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Determination of Local Gas Hold‐up and Volumetric Mass Transfer Co‐efficient in a Bubble Column by Means of an Ultrasonic Method and Neural Network
Author(s) -
Supardan M.D.,
Maezawa A.,
Uchida S.
Publication year - 2003
Publication title -
chemical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.403
H-Index - 81
eISSN - 1521-4125
pISSN - 0930-7516
DOI - 10.1002/ceat.200301752
Subject(s) - mass transfer , bubble , ultrasonic sensor , artificial neural network , column (typography) , work (physics) , bubble column reactor , mechanics , materials science , heat transfer , acoustics , gas bubble , chemistry , computer science , mechanical engineering , physics , thermodynamics , artificial intelligence , engineering , connection (principal bundle)
Previous work has proven the capability of ultrasonic and neural network methods to predict the hydrodynamic behavior of a bubble column. There is still a problem in applying this method to the case where the mass and the heat transfer occur in a bubble column. We present the implementation of a novel technique based on an ultrasonic and neural network, to simultaneously determine ϵ G and k L a , in a 2‐D bubble column. Preliminary results showing the capability of the proposed method will be presented.