Parametrized Model Order Reduction (PMOR): Sparse Data and Sparse Models

The main objective of this project is the development of robust and stable rational modelling algorithms to build parametrized reduced order models for complex physical systems. The order and complexity of the scalable rational models are specifically tailored towards the application at hand. The approximation and/or interpolation models are based on sparse scatterded data,spread over the design space of interest, and the models are aimed at to be sparse themselves in order to guarantee a minimal complexity.