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Prediction of Dispersed Phase Holdup in the Kühni Extraction Column Using a New Experimental Correlation and Artificial Neural Network

Publish Year: 1398
Type: Journal paper
Language: English
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JR_IJOGST-8-4_006

Index date: 26 May 2020

Prediction of Dispersed Phase Holdup in the Kühni Extraction Column Using a New Experimental Correlation and Artificial Neural Network abstract

In this work, the dispersed phase holdup in a Kühni extraction column is predicted using intelligent methods and a new empirical correlation. Intelligent techniques, including multilayer perceptron and radial basis functions network are used in the prediction of the dispersed phase holdup. To design the network structure and train and test the networks, 174 sets of experimental data are used. The effects of rotor speed and the flow rates of the dispersed and continuous phases on the dispersed phase holdup are experimentally investigated, and then the artificial neural networks are designed. Performance evaluation criteria consisting of R2, RMSE, and AARE are used for the models. The RBF method with R2, RMSE, and AARE respectively equal to 0.9992, 0.0012, and 0.9795 is the best model. The results show that the RBF method well matches the experimental data with the lowest absolute percentage error (2.1917%). The rotor speed has the most significant effect on the dispersed phase holdup comparing to the flow rates of the continuous and dispersed phases.

Prediction of Dispersed Phase Holdup in the Kühni Extraction Column Using a New Experimental Correlation and Artificial Neural Network Keywords:

Prediction of Dispersed Phase Holdup in the Kühni Extraction Column Using a New Experimental Correlation and Artificial Neural Network authors

Mohsen Keshavarz

M.S. Student, School of Chemical, Petroleum, and Gas Engineering, Iran University of Science and Technology, P.O. Box ۱۶۸۴۶-۱۳۱۱۴, Tehran, Iran

Ahad Ghaemi

Associate Professor, School of Chemical Engineering, Iran University of Science and Technology, P.O. Box ۱۶۸۴۶-۱۳۱۱۴, Tehran, Iran

Mansour Shirvani

Associate Professor , School of Chemical Engineering, Iran University of Science and Technology, P.O. Box ۱۶۸۴۶-۱۳۱۱۴, Tehran, Iran

Ebrahim Arab

M.S. Student, School of Chemical Engineering, Iran University of Science and Technology, P.O. Box ۱۶۸۴۶-۱۳۱۱۴, Tehran, Iran

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Arab E., Ghaemi A., and Torab‐Mostaedi M., Experimental Investigation of ...
Asadollahzadeh M., Shahhosseini S., Torab-Mostaedi M., and Ghaemi A., Mass ...
Asadollahzadeh M., Torab-Mostaedi M., Shahhosseini S., and Ghaemi A., Using ...
Attarakih M., Hlawitschka M. W., Abu-Khader M., Al-Zyod S., and ...
Broomhead D. S. and Lowe D., Radial Basis Functions, Multi-variable ...
Buchbender F., Onink F., Meindersma G. W., and Pfennig A., ...
Chen J., Fu R., Xu S., Wu Q., and Song ...
Dabiri-atashbeyk M., Koolivand-Salooki M., and Esfandyari M., Comparing Two Methods ...
Du K.L. and Swamy M. N. S., Neural Networks in ...
Gandhi A. B., Joshi J. B., Estimation of Heat Transfer ...
Gomes L. N., Guimarães M. L., Regueiras P. F. R., ...
Hagan M. T. and Menhaj M. B., Training Feedforward Networks ...
Hassoun M. H., Fundamentals of Artificial Neural Networks, Proceedings of ...
Haunold C., Cabassud M., Gourdon C., and Casamatta G., Drop ...
Hemmati A. R., Shirvani M., Torab-Mostaedi M., and Ghaemi A., ...
Hemmati A. R., Torab-Mostaedi M., Shirvani M., and Ghaemi A., ...
Hufnagl H., McIntyre M., and Blaß E., Dynamic Behavior and ...
Kumar A. and Hartland S., A Unified Correlation for the ...
Lashkarbolooki M., Shafipour Z. S., and Hezave A. Z., Trainable ...
Mohebian R., Riahi M. A., and Kadkhodaie-Ilkhchi A., A Comparative ...
Moreira É., Pimenta L. M., Carneiro L. L., Faria R. ...
Mögli A. and Bühlmann U., The Kühni Extraction Column, Handbook ...
Neto A. P. and Mansur M. B., Transient Modeling of ...
Oliveira N. S., Silva D. M., Gondim M. P. C., ...
Rode S., Durand A., Mabille I., and Favre E., Flooding ...
Rumelhart D. E., Hinton G. E., and Williams R. J., ...
Sharker S., Phillips C. R., and Mumford C. J., Characterization ...
Tahershamsi A. H., Ghaemi A., and Shirvani M., Modeling and ...
Torab-Mostaedi M., Ghaemi A., Asadollahzadeh M., and Pejmanzad P., Mass ...
Torab-Mostaedi M., Jalilvand H., and Outokesh M., Dispersed Phase Holdup ...
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