On The Estimation Of Phase Behavior Of CO2-Based Binary Systems Using ANFIS Optimized By GA Algorithm

Abstract

Since the world average temperature is on the rise, severe measurements should be considered due to decrease the concentration of greenhouse gases which are the main reason of global warming. Geological sequestration of the CO2 speculated as one of the most efficient method for mitigate the problem. As the injected CO2 stream is not always a pure one, a more accurate assessment of the impurities effects on various part of the sequestration process would be desired. As equations of state are not able to completely support the thermodynamic attributes of impure CO2 injected stream, developed computational modeling would be more appropriate. In this study, due to obtain a way of predicting vapor liquid equilibrium of CO2 binary mixtures, not fully depending on the experimental data, a novel and accurate computational method is presented. This alternative, uses Adaptive Neuro-Fuzzy Interference System (ANFIS) together with Genetic Algorithm as an optimization tool. As a result, the developed model shows a great i