Deep learning-based visual prediction of hydrogen distribution in a passive autocatalytic recombiner

Maintaining the operational stability of Nuclear Power Plants (NPPs) during severe accident environments requires a comprehensive understanding of local hydrogen distribution. To mitigate hydrogen-associated risks, Passive Autocatalytic Recombiners (PARs), which operate passively through catalytic r...

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Hauptverfasser:	Won Jun Kim, Jaehoon Jung, Cong Truong Dinh, Sung Goon Park
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Elsevier 2026-01-01
Schriftenreihe:	Nuclear Engineering and Technology
Schlagworte:	Passive autocatalytic recombiner Hydrogen prediction Convolutional neural networks Auto-encoder
Online-Zugang:	http://www.sciencedirect.com/science/article/pii/S1738573325004656
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