Multilevel Flow Modeling for Nuclear Power Plant Diagnosis

As complexity and safety requirements of current and future nuclear power plants increase, innovative methods are being investigated to perform accurate and reliable system diagnoses. Detecting malfunctions, identifying their causes and possibly predicting their consequences are major challenges, especially if extended to the whole plant. Monitoring plant performances by means of data reconciliation techniques has proved successful to detect anomalies during operation, provide early warnings and eventually schedule maintenance. At the same time, the large amount of information provided by large-scale monitoring systems is hard to handle manually. In this paper, the use of an innovative function-oriented modeling approach, called Multilevel Flow Modeling, is proposed for performing an automatic analysis of the outcomes of the monitoring systems with the aim of identifying the root causes of the possibly detected anomalies. The combination of a data reconciliation system and the Multilevel Flow Modeling approach is illustrated with regard to the secondary loop of the Loviisa-2 Pressurized Water Reactor located in Finland.