A mathematical model is the key to understanding the behaviour of a measurement system and interpreting the data it produces. Models are developed on the basis of physical theory and from the analysis of data.
What We Do
Our discrete and continuous mathematical modelling activity encompasses:
- modelling of physical systems
- development of empirical models
- data visualisation
- mathematical modelling for biotechnology applications
- running training courses
Discrete modelling involves the modelling of discrete data, i.e., data that represent a finite number of attributes of a system in a finite number of states, typically described by algebraic equations. It covers such areas as model construction, data approximation and smoothing and signal processing. The classic example is the fitting of a straight line to measurement data.
Continuous models describe a physical problem using ordinary or partial differential equations. In general, such models do not have analytic solutions and so they require approximate solution methods such as finite elements, finite differences, boundary elements, and finite volumes. Typically these methods involve splitting the region of interest into a set of small elements, producing a discrete approximation of the differential equation in each element, and solving all of the discrete approximations simultaneously. Continuous modelling is used in many fields, including stress analysis, heat flow, acoustic and electromagnetic wave propagation, and vibrational analysis.
- Heat Radiation Modelling for Dosimetry in Radiotherapy
- Multiscale modelling: a new challenge for physicists and mathematicians
- Near-field to far-field prediction for underwater acoustics
- SSfM Best Practice Guide 4: Discrete Modelling
- SSfM Best Practice Guide 5: Software Re-use: Guide to METROS
- SSfM Best Practice Guide 10: Discrete Model Validation
- Continuous Modelling in Metrology
- Modelling Discrete Data