Simultaneous prediction of the critical and sub-critical phase behavior in mixtures using equations of state III. Methane-n-alkanes

Ilya Polishuk, Jaime Wisniak, Hugo Segura

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

The present study compares the ability of three semi-predictive approaches, namely, the Global Phase Diagram-based semi-predictive approach (GPDA), the Predictive Soave-Redlich-Kwong (PSRK) and the Linear Combination of the Vidal and Mixing rules (LCVM), to describe the phase equilibrium data in the homologous series methane-n-alkanes. The results obtained for the series under consideration demonstrate, similarly as shown before for the homologue series carbon dioxide-n-alkanes, that GPDA predicts the data more accurately than the GE-based models correlate them. In particular, GPDA predicts the critical points very accurately and yields a qualitatively correct picture of the global phase behavior in the series. In contrast, both PSRK and LCVM overestimate the critical pressures and generate false liquid-liquid split in the system methane-n-pentane. Although, the GE-based models yield more accurate results for dew-point data at high temperatures, GPDA predicts these data better at the moderated and low temperatures. In addition, it is clearly better in predicting the bubble-point data. PSRK is more accurate than LCVM in description of the homologues lighter than methane-n-decane, however it fails to predict the data of the heavier ones.

Original languageEnglish
Pages (from-to)4363-4376
Number of pages14
JournalChemical Engineering Science
Volume58
Issue number19
DOIs
StatePublished - 1 Jan 2003
Externally publishedYes

Keywords

  • Alkanes
  • Equation of state
  • Methane
  • Parameter identification
  • Phase equilibria
  • Supercritical fluid

Fingerprint

Dive into the research topics of 'Simultaneous prediction of the critical and sub-critical phase behavior in mixtures using equations of state III. Methane-n-alkanes'. Together they form a unique fingerprint.

Cite this