Reactor behavior, simulation

In the following sections we describe simulation results providing new Insights Into general MOCVD reactor behavior as well as the two major practical considerations, film uniformity and Interface width. 

In many respects, the solutions to equations 12.7.38 and 12.7.47 do not provide sufficient additional information to warrant their use in design calculations. It has been clearly demonstrated that for the fluid velocities used in industrial practice, the influence of axial dispersion of both heat and mass on the conversion achieved is negligible provided that the packing depth is in excess of 100 pellet diameters (109). Such shallow beds are only employed as the first stage of multibed adiabatic reactors. There is some question as to whether or not such short beds can be adequately described by an effective transport model. Thus for most preliminary design calculations, the simplified one-dimensional model discussed earlier is preferred. The discrepancies between model simulations and actual reactor behavior are not resolved by the inclusion of longitudinal dispersion terms. Their effects are small compared to the influence of radial gradients in temperature and composition. Consequently, for more accurate simulations, we employ a two-dimensional model (Section 12.7.2.2). 

As many other industries, the fine chemical industry is characterized by strong pressures to decrease the time-to-market. New methods for the early screening of chemical reaction kinetics are needed (Heinzle and Hungerbiihler, 1997). Based on the data elaborated, the digital simulation of the chemical reactors is possible. The design of optimal feeding profiles to maximize predefined profit functions and the related assessment of critical reactor behavior is thus possible, as seen in the simulation examples RUN and SELCONT. 

In a first step this control algorithem was tested by a simulation of the whole circuittaking into consideration reactor behavior,reaction rate equation. discontinuous analysis. analytical errors and control-strategy. 

It should be noted that if a differential mass, energy and electron balance approach were followed to describe the reactor s behavior one would obtain a set of non-linear, partial, integro-differential equations. However, since the reactor is simulated by a two-dimensional array of mixing cells, a large number of algebraic equations result in which there are no differentials and in which double integrals are replaced by double summations. 

At present there is no systematic work on simulation and design of packed bed nonadiabatic reactors of industrial size where a deactivation process occurs. The purpose of this work is to analyze the operation of a nonadiabatic deactivating catalyst bed and to develop simple techniques for simulation. Based on hydrogenation of benzene,full-scale reactor behavior is calcu lated for a number of different operational conditions. Radial transport processes are incorporated in the model, and it is shown that the two-dimensional model is necessary in some cases. 

A plot of E 6) versus 0 is shown in Figure 8.4.2 for various amounts of dispersion. Notice that as Pea oo (no dispersion), the behavior is that of a PER while as PCa- Q (maximum dispersion), it is that of a CSTR. Thus, the axially-dispersed reactor can simulate all types of behaviors between the ideal limits of no back-mixing (PFR) and complete backmixing (CSTR). 

Fig. 6. Behavior of De-NOx flow reversal reactor. (Computer simulation based on model SCR reaction kinetics). (I, , , ), (2,2 ,2 ,2 ) and (3,3 ,3 ,3 ) temperature, gas phase ammonia concentration, ammonia coverage, and NOx conversion profiles at the beginning, middle and end of flow reversal period.

Two dimensional models permit more realistic simulation of fixed bed reactor behavior than the one-dimensional models discussed previously. Experimental measurements indicate that the fluid temperature and composition are not uniform across a section of the tube normal to the flow. The one dimensional models discussed earlier neglect the radial resistance to heat and mass transfer and thereby assume a uniform temperature and composition for each longitudinal position. This assumption is a vast oversimplification when... 

Both configurations are described in the following paragraphs. MR is then modeled and simulated to assess the effects of operating conditions on reactor behavior, while for a description of a real RMM installation refer to Chap. 10. 

Baiker, A., and Bergougnan, M. Investigation of a fixed-bed pilot plant reactor by dynamic experimentation. Part 2. Simulation of reactor behavior. Can. J. Chem. Eng. 63(1), 146-154, 1985. 

Axial dispersion and wall effects in narrow fixed beds with aspect ratios < 10 were investigated, both by classical methods and by NMR imaging." The residence time distribution (RTD) in the center and at the wall was measured by using water/NaCl-soln. as tracer, and subsequently compared with radial velocity profiles based on NMR imaging. The effects of the aspect ratio and particle Reynolds number on dispersion and on the degree of nonuniformity of the velocity profile were studied. The NMR results are consistent with the RTD and also with literature data of numerical simulations. For low aspect ratios, dispersion/wall effects have a strong effect on the reactor behavior, above all, in cases where a low effluent concentration is essential, as proven by breakthrough experiments with the reaction of H2S with ZnO. 

The design, analysis, and simulation of reactors thus becomes an integral part of the bioengineering profession. The study of chemical kinetics, particularly when coupled with complex physical phenomena, such as the transport of heat, mass, and momentum, is required to determine or predict reactor performance. It thus becomes imperative to uncouple and unmask the fundamental phenomenological events in reactors and to subsequently incorporate them in a concerted manner to meet the objectives of specific applications. This need further emphasizes the role played by the physical aspects of reactor behavior in the stabUity and controUabifity of the entire process. The foUowing chapters in this section demonstrate the importance of aU the concepts presented in this introduction. 

Chapter 8 is dedicated to the modeling of heavy oil upgrading via hydroprocessing. Experimental studies for generation of kinetic data, catalyst deactivation, and long-term stability test are explained. Mass and heat balance equations are provided for the reactor modeling for steady-state and dynamic behavior. Simulations of bench-scale reactor and commercial reactor for different situations are also reported. 

The objectives of this presentation are to discuss the general behavior of non isothermal chain-addition polymerizations and copolymerizations and to propose dimensionless criteria for estimating non isothermal reactor performance, in particular thermal runaway and instability, and its effect upon polymer properties. Most of the results presented are based upon work (i"8), both theoretical and experimental, conducted in the author s laboratories at Stevens Institute of Technology. Analytical methods include a Semenov-type theoretical approach (1,2,9) as well as computer simulations similar to those used by Barkelew LS) ... 

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