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Validation of models is discussed and a hierarchical modelling approach involving all of three modelling methods is briefly mentioned, which gives an overview of the design for implementing a generic diagnostic tool on SOFC system.
The validation of models obtained showed good agreement between modelled and independent experimental results.
This can detrimentally impact on the verification and validation of models and makes the development of extensible and reusable modelling tools difficult.
The UML as the most popular modeling language is not able to ensure this which delegates the validation of models to further tasks.
The data can assist the validation of models for ⟨χ⟩.
Still, for validation of models and simulations, accurate experimental data is a requisite.
In this section, the validation of models with identified parameters in time domain are presented.
The calibration and validation of models were done using the available input parameters.
Likewise, Ørsted data were only used for the validation of models at satellite altitude.
This has made the development and validation of models incorporating turbulence difficult.
Validation of models and control schemes is performed by using the MATLAB/Simulink environment.
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