Prediction of velocity profile of water based copper nanofluid in a heated porous tube using CFD and genetic algorithm
Abstract The heat transfer improvements by simultaneous usage of the nanofluids and metallic porous foams are still an attractive research area. The Computational fluid dynamics (CFD) methods are widely used for thermal and hydrodynamic investigations of the nanofluids flow inside the porous media....
Enregistré dans:
Auteurs principaux: | Tiziana Ciano, Massimiliano Ferrara, Meisam Babanezhad, Afrasyab Khan, Azam Marjani |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/64e7da7f2de447f4b2337f1bda2bca3e |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Velocity prediction of nanofluid in a heated porous pipe: DEFIS learning of CFD results
par: Meisam Babanezhad, et autres
Publié: (2021) -
Pressure and temperature predictions of Al2O3/water nanofluid flow in a porous pipe for different nanoparticles volume fractions: combination of CFD and ACOFIS
par: Meisam Babanezhad, et autres
Publié: (2021) -
Multidimensional machine learning algorithms to learn liquid velocity inside a cylindrical bubble column reactor
par: Meisam Babanezhad, et autres
Publié: (2020) -
Performance and application analysis of ANFIS artificial intelligence for pressure prediction of nanofluid convective flow in a heated pipe
par: Meisam Babanezhad, et autres
Publié: (2021) -
Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm
par: Meisam Babanezhad, et autres
Publié: (2021)