The evolution of the microstructure and the mechanical properties of a 15-6 martensite precipitated hardened (15-6 PH) stainless steel after thermal treatment and long-term aging at 480 °C were investigated. Compared with 17-4 PH steel, the content of Cr decreased and Ni increased in the newly developed 15-6 PH steel; therefore, reversed austenite formed after thermal treatment at 620 °C of the solution-treated 15-6 PH steel. Although the reversed austenite may reduce the strength of the steel, it is very beneficial for the inhibition of the aging brittleness of the steel. During the accelerated thermal aging at 480 °C, the Cu-rich phase gradually coarsened, and its crystal structure changed, while the reversed austenite phase sightly increased and the Charpy impact energy maintained a rather high value. The increase of the reversed austenite content can offset the reduction of the strengthening effect of the Cu-rich phase and therefore maintain an excellent impact property of the material after thermal aging.

Ferritic/martensitic (F/M) steel is a candidate material for key structures in fourth-generation nuclear energy systems (such as fusion reactors and fast reactors). Irradiation hardening behavior is a core index to evaluate the material’s stable performance in a high-neutron-irradiation environment. In this study, based on 2048 composition and property data, a correlation model between key elements and their interactions and irradiation hardening in F/M steel was constructed using a Bayesian optimization neural network, which realized quantitative prediction of the effect of composition on hardening behavior. Studies have shown that the addition of about 9.0% Cr, about 0.8% Si, Mo content higher than about 0.25%, and the addition of Ti, Mn can effectively suppress the irradiation hardening of F/M steel, while the addition of N, Ta, and C will aggravate its irradiation hardening, and the addition of W and V has little effect on the irradiation hardening of F/M steel. There is an interaction between the two elements. C-Cr has a strong synergistic mechanism, which will cause serious hardening when the content is higher than 0.05% and the Cr content is higher than 10%. Cr-Si has a strong antagonistic mechanism, which can achieve the comprehensive irradiation hardening effect in the 9Cr-0.8Si combination. N-Mn needs N controlled lower than 0.01%. Mo-W needs to control Mo content higher than 0.5% to alleviate irradiation hardening. There is a weak synergistic effect in Si-V; when the content is between 0.3% and 0.8% and the V content is between 0.2% and 0.3%, it can assist in optimizing the composition of F/M steel. Through the optimization of multi-element combination, the composition of F/M steel with lower irradiation hardening can be designed.

The main reason that restricts the increase of fast reactor burnup is the irradiation swelling of the cladding. The reported research shows that the main elements and trace alloy/impurity elements have a great influence on the irradiation swelling. However, the behavior of the above elements in the process of coupling with irradiation defects is complex, and it is difficult to directly measure the relationship between these elements, irradiation defects and microstructure evolution in experiments. The emergence of machine learning and big data mining technology will help to gain new understanding of the impact of irradiation swelling on austenitic stainless steel, so as to find a new type of austenitic stainless steel cladding material resistant to irradiation swelling. Therefore, in this work, about 1000 groups of data such as composition, irradiation conditions and irradiation swelling of austenitic stainless steel are collected, and the data are cleaned and screened for modelling by machine learning. The deep neural network with back propagation is used in this work, and the correlation between alloy composition such as Cr, Ni, Ti and C, irradiation dose and temperature and irradiation swelling of austenitic stainless steel is established. The results show that the addition of a certain amount of Ti and Si can effectively inhibit the irradiation swelling of austenitic stainless steel, but the addition of Ni will aggravate the swelling effect. The addition of Cr, Ni, Ti and Si will increase the swelling inflection point dose, while the addition of C and P will reduce the swelling inflection point dose. Besides, the influence of multi factor coupling such as composition on irradiation swelling of austenitic stainless steel will help to promote the material optimization design of austenitic stainless steel cladding material.

Irradiation embrittlement occurs in the cladding materials of fusion reactors during irradiation. Determining the ductile–brittle transition temperature via Charpy impact testing is the primary method for evaluating irradiation embrittlement. Standard-sized V-shaped Charpy impact specimens (CVN) are too large in size and have high induced radioactivity. Small-sized specimens (KLST) can solve these problems, but the performance data measured from small-sized specimens are different from those of standard specimens. In other words, there is a size effect in impact performance. The notch size and hammer impact speed of KLST specimens are different from those of CVN specimens. The influence of these factors on impact performance requires further study. In response to these issues, on the basis of the previous experiments conducted by the research group, GTN damage models of CVN specimens and KLST specimens are constructed using the inverse operation method. Numerical simulation of the impact on the upper platform area is carried out for KLST specimens and variable-sized KLST specimens. Compared with the test results, the numerical simulation results are in good agreement, verifying the accuracy and reliability of the model. The results show that the notch angle and radius have little influence on the plastic zone. The cross-sectional area of the notch has a significant impact on the plastic zone. The impact velocity within the range of 3.8 m/s to 5.24 m/s affects the impact response process, but does not affect the load–displacement curve, the length of the non-plastic deformation zone, or the volume of the plastic zone.