Deactivation kinetic model

A realistic selective deactivation kinetic model should use a different aj-t relationship to describe the evolution with time-on-stream of each cracking reaction. Therefore, several values of Vj dj should be known and used. This approach would introduce too many... 

A realistic selective deactivation kinetic model should use a different aj-t relationship to describe the evolution with time-on-stream of each cracking reaction. Therefore, several values of yj and dj should be known and used. This approach would introduce too many parameters in the control model of the riser or of the overall FCCU For this reason (attd until more basic research and verification can be done on this subject) we will use here a non-selective deactivation model with only one a-t kinetic equation and only one value each for V and d. Since in principle this is not correct (21) the predicted (using this non-sclectivc deactivation model) product distribution at the riser exit (the gasoline yield mainly) will differ somewhat from the real one (20). 

The selection of the more suitable deactivation kinetic model and the calculation of the kinetic parameters have been carried out by minimizing the following error objective function ... 

Only a minority of reports in homogeneous, specifically homogeneous transition metal catalysis, deals with deactivation. Kinetic models for a simple case of inhibition, with siphoning off catalytic material from the active cycle into an external pathway, were considered in Section 5.4.2. The examples in Chapter 5 considered reversible inactivation and the off-cycle step could be essentially considered as a hanging vertex. 

A kinetic model which accounts for a multiplicity of active centres on supported catalysts has recently been developed. Computer simulations have been used to mechanistically validate the model and examine the effects on Its parameters by varying the nature of the distrlbultons, the order of deactivation, and the number of site types. The model adequately represents both first and second order deactivating polymerizations. Simulation results have been used to assist the interpretation of experimental results for the MgCl /EB/TlCl /TEA catalyst suggesting that... 

Evaluation of F(x) for Second Order Deactivation. As mentioned earlier for the case of second order decay F(x) cannot be derived analytically, however numerical calculation of F(x) or Its evaluation from simulated rate data Indicates that the function defined In Equation 11 provides an excellent approximation. This was also confirmed by the good fit of model form 12 to simulated polymerization data with second order deactivation. Thus for second order deactivation kinetics the rate expression Is Identical to Equation 12 but with 0 replacing 02. 

Computer simulations have been useful for validating a kinetic model that Is not easily tested. The model was equally capable of describing multi-site polymerizations which can undergo either first or second order deactivation. The model parameters provided reasonably accurate kinetic information about the Initial active site distribution. Simulation results were also used as aids for Interpretation of experimental data with encouraging results. 

Thus it is important to obtain reliable models for catalyst deactivation and to investigate, whether it is possible to decouple the deactivation model from the kinetic model or if it is necessary to treat the catalyst deactivation as one of the surface reactions on the catalyst [45]. 

The rigorous kinetic modeling with the incorporation of the diffusion step allows explaining the deactivation of the carbon filament growth and the influence of the affinity for carbon formation on the nucleation of the filamentous carbon. 

One can and should enquire about the time-scale of the spectroscopic measurements and the reaction time-scales. In general, there will be a few observable species i. e. organometallics, associated with the induction kinetics, and the deactivation kinetics. Therefore, the kinetic time-scales are similar to the half-lives of these species. If is short compared to the half-lives of these species, both the induction and deactivation kinetics can be modeled accurately. 

The model includes fundamental hydrocarbon conversion kinetics developed on fresh catalysts (referred to as start-of-cycle kinetics) and also the fundamental relationships that modify the fresh-catalyst kinetics to account for the complex effects of catalyst aging (deactivation kinetics). The successful development of this model was accomplished by reducing the problem complexity. The key was to properly define lumped chemical species and a minimum number of chemical reaction pathways between these lumps. A thorough understanding of the chemistry, thermodynamics, and catalyst... 

In this chapter the following topics will be reviewed KINPTR s start-of-cycle and deactivation kinetics, the overall program structure of KINPTR, the rationale for the kinetic lumping schemes, the model s accuracy, and examples of KINPTR use within Mobil. As an example, the detailed kinetics for the C6 hydrocarbons are provided. 

While the 13 hydrocarbon lumps accurately represent the hydrocarbon conversion kinetics, they must be delumped for the deactivation kinetics. In addition, delumping is necessary to estimate many of the product properties and process conditions important to an effective reformer process model. These include H2 consumption, recycle gas H2 purity, and key reformate properties such as octane number and vapor pressure. The following three lump types had to be delumped the C5- kinetic lump into Cl to C5 light gas components, the paraffin kinetic lumps into isoparaffin and n-paraffin components, and the Cg+ kinetic lumps into Cg, C9, C10, and Cn components by molecular type. 

The gradual loss of catalytic activity adds more to the existing complexity of catalytic systems. Thus, it has to be taken into account during the modeling of such systems. During the presentation of each deactivation mechanism, some kinetic models were given. Here, the... 

Kodama et al. (1980) developed a detailed HDS and HDM model for deactivation of pellets and reactor beds. The model included reversible kinetics for coke formation, which contributed to loss of porosity. Second-order kinetics were used to describe both HDM and HDS reaction rates, and diffusivities were adjusted on the basis of contaminant volume in the pores. The model accurately traced the history of a reactor undergoing deactivation. This model, however, contains many parameters and is thus more correlative than theoretical or discriminating. 

Thus, when constructing a kinetic model for the synthesis of vinyl chloride on the "HgCl-coal catalyst, the following postulates were used (a) the type of the kinetic equations is independent of the concentration of the active salts (b) changes in the catalyst activity in any case (mercuric chloride deactivation, removal, etc.) can be treated simply as changes in the active salt concentration [77]. 

The first two schemes correspond to cases when coke precursors arise from intermediates appearing before the slow surface step, while schemes (2c) and (2d) model the formation of blocking agents out of intermediates generated beyond the limiting step. Each of these mechanisms may bring to specific pecularities of the deactivation kinetics, depending on the power... 

This simple analysis is semi empirical it is not a description of the diffusion limited reaction within the crystals but allows one to take into account both phenomena, in order to provide kinetic models for FCC reactor description [11]. Experimental results on the three feedstocks are shown in figure 1, with the deactivation function determined according to the method described in [10]. Curves are calculated from equation (3) after fitting E and F. These values are reported in table 2. 

The results show that the specificities of catalyst deactivation and it s kinetic description are in closed connection with reaction kinetics of main process and they form a common kinetic model. The kinetic nature of promotor action in platinum catalysts side by side with other physicochemical research follows from this studies as well. It is concern the increase of slow step rate, the decrease of side processes (including coke formation) rate and the acceleration of coke transformation into methane owing to the increase of hydrogen contents in coke. The obtained data can be united by common kinetic model.lt is desirable to solve some problems in describing the catalyst deactivation such as the consideration of coke distribution between surfaces of metal, promoter and the carrier in the course of reactions, diffusion effects etc,. 

The kinetic and deactivation models were fitted by non-linear regression analysis against the experimental data using the Modest software, especially designed for the various tasks -simulations, parameter estimation, sensitivity analysis, optimal design of experiments, performance optimization - encountered in mathematical modelling [6], The main interest was to describe the epoxide conversion. The kinetic model could explain the data as can be seen in Fig. 1 and 2, which represent the data sets obtained at 70 °C and 75°C, respectively. The model could also explain the data for hydrogenated alkyltetrahydroanthraquinone. 

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