Description
Reduced Order Modelling
is a new generation
of techniques which allow us to obtain parametric solutions
of complex models that can be particularized
in real time
for any value
of the parameters.
Organisation
Laboratory
for Manufacturing Systems & Automation (LMS) - University
of Patras - PANEPISTIMIO PATRON
Comments
CO2 emissions (
in %) Additional KPIs Contribution to
the reduction
of energy use and CO2 emissions Reduction
of waste (
in %) Additional KPIs Contribution to
the reduction
of waste project_id_EC super_admin
Investigating Data-Driven Systems as Digital Twins: Numerical Behavior of Ho–Kalman Method for Order Estimation
Result title
Investigating
Data-Driven Systems as Digital Twins: Numerical Behavior
of Ho–Kalman Method
for Order Estimation
Non-intrusive Sparse Subspace Learning for Parametrized Problems
Result description
Aguado, Francisco ChinestaJournal title: Archives
of Computational Methods
in EngineeringJournal number: 26/2Journal publisher: International Center
for Numerical Methods
in EngineeringPublished year: