Mechanical Engineering Journal (Jan 2024)
The influence of alloy composition on neutron irradiation swelling of austenitic stainless steel by deep neural network
Abstract
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.
Keywords
