FCC Models

A special group of particles that are often produced are the icosahedral (I5) and decahedral (D5) structures shown in Fig. 9. These particles have a fivefold symetry axis which is forbidden for infinite crystals. Yang (1 0) has described these particles using a non-Fcc model. The particles are composed by five (D5) and twenty (I5) tetrahedral units in twin relationship. However the units have a non-Fcc structure. The decahedral is composed by body-centered orthorhombic units and the icosahedral by rhombohedral... 

In Fig. 10 the micro-diffraction patterns of I5 and D5 particles are shown. These patterns are identical to the ones calculated by Yang et al. (1 1) based on the non-Fcc model. This type of particles is a very important example of departures from the Fee bulk symmetry. In addition is also an example of pol i hedral particles formed by several units. 

The major advantage of the prepared neural network FCC model is that it does not require a lot of input information. In addition, the model can be updated whenever new input-output information for the FCC unit is made available. This can be done by retraining the neural network starting from the old connection weights as an initial guess for the optimization process and by including the new set of data within the overall set used to train the network. 

Not listed in Table 6.4 of possible unit modifications are improved unit controls. These can be applied in many ways to both the reactor/regenerator and gas plant. Operating closer to limits increases revenue by forcing the operation to several limits rather than one or two. A good FCC model is needed if all the benefits are to be realized. 

Based on these kinetic relations and using the simple two-phase model for bubbling fluidized beds, the FCC model equations for the steady states of the unit can be given in dimensionless form as follows ... 

Saraf, A. V., Silerman, M. A., and Ross, J. L. FCC Modeling Based on Advanced Feed Characterization Techniques, in Circulating Fluidized Bed Technology IV (Amos A. Avidan, ed.), pp. 559-564. Somerset, Pennsylvania (1993). 

Li and Rabitz" used the above approach to further contract the well-known 10-lump FCC model to a five-lump model with essentially the same predictive power for product slate changes. Moreover, if gasoline is the only unlumped species, then three lumps suffice. For nonane reforming, this approach reduces the number of liunps from 14 to 5 without significant errors if the total aromatics is kept imliunped. ... 

In another approach to modeling the effects of FCC feed pretreating, the FCC model receives a blend of hydrotreated feed from AHYC with straight-run feed from a tank model. The latter case is discussed here. 

There is significant previous work that addresses the issues of process dynamics and control for the integrated FCC unit We particularly note the efforts by Arbel et al. [2] and McFarlane et al. [3] in this regard. Subsequent authors [4, 5] use similar techniques and models to identify control schemes and yield behavior. However, most of the earlier work uses a very simplified reaction chemistry (yield model) to represent the process kinetics. In addition, prior work in the literamre (to our knowledge) does not connect the integrated FCC model with the complex FCC fractionation system. This work fills the gap between the development of a rigorous kinetic model and industrial apphcation in a large-scale refinery. 

We can divide the literature on FCC modeling into two categories kinetic and unit-level models. Kinetic models focus on chemical reactions taking place within the riser or reactor section of the FCC unit, and attempt to quantify the feed as a mixture of chemical entities to describe the rate of reaction from one chemical entity to another. In contrast, unit-level models contain several submodels to take into account the integrated nature of modem FCC units. A basic unit-level model contains submodels for the riser/reactor, regenerator and catalyst transfer sections. 

Table 4.2 Survey of related published literature for integrated FCC modeling. 

Aspen HYSYS Petroleum Refining FCC Model 159 Table 4.3 Required submodels for a basic simulation of a complete FCC unit. 

The Aspen HY SYS Petroleum Refining FCC model relies on a series of submodels that can simulate an entire operating unit while satisfying the riser and regenerator heat balance. Note that the configuration is similar to the minimum submodels listed in Table 4.3 of the previous section. We summarize Aspen HYSYS Petroleum Refining submodels in Table 4.4 and highlight some key features in subsequent sections. 

Aspen HYSYS Petroleum Refining FCC Model 163 Table 4.5 Summary of 21-lump kinetics (adapted from [6]). 

Calibrating the Aspen HYSYS Petroleum Refining FCC Model... 

Given the variety of feedstock that the FCC unit processes, it is unlikely that a single set of kinetic parameters will provide accurate and industrially useful yield and property predictions. In addition, changes in catalyst may significantly alter the yield distribution. Therefore, it is necessary to calibrate the model to a base scenario. Table 4.6 lists the key calibration parameters for the FCC model. We group them by their effects on the model predictions. 

Aspen HYSYS Petroleum Refining includes a method to convert limited feed information (distillation curve, density, viscosity, refractive index, etc.) into kinetic lumps for use in the unit-level FCC model. In this section, we present an alternative method based on data and methods available in the public literature. We extend the work by Bollas et al. [52] to infer the kinetic lump composition from limited process data. This method uses techniques to normalize the distillation curve, cut the distillation curve into boiling-point lumps, and infer the composition of the each of these boiling-point lumps. We have developed all of these techniques into spreadsheets using Microsoft Excel. These spreadsheets are available in the DVD accompanying this text... 

We overcome these problems by using the detailed FCC model developed in this work. We have shown that the FCC model can predict yields accurately for varying process conditions. To apply the FCC model into the refinery LP, we must first convert the large non-linear model in to a linear yield model. We can then use the coefficients from this generated linear yield model directly in the LP for the refinery. We show the process for generating the hnear yield coefficients in Figure 4.36. We have found that 4—5% is a reasonable value for CHANGE% (variable perturbation) for most of the important feed attributes in the FCC process. 

Table 4.20 to Table 4.23 give detailed feeds, products and operation data for a typical UOP FCC process. Values that have been estimated are marked with a. We extensively discussed methods to eshmate required properties for FCC modeling in Chapter 1. Operating conditions for the frachonation section largely depend on the FCC unit effluent and are relahvely stahc, so they are not given here. 

The first step in creating the model is the selection of a standard set of components and a thermodynamic basis to model the physical properties of these components. When we create a new simulation, we must choose the components and thermodynamics appropriate for the process using the Simulation Basis Manager. The Simrdation Basis Manager allows us to define components and associated thermodynamics in Aspen HYSYS. Components maybe added manually through the Add button shown in Figure 4.41. However, we have a predetermined set of components for the FCC model. 

Once we import a component list, HYSYS will create a new component list called Component List-1 . We can view the elements of this component lists by selecting Component llst-l and clicking on View in the Simulation Basis Manager (Figure 4.43). We can add additional components or modify the order of the elements in the component list We note drat the standard FCC component list is quite complete and model most refining processes. The rigorous FCC model does not predict components that are not part of the petroleumCompl. cml list. However, these additional components may be used in production fractionation models ofthe associated with the FCC model. For the purposes of this simulation, we will add cis-2-butene and benzene. 

The FCC system is mostly hypothetical and light hydrocarbons. Consequently, the Peng-Robinson equation of state is sufficient. We discuss the implications of the process thermodynamics in Chapter 1. In the case of the FCC model, equation of state or hydrocarbon correlation methods (Grayson-Streed, etc.) can sufficiently model the processs. 

The initial flowsheet presents a blank interface where we can place different objects from the Object palette shown in Figure 4.48. The initial tool palette only shows typical unit operations anddoesnot show the advanced Aspen HYSYS Petroleum Refining objects. We will use both toolbars to build the complete FCC model. We can bring up the advanced palette by pressing F6. 

The solver indicates the vicinity of the solution through columns 5 and 6. The Worst Model column indicates which part of the FCC model is furthest from the solution. This is useful for tracking down issues when the model fails to converge. 

In general, the FCC model should converge within 20 seconds on recent computer hardware. If solution requires more than 20 seconds, it is likely that one or more specifications conflict... 

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