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• 9 chemical contents and 3 irradiation conditions were used as input factors. • The probability density distribution of Δ RT NDT was used to evaluated the model performance. • The GBDT model has the best performance, its prediction is close to that of ASTM E900-15. • FNF, T and the content of Cu, Ni, C are the most important 5 factors for irradiation embrittlement. A reliable irradiation embrittlement model of reactor pressure vessel (RPV) is critical to the safe operation and life extension of nuclear power plants (NPP). In this study, 474 datasets from NUREG/CR-6551 and 6 machine learning (ML) methods were adopted to accurately predict the irradiation embrittlement behavior (Δ RT NDT) of RPV with comprehensive input factors involving irradiation conditions and metal composition. The GBDT model has the best prediction performance. The calculated result by GBDT model is close to those of JEAC-4201 and ASTM E900-15. Cu content is the most sensitive factor for Δ RT NDT , followed by neutron fluence. This work demonstrates a successful application of ML in promoting NPP safety and RPV materials design. [ABSTRACT FROM AUTHOR]

In situ irradiation in transmission electron microscope following pre-irradiation was performed on Fe-0.6Ni alloy to investigate the growth of dislocation loops under irradiation. The observations showed two types of loop growth behaviour. One type was almost linear growth with irradiation dose, possibly caused by loop absorbing freely migrating defects. The other was abrupt growth with rapid increase in diameter. It was found that nanometre-sized loop might migrate one-dimensionally, following which the large loop could absorb the small loop. This process can result in the abrupt growth of loop and broadening of loop size distribution. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Neutron irradiation following thermal ageing experiments were performed using Fe-Cu, Fe-Cu-Ni, Fe-Cu-Ni-Mn, and Fe-Cu-Si alloys to investigate the effects of Ni, Mn, and Si on the formation of Cu-rich clusters and their chemical composition. Atom probe tomography showed that Ni and Mn increased the number density of Cu-rich clusters. This can be caused by that Ni and Mn reduce the formation energy of Cu nuclei, thus enhancing the Cu nucleation rate. Mn may also enhance the heterogeneous nucleation of Cu because of its strong interaction with self-interstitial atoms. In addition, Mn can accelerate solute diffusion during thermal ageing. A high Ni alloying content enhanced the Mn concentration in the clusters as well as the Ni concentration, which is believed to be caused by the thermodynamic relationship between Ni and Mn. In Fe-Cu-Si alloys, the Si concentration in the clusters was very low and was comparable to the Si alloying content. This indicates that Si atoms hardly cluster with Cu. [ABSTRACT FROM AUTHOR]

A multiscale modeling approach was applied to investigate the nucleation process of CRPs (copper rich precipitates, i.e., copper-vacancy clusters) in α-Fe containing 1 at.% Cu during irradiation. Monte-Carlo simulations were performed to investigate the nucleation process, with the rate theory equation analysis to evaluate the concentration of displacement defects, along with the molecular dynamics technique to know CRP thermal stabilities in advance. Our MC simulations showed that there is long incubation period at first, followed by a rapid growth of CRPs. The incubation period depends on irradiation conditions such as the damage rate and temperature. CRP’s composition during nucleation varies with time. The copper content of CRPs shows relatively rich at first, and then becomes poorer as the precipitate size increases. A widely-accepted model of CRP nucleation process is finally proposed. [ABSTRACT FROM AUTHOR]

Abstract: The correlation between recent PAS results and the outcomes from mechanical testing of RPV model alloys are presented, here significant changes due to different chemical composition and different irradiation levels are observed. The influence of alloying elements to the microstructure degradation process following irradiation was identified by analysis of the mean-lifetime parameter, since an interesting interdependency of this parameter with hardness was observed. [Copyright &y& Elsevier]