Imagine trying to build a car but having to wait years to see if the metal rusts. This project uses computer simulations and AI to predict how nuclear plant materials age without waiting decades for real-world results. It's like moving from a slow 'wait and see' method to a fast 'design and predict' digital blueprint.
Nuclear material qualification is traditionally slow and relies on long-term observation, which delays the deployment of new reactor designs and increases costs for maintaining old plants.
A coordinated network of 5 research lines producing digital twins, acceleration platforms, and intelligent health monitoring systems for nuclear materials.
If you are a plant operator dealing with aging reactor components — this project developed intelligent health monitoring systems that predict material behavior. This allows you to extend the life of existing reactors safely and reduce unplanned downtime.
If you are a manufacturer dealing with slow qualification cycles for new metals — this project developed acceleration platforms and test-beds. This reduces the time it takes to prove a new material is safe for nuclear use, speeding up your time-to-market.
If you are an inspection company dealing with outdated manual checks — this project developed non-destructive examination tools and digital twins. This enables more accurate, automated health monitoring of critical energy infrastructure.
The total budget is approximately €36 million, with nearly €20 million provided by EU contributions.
The project is currently in the coordination and development phase, focusing on creating test-beds and acceleration platforms to streamline industrial qualification.
Based on available project data, the project focuses on coordination and open calls for research lines, but specific licensing terms are not detailed in the summary.
The project period runs from October 1, 2024, to September 30, 2029.
Integration is achieved through intelligent health monitoring systems and predictive methodologies for materials behavior during actual operation.
The consortium is heavily weighted toward research and academia, with 22 research organizations and 10 universities. However, there is a clear industrial link with 7 industry partners (16% ratio), including 2 SMEs, ensuring that the digital tools developed for nuclear materials are aligned with actual market needs and regulatory requirements across 19 countries.
Contact CIEMAT in Spain for partnership opportunities regarding nuclear material qualification.
Contact SciTransfer to identify specific SMEs within the 43-partner network for procurement.
