TY - DATA
T1 - Data underlying the research of Innovative control model and strategy development and applications to MSFR
PY - 2023/12/06
AU - Nicolò Abrate
AU - Nicolò Caruso
AU - Sandra Dulla
AU - Nicola Pedroni
AU - Stefano Lorenzi
UR - 
DO - 10.4121/0ae20eee-97a6-4634-9f57-eb1887018fc2.v1
KW - Molten Salt Fast Reactor
KW - Nuclear Power Plant
KW - Incident Detection Method
KW - kNN classification
KW - System level modelling
N2 - <p>The dataset refers to the research activity performed in the framework of the EU project SAMOSAFER, Task 6.3 - Innovative control model and strategy development</p><p>and applications to MSFR.</p><p><br></p><p>In this activity, an innovative incident detection method has been developed, aiming at improving the safety and reliability of the Molten Salt Fast Reactor</p><p>power plant, focusing on operational scenarios involving some deviations from normal operational conditions.</p><p><br></p><p>The data-driven incident detection and classification methodology (based on the kNN algorithm) aims at identifying abnormal plant conditions thanks to a</p><p>continuous monitoring of some measurable system parameters and variables (e.g., the molten salt temperatures in the secondary circuit).</p><p><br></p><p>In order to train the algorithm, a set of numerical, time-dependent simulation is carried out at the system-level (primary circuit, secondary circuit and</p><p>balance of plant) with the Modelica language.</p>
ER -