AI RESEARCH
Physics-informed neural network for predicting fatigue life of unirradiated and irradiated austenitic and ferritic/martensitic steels under reactor-relevant conditions
arXiv CS.LG
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ArXi:2508.17303v3 Announce Type: replace This study proposes a Physics-Informed Neural Network (PINN) framework to predict the low-cycle fatigue (LCF) life of irradiated austenitic and ferritic/martensitic (F/M) steels used in nuclear reactors. These materials undergo cyclic loading, neutron irradiation, and elevated temperatures, leading to complex degradation mechanisms that are difficult to capture with conventional empirical or purely data-driven models.