SOLUTION ALGORITHMS AND PARAMETER SENSITIVITY ANALYSIS FOR THE SPHCT EQUATION OF STATE

Citation
Rd. Shaver et al., SOLUTION ALGORITHMS AND PARAMETER SENSITIVITY ANALYSIS FOR THE SPHCT EQUATION OF STATE, Fluid phase equilibria, 113(1-2), 1995, pp. 61-77
Citations number
16
Categorie Soggetti
Engineering, Chemical","Chemistry Physical
Journal title
ISSN journal
03783812
Volume
113
Issue
1-2
Year of publication
1995
Pages
61 - 77
Database
ISI
SICI code
0378-3812(1995)113:1-2<61:SAAPSA>2.0.ZU;2-2
Abstract
The simplified perturbed hard chain theory (SPHCT) equation of state ( EOS) possesses several attractive features. We have been exploring pos sible modifications to the equation to improve its performance for bot h equilibrium and volumetric property calculations. (In a companion st udy, we have outlined our strategies for modifying the SPHCT EOS.) As a precursor to our study of modifications to the SPHCT EOS, we (a) dev eloped a robust solution algorithm for the SPHCT, (b) established a no vel approach to solving the critical-point constraint equations, and ( c) performed a parameter sensitivity analysis study for the equation, each of which is described in the present work, These results provided valuable guidance to our efforts in modifying the SPHCT EOS, which ar e presented in a companion article. The robust algorithm developed for solution of the SPHCT EOS employs a solution equation written in term s of the compressibility factor. This algorithm exhibits better behavi or near both the liquid and vapor roots than previous solution equatio ns. However, this robust behavior requires increased computation time during parameter regressions. The SPHCT parameter sensitivity analysis shows that the characteristic temperature (T) and the maximum coordi nation number (Z(M)) have very strong influences on calculated vapor p ressures and phase densities. Further, application of the critical con straints yields more stable parameterization than is obtained by utili zing the SPHCT equation in its original form. Simple correlations are presented for solving the critical point constraints. The correlations (a) significantly reduce computational time and complexity and (b) fa cilitate application of the critical point constraints without the nee d to embed complicated numerical routines within existing EOS computer codes.