Modeling the phase equilibria of asymmetric hydrocarbon mixtures using molecular simulation and equations of state

Monte Carlo simulation (MC) is combined with equations of state (EoS) to develop a methodology for the calculation of the vapor–liquid equilibrium (VLE) of multicomponent hydrocarbon mixtures with high asymmetry. MC simulations are used for the calculation of the VLE of binary methane mixtures with...

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Bibliographic Details
Published in:AIChE journal 2019-02, Vol.65 (2), p.792-803
Main Authors: Nikolaidis, Ilias K., Poursaeidesfahani, Ali, Csaszar, Zsolt, Ramdin, Mahinder, Vlugt, Thijs J. H., Economou, Ioannis G., Moultos, Othonas A.
Format: Article
Language:English
Subjects:
Alkanes
Computer simulation
Equations of state
gas condensates
Hydrocarbons
Interaction parameters
Liquid-vapor equilibrium
Mathematical models
Modelling
Monte Carlo
Monte Carlo simulation
Organic chemistry
Phase equilibria
phase equilibrium
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Summary:Monte Carlo simulation (MC) is combined with equations of state (EoS) to develop a methodology for the calculation of the vapor–liquid equilibrium (VLE) of multicomponent hydrocarbon mixtures with high asymmetry. MC simulations are used for the calculation of the VLE of binary methane mixtures with long n‐alkanes, for a wide range of temperatures and pressures, to obtain sufficient VLE data for the consistent fitting of binary interaction parameters (BIPs) for the EoS. The Soave‐Redlich‐Kwong (SRK), Peng‐Robinson (PR), and Perturbed Chain ‐ Statistical Associating Fluid Theory (PC‐SAFT) EoS are considered. The ability of each EoS to correlate the VLE data is assessed and the selected ones are used to predict the VLE of multicomponent gas condensate mixtures. MC simulations proved to be very accurate in predicting the VLE in all conditions and mixtures considered. The BIPs regressed from the simulation dataset lead to equally accurate modeling results for multicomponent mixtures, compared to those regressed from experimental data. © 2018 American Institute of Chemical Engineers AIChE J, 65: 792–803, 2019
ISSN:0001-1541
1547-5905
DOI:10.1002/aic.16453