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

Module aims

This module continues 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

Learning outcomes

On completion of this module, students will be able to:

1. Solve some simple linear 2D partial differential equations using the method of separation of variables

2. Employ interpolation in the representation of fields and to write python code to interpolate fields on triangulated 2D domains

3. Develop finite difference schemes for differential forms of PDE an finite volume schemes for integral forms of PDE

4. Create python code to solve some simple 2D PDEs using finite difference and finite volume methods

5. Explain the concepts of convergence and consistency in the context of numerical methods

6. Create python code for the direct and iterative solution of systems of linear equations

7. Explain and apply fourier transforms and be able to apply discrete fourier transforms to data using python

 

Module syllabus

Root finding

Fourier transforms 

Analytical Solution of PDEs

Interpolation

Numerical differentiation

Numerical integration

Finite difference methods

Finite volume methods

Iterative solutions of systems of linear equations

Pre-requisites

 ME1-HMCP

Teaching methods

Students will be introduced to the main topics through lectures 2hr per week), supported by technology (eg PowerPoint, Panapto and Blackboard, MATLAB). Short activities (using interactive pedagogies) will occasionally be introduced in the classroom setting to reinforce learning, for example through mentimeter and the like. You will be provided with problem solving sheets and should complete these as part of your independent study. Tutorials sessions (1hr per week) will provide small group interaction with teaching staff where you are expected to engage in discussion on specific problems. Lab based programming practicals (1-2hrs per week) are held throughout autumn and spring terms.

Assessments

Assessment details        
      Pass mark   
Grading method Numeric   40%
         
         
Assessments        
Assessment type Assessment description Weighting Pass mark Must pass?
Examination 3 Hour exam 66% 40% N
Examination Progress test 4% 40% N
Coursework Computing quizzes  8% 40% N
Coursework Computing Final test 22% 40% N

Reading list

Module leaders

Dr Nicolas Cinosi
Dr Richard Jan van Arkel