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Natural gas viscosity estimation using density based models
, Article Canadian Journal of Chemical Engineering ; Volume 91, Issue 6 , JUL , 2013 , Pages 1183-1189 ; 00084034 (ISSN) ; Jarrahian, A ; Sharif University of Technology
2013
Abstract
Accurate value determination of natural gas viscosity plays a key role in its management as it is one of the most important parameters in natural gas engineering calculations. In this study, a comprehensive model is suggested for prediction of natural gas viscosity in a wide range of pressures, temperatures, densities and compositions. The new model can be applicable for gases containing heptane plus and non-hydrocarbon components. It is validated by the 2011 viscosity data from 18 different gas mixtures. Compared to existing similar models and correlations, its results are quite satisfactory
Viscosity prediction of ternary mixtures containing ILs using multi-layer perceptron artificial neural network
, Article Fluid Phase Equilibria ; Volume 326 , 2012 , Pages 15-20 ; 03783812 (ISSN) ; Hezave, A. Z ; Al Ajmi, A. M ; Ayatollahi, S ; Sharif University of Technology
Elsevier
2012
Abstract
Ionic liquids (ILs) have been considered as a good candidate to be replaced by the conventional solvent in recent years due to their potential consumptions and unique properties. In the present study, artificial neural network was used to predict the ternary viscosity of mixtures containing ILs. A collection of 729 experimental data points were gathered from the previously public shed literatures. Different topologies of a multilayer feed forward artificial neural network (MFFANN) were examined and optimum architecture was determined. Ternary viscosity data from the literature for 5 ILs with 547 data points have been used to train the network. In addition, to differentiate dissimilar...