Hydrate formation may be a common occurrence during oil and gas drilling and production operation when temperature of these solid crystalline compounds that formed in the presence of free water, decreases at elevated pressure. Also they have often been found responsible for operating difficulties at wellheads, pipelines and other processing equipment. Nowadays, because of the importance of predicting hydrate formation condition, different accurate methods have been used. Besides the experiential correlations that are common for predicting, the developments in the field of modeling lead to use of different methods of this one like thermodynamic way. In fact, because of reducing the risk of experimental uncertainties and also removing the need for intricate analytic equations and empirical correlations, the Computational Intelligence model, which result in the lowest error and based on experimental data, is strongly Downloaded by [University of Nebraska, Lincoln] at 03:59 08 October 2015 A c c e p t e d M a n u s c r i p t proposed to solve complex industrial problems. In this article, in order to predict gas hydrate formation condition two smart techniques are established based on feed-forward neural network (ANN) which is optimized by imperialist competitive algorithm (ICA). The ICA-ANN model is conducted utilizing the empirical data released in the literature and finally the performance of ICA-ANN model is compared with conventional ANN model, Furthermore they has been compared with an accurate thermodynamic model at different operating conditions. The outcomes, contrary to expectations, establish that the ICA-ANN model has poor performance to compare with ANN.
Thermodynamic modeling of surface tension of different electrolyte systems in presence of gas phase is studied. Using the solid-liquid equilibrium, Langmuir gas-solid adsorption, and ENRTL activity coefficient model, the surface tension of electrolyte solutions is calculated. The new model has two adjustable parameters which could be determined by fitting the experimental surface tension of binary aqueous electrolyte solution in single temperature. Then the values of surface tension for other temperatures in binary and ternary system of aqueous electrolyte solution are predicted. The average absolute deviations for calculation of surface tension of binary and mixed electrolyte systems by new model are 1.98 and 1.70%, respectively.
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