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Conflict of Interest: In relation to this article, we declare that there is no conflict of interest.

Publication history: Received October 4, 2013
Accepted November 26, 2013

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Predicting the velocity distribution of Rushton turbine impeller in mixing of polymeric liquids using fuzzy neural network models

Ali Aminian Mansour Jahangiri^†

Faculty of Chemical, Petroleum and Gas Engineering, Semnan University, P. O. Box 35195-363, Semnan, I. R. Iran

mjahangiri@semnan.ac.ir

Korean Journal of Chemical Engineering, May 2014, 31(5), 772-779(8), 10.1007/s11814-013-0255-9

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Abstract

Velocity profiles are helpful for the confident design of mixing tanks and chemical reactors in mixing processes. A fuzzy model and an artificial neural network have been presented for accurate prediction of velocity distribution of Rushton turbine impeller (RTI) for the mixing of polymeric liquids in the lower transition region: 35

Keywords

Fuzzy Artificial Neural Network Velocity Distribution Rushton Turbine Impeller Polymeric Liquids

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