Module overview
This module provides an in-depth coverage of key numerical analysis methods that are used to solve practical everyday problems that occur throughout engineering. You will learn the theory underlying these methods and how to code algorithms for these methods using Matlab® programming environment. Numerical Methods is an essential core module that aims to teach you the skill of managing and solving practical engineering problems through critical and logical thinking.
Linked modules
Pre-requisite: MATH1054
Aims and Objectives
Learning Outcomes
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- Apply numerical methods algorithms in practice. This includes methods such as error quantification and mitigation, root finding, regression analysis, numerical differentiation and integration, Fourier transformation, Eigenvalues & Eigenvectors, solving differential equations and linear systems.
- Write, compile, execute and test programs using MATLAB to solve a range of problems numerically.
- Utilise user manuals and online help pages/tutorials to learn and gain familiarity with commercial software platforms.
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Demonstrate the accuracy of a numerical solution.
- Recognise engineering problems that may be approximated/solved numerically using numerical methods.
- Convert an algorithm into a programming script.
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- Present data and analyse results in a scientific manner.
- Use of MATLAB software for coding.
- Conceptualise the solution of practical engineering problems using systematic steps (i.e., a programmable algorithm).
- Time management and independent learning.
- Think in a logical and critical manner.
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- The significance of numerical methods in modern day life and technology as well as their applications in solving a wide range of practical engineering problems.
- The theory of most common numerical methods that are used by scientists and engineers.
Syllabus
Part 1: Numerical analysis for engineers
Types of errors and propagation of errors; Numerical solution of non-linear equations; Regression analysis/Curve fitting methods; Taylor series and applications; Numerical differentiation & integration (quadrature); Ordinary Differential Equation solvers; Partial differential equations
Part 2: Programming for engineers (MATLAB)
Writing, compiling and executing MATLAB codes to solve a range of practical numerical problems through a mixture of lectures and computer workshops.
Learning and Teaching
Teaching and learning methods
Teaching methods include
• Lectures
• Computer workshops
Learning activities include
• Worked examples
• Tutorial problems
• Exercise problems
• Private study
PowerPoint slides, tutorial problems solutions, worked examples, and recorded lectures available from module Blackboard.
| Type | Hours |
|---|---|
| Preparation for scheduled sessions | 12 |
| Lecture | 24 |
| Follow-up work | 24 |
| Wider reading or practice | 20 |
| Completion of assessment task | 26 |
| Revision | 24 |
| Supervised time in studio/workshop | 16 |
| Tutorial | 4 |
| Total study time | 150 |
Resources & Reading list
General Resources
ABAQUS. User manual
Internet Resources
Mathworks references (Mathworks is the official owner of Matlab).
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Laboratory Examination | 50% |
| Laboratory Examination | 50% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Final Assessment | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Final Assessment | 100% |
Repeat Information
Repeat type: Internal & External