m.a.r.i.n.A.I.

m.a.r.i.n.A.I. -  aims to reduce underwater radiated noise (URN) from ship and motor yacht propellers. It employs an innovative methodology based on Computational Fluid Dynamics (CFD) and hydroacoustic simulations to train a Machine Learning algorithm. The final result will be a specialized tool for designing more efficient propulsion systems, reducing noise emissions, fuel consumption, and overall design time.

Eligible Expenditure: €1,572,912.64

PR FESR FVG Grant: €1,021,794.57 (including a 40% EU contribution)