Undergraduate - UnitMTE3590 - Modelling of materials

This unit entry is for students who completed this unit in 2012 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

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6 points, SCA Band 2, 0.125 EFTSL

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Level	Undergraduate
Faculty	Faculty of Engineering
Offered	Clayton Second semester 2012 (Day)
Coordinator(s)	Assoc Professor Christopher Hutchinson/Assoc Professor Chris Davies

Synopsis

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.

Outcomes

On successful completion of this units students will:

understand the role (and potential role) of modelling and simulation in understanding material behaviour
appreciate the different types of modelling approaches that can be used (empirical, semi-empirical, physically-based, etc) and the advantages and disadvantages of each
understand the methodology used to construct and test models in materials science and engineering
understand the general principles, advantages and disadvantages underlying the most common modelling techniques used in materials science and engineering and the time and length scale at which they are applicable
for a given problem in materials science and engineering, understand exactly which types of modelling approaches could provide helpful insight to the problem, and experience formulating a model for the problem, simulating results and analysing the outcomes.