Data underlying the research of Innovative control model and strategy development and applications to MSFR

The dataset refers to the research activity performed in the framework of the EU project SAMOSAFER, Task 6.3 - Innovative control model and strategy developmentand applications to MSFR.<br>In this activity, an innovative incident detection method has been developed, aiming at improving the safety and reliability of the Molten Salt Fast Reactorpower plant, focusing on operational scenarios involving some deviations from normal operational conditions.<br>The data-driven incident detection and classification methodology (based on the kNN algorithm) aims at identifying abnormal plant conditions thanks to acontinuous monitoring of some measurable system parameters and variables (e.g., the molten salt temperatures in the secondary circuit).<br>In order to train the algorithm, a set of numerical, time-dependent simulation is carried out at the system-level (primary circuit, secondary circuit andbalance of plant) with the Modelica language.