Artificial intelligence applied to simulation of radiation damage in ferritic alloys

Molecular dynamics (MD) is the only computational tool that, without any approximation, can be applied to study atomic level phenomena involving radiation-produced point-defects and their evolution driven by mutual interaction. Kinetic Monte Carlo (KMC) is suitable to extend the timeframe of an atomic level simulation to simulate an irradiation process, but all mechanisms involved must be known in advance, e.g. from MD studies. The present work is an effort to integrate artificial intelligence (AI) techniques, essentialy an artificial neural network (ANN) and a fuzzy logic system (FLS), in order to build an adaptive model capable of improving both the physical reliability and the computational efficiency of a KMC model fully parameterised on MD results.