VoidGAN: A generative adversarial network for high-fidelity void fraction signal generation in nuclear reactor thermal hydraulics

Energy 2026

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Authors: Hanyu Wang, Shuichiro Miwa, Wen Zhou, Ryo Yokoyama, Koji Okamoto

DOI: 10.1016/j.energy.2026.140204

Cited by: 0

References: 39

Fields of Study & Subjects

Nuclear Engineering Thermal-Hydraulics Model Reduction and Neural Networks Heat Transfer and Boiling Studies

References 39