MTE4590 - Modelling of materials

Overview

An introduction to the computational/modelling approaches currently available in materials science and engineering is provided. The reasons for using modelling approaches are discussed and the different types of models available are outlined. For each of the length scales important in understanding material behaviour (nano-, micro-, meso- and macro-), the available modelling techniques are outlined and their principles, methods of implementation, advantages, disadvantages and perceived future developments are discussed. Examples of modelling approaches will be selected from all classes of materials. The general methodology used for constructing models is emphasised.

Offerings

S2-01-CLAYTON-ON-CAMPUS

Requisites

Prerequisite

MAE3411

6 CP

Aerospace structural mechanics

CHE3167

6 CP

Transport phenomena and numerical methods

ECE3093

6 CP

Optimisation estimation and numerical methods

MTE3101

6 CP

Materials in a complex world 1: People, projects and data

MTE3547

6 CP

Materials characterisation and modelling

MAE3456

6 CP

Aerospace computational mechanics

MEC3456

6 CP

Engineering computational analysis

AND

ENG1014

6 CP

Engineering numerical analysis

ENG1060

6 CP

Computing for engineers

AND

ENG2005

6 CP

Advanced engineering mathematics

Contacts

Chief Examiner(s)

Professor Nikhil Medhekar

Unit Coordinator(s)

Professor Nikhil Medhekar

Teaching approach

Problem-based learning

Peer assisted learning

Active learning

Assessment summary

Continuous assessment: 70%

Final assessment: 30%

This unit contains hurdle requirements that you must achieve to be able to pass the unit. You are required to achieve at least 45% in the total continuous assessment component and at least 45% in the final assessment component. The consequence of not achieving a hurdle requirement is a fail grade (NH) and a maximum mark of 45 for the unit.

Assessment

1 - Minor assignment

2 - Major assignment

3 - Final assessment

Scheduled and non-scheduled teaching activities

Practical activities

Workshops

Workload requirements

Workload

The minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of 3-6 hours of scheduled learning activities and 6-9 hours of independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.

Learning resources

Required resources

Other unit costs

The following item is mandatory for practical aspects of the unit and should be purchased at your own cost as you will be reusing them throughout your course.

Calculator

Availability in areas of study

Minor: Computational engineering