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- UCAS institution code
MEng Aerospace Engineering with Industrial Experience / Course details
Year of entry: 2024
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Course unit details:
|Unit level||Level 2|
|Teaching period(s)||Semester 1|
|Offered by||Department of Mathematics|
|Available as a free choice unit?||No|
|Unit title||Unit code||Requirement type||Description|
The course unit aims to provide a second year course in mathematics and statistics to students in the School of MACE.
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.
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.
Coursework (week 9) Weighting within unit 20%
Examination (semester 1) Weighting within unit 80%
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)
|Scheduled activity hours|
|Independent study hours|
|Robert Gaunt||Unit coordinator|
|Chris Johnson||Unit coordinator|
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