Physics-informed neural network with transfer learning (TL-PINN) based on domain similarity measure for prediction of nuclear reactor transients

Nuclear reactor safety and efficiency can be enhanced through the development of accurate and fast methods for prediction of reactor transient (RT) states. Physics informed neural networks (PINNs) leverage deep learning methods to provide an alternative approach to RT modeling. Applications of PINNs...

Descripción completa

Detalles Bibliográficos
Autores principales: Prantikos, Konstantinos, Chatzidakis, Stylianos, Tsoukalas, Lefteri H., Heifetz, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10558465/
https://www.ncbi.nlm.nih.gov/pubmed/37803015
http://dx.doi.org/10.1038/s41598-023-43325-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10558465/
https://www.ncbi.nlm.nih.gov/pubmed/37803015
http://dx.doi.org/10.1038/s41598-023-43325-1

Ejemplares similares