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Prediction of Extraction Efficiency in Rdc Column Using Artificial Neural Network | ||
| Journal of Engineering | ||
| Article 1, Volume 14, Issue 2, 2008, Pages 2607-2621 | ||
| Authors | ||
| Chalak S. Omar; Adil. A. A. Al-Hemiri | ||
| Abstract | ||
| 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. | ||
| Keywords | ||
| Rotating disc contactor; Extraction Efficiency; Artificial Neural Network; Back; propagation algorithm | ||
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