Reactor axial distribution

In this paper, TiCU was oxidized in the flow reactor at various temperature and gas flow rate. The wall scales were characterized by scan electron microscopy and X-ray diffraction. The effects of reactor wall surface state, radial growth of scale layer and reactor axial temperature distribution on scaling formation were discussed. At the same time, the mechanism of scaling on the reactor wall was explored furthermore. 

Chemical Kinetics, Tank and Tubular Reactor Fundamentals, Residence Time Distributions, Multiphase Reaction Systems, Basic Reactor Types, Batch Reactor Dynamics, Semi-batch Reactors, Control and Stability of Nonisotheimal Reactors. Complex Reactions with Feeding Strategies, Liquid Phase Tubular Reactors, Gas Phase Tubular Reactors, Axial Dispersion, Unsteady State Tubular Reactor Models... 

Area 300 is controlled using a distributed control system (DCS). The DCS monitors and controls all aspects of the SCWO process, including the ignition system, the reactor pressure, the pressure drop across the transpiring wall, the reactor axial temperature profile, the effluent system, and the evaporation/crystallization system. Each of these control functions is accomplished using a network of pressure, flow, temperature, and analytical sensors linked to control valves through DCS control loops. The measurements of reactor pressure and the pressure differential across the reactor liner are especially important since they determine when shutdowns are needed. Reactor pressure and temperature measurements are important because they can indicate unstable operation that causes incomplete reaction. 

Third, there may be a concentration gradient of reactants and products along the length of the catalyst bed. If the structure of the catalyst depends upon the composition of the gas phase, then an average of the various structures will be measured. There is little discussion of this topic in the literature of XAFS spectroscopy of working catalysts. An extreme example of structural variations within a sample is discussed in Section 6, where there is a discussion of XAFS spatially resolved spectra recorded to allow direct observation of the axial distribution of phases present. If the XAFS data are not measured with spatial resolution, then it is recommended that XAFS data be measured under differential conversion conditions. However, if the aim of the experiment is to relate the catalyst structure directly to that in some industrial catalytic processes, then differential conversion conditions will only reflect the structure of the catalyst at the inlet of the bed. To learn about the structure of the catalyst near the outlet of the bed, the reaction has to be conducted at high conversions. If it is anticipated that this operation will lead to variations in the catalyst structure along the bed, then the feed to the micro-reactor should be one that mimics the concentration of reactants toward the downstream end of the bed (i.e., products should be added to the reactants). 

Axial distribution of kobOb has been shown to have only a minor effect on the performance of fluid catalyst reactors (K14, M28). It has been shown in Section II that (a) bubbles from a single nozzle break up in rising a certain distance to attain a final size (b) bubbles from a perforated plate associate together when rising and (c) stays fairly constant axially thereafter. 

The concept of the successive contact mechanism has been given its simplest form by dividing the fluidized catalyst bed into two parts—dense phase and dilute phase. The concept has been found to apply to bed performance, as shown in the preceding section. The reactor model has been developed on the basis of several simplifying assumptions, partly to retain mathematical simplicity as a workable design equation accounting for the relative effects of the variables, and partly due to a relative lack of information about bed performance. Further properties of the mechanism are examined here, particularly as to axial distribution of reactivity inside the bed. 

In discussing the yield from a reactor, the temperature distribution inside the reactor must be investigated. In the dense phase of fluid beds, the heat-transfer coefiicient between the bed and waU has been widely studied (LIO, MI4, M15, M16, T22, V5, W3, W5). Botterill (B12) has reviewed the recent literature studies of heat transfer in the dilute phase are quite limited in number. Shirai (S9, Sll), Furusaki (F15), and Morooka et al. (M50) studied the heat-transfer coefiicient in the dilute phase as well as in the dense phase. They found that the heat-transfer coefficient between the bed and the wall decreases as the bed density decreases, which will cause an axial distribution of temperature in bed. 

Wang et al. " compared the model predictions to experimental data on the desulfurization of simulated coal gas from a laboratory-scale fixed-bed reactor and from a process development reactor operated on actual coal gas. The solid reactant was formed from cylindrical pellets of zinc and titanium oxides. Data from six experiments using different temperatures, pressures, feed gas flow rates, and feed gas H2S concentrations were available. Product gas concentrations were measured as a function of time, and the axial distribution of sulfur within the reactor was determined at the conclusion of the test. 

Figure 3.2 reports typical radiative flux axial distributions in mW cm for a black-light lamp (BL). The values were obtained using a UVX digital radiometer at 3.1 cm from the reactor axis. 

FIGURE 3.2. Typical BL lamp radiative flux axial distribution at 3.1 cm from the reactor axis. (Reprinted with permission from Ind. Eng. Chein. Res., 40(23), M. Salaices, B. Serrano and H.I. de Lasa, Photocatalytic conversion of organic pollutants Extinction coefiicients and quantum efficiencies, 5455-5464. Copyright 2001 American Chemical Society). 

A reference to this method of operation was made earlier. There are several instances of industrial organic reactions that are bimolecular and exothermic. An important example is the production of chloromethanes. The temperature rise can be controlled by axially distributed addition of chlorine at several discrete points into a packed-bed, fluidized-bed, or empty tube reactor through which methane is passed (Doraiswamy et al., 1975). The membrane is an ideal choice for such reactions because now it can be allowed to permeate over the entire length of the membrane from the shell side into the inner tube or vice versa. 

Knowledge about the mechanism of deposition of corrosion products onto the fuel rod surfaces is still limited. The dissimilar elemental concentrations for the brushed and scraped fractions in the filter/demineralizer plants are probably due to the fact that these two fractions were created by different mechanisms. The brushed fraction most likely results from the deposition of suspended particles from the reactor water, while the scraped fraction is assumed to be formed by precipitation of dissolved corrosion product species. The axial distributions of both fractions of the deposits on the fuel rod surfaces usually show differences which also suggest that they were generated by different mechanisms. The brushed fraction shows a characteristic profile, in which the corrosion products deposit preferentially near the bundle inlet and which can be correlated with the fluid shear at the heat transfer surface. This distribution is consistent with the assumption that particle deposition is the predominant mechanism for the buildup of the loosely-adherent deposits, since low fluid shear favors particle deposition. On the other hand, the axial profile of the tenacious fraction is quite different, being relatively constant over the middle region of the bundle and decreasing towards each end. 

Here, we present the basic idea for the formulation of one-dimensional distributed models for a single-input, single-output, and single-reaction tubular reactor. Axial dispersion is neglected in this preliminary stage then, it will be introduced and discussed later in this chapter. 

The velocity profiles and the axial distribution of volume fraction of solid particles are shown in Fig 4.12. The solid velocity pattern did show a non-axial symmetric behavior. The axial distribution of the solid phase was close to uniform. Figure 4.13 displays the outlet fractions of hydrogen, methane, and CO2 in the gas phase as achieved for the SMR and SE-SMR processes operated in a BFB reactor. In the SMR results, the outlet molar fraction of H2 is only 75 %, thus a considerable amount of CO2 and CH4 are emitted out of the reactor. In the SE-SMR process results, both the conversion of methane and the adsorption of CO2 are larger than 99 %. The simulation results show that the integration of CO2 sorption in the SMR process can enhance the methane conversion to hydrogen to near the equilibrium composition in the BFB reactor. 

Glaser and Litt (G4) have proposed, in an extension of the above study, a model for gas-liquid flow through a b d of porous particles. The bed is assumed to consist of two basic structures which influence the fluid flow patterns (1) Void channels external to the packing, with which are associated dead-ended pockets that can hold stagnant pools of liquid and (2) pore channels and pockets, i.e., continuous and dead-ended pockets in the interior of the particles. On this basis, a theoretical model of liquid-phase dispersion in mixed-phase flow is developed. The model uses three bed parameters for the description of axial dispersion (1) Dispersion due to the mixing of streams from various channels of different residence times (2) dispersion from axial diffusion in the void channels and (3) dispersion from diffusion into the pores. The model is not applicable to turbulent flow nor to such low flow rates that molecular diffusion is comparable to Taylor diffusion. The latter region is unlikely to be of practical interest. The model predicts that the reciprocal Peclet number should be directly proportional to nominal liquid velocity, a prediction that has been confirmed by a few determinations of residence-time distribution for a wax desulfurization pilot reactor of 1-in. diameter packed with 10-14 mesh particles. 

Solution The numerical integration techniques require some care. The inlet to the reactor is usually assumed to have a flat viscosity profile and a parabolic velocity distribution. We would like the numerical integration to reproduce the paraboUc distribution exactly when q, is constant. Otherwise, there will be an initial, fictitious change in at the first axial increment. Define... 

A well-defined bed of particles does not exist in the fast-fluidization regime. Instead, the particles are distributed more or less uniformly throughout the reactor. The two-phase model does not apply. Typically, the cracking reactor is described with a pseudohomogeneous, axial dispersion model. The maximum contact time in such a reactor is quite limited because of the low catalyst densities and high gas velocities that prevail in a fast-fluidized or transport-line reactor. Thus, the reaction must be fast, or low conversions must be acceptable. Also, the catalyst must be quite robust to minimize particle attrition. 

Washout experiments can be used to measure the residence time distribution in continuous-flow systems. A good step change must be made at the reactor inlet. The concentration of tracer molecules leaving the system must be accurately measured at the outlet. If the tracer has a background concentration, it is subtracted from the experimental measurements. The flow properties of the tracer molecules must be similar to those of the reactant molecules. It is usually possible to meet these requirements in practice. The major theoretical requirement is that the inlet and outlet streams have unidirectional flows so that molecules that once enter the system stay in until they exit, never to return. Systems with unidirectional inlet and outlet streams are closed in the sense of the axial dispersion model i.e., Di = D ut = 0- See Sections 9.3.1 and 15.2.2. Most systems of chemical engineering importance are closed to a reasonable approximation. 

Axial Dispersion. Rigorous models for residence time distributions require use of the convective diffusion equation. Equation (14.19). Such solutions, either analytical or numerical, are rather difficult. Example 15.4 solved the simplest possible version of the convective diffusion equation to determine the residence time distribution of a piston flow reactor. The derivation of W t) for parabolic flow was actually equivalent to solving... 

Given k fit) for nny reactor, you automatically have an expression for the fraction unreacted for a first-order reaction with rate constant k. Alternatively, given ttoutik), you also know the Laplace transform of the differential distribution of residence time (e.g., k[f(t)] = exp(—t/t) for a PER). This fact resolves what was long a mystery in chemical engineering science. What is f i) for an open system governed by the axial dispersion model Chapter 9 shows that the conversion in an open system is identical to that of a closed system. Thus, the residence time distributions must be the same. It cannot be directly measured in an open system because time spent outside the system boundaries does not count as residence but does affect the tracer measurements. 

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