Research on thermodynamic features of transients in the primary loop of nuclear power plant

The primary circuit transient of nuclear power plants serves as a crucial indicator for assessing the fatigue of primary circ uit materials. To facilitate the systematic management of transient data, an automatic classification tool was developed, designed to autonomously identify, classify, and manage the entire statistical process associated with these transients. The classification of transient data employs a variety of technical solutions, including thermodynamic feature rule classification, neural networks, and image recognition. The outcomes of this development reveal that by analyzing and extracting the thermodynamic characteristics of the primary loop's transients, a rule classification algorithm based on these thermo dynamic properties can be established. This algorithm can function as a foundational identification scheme and provide a reference for the results generated by intelligent algorithms.