{
"Version": "2.2.2",
"Updated": "2025-11-10"
}This module will give a view of how numeric simulations can be applied to problems in Design Engineering (and some problems selected from physical, biological, and social sciences). An underpinning of numerical methods, algorithms, and analysis tools will complement applications to a range of systems, such as infection modelling and crowd dynamics. We will explore how results can be interpreted, visualised, and how much we should trust them with tools to analyse these questions. The module will range from numeric underpinning to chaos and game theory with a range of applications that will give an early career researcher a window into the range of tools available to them.
On completion of this module, you will be better able to:
- Apply a range of numerical and computational methods.
- Construct numerical and mathematical models that capture the key features of a design engineering problem.
- Analyse algorithms for stability, accuracy, and computational complexity.
- Interpret simulation results and their implications in their wider design engineering context.
- Represent simulation results and data graphically for understanding, exploration, and communication.
Details of the Assessment Brief found here.
- Love, Predators, and Dynamic Systems
- Pendulum Systems and Runge Kutta Methods
- Bifurcations
- Limit Cycles, Logistic Growth, Lorenz Attractor
- Double Pendulum and Poincaré maps
- IEEE Floats and Numeric Error
A sample of previous submissions can be found on Blackbaord.
- 2.3.0 All notebooks (Double Pendulum and Poincaré maps, Limit Cycles, Logistic Growth, Lorenz Attractor, IEEE Floats and Numeric Error ).
- 2.2.2 Bifurcations.
- 2.2.1 Previous submissions.
- 2.2.0 Uploaded Logistic Predator Prey notebook.
- 2.1.1 Uploaded Runge Kutta Fehlberg notebook.
- 2.1.0 Runge Kutta.
- 2.0.0 Initial Release.