The goal of POEAM is to improve the safety, reliability and long-term operation of Generation II and III light water reactors (LWR), including pressurised water reactors (PWRs) and boiling water reactors (BWRs), by assessing the environmentally-assisted cracking (EAC) resistance of structural components produced by additive manufacturing (AM). The experimental data generated in the project will be structured and used to train AI-assisted models aimed at improving the prediction of crack initiation in nuclear components, thereby supporting ageing management, anticipative maintenance strategies and safe long-term operation of the existing reactor fleet. The POEAM objectives are aligned with the scope of the call HORIZON-EURATOM-LS-2026-01-01 and NUGENIA roadmap, as well as with the SNETP Strategic Research and Innovation Agenda.

POEAM has a significant role in contributing to the safe and economic operation of nuclear power plants (NPPs). The EAC testing performed in POEAM, supported by the microstructural characterisation, will elucidate whether the studied AM materials will be susceptible to cracking in PWR and BWR water chemistries. Verifying the EAC resistance enables the introduction of new AM methods when replacing components with complex geometries in NPPs. The obvious benefit will be the safe use of such materials supporting the long-term operation of NPPs.

POEAM has a significant role in contributing to the safe and economic operation of nuclear power plants (NPPs). The EAC testing performed in POEAM, supported by the microstructural characterisation, will elucidate whether the studied AM materials will be susceptible to cracking in PWR and BWR water chemistries. Verifying the EAC resistance enables the introduction of new AM methods when replacing components with complex geometries in NPPs. The obvious benefit will be the safe use of such materials supporting the long-term operation of NPPs.

Key technical and strategic highlights include: i) Multi-scale & multi-physics integration, ii) Coupled degradation and accidental hazard assessment, iii) physics-informed AI surrogate acceleration, iv) SFP composite interface integrity, and v) Open European knowledge asset & training

VTT / CVR / CIEMAT / ZAG / MINES / Kauno technologijos universitetas / CEA / Framatome GmbH / Framatome SAS / Agencia Estatal Consejo Superior de Investigaciones Científicas / Chimikotechnologitchen I Metalurgitchen Universitet / ASNR / Innomerics S.L. / PSI / JRC Petten / University of Manchester / University of Bristol

Project coordinator:

Ahsan Chonche (ahsan.chonche@vtt.fi)