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Meeting Materials in Nuclear Energy Systems (MiNES) 2025
Symposium Materials in Nuclear Energy Systems (MiNES) 2025
Presentation Title Machine Learning Approach to Predict Solubility of Hydrogen in Zircalloy Alloys
Author(s) Kunok Chang, Sanghyun Ji
On-Site Speaker (Planned) Kunok Chang
Abstract Scope Predicting the hydrogen solubility of commercial Zircalloy alloys using existing CALPHAD-based predictions had room for improvement in terms of prediction accuracy, especially since the irradiation effect needed to include nonequilibrium effects. In this study, we conducted research to predict the hydrogen solubility of Zircalloy-2 and Zircalloy-4 alloys using machine learning and compared the accuracy with predictions made using thermodynamic modeling.
Proceedings Inclusion? Undecided

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