Course Title: Computational Engineering Analysis

Part A: Course Overview

Course Title: Computational Engineering Analysis

Credit Points: 12.00


Course Code




Learning Mode

Teaching Period(s)


City Campus


115H Aerospace, Mechanical & Manufacturing Engineering


Sem 2 2012,
Sem 2 2013,
Sem 1 2014,
Sem 1 2015,
Sem 1 2016


City Campus


172H School of Engineering


Sem 1 2017,
Sem 1 2018,
Sem 2 2019

Course Coordinator: A/Prof Raj Das

Course Coordinator Phone: +61 3 9925 6123

Course Coordinator Email:

Course Coordinator Location: Bundoora East Campus: Building 251, Level 3, Room 60

Pre-requisite Courses and Assumed Knowledge and Capabilities


Course Description

This course provides an introduction to modern computing tools and methodologies for computational analysis for engineers. The course will cover the basic components and the architecture of computers and numerical methods for the solution of problems in various engineering applications. Different numerical methods will be introduced and implemented using a programming software package. Elementary engineering analysis as well as more extensive applications will be conducted using the programming software package. Solutions to a variety of engineering problems will be obtained using a range of numerical methods.       

Objectives/Learning Outcomes/Capability Development

This course develops and assesses the following program learning outcomes (PLOs):

• Conceptual understanding of the mathematics, numerical analysis, statistics, and computer and information sciences which underpin the engineering discipline
• Fluent application of engineering techniques, tools and resources

Course Learning Outcomes (CLOs):

Upon successful completion of the course, you should be able to:

1. Understand the basic computing tools and numerical methods for computational simulation and modelling of engineering problems

2. Use programming languages to model and solve engineering problems

3. Determine appropriate computational tools for solving a range of engineering problems

4. Develop computational algorithms and implement them in software by writing custom scripts and functions to solve specific engineering problems

5. Describe the process of developing custom software, ranging from the initial design, implementation, debugging and error handling, ending up with a robust application



Overview of Learning Activities

Learning activities can include lectures, tutorials, tutorial assignments, a project, and a final exam. Online learning, and directed problem-solving activities will be achieved through the Matlab Assignment and Project tasks. A number of tutorial assignments will be given which follow on from the theory covered in the lectures and the work covered during tutorials. The large Project will involve work covered in tutorials, but will also require knowledge drawn from a wider range of resources. The emphasis will be on hands-on learning in computer laboratories.



Overview of Learning Resources

Course-related resources will be provided on the course Canvas site, which is accessed through myRMIT. This material can include course notes, tutorial problems and solutions, details related to the programming software Matlab tutorial assignments and the larger assignment, and 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).
Assessment will be determined mainly from individual submissions, rather than from group work, and will include a number of tutorial-based Matlab assignments, the larger Matlab Project and the final examination.

Assessment items:  Matlab tutorial assignments (individual)
Weighting of final grade:  40%  
Related course learning outcomes: 1, 2, 3, 4
Description:  Four Matlab Assignments conducted over a 8 week period

Assessment items:  Matlab Project (individual)
Weighting of final grade:  20%  
Related course learning outcomes:  2, 3, 4, 5
Description:  Large-scale Matlab Project conducted over a 5 week period

Assessment item:  Final Exam (individual)
Weighting of final grade:  40%  
Related course learning outcomes:  1, 2, 3, 4, 5
Description:  Two-hour duration closed-book examination.