Combining simulations and machine learning for neutron noise-based core diagnostics
Paper i proceeding, 2021

This paper gives an overview of the neutron noise-based core monitoring technique developed as part of the Horizon 2020 CORTEX project. This method relies on machine learning architectures trained and validated using advanced simulations of postulated anomalies in nuclear reactors. Using neutron flux measurements in operating reactors allows thereafter for the detection, classification and characterization of actual disturbances existing in the system.

machine learning

neutron noise

core monitoring and diagnostics

Författare

Christophe Demaziere

Chalmers, Fysik, Subatomär, högenergi- och plasmafysik

Proc. Tech. Meeting on Artificial Intelligence for Nuclear Technology and Applications (AI4Atoms)

Tech. Meeting on Artificial Intelligence for Nuclear Technology and Applications (AI4Atoms)
Vienna, Austria,

Core monitoring techniques and experimental validation and demonstration (CORTEX)

Europeiska kommissionen (EU) (754316CORTEX), 2017-09-01 -- 2021-08-31.

Styrkeområden

Energi

Ämneskategorier

Annan fysik

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2021-10-31