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...

Descrizione completa

Dettagli Bibliografici

Autori principali:	Won Jun Kim, Jaehoon Jung, Cong Truong Dinh, Sung Goon Park
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2026-01-01
Serie:	Nuclear Engineering and Technology
Soggetti:	Passive autocatalytic recombiner Hydrogen prediction Convolutional neural networks Auto-encoder
Accesso online:	http://www.sciencedirect.com/science/article/pii/S1738573325004656
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!