MSCA-SE.26.Nava

Objective:

MOST-PINN, Monitoring Offshore Structures using Physics-Informed Neural Networks, is an international network of excellence comprising academic researchers in Engineering, Offshore Renewable Energy ORE, Computer Science, and Applied Mathematics, as well as scientists from Industry. Aligned with the ERA strategic agenda on green and digital transitions, MOST-PINN aims to create long-term impact by developing physics-informed neural networks for the ORE domain. The project contributes directly to UN Sustainable Development Goals 7 and 13 by promoting clean, affordable, and secure energy while mitigating climate change. Through an ambitious R&D+i program and supported by a strategic secondment plan, MOST-PINN addresses key engineering challenges in ORE to reduce costs and increase reliability. The activities focus on: (i) developing adaptive control strategies for wave energy converters to increase energy production while reducing detrimental loads; and (ii) advancing the development of preventive maintenance strategies through structural health monitoring of mooring lines in floating offshore wind turbines, enabling early damage detection. These challenges are addressed through rigorous mathematical frameworks that integrate physics-informed neural networks and uncertainty quantification. By combining expertise across simulation engineering, ORE, computer science, and applied mathematics, the network fosters interdisciplinary collaboration. Intersectoral exchanges with industry ensure the applicability of the solutions in real-world cases, while secondments with third-country institutions bring specialized expertise and a global perspective. MOST-PINN provides researchers with a unique opportunity for high-quality training, international collaboration, and enhanced career development. MOST-PINN outputs impact directly on the affordability of ORE; the networking activities for stakeholders and society will thrive the social awareness and acceptability in ORE.