Physical properties pseudocomponents

The previous sections in this chapter address the creation of pseudocomponents by cutting an assay curve into a set of discrete components based on boiling-point ranges. We also briefly alluded to physical properties and process thermodynamics selection in the earlier workshops of this chapter. In this section, we consider, in detail, the problem of how to represent these components in the process modeling software. There are two major concerns in this area physical properties of pseudocomponents and selection of a thermodynamic system that can deal with these hydrocarbon pseudocomponents in the context of refinery modeling. 

The vapor pressure of pseudocomponents is also an important property when an equation-of-state approach is not used. All other approaches to process thermo-dynamics require some form of vapor-pressure correlation. The vapor pressure for pure hydrocarbons has been extensively tabulated in many component databases such as DIPPR (Design Institute for Physical Property Research, American Institute of Chemical Engineers) and significant libraries are available in modern process modeling software. Several correlations are available in the literature for the vapor pressure of pseudocomponents. It is important to recall that the vapor pressure and heat vaporization are related through the Clausius-Clapeyron [17] Equation (Equation (1-46)). This relationship imposes a constraint if we wish the model to be thermodynamically consistent In general, most of the popular correlations for vapor pressure such as the Lee-Kesler [9,10] agree well with heat of vaporization correlations and maintain thermodynamic consistency. We present the Lee-Kesler vapor pressure correlation in Equation (1.47). 

While this chapter has focused extensively on the requirements for modeling fractionation systems, we can use the same techniques in the context of modeling refinery reaction process as well. We illustrate this process in Chapters 4 through 6 of this text It is possible to obtain good predictive results for fractionation systems provided that we make reasonable choices for the thermodynamic models and physical properties of the pseudocomponents involved. 

For any process simulation that involves only vapor-liquid phases, certain key physical and thermodynamic properties must be available for each phase. Table 1.3 lists these properties for all phases. We can typically obtain these properties for pure components (i.e. n-hexane, n-heptane, etc.) from widely available databases such as DIPPR [2]. Commercial process simulation software (including Aspen HYSYS) also provides a large set of physical and thermodynamic properties for a large number of pure components. However, using these databases requires us to identify a component by name and molecular structure first, and use experimentally measured or estimated values from the same databases. Given the complexity of crude feed, it is not possible to completely analyze the crude feed in terms of pure components. Therefore, we must be able to estimate these properties for each pseudocomponent based on certain measured descriptors. 

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