The Prediction of Surface Tension of Ternary Mixtures at Different Temperatures Using Artificial Neural Networks
- سال انتشار: 1393
- محل انتشار: فصلنامه علوم و فناوری نفت و گاز، دوره: 3، شماره: 3
- کد COI اختصاصی: JR_IJOGST-3-3_005
- زبان مقاله: انگلیسی
- تعداد مشاهده: 351
نویسندگان
Thermodynamics Research Laboratory, School of Chemical Engineering, Iran University of Science & Technology, Tehran, Iran
Young Researchers and Elites Club, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran
Thermodynamics Research Laboratory, School of Chemical Engineering, Iran University of Science & Technology, Tehran, Iran
چکیده
In this work, artificial neural network (ANN) has been employed to propose a practical model forpredicting the surface tension of multi-component mixtures. In order to develop a reliable modelbased on the ANN, a comprehensive experimental data set including 15 ternary liquid mixtures atdifferent temperatures was employed. These systems consist of 777 data points generally containinghydrocarbon components. The ANN model has been developed as a function of temperature, criticalproperties, and acentric factor of the mixture according to conventional corresponding-state models.80% of the data points were employed for training ANN and the remaining data were utilized fortesting the generated model. The average absolute relative deviations (AARD%) of the model for thetraining set, the testing set, and the total data points were obtained 1.69, 1.86, and 1.72 respectively.Comparing the results with Flory theory, Brok-Bird equation, and group contribution theory hasproved the high prediction capability of the attained model.کلیدواژه ها
Surface Tension, Mixtures, Artificial Neural Networkاطلاعات بیشتر در مورد COI
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