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Effect of promoters and secondary fluidizing medium on mixing: statistical and ANN approaches
Author(s) -
Mohanty Y. K.,
Mohanty B. P.,
Roy G. K.,
Biswal K. C.
Publication year - 2008
Publication title -
asia‐pacific journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.348
H-Index - 35
eISSN - 1932-2143
pISSN - 1932-2135
DOI - 10.1002/apj.179
Subject(s) - mixing (physics) , factorial experiment , artificial neural network , particle (ecology) , mathematics , statistical analysis , design of experiments , biological system , chemistry , simulation , statistics , engineering , physics , artificial intelligence , computer science , biology , ecology , quantum mechanics
Factorial design (statistical approach) and artificial neural network (ANN) models have been developed for the prediction of mixing the index with four system parameters, such as static bed heights, average particle densities, average particle sizes and gas velocities, under four different experimental conditions, viz. , only primary air, simultaneous primary and secondary air, disc promoter and rod promoter. The values of the mixing index obtained through the developed models are found to agree well with their experimental counterparts. It has also been found from these investigations that under simultaneous primary and secondary air supply conditions the best mixing performance is achieved, i.e. I M ≈ 1.0, as compared to rod promoter, disc promoter, and only primary air supply. Copyright © 2008 Curtin University of Technology and John Wiley & Sons, Ltd.