Velocity prediction of nanofluid in a heated porous pipe: DEFIS learning of CFD results
Abstract Utilizing artificial intelligence algorithm of adaptive network-based fuzzy inference system (ANFIS) in combination with the computational lfuid dynamics (CFD) has recently revealed great potential as an auxiliary method for simulating challenging fluid mechnics problems. This research area...
Main Authors: | Meisam Babanezhad, Iman Behroyan, Azam Marjani, Saeed Shirazian |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2021-01-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-020-79913-8 |
Similar Items
-
Pressure and temperature predictions of Al2O3/water nanofluid flow in a porous pipe for different nanoparticles volume fractions: combination of CFD and ACOFIS
by: Meisam Babanezhad, et al.
Published: (2021-01-01) -
Performance and application analysis of ANFIS artificial intelligence for pressure prediction of nanofluid convective flow in a heated pipe
by: Meisam Babanezhad, et al.
Published: (2021-01-01) -
Predicting Air Superficial Velocity of Two-Phase Reactors Using ANFIS and CFD
by: Meisam Babanezhad, et al.
Published: (2020-12-01) -
Prediction of velocity profile of water based copper nanofluid in a heated porous tube using CFD and genetic algorithm
by: Tiziana Ciano, et al.
Published: (2021-05-01) -
Prediction of Nanofluid Characteristics and Flow Pattern on Artificial Differential Evolution Learning Nodes and Fuzzy Framework
by: Meisam Babanezhad, et al.
Published: (2020-08-01)