Mathematics

Parametrized optimal control problems governed by partial differential 
equations are usually exploited in environmental marine sciences and 
engineering in order to reliably describe different configurations 
depending on physical parameters representing several natural phenomena.

Environmental parametrized optimal control problems require a demanding 
computational effort: in this talk, we propose reduced order methods as 
an appropriate and rapid approach to solve this issue.

A POD-Galerkin reduction approach is presented, with a focus on two 
environmental applications: a pollutant control in the Gulf of Trieste 
and a solution tracking governed by quasi-geostrophic equations 
describing nonlinear North Atlantic Ocean dynamic.

This is a joint work with Francesco Ballarin, Prof. Renzo Mosetti (OGS) 
and Prof. Gianluigi Rozza