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Optimization of machine learning models for the safeguards verification of spent fuel assemblies

 Thesis in external company     Thesis abroad

keywords MACHINE LEARNING, SPENT FUEL

Reference persons RAFFAELLA TESTONI

External reference persons DR. Riccardo Rossa (SCK-CEN)

Research Groups TESIN

Description Previous work focused on the development of machine learning models for the classification of fuel assemblies according to the percentage of replaced fuel pins. The machine learning models demonstrated the ability to detect the fuel diversion and to estimate the percentage of replaced pins. The proposed work will build on previous research and will further optimize the models.

Deadline 03/03/2023      PROPONI LA TUA CANDIDATURA