Deep learning predicts boiling heat transfer
Abstract Boiling is arguably Nature’s most effective thermal management mechanism that cools submersed matter through bubble-induced advective transport. Central to the boiling process is the development of bubbles. Connecting boiling physics with bubble dynamics is an important, yet daunting challe...
Guardado en:
Autores principales: | Youngjoon Suh, Ramin Bostanabad, Yoonjin Won |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/619782d4fc9644759b6eb386b03e90c7 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Boiling and quenching heat transfer advancement by nanoscale surface modification
por: Hong Hu, et al.
Publicado: (2017) -
A Deep Learning Perspective on Dropwise Condensation
por: Youngjoon Suh, et al.
Publicado: (2021) -
Critical heat flux prediction model of pool boiling heat transfer on the micro-pillar surfaces
por: Yonghai Zhang, et al.
Publicado: (2021) -
Heat Transfer of Single and Binary Systems in Pool Boiling
por: Balasim A. Abid, et al.
Publicado: (2010) -
Heat Transfer of Single and Binary Systems inPool Boiling
por: Abbas J. Sultan, et al.
Publicado: (2010)