Data processing methodologies applied to dynamic PRA: an overview

The use of dynamic event trees (DETs) can serve as a powerful tool for the dynamic probabilistic risk assessment (DPRA) of nuclear power plants. The DETs have the capability to more accurately model the complex interactions and events which may occur during a transient. One of the challenges of DPRA through DETs is the management of the resulting very large data sets. Hence, the need for a methodology able to handle high volumes of data in terms of both cardinality (due to the high number of uncertainties included in the analysis) and dimensionality (due to the complexity of systems) arises. Hierarchical and partitional clustering methodologies are compared and evaluated with regard to their potential to analyze large scenario datasets generated by DETs using several different data sets