Density pseudocomponents

Oxide component proportions, pseudocomponent values, density (d) and mass loss (ML) values for duplicate runs of the simplex centroid mixture design used for studying SiC-based ceramics... 

The results can be seen by going to Components, Petro Characterization, and Results on the Data Browser. Figure 11.15 gives a partial list of the pseudocomponents. Note that each has a normal boiling point, density, molecular weight, and critical properties. 

Fstimate the density distribution of pseudocomponents if only the bulk density is available ... 

Figure 1.5 Comparison of the pseudocomponents generated from constant Watson K factor and density distribution (data obtained from [1]).

We show in previous sections that the minimal amount of information to create pseudocomponents is a distillation curve and a specific gravity or density distribution. If only the bulk density is available, we can use the constant Watson X-Factor assumption to estimate the density distribution. If only a partial density distribution is available, we can use the beta function to extrapolate an incomplete... 

Once we have obtained the boiling point, density or specific gravity, molecular weight and critical properties of a particular pseudocomponent, we can also generate estimates for other required properties for process simulation shown in Table 1.3. The accuracy of these predictions is largely a function of the accuracy of the molecular weight and critical property predictions. In addition, depending on the thermodynamic method chosen, we may not require any correlations for certain properties. For example, if we choose an equation-of state approach, we do not require any additional correlations for the vapor pressure (Pvap) heat of vaporization (AHvap), since these values will be calculated directly by the equation... 

Once we obtain the TBP and density curve, we can cut the components into a number of pseudcomponents. Each of these pseudocomponents has at least a TBP and density, by definition. The number of pseudocomponents for each cut point range can vary depending on the product range of the fractionation system. We have suggested the number of pseudocomponents for a few product ranges in Table 1.2. Subsequent chapters of this text include more information for specific fractionation systems. 

We also select a thermodynamic system to model vapor-hquid equilibrium for these pseudocomponents. For crude fractionation columns, an euqation-of-state (EOS) approach yields good results. However, an EOS approach does not predict liquid densities accurately and tends to give poor equilibrium predictions of heavy pseudocomponents. We can improve the EOS density predictions with more accurate density correlations such as COSTALD. If the feed and products contain significant amounts of heavy products, it may be better to rely on empirical thermodynamic models such as Grayson-Streed or BK-10. 

We define the assay as shown in Figure 2.58. We must define the bulk density and distillation curve at a minimum to qualify the pseudocomponents required for the model. We specify the density from the data in Table 2.14. We can enter the distillation data by selecting the Distillation option in the Input Data . 

However, we must pay more attention to correctly representing the atmospheric residue while using VDU operation and production data to build a VDU model. This follows because the atmospheric residue is an intermediate stream rather than a final product, and a detailed stream analysis is usually not available. Most likely, we can only have the analysis results of the distillation curve below 540 °C and the bulk density of the atmospheric residue. While using commercial simulators to construct the atmospheric residue based on an incomplete feed analysis, the resulting pseudocomponent distribution may not represent atmospheric residue well. 

There are various correlations to estimate pseudocomponent molecular weight based on standard liquid density and TBP. Riazi [37] presents a comprehensive review and comparison of published correlations. 

Figures 6.45 to 6.48 illustrate the specific gravity predictions of liquid products, which are calculated by Aspen HYSYS. The accurate predictions not only reflect the accuracy of the model to predict specific gravity of the liquid product, but also demonstrate that the delumping method described in Section 6.4.5 is able to carry over density distribution to pseudocomponents based on boiling-point ranges.

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