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Prediction of Extraction Efficiency in Rdc Column Using Artificial Neural Network

Authors: Chalak S. Omar --- Adil. A. A. Al-Hemiri
Journal: Journal of Engineering مجلة الهندسة ISSN: 17264073 25203339 Year: 2008 Volume: 14 Issue: 2 Pages: 2607-2621
Publisher: Baghdad University جامعة بغداد


An application of neural network technique was introduced in modeling extraction efficiency in RDC column, based on a data bank of around 352 data points collected in the open literature. Three models were made, using back-propagation algorithm, the extraction efficiency was found to be a function of seven dimensionless groups: Weber number (we), ( ), ( ), ( ), ( ), ( ) and ( ). Statistical analysis showed that the proposed models have an average absolute error (AARE) and standard deviation (SD) of 12.23% and 10.61% for the first model, 5.35% and 6.21% for the second model, 8.34% and 7.59% for the third model. The developed correlations also show better prediction over a wide range of operating conditions, physical properties and column geometry.

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