Design of Experiment (DoE) constitutes a key step in both model development and system analysis. DoEs can be used to:
- Generate initial experimental process conditions
- Explore model parameter space
- Perform global parameter estimation and optimisation
- Generate data for constructing surrogate models
- Infill experimental data using model evaluations
The DoE tools in MoDS offer designs that are easy to setup and extend. They prioritise comprehensive coverage of the parameter space whilst aiming to maximise the information obtained and minimise the number of model evaluations. The options include:
- A range of traditional DoE methods
- Cutting-edge low discrepancy sequences
- An advanced “intelligent” DoE method
