Detailed module information
Module information on this degree can be found below, separated by year of study.
The module information below applies for the current academic year. The academic year runs from August to July; the 'current year' switches over at the end of July.
Students select optional courses subject to rules specified in the Mechanical Engineering Student Handbook, for example at most three Design and Business courses. Please note that numbers are limited on some optional courses and selection criteria will apply.
Mathematics and Computing 2
To continue the development of key mathematical and computational skills relevant to the wider mechanical engineering programme. Topics include the analytical solution of partial differential equations, basic numerical methods (interpolation, differentiation, integration), discrete methods for the solution of PDEs (finite difference, finite volume) and the iterative solution of systems of equations. For all of these topics, practical implementation through programming is studied. These skills and techniques are in support of ME2, ME3 and ME4 modules.
ECTS units: 10
To be able to solve some simple linear 2D partial differential equations using the method of separation of variables
To understand and employ interpolation in the representation of fields and to write python code to interpolate fields on triangulated 2D domains
To be able to develop finite difference schemes for differential forms of PDE
To be able to develop finite volume schemes for integral forms of PDE
To be able to write python code to solve some simple 2D PDEs using finite difference and finte volume methods
To understand the concepts of covergence and consistency in the context of numerical methods
To understand and be able to write python code for the direct and iterative solution of systems of linear equations
To understand fourier transforms and be able to apply discrete fourier transforms to data within python
Analytical Solution of PDEs
Finite difference methods
Finite volume methods
Iterative solutions of systems of linear equations
|Allocation of study hours||Hours|
|Assessment type||Assessment description||Weighting||Grading method||Pass mark||Must pass?|
|Examination||3 hour exam (6 questions)||60%||Numeric||40%||Y|
|Coursework||Autumn term programming test||18%||Numeric||40%||N|
|Coursework||Spring term programming test||18%||Numeric||40%||N|
Module leadersDr Nicolas Cinosi
Dr Richard Jan van Arkel