T = absolute temperature q yi yi,j yiF yiR Superscripts 00 = value at infinite dilution ' = value for solute-free mixture Subscripts s = solvent species = mole fraction of component i in solution = activity coefficient of component i in general = activity coefficient of component i in the ii = factor defined by Equation (34) or (56) = factor defined by Equation (23) = unsymmetric normalization of activity coefficients binary u = solute speciesA new correlation has been developed for the densities of saturated liquids and their mixtures. The correlation is relatively easy to use and is applicable to a wide variety of liquids. The saturated liquid density correlation is flexible and consistent and requires only reduced temperature, acentric factor, and a characteristic volume for each pure compound. Mixing rules are given. When tested against a data base of 2 657 points of pure compound liquid density data for 97 hydrocarbons and 1 851 points for 103 other compounds, the new correlation gave an average absolute error of 0.37% compared to 2.14% for the Yen-Woods correlation and 0.50% for the SDR equation as modified by Spencer and Danner. For 2 994 points of liquid mixture density data for 167 mixtures, the new correlation gave an average absolute error of 1.40% compared to 5.64v0 for the Yen-Woods correlation and 2.95% for the SDR equation. Characteristic volumes are listed for 200 compounds; they are generalized as functions of acentric factor for various types of compounds and are compared to critical volumes. SCOPEThe objective of this work was to develop and extensively test an equation for the computation of saturated liquid densities of pure compounds and their bubble point mixtures that has the following attributes: sufficiently general to apply to a wide range of compound classes, flexible enough to allow accurate calibration to known pure compound data, predictive in those cases where such data are unavailable or of uncertain accuracy, mathemati-cally consistent in that there are no discontinuities in the value or slope in the range 0.25 < T R < 0.98, capable of being calibrated to mixtures for precise work, and simple enough for inclusion in process simulators and on microprocessors. In order to provide extensive testing and evaluation, it was necessary to develop an experimental data base representative of the wide variety of compounds and mixtures of interest. CONCLUSIONS AND SIGNIFICANCEA corresponding states equation which explicitly relates the saturated liquid volume of a pure compound to its reduced temperature and a readily available parameter, termed the characteristic volume, has been developed. The characteristic volumes are reported for 200 pure compounds. An evaluated set of mixing rules is presented.The saturated liquid volumes obtained from the corresponding states liquid density (COSTALD) equation reproduce 4 508 points of experimental data on 190 different compounds to within 0.375 average absolute percent over the reduced temperaturc range of 0.25 < T R < 0.98. For 141 binary systems, 13...

The Tait equation has been extended and generalized to permit the calculation of densities of compressed liquids and their mixtures to a pressure of 68,950 kPa (l0,ooO psia) using only critical temperature, critical pressure, Soave-Redlich-Kwong acentric factor, saturation pressure, and saturated volume for a pure liquid or the corresponding mixture parameters for a liquid mixture. This correlation, together with the correlation developed by Hankinson and Thomson (1979) (1965,1969). In order to achieve acceptable accuracy, the Yen-Woods (1966) correlation requires specific parameters for each compound. The Tait (1888) and Hudleston (1937) equations also lack mixing rules and have generally been used to fit and smooth experimental data.In this work the Tait equation was extended and its parameters were generalized as functions of an acentric factor derived from the Soave-Redlich-Kwong equation of state, critical temperature, and critical pressure. The saturated density and saturation pressure of the liquid which are used in the Tait equation were calculated using the saturated liquid density correlation developed by Hankinson and Thomson (1979) and a generalized vapor pressure equation. The two density correlations together comprise COSTALD, a unified method of estimating saturated and compressed densities of pure liquids and liquid mixtures. CONCLUSIONS AND SIGNIFICANCEThe Tait (1888) equation has been extended to permit accurate prediction of compressed densities of a wide variety of liquids and mixtures for temperatures in the general range of 50 to 600 K and pressures from saturation to 68,950 kPa (l0,ooO psia) using only critical temperature, critical pressure, SRK acentric factor, saturated volume, and saturation pressure for a pure liquid or the corresponding parameters for a mixture.A universal temperature dependence for all nonpolar and slightly polar liquids and mixtures was determined for the constant B in the Tait equation. Both Tait equation constants, B and C , were generalized as functions of the SRK acentric factor. Densities calculated using the extended Tait equation in conjunction with a saturated liquid density equation, COS-TALD (Corresponding STAtes Liquid Density), recently developed by Hankinson and Thomson (1979), were compared with those calculated using the Yen-Woods (1966) method. The data base used for testing consisted of 6,338 density points for pure, nonpolar liquids, 1,352 points for polar and quantum liquids, and 6,926 mixture density points including 319 points for LNG/LPG mixtures.The COSTALD correlation is shown to be the most general and most accurate compressed liquid density correlation yet published. Average absolute errors in densities calculated using COSTALD were 0.446% and 2.57% for pure nonpolar and polar liquids respectively compared to 1.49% and 3.48% errors obtained with the Yen-Woods method. COSTALD gave 0.369% and 1.61% average absolute errors for LNG/LPG mixtures and for all mixtures compared to 1.46% and 2.51% for the YenWoods method.The two parts of the COST...

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DIPPR, a Sponsored Research group of AIChE, has made a significant impact on the chemical process industries by improving thermodynamic and physical property data for process engineering. Participating organizations include chemical and petroleum producers, engineering contractors, software vendors, and government agencies. Projects are proposed and funded by interested DIPPR participants. By involvement of participants, guidance by project sponsors, annual accountability, and dissemination of project results, DIPPR has enjoyed continued success in satisfying industry data needs.

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