Multiscale modelling in nuclear ferritic steels: From nano-sized defects to embrittlement. (October 2022)

• Record Type: Journal Article
• Authors: Castin, N.; Bonny, G.; Konstantinović, M.J.; Bakaev, A.; Bergner, F.; Courilleau, C.; Domain, C.; Gómez-Ferrer, B.; Hyde, J.M.; Messina, L.; Monnet, G.; Pascuet, M.I.; Radiguet, B.; Serrano, M.; Malerba, L.
• Is Part Of: Materials today physics. Volume 27(2022)
• Publication Date: 2022-10
• Subjects: Materials science -- Periodicals; Physics -- Periodicals; Electronic journals; 530.41
• DOI: 10.1016/j.mtphys.2022.100802
• Languages: English
• ISSNs: 2542-5293

Abstract

Abstract: Radiation-induced embrittlement of nuclear steels is one of the main limiting factors for safe long-term operation of nuclear power plants. In support of accurate and safe reactor pressure vessel (RPV) lifetime assessments, we developed a physics-based model that predicts RPV steel hardening and subsequent embrittlement as a consequence of the formation of nano-sized clusters of minor alloying elements. This model is shown to provide reliable assessments of embrittlement for a very wide range of materials, with higher accuracy than industrial correlations. The core of our model is a multiscale modelling tool that predicts the kinetics of solute clustering, given the steel chemical composition and its irradiation conditions. It is based on the observation that the formation of solute clusters ensues from atomic transport driven by radiation-induced mechanisms, differently from classical nucleation-and-growth theories. We then show that the predicted information about solute clustering can be translated into a reliable estimate for radiation-induced embrittlement, via standard hardening laws based on the dispersed barrier model. We demonstrate the validity of our approach by applying it to hundreds of nuclear reactors vessels from all over the world. Graphical abstract: Image 1 Highlights: Radiation-induced embrittlement of steels limits the lifetime of nuclear power plants. We predict embrittlement with a physics-based model, combining two tools. Tool 1: Multiscale modelling of the kinetics of Ni–Mn–Si–P–Cu clustering. Tool 2: Embrittlement is assessed from the volume fraction of Ni–Mn–Si–P–Cu clusters. We demonstrate that the achieved predictions surpass the existing models.