MTE5190 · Advanced materials modelling

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.

Areas of study: E6014 Master of Engineering - Specialisation: Materials engineering

Offerings

The Handbook publishes no offerings for this unit.

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Continuous assessment: 100%

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. assess the role (and potential role) of modelling and simulation in understanding material behaviour
2. appreciate the different types of modelling approaches that can be used (empirical, semi-empirical, physically-based, etc) and the advantages and disadvantages of each
3. understand the methodology used to construct and test models in materials science and engineering
4. analyse 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
5. demonstrate an ability to identify a physical problem in materials science and engineering, assess the exact type of modelling approach could provide useful solution to the problem, define and formulate the model, analyse the results and communicate the outcomes.

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.

Student experience, not official rules. Nothing here changes what the Handbook says.