Greydient
GREYDIENT is an innovative training network focused on advancing grey-box modelling approaches for multi-fidelity modeling, reliability analysis, and uncertainty quantification. The project aims to merge data from various sensors with advanced computational models to enhance the safety and reliability of systems, particularly in the automotive sector, but with broader applications in engineering and beyond. By combining data-driven machine learning with simulation models, GREYDIENT seeks to create intelligent systems and networks for continuous monitoring, optimization, and control of complex processes. The consortium comprises leading European academic institutions and industrial partners, fostering research and development in areas like uncertainty quantification and reliability of systems.
Greydient
GREYDIENT is an innovative training network focused on advancing grey-box modelling approaches for multi-fidelity modeling, reliability analysis, and uncertainty quantification. The project aims to merge data from various sensors with advanced computational models to enhance the safety and reliability of systems, particularly in the automotive sector, but with broader applications in engineering and beyond. By combining data-driven machine learning with simulation models, GREYDIENT seeks to create intelligent systems and networks for continuous monitoring, optimization, and control of complex processes. The consortium comprises leading European academic institutions and industrial partners, fostering research and development in areas like uncertainty quantification and reliability of systems.