# ES2A9 Engineering Mathematics and Technical Computing

## Module Information

### Scope

This module is one of the second year modules for:

 Core: Automotive Engineering Civil Engineering Electronic Engineering Engineering Engineering Business Management Engineering and Business Studies Manufacturing and Mechanical Engineering. Mechanical Engineering Systems Engineering Computer Systems Engineering

### Aims

To build on the fundamental material introduced in ES183 Engineering Mathematics and Systems Modelling thereby ensuring that students are equipped with the necessary analytical and computational tools to tackle advanced material in modules taught in later years. To present and provide skills in the application of more advanced mathematics and systems modelling concepts that underpin all areas of the Warwick Engineering
Curriculum. To develop skills in the use of MATLAB for modelling and analysis of engineering systems. To introduce computer programming concepts and develop programming skills within MATLAB.

### Learning Outcomes

By the end of the module the student should be able to...

• Recognise and apply advanced mathematical tools and techniques to solve engineering based problems
• Develop complex mathematical models of engineering systems
• Solve complex engineering problems using MATLAB
• Understand and apply computer programming concepts and methods using MATLAB.

### Syllabus

Sequences, series, limits and Taylor series.

Fourier series.

Partial differentiation and vector calculus.

Applied linear algebra: linear matrix/vector equations and their solution (applications such as linear regression analysis, electrical circuits and fluid networks); eigenvalue/eigenvector analysis (applications such as oscillation in circuits, structural dynamics, solution of state variable models and stability analysis); multidimensional Taylor series, linearization and extrema of functions.

Fourier transforms, z-transforms.

Partial differential equations and their solution (examples to include: wave equation, diffusion equation and Laplace equation).

Numerical methods: Newton-Raphson iteration, Euler integration of initial value ODE’s, numerical integration of functions, linear programming.

MATLAB as a system modelling and analysis tool.

Elementary computer programming concepts and constructs, illustrated using MATLAB as a prototype programming tool.

### Teaching Methods

This module includes 26 hours of lectures, 2 hours of examples classes, 2 hours of revision class, 2 hours of formative tests and 12 hours of laboratory sessions.

Required self-study: 106 hours

### Assessment

A 15 CATS module: 100% examined via a 3 hour paper consisting of all compulsory questions.

Student Resources

Staff Pages