AER201 Mathematics for Aerospace Engineers
|Semester 1, 2021/22||10 Credits|
|Lecturer:||Dr Nils Mole||Timetable|
|Aims||Outcomes||Teaching Methods||Assessment||Full Syllabus|
This module consolidates previous mathematical knowledge and develops new mathematical techniques relevant to the Aerospace Engineering discipline.
Prerequisites: MAS156 (Mathematics (Electrical and Aerospace))
Not with: MAS241 (Mathematics II (Electrical))
No other modules have this module as a prerequisite.
Outline syllabusMathematical Methods: Functions of complex variables; transforms; calculus including stationary points, double integrals and differentiation of scalar and vector fields. Probability: Fundamental probabilistic notions such as random variables, discrete, continuous, uni and multi variate distributions and their properties.
AimsConsolidate previous mathematical knowledge. Provide the necessary mathematical and probabilistic background for level 2, 3 and 4 in both the Aeromechanics and Avionics streams in Aerospace Engineering.
Learning outcomesLO1 - have a working knowledge of functions of a complex variable; LO2 - be able to solve problems requiring use of the Laplace transform; LO3 - be familiar with the properties of the Fourier transform and its inverse; LO4 - be able to calculate Fourier series; LO5 - be able to determine stationary points for scalar functions; LO6 - be able to calculate double integrals; LO7 - be able to differentiate scalar and vector fields; LO8 - explain and apply fundamental probabilistic notions such as random variables, discrete, continuous, uni and multi variate distributions and their properties.
There will be a combination of lectures and tutorials in approximately a two to one ratio. The tutorials will allow students to work through examples and problems with the support of their tutor.
22 lectures, 11 tutorials
The module will be assessed by an in-person exam, duration 2 hours.
A: Mathematical Methods 1. Functions of a complex variable 2. Laplace transform 3. Fourier transform and its inverse 4. Fourier series 5. Determining stationary points for scalar functions 6. Double integration 7. Differentiation of scalar and vector fieldsB: Probability 1. Definitions of probability 2. Conditional probability and independence 3. Discrete and continuous random variables 4. Discrete, continuous, uni- and multi-variate distributions 5. Expectation, variance, covariance and correlation 6. Bayes' Theorem 7. Functions of random variables and Central Limit Theorem