- UCAS course code
- HHP3
- UCAS institution code
- M20
MEng Mechatronic Engineering with Industrial Experience
Year of entry: 2024
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Course unit details:
Numerical Analysis
Unit code | EEEN30101 |
---|---|
Credit rating | 10 |
Unit level | Level 3 |
Teaching period(s) | Semester 1 |
Available as a free choice unit? | No |
Overview
Brief description of the unit:
The unit gives an introduction to numerical methods that are routinely used by engineers in analysis and design.
Topics will include: root finding and optimization; solving linear algebraic systems; curve fitting; numerical integration and differentiation; numerical solutions of simple ordinary differential equations and partial differential equations.
There will be an emphasis on numerical accuracy, numerical stability and computational efficiency. Meanwhile the techniques will be illustrated on examples from the Electrical and Electronic Engineering, Electronic Engineering and Mechatronic Engineering streams. These will include: circuit analysis, power flow optimization; digital signal processing; plotting V/I characteristics; finding transfer function poles; realizing transfer function responses.
Lecture material will be illustrated with Matlab examples. Students are encouraged to implement the techniques on other software platforms.
Pre/co-requisites
Unit title | Unit code | Requirement type | Description |
---|---|---|---|
Signals and Systems | EEEN20131 | Pre-Requisite | Compulsory |
Mathematics 2E1 | MATH29681 | Pre-Requisite | Compulsory |
Aims
The course unit unit aims to:
Reinforce students' confidence in using Matlab and other software platforms suitable for numerical analysis.
Give an overview of numerical methods routinely used by electrical, electronic and mechatronic engineers.
Illustrate their application on examples encountered in other 1st, 2nd and 3rd year units.
Learning outcomes
On the successful completion of the course, students will be able to:
ILO 1 - Calculate numerical solutions to integration problems and the time evolution of simple dynamical systems
ILO 2 - Code simple algorithms for root finding, LU decomposition and least squares
ILO 3 - Solve simple line fitting and optimization problems
ILO 4 - Explain the role of randomisation for non-convex optimisation problems
ILO 5 - Analyse numerical accuracy in the context of floating point arithmetic and determine suitable stopping criteria for numerical computation
ILO 6 - Factorize matrices and interpret their rank, condition number and singular values in terms of linear algebraic equations modelling physical applications
ILO 7 - Write code for numerically efficient matrix computation
Teaching and learning methods
Assessment methods
Method | Weight |
---|---|
Other | 20% |
Written exam | 80% |
Coursework
Coursework forms 20% of the unit assessment
Assignments related to both the laboratory sessions
Feedback methods
.
Recommended reading
S C Chapra. Applied Numerical Methods with MATLAB for Engineers and Scientists, 3rd edition, McGraw-Hill 2012
Study hours
Scheduled activity hours | |
---|---|
Lectures | 20 |
Practical classes & workshops | 6 |
Tutorials | 4 |
Independent study hours | |
---|---|
Independent study | 70 |
Teaching staff
Staff member | Role |
---|---|
Sareh Malekpour | Unit coordinator |
Zhenhong Li | Unit coordinator |