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Holdup prediction in inverse fluidization using non-Newtonian pseudoplastic liquids: Empirical correlation and ANN modeling
B DAS, U P GANGULY, N BAR,
Published in Elsevier
2015
Volume: 273
   
Pages: 83 - 90
Abstract
The bed expansion characteristics in inverse fluidization using non-Newtonian liquids are reported. Experiments have been carried out using single and binary systems of four different polymeric solids and four different non-Newtonian pseudoplastic liquids in two different columns. Empirical correlation has been developed to determine the bed expansion characteristics as a function of physical and dynamic variables of the system. A multilayer perceptron trained with backpropagation and Levenberg-Marquardt algorithm have been used for the Artificial Neural Network (ANN) analysis. Four different standard transfer functions in a single hidden layer are used. The ANN model with Levenberg-Marquardt algorithm with transfer function 2 having 12 processing elements in hidden layer gives good predictability of the bed height. Statistical analysis indicates that both the empirical correlation and the ANN prediction give acceptable results. © 2014 Elsevier B.V.
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JournalData powered by TypesetPowder Technology
PublisherData powered by TypesetElsevier
ISSN0032-5910