Model based in neural networks for the prediction of the mass transfer coefficients in bubble columns. Study in Newtonian and Non-Newtonian fluids.

Authors
Alvarez, E Correa, JM Riverol, C Navaza, JM
Citation
E. Alvarez et al., Model based in neural networks for the prediction of the mass transfer coefficients in bubble columns. Study in Newtonian and Non-Newtonian fluids., INT COMM HE, 27(1), 2000, pp. 93-98
Citations number
4
Categorie Soggetti
Mechanical Engineering
Journal title
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER
ISSN journal
07351933 → ACNP
Volume
27
Issue
1
Year of publication
2000
Pages
93 - 98
Database
ISI
SICI code
0735-1933(200001)27:1<93:MBINNF>2.0.ZU;2-P
Abstract
A comprehensive study for the prediction of the volumetric transfer coeffic ient k(L)a with Newtonian and Non-Newtonian fluids in bubble columns is the objective of this work. The evaluation of the hydrodynamic characteristics of the bubble columns and delineated the different hydrodynamic regimes co nsidering column geometry, gas flow, liquid height and type of fluid (Newto nian and non-Newtonian) suggest a general applicability of the proposed mod el. A new learning pattern based in the design parameters of the bubble col umns is proposed. (C) 2000 Elsevier Science Ltd.