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Late News Poster Session: On-Demand Poster Session: Nuclear Materials
Program Organizers: TMS Administration

Monday 8:00 AM
March 14, 2022
Room: Nuclear Materials
Location: On-Demand Poster Hall

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Defect Structure Classification of Neutron-irradiated Graphite Using Supervised Machine Learning: Jiho Kim¹; Kunok Chang¹; ¹Kyung Hee University
     Graphite is used widely as a moderator or reflector in the nuclear industry. Therefore, the behavior of graphite after neutron irradiation needs to be studied. The neutron irradiation damage is assumed as the PKA damage model in three-dimensional space. We used molecular dynamics to simulate the neutron irradiation of graphite. We applied various PKA directions and incident neutron energies, up to 1500 eV, to find out defect structures.Simulation result shows four groups of defects: structural defect, energy defect, vacancy, and near-defect structure. The results were evaluated with decision tree, a supervised machine learning technique, to classify the number of defect structures.

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