Key facts
Details for course being taught in current academic year
Level M - 15 credits - spring term
E-learning links
Resources
Course description
Course outline
Linear multistep methods and Runge-Kutta methods. Consistency, stability and convergence theory. Absolute stability. Initial boundary value problems. Finite difference method. Finite element method. Modes of application, error analysis.
Pre-requisite
Recommended course prerequisites
General ODE theory, Further Analysis, Applied and Numerical Mathematics.
Learning outcomes
On completing the course successful students should
* know the basic concepts of convergence and stability as related to Runge-Kutta and linear multistep methods;
* be able to derive order conditions for the methods, and use them to construct methods or determine the order of a given method;
* be familiar with Linear Stability Theory concepts for their methods;
* understand initial boundary value PDE problems and possible numerical approaches;
* derive basic error analysis;
* be able to implement methods in MATLAB.
Library
Recommended Texts:
K.E. Atkinson: An Introduction to numerical analysis - Wyley (1989)
A. Iserles: A first course in the numerical analysis of differential equations - CUP (1995)
Assessments
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 30.00% | |
| Project Report | Summer Week 4 | 100.00% |
| Unseen Examination | Summer Term (2 hours) | 70.00% |
Resit mode of assessment
| Type | Timing | Weighting |
|---|---|---|
| Unseen Examination | Summer Vacation (2 hours ) | 100.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
Teaching methods
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Spring Term | LECTURE | 1 hour | 1111111111 |
| Spring Term | LECTURE | 2 hours | 1111111111 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.