Course Title: Advanced CAE for Automotive Applications

Part A: Course Overview

Course Title: Advanced CAE for Automotive Applications

Credit Points: 12.00


Course Code




Learning Mode

Teaching Period(s)


City Campus


115H Aerospace, Mechanical & Manufacturing Engineering


Sem 2 2009,
Sem 2 2010,
Sem 2 2011,
Sem 2 2012,
Sem 2 2014,
Sem 2 2015,
Sem 2 2016


City Campus


172H School of Engineering


Sem 2 2017,
Sem 2 2018,
Sem 2 2019,
Sem 2 2020

Course Coordinator: Prof. Mohammad Fard

Course Coordinator Phone: +61 3 9925 6044

Course Coordinator Email:

Course Coordinator Location: B251-003-023

Course Coordinator Availability: By appointment

Pre-requisite Courses and Assumed Knowledge and Capabilities


Course Description

This course will enable you to develop advanced knowledge and skills in CAE modelling and simulations for automotive applications. Upon completion of this course you will be able to utilise CAE techniques in your chosen field of applications. You will also develop advanced knowledge and skills in CAE modelling and simulations. This includes problem definition, analysis, modelling, simulation, and interpretation of modelling and simulation results. 

The course will cover the following areas: 

  • Automotive CAE NVH Analysis 
  • Automotive CAE Crash Analysis. 
  • Automotive CAE Concept Modelling
  • Automotive Trimmed Body (T/Body) CAE Modelling Method

Automotive CAE NVH Analysis 
This topic introduces you to advanced NVH CAE structural modelling and analysis technology applied to relevant automotive applications. You will also be provided with appropriate skills for improving NVH performance of the car body. 

Automotive CAE Crash Analysis 
You will be equipped with adequate skills for the numerical modeling of advanced non-linear automotive applications. You will be able to solve with competence practical problems related to automotive structures, which include static and dynamic analysis, large deformations and crash simulation. Further, you will develop awareness of professional, legal and ethical standards through crash analysis and simulations. 

Automotive CAE Concept Modelling

CAE Concept modelling is new method of CAE modelling in automotive industry. All students will learn to design their own concept CAE model.

Automotive Trimmed Body (T/Body) CAE Modelling Method

You will learn various techniques for modelling of vehicle T/Body.


Objectives/Learning Outcomes/Capability Development

Program Learning Outcomes (PLOs)

This course contributes to the development of the following program learning outcomes:

1. Needs, Context and Systems

Describe, investigate and analyse complex engineering systems and associated issues (using systems thinking and modelling techniques)

2. Problem Solving and Design

Develop creative and innovative solutions to engineering problems

3. Analysis

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.

Apply underpinning natural, physical and engineering sciences, mathematics, statistics, computer and information sciences.

4. Professional Practice

Apply systematic approaches to the conduct and management of engineering projects

Demonstrate effective team membership and team leadership

Communicate in a variety of different ways to collaborate with other people, including accurate listening, reading and comprehension, based on dialogue when appropriate, taking into account the knowledge, expectations, requirements, interests, terminology and language of the intended audience

Course Learning Outcomes (CLOs)

Upon completion of this course you should be able to:

  1. Apply computer-based virtual design to mechanical systems
  2. Predict and evaluate the performance of mechanical systems using a range of computer aided engineering tools, taking into consideration the limitations of the modelling techniques. 
  3. Perform realistic simulation of mechanical systems to explore design alternatives and identify optimal performance
  4. Demonstrate an understanding of the concepts and application of mathematics and numerical analysis in the context of engineering design and development

Overview of Learning Activities

Learning activities throughout the course include: Lectures, tutorials, presentations, group discussions, project work, and computer based analysis exercises.

Overview of Learning Resources

Comprehensive notes will be provided for each topic/lecture session and you are expected to use out of class study time to review them so as to keep up with the progress of the course. Some classes will be spent in case study CAE modelling and analyses. It is essential that you devote sufficient time reading each case ahead of the class in preparation for contributing actively to the discussion.

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 item:  Homework
Weighting of final grade:  30%
Related course learning outcomes: 1, 2, 3, 4
Description:  You will undertake problem-based homework related to the selected option of the course. This will involve CAE case studies including problem definition, analysis, modelling, simulation, and interpretation of modelling and simulation results.

Assessment item:  Major assignment
Weighting of final grade:  25%
Related course learning outcomes:  1, 2, 3, 4
Description:  There will be a major assignment in you will develop your own CAE model for CAE engineering and design. You will be required to provide brief presentations of your simulations.

Assessment item:  Exam
Weighting of final grade:   45%
Related course learning outcomes: 1, 2, 3, 4
Description:  The final semester exam will test your ability and understanding to analyse mechanical systems, make the appropriate modelling and simulation decisions as well as your ability to interpret the resulting outcomes of a simulation.