Learning interpretable models for stress corrosion of stainless steels exposed in the primary environment of PWRs

Leader: Josiane Nguejio Nguimatsia

Stress corrosion cracking (SCC) of stainless steels is one of the main degradation phenomena of the primary circuit components of Pressurized Water Reactors (PWRs). Understanding this cracking mechanism is absolutely essential for extending the operating life of the reactors. Previous studies have highlighted parameters that more or less influence the sensitivity of the material to SCC, such as the work hardening rate, the chemical composition of the alloy, or the environmental conditions (temperature, oxygen, etc.). With a large number of critical parameters and the presence of strong coupling effects, a fairly substantial grid of experimental tests is often considered to help understand the mechanism. The AMICCO project adopts an innovative approach that avoids rather long and costly research steps by targeting relevant tests as well as material parameters that can improve environmental performance. This approach uses a symbolic artificial intelligence tool, ExpressiF, capable of processing spatial and temporal data and combining them to support explainable decision-making. The objectives will be to define areas of sensitivity to CCS based on critical parameters identified in the model, and to provide data related to the development of new materials through additive manufacturing.