Description
The research represents a groundbreaking application of artificial intelligence to nuclear fuel assembly optimization, specifically targeting the NuScale Small Modular Reactor design . The work addresses critical challenges in nuclear fuel cycle optimization by developing an automated, physics-informed reinforcement learning framework that significantly outperforms traditional optimization methods
| Technical Track | Student Competition |
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Primary author
Mukhammadyusuf Abduvakkosov
(Master's Program Student in Department of Nuclear Power Plant Engineering, KEPCO International Nuclear Graduate School (KINGS), Ulsan, South Korea)
Co-author
Prof.
Chang Joo Hah
(Professor,Nuclear Core Design, KEPCO International Nuclear Graduate School)
