Dynamic modeling of crossflow microfiltration using neural networks

Dornier Manuel, Decloux Martine, Trystram Gilles, Lebert André. 1995. Dynamic modeling of crossflow microfiltration using neural networks. Journal of Membrane Science (98) : pp. 263-273.

Journal article ; Article de revue à facteur d'impact
Full text not available from this repository.

Autre titre : Modélisation dynamique de la microfiltration des flux croisés utilisant les réseaux neuraux

Abstract : The neural network theory was usedd to dynamically model membrane fouling for a raw sugar syrup feed stream. The use of neural networks enabled us to integrate the effects of hydrodynamic conditions on the time evolution of the total hydraulic resistance of the membrane under constant temperature and feed stream concentration. The results obtained satisfactorily model the effects of both constant and variable transmembrane pressure and crossflow velocity as the filtration was followed through time. The effects of the hidden network structure as well as the scatter of data on the quality of modeling are discussed in this paper. (Résumé d'auteur)

Mots-clés Agrovoc : Canne à sucre, Sirop de glucose, Écoulement de fluide, Hydrodynamique, Microfiltration, Membrane, Modèle de simulation, Modélisation

Classification Agris : Q02 - Food processing and preservation
U10 - Computer science, mathematics and statistics

Auteurs et affiliations

  • Dornier Manuel
  • Decloux Martine
  • Trystram Gilles
  • Lebert André

Autres liens de la publication

Source : Cirad - Agritrop (

View Item (staff only) View Item (staff only)

[ Page générée et mise en cache le 2021-01-18 ]