- UCAS course code
- H400
- UCAS institution code
- M20
Bachelor of Engineering (BEng)
BEng Aerospace Engineering
Hands-on, highly transferable, and here at one of the most targeted Universities, there's no better place to launch your career (HiFliers 2024)
Duration: 3 years
Year of entry: 2025
UCAS course code: H400 / Institution code: M20
- Key features:
Scholarships available
Field trips
- Typical A-level offer: A*AA including specific subjects
- Typical contextual A-level offer: AAA including specific subjects
- Refugee/care-experienced offer: AAB including specific subjects
- Typical International Baccalaureate offer: 37 points overall with 7,6,6 at HL, including specific requirements
Fees and funding
Fees
Tuition fees for home students commencing their studies in September 2025 will be £9,535 per annum (subject to Parliamentary approval). Tuition fees for international students will be £34,000 per annum. For general information please see the undergraduate finance pages.
Policy on additional costs
All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).
Scholarships/sponsorships
Course unit details:
Mathematics 2M1
| Unit code | MATH29661 |
|---|---|
| Credit rating | 10 |
| Unit level | Level 2 |
| Teaching period(s) | Semester 1 |
| Available as a free choice unit? | No |
Pre/co-requisites
| Unit title | Unit code | Requirement type | Description |
|---|---|---|---|
| Mathematics 1M2 | MATH19662 | Pre-Requisite | Compulsory |
Aims
The course unit aims to provide a second year course in mathematics and statistics.
Learning outcomes
Knowledge and understanding: Demonstrate knowledge of the mathematical topics in the syllabus and their relevance to Mechanical, Aerospace, and Civil, Engineering.
Intellectual skills: Be able to carry out routine operations involving the topics in the syllabus.
Transferable skills and personal qualities: Have a set of tools and methods that can be applied in the courses given in the host department or in subsequent years.
Syllabus
3 Multiple and Line Integrals. Construction and evaluation of double integrals including changing the order of the
integrations. Change of variable including the Jacobian. Introduction to triple integrals. Further Line integrals. Note 3
5 lectures: Vector Calculus. Scalar and Vector fields. Gradient, divergence and curl. Laplacian. Identities. Line and Surface integrals involving vectors. Vector integral theorems.
3 lectures: Laplace Transforms: Definition. Transforms and Inverse Transforms of Simple Functions. Transforms of derivatives and integrals. Convolution, Solution of Ordinary Differential Equations using Laplace Transforms.
4 lectures: Numerical Methods. Interpolation and Least Squares approximation. Further numerical integration, integration rules, numerical integration where interval or function becomes infinite. Solution of systems of non-linear algebraic equations.
8 lectures: General notion of a random variable, including its definition and the range space.
Discrete random variables – definition and explanation; probability mass function (pmf); discrete Uniform distribution; Binomial distribution; mean and variance of discrete random variables.
Continuous random variables – definition and explanation; probability density function (pdf); Uniform distribution; Exponential distribution; Normal distribution; mean and variance of continuous random variables.
Linear transformations of random variables. ie. Y=aX+b. Mean and variance of Y.
The cumulative distribution function for discrete and continuous random variables; calculating Normal probabilities (standardising), characteristic load and strength.
Normal approximation to the Binomial distribution. Application to quality control.
Assessment methods
| Method | Weight |
|---|---|
| Other | 20% |
| Written exam | 80% |
Coursework (week 9) Weighting within unit 20%
Examination (semester 1) Weighting within unit 80%
Recommended reading
E. Kreysig, Advanced Engineering Mathematics, John Wiley
G James et. al., Modern Engineering MathematicsPearson
G James et. al., Advanced Modern Engineering MathematicsPearson
HELM (Helping Engineers Learn Mathematics)
Study hours
| Scheduled activity hours | |
|---|---|
| Lectures | 24 |
| Tutorials | 11 |
| Independent study hours | |
|---|---|
| Independent study | 65 |
Teaching staff
| Staff member | Role |
|---|---|
| David Silvester | Unit coordinator |
| Mike Simon | Unit coordinator |
Additional notes
This course unit detail provides the framework for delivery in 20/21 and may be subject to change due to any additional Covid-19 impact.
Please see Blackboard / course unit related emails for any further updates