Empirical Estimation Poling

Whenever measured values of diffusivities are available, they should be used. Typically, measurement errors are less than those associated with predictions by empirical or even semitheoretical equations. A few general sources of data are Sec. 2 of this handbook e.g., experimental values for gas mixtures are listed in Table 2-371. Estimation methods for some gaseous applications appear in Eqs. (2-150) through (2-154). Other pertinent references are Schwartzberg and Chao Poling et al. Gammon et al. and Daubert and Danner. Many other more restricted sources are listed under specific topics later in this subsection. 

Estimate It. There are a relatively small number of atomic elements and a much larger but still countable number of molecular species of interest to chemical engineers. Chemical species can be combined into mixtures in an infinite number of ways, however, and it is clearly impossible to tabulate physical property data for even a small fraction of the possible combinations. Moreover, even when data are found they are likely to have been determined for conditions other than the ones for which you need them. Reid, Prausnitz, and Poling summarize a large number of empirical correlations that express physical properties of a mixture in terms of the... 

It often happens that tabulated vapor pressure data are not available at temperatures of interest, or they may not be available at all for a given species. One solution to this problem is to measure p at the desired temperatures. Doing so is not always convenient, however, especially if a highly precise value is not required. An alternative is to estimate the vapor pressure using an empirical correlation for p" T). Reid, Prausnitz, and Poling summarize and compare vapor pressure estimation methods, several of which are given in the paragraphs that follow. 

If no material values can be found in the literature, which is often the case for binary and ternary data, they should initially be estimated by using empirical formulas or realistic values [Sandler 1999, Poling 2001]. 

The methods used to estimate gas mixture thermal conductivity are less accurate as compared to empirical data than those used to estimate gas mixture viscosity. Thermal conductivity is more susceptible to variations in the size of the molecules, variations in mass, concentration dependence, and temperature dependence (Singh, Dham, and Gupta, 1992). Additionally, the kinetic theory assumes a single average of the mean molecular velocities deviations from actual thermal conductivity may be accounted for in the wide spectrum of molecular velocities in a mixture (Poling, Prausnitz, and O Connell, 2001). Therefore, there is a greater expected error in HeXe gas mixture thermal conductivities than in gas mixture viscosities. 

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