2017/18 Taught Postgraduate Module Catalogue

MECH5315M Engineering Computational Methods

15 creditsClass Size: 200

Module manager: Dr D Ruprecht
Email: D.Ruprect@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2017/18

Pre-requisites

MECH1520

Engineering Mathematics

Module replaces

MECH 5510M Computational & Experimental Methods

This module is not approved as an Elective

Module summary

The module introduces students to the basic computational methods used to solve engineering problems modelled by ordinary differential equations and parabolic or hyperbolic partial differential equations. They will also learn how to implement the learned methods in practice. Engineering simulation software packages rely on computational methods and a good understanding is crucial to knowledgeably use them.

Objectives

On successful completion of this module, students should understand the basic concepts of computational methods used in engineering. In order to fulfil this goal, the module will be divided into three sections.
The first section discusses numerical methods for ordinary differential equations, extending knowledge from undergraduate engineering mathematics.
The second section will acquaint the students with examples of dissipative partial differential equations, e.g. for modelling heat diffusion, and how to solve them numerical.
The third section is concerned with hyperbolic partial differential equations used to model e.g. waves.
In addition to mathematical skills, the students will also learn how to implement the learned methods in practice via computer laboratory work.

Learning outcomes
Overview of different computational methods and types of problems; understanding of different mathematical models and knowledge which computational methods are appropriate; familiarity with important properties of computational methods; capability to transfer learned method into software

Syllabus

1. Basic programming methodology for computational methods.
2. Initial value problems and ordinary differential equations: Euler method, Runge-Kutta methods and multi-step methods.
3. Parabolic partial differential equations: finite difference methods, spectral methods.
4. Hyperbolic partial differential equations: finite difference methods, finite volumes, dispersion relations.

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	32	1.00	32.00
Practical	6	2.00	12.00
Private study hours			106.00
Total Contact hours			44.00
Total hours (100hr per 10 credits)			150.00

Private study

2 hours of preparation for and study after each lecture for a total of 64 hours.
2 practical exercises requiring 6 hours each and a final assignment requiring 30 hours to complete for a total of 42 hours.

Opportunities for Formative Feedback

Students have to complete two computer exercises. These will demonstrate understanding of both the methods as well as programming skills and allow to monitor progress throughout the course. In addition, ungraded multiple choice tests will be provided through VLE to also monitor progress. Finally, the report at the end of the modules ties everything together and allows for a comprehensive assessment of learning outcome.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Report	Programs plus 5 pages report	50.00
Computer Exercise	Programs plus 1 page text (2 exercises)	50.00
Total percentage (Assessment Coursework)		100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

There is no reading list for this module

Last updated: 16/10/2017

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