The module introduces concepts of modelling materials problems relating to structure, structure evolution of materials. A number of models are introduced and discussed across length scales, ranging from electronic/atomistic to continuum methods and methods for selecting the right model for a given problem will be introduced. It will also be demonstrated how these models can be used to solve both industrially relevant problems and questions in materials science and engineering. Selected aspects of computational materials design – especially for alloys – will be covered.
These link to the following topics in the 2017 QAA Materials Subject Benchmark Statements:
vi computational simulation of materials across the length-scales and corresponding time-scales, from atomistic (classical and quantum) to finite elements
Learning Outcomes
By the end of the module students should be able to:
Describe modelling methods commonly used in materials modelling, applicable at different length scales
State the underlying principle from which models, which were taught in lectures, were derived and state the relevant equations where appropriate
State assumptions made for each of the model
State the limitations of the model
Be able to select the appropriate model for a given materials problem, from the models covered in the lectures
Distinguish between model and numerical methods used to solve model equations
Name commonly used numerical methods, such as FD, FEM and others, state the underlying principles and strengths and limitations
Put models, as covered in the lectures, into context with regard to length and time scales covered by the models
Describe the difference between discrete and continuum modelling approaches and state relevant strength and weaknesses
These link to the AHEP v4 learning outcomes:
Apply knowledge of mathematics, statistics, natural science and engineering principles to the solution of complex problems. Some of the knowledge will be at the forefront of the particular subject of study (C1)
Analyse complex problems to reach substantiated conclusions using first principles of mathematics, statistics, natural science and engineering principles (C2)
Select and apply appropriate computational and analytical techniques to model complex problems, recognising the limitations of the techniques employed (C3)
Use practical laboratory and workshop skills to investigate complex problems (C12/M12)
Select and apply appropriate materials, equipment, engineering technologies and processes, recognising their limitations (C13/M13)
Apply a comprehensive knowledge of mathematics, statistics, natural science and engineering principles to the solution of complex problems. Much of the knowledge will be at the forefront of the particular subject of study and informed by a critical awareness of new developments and the wider context of engineering (M1)
Formulate and analyse complex problems to reach substantiated conclusions. This will involve evaluating available data using first principles of mathematics, statistics, natural science and engineering principles, and using engineering judgment to work with information that may be uncertain or incomplete, discussing the limitations of the techniques employed (M2)
Select and apply appropriate computational and analytical techniques to model complex problems, discussing the limitations of the techniques employed (M3)
Assessment
31201-01 : Computing Assignment : Coursework (50%)
31201-02 : Class test : Class Test (50%)