional use and management of information. 
  • Ability to clearly acknowledge your own contributions and the contributions from others and distinguish contributions you may have made as a result of discussions or collaboration with other people.
Capability Development  The learning outcomes will enable you to develop the following capabilities: 
  • Apply the processes, procedures and techniques which are required for the successful execution of systems engineering methodology to resolve different types of complex problems faced by senior manager, at an earlier stage of system design. These problems may relate to system specification, requirements allocation, maintenance concepts, and critical issue resolution.
  • Gain skills on system modelling and characterization by undergoing a structured walkthrough of a sample product and process engineering problem. 
  • Create system reports and system specification documents within the simulation environment. 
  • Interpret and verify how the system would perform in its working environment. 
  • Apply control mechanism and management function to ensure that the system achieve its purpose. 


Overview of Learning Activities

The course activities include lectures, computer laboratory modelling tutorials, presentations, group discussions, assignments and reports on case studies.

Overview of Learning Resources

Course-related resources will be provided on Blackboard, which is accessed through myRMIT. This can include lecture material, supplementary course notes, problem sheets and solutions, and useful references.

Overview of Assessment

X This course has no hurdle requirements.
☐ All hurdle requirements for this course are indicated clearly in the assessment regime that follows, against the relevant assessment task(s) and all have been approved by the College Deputy Pro Vice-Chancellor (Learning & Teaching).

The purpose of assessment is to determine whether you have acquired aimed capabilities.    Assignments are designed based on the principles and theory developed in this course as well as current industry systems modelling and simulation analysis issues at the time when this course is run.    Assessment 1: Assignment   Weighting of final grade: 35%   Description:  You will submit results of the modelling for an engineering system, using Matlab/Simulink, based on a characterisation of that system in terms of its essential elements.   Assessment 2: Assignment   Weighting of final grade:  35%   Description:  You will submit a report on your work assessing and selecting a model for an engineering system, then interpreting the simulation results of that model.   Assessment item:  Group Project Report   Weighting of final grade: 30%   Description:  You will present and defend the assessment within a collaborative engineering design and development project, which should include selection and interpretation of modelling and simulation results of an engineering system.