Uncertainty analysis based on Bayesian inference for partial defect verification of PWR spent nuclear fuel

Uncertainty analysis based on Bayesian inference for partial defect verification of PWR spent nuclear fuel

Ensuring the integrity of spent nuclear fuel (SNF) is essential for nuclear non-proliferation efforts. While detecting gross defects is relatively straightforward, identifying partial defects remain challenging. This study proposes a Bayesian inference method implemented by our newly developed Yonse...

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Bibliographic Details
Main Authors: Hojik Kim, Hyung-Joo Choi, Woojin Kim, Seungmin Lee, Chul Hee Min, Sung-Woo Kwak
Format: Article
Language:English
Published: Elsevier 2025-10-01
Series:Nuclear Engineering and Technology
Subjects:
Spent nuclear fuel
Partial defect
Bayesian inference
Gamma emission tomography
Monte Calro
Online Access:http://www.sciencedirect.com/science/article/pii/S1738573325002475
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http://www.sciencedirect.com/science/article/pii/S1738573325002475

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