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Prediction of the Point Efficiency of Sieve Tray Using Artificial Neural Network

Authors: Firas N. Hassan --- Adil. A. Al-Hemiri عادل احمد عوض
Journal: Iraqi Journal of Chemical and Petroleum Engineering المجلة العراقية للهندسة الكيمياوية وهندسة النفط ISSN: 19974884/E26180707 Year: 2009 Volume: 10 Issue: 4 Pages: 57-62
Publisher: Baghdad University جامعة بغداد

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Abstract

An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a data bank of around33l data points collected from the open literature.Two models proposed,using back-propagationalgorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surfacetension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless group: Flowfactor (F), Reynolds numberfor liquid (ReL), Reynolds numberfor gas through hole (Reg), ratio of weir height to hole diqmeter (hw/dH), ratio of pressure of process to atmosphere pressure (P/Pa), Weber number (lTe).Statistical analysis showed that the proposed models have an average absolute relative enor (AARE) of 9.3% and standard deviation (SD) of 9.7%forfirst model, AARE of 9.35% and SD of 10.5%for second model and AARE of 9.8%and SD of 7.5%for the third model.

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