Development of the Machine Learning-based Safety Significant Factor Inference Model for Diagnosis in Autonomous Control System

•A Digital Twin for Diagnosis (DT-D) is designed to infer the plant damage states.•A Safety Significant Factor (SSF) is introduced to represent the reactor states.•A Recurrent Neural Network (RNN) is used to develop the SSF inference model (SSFIM).•As the DT-D, the SSFIM is well-generalized, accurate, effective, and robust model.•The SSFIM shows successful model performance in loss of flow accident.