Application of artificial neural network (ANN-MLP) for the prediction of fouling resistance in heat exchanger to MgO-water and CuO-water nanofluids
In this work, an artificial neural network (ANN) model was developed with the aim of predicting fouling resistance for heat exchanger, the network was designed and trained by means of 375 experimental data points that were selected from the literature. These data points contain six inputs, including...
Enregistré dans:
Auteurs principaux: | Ahmed Benyekhlef, Brahim Mohammedi, Djamel Hassani, Salah Hanini |
---|---|
Format: | article |
Langue: | EN |
Publié: |
IWA Publishing
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/b9e8fccc2c064480b41687bd2dcf7b51 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
A Contribution to the Modelling of Fouling Resistance in Heat Exchanger-Condenser by Direct and Inverse Artificial Neural Network
par: Ahmed Benyekhlef, et autres
Publié: (2021) -
EFFECT OF THE MEMBRANE CHARACTERISTICS AND OPERATION MODES, IN THE FOULING OF ULTRAFILTRATION MEMBRANES BY NATURAL ORGANIC MATTER (NOM)
par: GARCÍA,CESAR, et autres
Publié: (2012) -
In-situ manipulation of gel layer fouling into gel layer membrane formation on porous supports for water treatment
par: Syed Sibt-e-Hassan, et autres
Publié: (2022) -
Mitigating Silica Fouling and Improving PPCP Removal by Modified NF90 Using In Situ Radical Graft Polymerization
par: Yi-Li Lin, et autres
Publié: (2021) -
Entropy generation for MHD natural convection in enclosure with a micropolar fluid saturated porous medium with Al2O3Cu water hybrid nanofluid
par: A. Mahdy, et autres
Publié: (2021)