Development of an Artificial Neural Network Model and an Empirical Correlation for Predicting the Isobaric Instantaneous Thermal Expansion Coefficient of Crude Oils
Abstract:The coefficient of isobaric thermal expansion of crude oils is essential in thermal methods of production and surface facilities design. The literature has no simple mathematical model to predict the instantaneous thermal expansion coefficient. Therefore, this study presents an artificial neural network (ANN) model and an empirical correlation for predicting crude oil's isobaric instantaneous thermal expansion coefficient. The input parameters for the ANN model and correlation are the usually measured paramete… Show more
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