Prediction of the Phase Behavior and Properties of Hydrocarbons with a One Parameter PC SAFT Approach Assisted by a Group Contribution Method
Modeling thermodynamic properties can be challenging when the data availability for parameters identification is limited. Fully predictive group contribution (GC) methods have been developed as an alternative to overcome data scarcity. However, in order to provide a higher degree of accuracy, most recent GC approaches require detailed information on the molecule's structure, which is not acquirable for systems with unspecified components. This work intends to establish the foundation to overcome this limitation. The proposed PC SAFT approach assisted by a homosegmented group contribution scheme permits parameters calculation with accuracy due to one adjustable parameter without requiring meticulous information regarding the molecular structure, for instance, the relative position between carbon centered groups. This semipredictive approach is especially suitable for cases in which some data are available but are not taken into consideration by current GC models. A genetic algorithm based routine was devel.