Chemical type lumps

The next class of kinetic models considers both chemical type lumps and boiling-point or yield lumps. For example, Jacob etal. [13] present a popular 10-lump model (shown in Figure 4.5) that includes coke and light ends (C), gasoline (G, C5 - 221 °C), light paraffin Pj heavy paraffin P, light naphthene Nj heavy... 

When a very large number of reactants occurs, as in the treatment of petroleum fractions with a virtually continuous spectrum of boiling points, the problem is made more tractable by lumping the composition. The lumps are made up of pseudo components with limited boiling ranges and of partcular chemical types such as aromatics, paraffins, naphthenes, olefins and so on. 

The key advantage of this lumped kinetic model is that the composition of lumps can be measured with various experimental techniques. In addition, the rate constants that arise from using this model are less sensitive to changes in feed and process conditions [14], This model has served as the basis for models that include more chemical types. Pitault et al. [15,16] have developed a 19-lump model that includes several olefin lumps. AspenTech [17,18] has developed a 21-lump model to address heavier and more aromatic feeds, which we will use to model reaction section of the FCC unit. We discuss this 21-lump model in a subsequent section. 

Figure 4.7 compares these kinetic models on the basis ofcomplexity and model fidelity. The yield lump models have the lowest complexity and require the least amount of data. Typically, the feed may be treated as a single lump and there are few reaction rates to calibrate. Chemical lumps require knowledge of chemical type of the lump, namely, the paraffin, naphthene and aromatic (PNA) content of each boiling-point range. Pathway and mechanishc models require the detailed analysis of the feed data to develop molecular representation. Additionally, pathway and mechanistic models require more data to calibrate the numerous kinetic parameters [6]. 

Fluxing lime is lump or pebble quicklime used as flux in steel (qv) manufacture the term may also be appHed more broadly to include fluxing of nonferrous metals and glass (qv). It is a type of chemical lime. 

Three different types of chemical mechanisms have evolved as attempts to simplify organic atmospheric chemistry surrogate (58,59), lumped (60—63), and carbon bond (64—66). These mechanisms were developed primarily to study the formation of and NO2 in photochemical smog, but can be extended to compute the concentrations of other pollutants, such as those leading to acid deposition (40,42). 

Material characteristics, both chemical and physical, should be considered, especially flowabihty. Abrasiveness, friability, and lump size are also important. Chemical effects (e.g., the effect of oil on rubber or of acids on metal) may dictate the structural materials out of which conveyor components are fabricated. Moisture or oxidation effects from exposure to the atmosphere may be harmful to the material being conveyed and require total enclosure of the conveyor or even an artificial atmosphere. Obviously, certain types of conveyors lend themselves to such special requirements better than others. 

Spaced-Bucket Centrifugal-Discharge Elevators These elevators (Fig. 21-5<7) are the most common. They are usually equipped with the style 1 or 2 buckets shown in Fig. 21-5/j. Mounted on a Belt or a chain, the buckets are spaced to prevent interference in loading or discharging. This type oi elevator will handle almost any free-flowing fine or small-lump material such as erain, coal, or dry chemicals. Buckets are loaded partly by material flowing directly into them... 

The quantitative estimation of species by SEC-GC-MS technique requires a mathematical solution. Two types of approaches for the quantitative estimation can be envisioned. One for the estimation of one or more selected species of interest. The second approach is based on grouping of various species in coal liquids into a few chemical lumps and estimating the quantity of these lumps by using the data derived from the analysis is technique. 

A distributed model is usually described by differential equations. Such a model differs from a lumped model that is generally described by transcendental equations. In chemical and biological engineering distributed systems often arise with tubular equipment. When a one-dimensional model is used for a distributed system there are two types of models ... 

Four types of REY zeolite (Si/Al = 4.8) with different crystal sizes and acidic properties were used. The physical and chemical properties of the fresh zeolites are given in Table 6.4. Polyethylene plastics-derived heavy oil, shown in Table 6.2, was used as the feed oil. The cracking reaction was conducted in a tubular reactor filled with catalyst particles under the following conditions time factor W/F = 0.2-3.0 kg-catkg oil h and reaction temperature = 300-450°C. The lumping of reaction products were gas (carbon number 1-4), gasoline (5-11), heavy oil (above 12), and a carbonaceous residue referred to as coke. The index of the gasoline quality used was the research octane number (RON), which was calculated from Equation 6.1 [31]. 

So far these processes have been modeled in terms of lumps. In catalytic cracking the 3-lump -and the 10-lump model [Nace et al, 1971 Jacob et al, 1976] are still widely used although the lumps are based on boiling ranges rather than on chemical nature. These models contain in general only one deactivation function of an empirical nature for the reactions of the various lumps, b their study of the catalytic cracking of n-hexane on a US-Y-zeolite in an electrobalance with recycle Beimaert et al, [1994] derived an empirical deactivation function of the type (2) for the various reactions, but with different a-values, as illustrated in Table 2 for the isomerizations. 

Dynamic simulations represent the temporal and the spatial behavior of a chemical process unit in the presence of perturbations or at process startup. There is a natural division in the types of numerical methods used to solve the equations describing the dynamic behavior of the process. In lumped parameter descriptions of the process units, the resulting equations are ordinary time evolution differential equations, whereas for distributed parameter descriptions of process units the resulting equations are parabolic partial differential equations. The numerical methods used to solve these equations are very different and necessitate a separate discussion. Numerical methods used to solve ordinary differential equations describing the dynamics are considered first followed by a discussion of the methods employed to solve evolution equations of the parabolic type. 

A target reaction is essential. This is easiest with chemical processes since the critical reaction i easily identified. With petroleum and other fuel processes, so many reactions exist that some degree of lumping into reaction types, perhaps with model compounds. Is necessary. 

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