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PROCESSIUM communicates at the SAFT 2011, Pau, October 24-25th 2011.
PROCESSIUM communicates at SAFT 2011, Pau, October 24-25th 2011.
IntroductionRecent equations of state (EoS) based on statistical thermodynamics, like the SAFT models (Statistical Associating Fluid Theory) [1] are promising for determining thermodynamic properties of associating and polar fluids and for the simulation of processes involving complex fluid mixtures. Some physical properties of fluids change drastically in the vicinity of the mixtures’ critical point. For many processes it is therefore important to accurately determine ther- modynamic properties close to the critical point. Unfortunately, classical equations of state including the PC-SAFT EoS [2] fail to represent the critical region. The reason is that mean field theory is not adequate at the critical point – rather, a renormalisation theory must be used that accounts for the diverging fluctuations in some parameters at the critical point. White proposed a renormalization procedure based on a perturbation approach using well defined inter- molecular potentials [3]. In this poster, we present results obtained for pure components and mixtures involving hydrocarbons and alcohols.
Renormalization Approach [4]
Results![]()
ConclusionThe renormalization theory of White applied with the PC-SAFT EoS leads to a significantly improved representation of the critical region in comparison with classical PC-SAFT EoS. Two approximations methods have been used, namely the phase-space cell approximation (PS) and the isomorphic approximation (I). They perform similarly for most mixtures and each of them displays stronger cases depending on the system concerned. In this work, a single interaction parameter was not able to fit simultaneously experimental x c -T c and x c -P c data. The PC-SAFT RG could be improved by finding an alternative way to obtain its parameters (here fitted to critical coordinates). PC-SAFT RG is nevertheless able to provide good estimates of mixtures critical points using subcritical data for tuning the parameters of the model. In order to continue the work of Moussa Dicko [13] and Chien-bin Soo [14], a new thesis dealing with calculations and measurements in the critical region should begin shortly.
References [1] W.G. Chapman et al., Fluid Phase Equilib., 52 (1989) 31-38. [2] J. Gross and G. Sadowski, Ind. Eng. Chem. Res., 40 (2001) 1244-1260. [3] J.A. White, Fluid Phase Equilib., 75 (1992) 53-64. [4] X. Tang and J. Gross, Ind. Eng. Chem. Res., 49 (2010) 9436–9444. [5] T.E. Daubert et al., Physical And Thermodynamic Properties Of Pure Chemicals. Data Compilation. Taylor & Francis, Washington D.C., mars 1997. [6] E.W. Lemmon et al., NIST Standard Reference Database 23. REFPROP, v9.0. Standard Reference Data, Gaithersburg, 2010. [7] V.A. Cymarnyi and V.M. Palaguta. Zh. Prikl. Khim. (Leningrad), 63 (1990) 905. [8] G.K. Lavrenchenko et al., Int. J. Refrig., 15 (1992) 386–392. [9] X. Courtial et al., Fluid Phase Equilibr., 277 (2009) 152–161. [10] P. Beranek and I. Wichterle. Fluid Phase Equilibr., 6 (1981) 279–282. [11] W.B. Kay., J. Chem. Eng. Data, 15 (1970) 46–52. [12] C-B Soo et al., J. of Supercritical Fluids, 55 (2010) 545–553. [13] M. Dicko, PhD Thesis, Mines Paristech, 2010. [14] M. Dicko, PhD Thesis, Mines Paristech, 2010.
Current addresses: *Processium, C.E.I. 3 - 62 Bd Niels Bohr - BP 2132 - 69603 Villeurbanne Cedex -France. **Laboratoire des Sciences des Procédés et des Matériaux, Université Paris 13 - 99 avenue Jean-Baptiste Clément - 93430 Villetaneuse - France
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