Teaching Responsibility
LJMU Schools involved in Delivery:
LJMU Partner Taught
Learning Methods
Lecture
Module Offerings
6502NCCG-JAN-PAR
6502NCCG-SEP-PAR
Aims
This module aims to build on the topics covered in the Further Mathematics module typical of Higher National Diploma programmes in Engineering, covering a range of engineering mathematics topics not normally covered in students’ previous studies but that are both useful at level 6 and a preparation for further study.
Students will also learn how to use industry-standard software to model and assist in the solution of engineering problems.
Learning Outcomes
1.
Recognise and apply advanced mathematical tools and techniques to solve engineering based problems
2.
Develop complex mathematical models of engineering systems
3.
Solve complex engineering problems using MATLAB
4.
Apply data analytics techniques to datasets produced by engineering processes and systems
Module Content
Outline Syllabus:
Sequences, series, limits and Taylor series, Fourier series. Multidimensional Taylor series, linearization and extrema of functions.
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)
Vector analysis: Revision of vectors and scalars, dot product and cross product. Vector differentiation, vector operators, gradient divergence and curl, vector integration in 3 dimensions, integral theorems.
Partial differential equations and their solution (examples to include: wave equation, diffusion equation and Laplace equation).
Fourier transforms, z-transforms.
Data analysis techniques: Regression, classification, PCA and design of experiments.
MATLAB as a system modelling and analysis tool.
Application of mathematical knowledge to broadly-defined engineering problems.
Sequences, series, limits and Taylor series, Fourier series. Multidimensional Taylor series, linearization and extrema of functions.
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)
Vector analysis: Revision of vectors and scalars, dot product and cross product. Vector differentiation, vector operators, gradient divergence and curl, vector integration in 3 dimensions, integral theorems.
Partial differential equations and their solution (examples to include: wave equation, diffusion equation and Laplace equation).
Fourier transforms, z-transforms.
Data analysis techniques: Regression, classification, PCA and design of experiments.
MATLAB as a system modelling and analysis tool.
Application of mathematical knowledge to broadly-defined engineering problems.