Micromixing influence

Li, xi and Chen, Gantang (1993). Study on the problem of micromixing Influence of mixing on the processes of rapid parallel reactions. Chem. Reaction Eng. Technologies, 9(4) 377-384 (in Chinese). 

In what follows, both macromixing and micromixing models will be introduced and a compartmental mixing model, the segregated feed model (SFM), will be discussed in detail. It will be used in Chapter 8 to model the influence of the hydrodynamics on a meso- and microscale on continuous and semibatch precipitation where using CFD, diffusive and convective mixing parameters in the reactor are determined. 

Using the SFM, the influence of micromixing and mesomixing on the precipitation process and properties of the precipitate can be investigated. Mass and population balances can be applied to the individual compartments and to the overall reactor accounting for different levels of supersaturation in different zones of the reactor. 

The failure of conventional criteria may be due to the fact that it is not only one mixing process which can be limiting, rather for example an interplay of micromixing and mesomixing can influence the kinetic rates. Thus, by scaling up with constant micromixing times on different scales, the mesomixing times cannot be kept constant but will differ, and consequently the precipitation rates (e.g. nucleation rates) will tend to deviate with scale-up. 

A qualitative analysis for influences of strong micromixing and fluctuation... 

Establishing the process sensitivity with respect to the above-mentioned factors is crucial for further scale-up considerations. If the sensitivity is low, a direct volume scale-up is allowed and the use of standard batch reactor configurations is permitted. However, many reactions are characterized by a large thermal effect and many molecules are very sensitive to process conditions on molecular scale (pH, temperature, concentrations, etc.). Such processes are much more difficult to scale up. Mixing can then become a very important factor influencing reactor performance for reactions where mixing times and reaction times are comparable, micromixing also becomes important. 

Note that we have used the fluid velocity U to describe convection of particles, which is valid for small Stokes number. In most practical applications, / is a highly nonlinear function of c. Thus, in a turbulent flow the average nucleation rate will depend strongly on the local micromixing conditions. In contrast, the growth rate G is often weakly nonlinear and therefore less influenced by turbulent mixing. 

Finally, we note that Dudukovic has shown that, for isothermal reactors, the degree of micromixing can significantly influence the appearance of multiple steady-state operating conditions, this being particularly likely for kinetic mechanisms which display maximum reaction rates at intermediate concentration levels [38, 39]. 

Figure 10.13 Influence of impinging velocity on micromixing time at oe=] 5...

Similar to the case of the investigation on micromixing, the impinging velocity cannot be adjusted and controlled directly, but is done by changing the rotary speed of the propellers, N. Prior to all the measurements the curve describing the relationship between (> and N was calibrated with the same method as that used in Ref. [110], and the results are shown in Fig. 11.2, in which the curve is, in turn, used for conversion between the rotary speed and the impinging velocity in the data treatment. The curve in Fig. 11.2 is essentially the same as that shown in Fig. 10.9 but with some differences in specific data. The existence of such differences is natural, because the shape of the propeller paddle and particularly the width of the gap between the paddle of the propeller and the drawing tube have a fundamental influence on the flow rate drawn by the propeller, while errors in mechanical manufacture are also unavoidable.. 

The pressure fluctuation must affect the condition of the micromixing in the device and thus promote process kinetics. The results to be introduced in the next chapter will provide the experimental evidence for this topic. Unfortunately, a quantitative description for such influences cannot as yet be made because of the complexity of the problems involved, and further investigations are certainly needed in order to make the relationships clear, particularly the influence of pressure fluctuation on micromixing. 

QUALITATIVE ANALYSIS FOR THE INFLUENCES OF PRESSURE FLUCTUATION AND MICROMIXING... 

Influences of micromixing and pressure fluctuation What are the mechanisms of their effects How can direct experimental evidence be obtained for these effects How can these influences be quantitatively described How can their individual contributions to the global influence be determined ... 

The effect of coalescence and break-up of droplets on the yield of chemical reactions was studied by Villermaux (33). Micromixing effects may occur even in batch reactors if there is a drop size distribution and mass-transfer control. Although practical rules for the design and scale-up of liquid-liquid reactors are available as Oldshue showed in the case of alkylation (152), many problems remain unsolved (.5) mass transfer effects, high hold-up fractions (> 20 %), large density differences, high viscosities, influence of surfactants. 

Figure 14 shows a plot of the Dispersion Index DI = Mw/M wersus the conversion X of the monomer for segregated flow (S) and well micromixed flow (M). The dramatic influence of segregation can be noticed at high conversion, especially with transfer to polymer. Moreover, an interesting effect is observed with diluted and slow initiators, namely an inversion of the relative position of S and M curves when the transfer constant ktp is increased. 

Figure 15. Effect of segregation on polymerization of styrene in cyclohexane solution. Standard CSTR with h baffles and a 6-blade turbine, V = 670 cm, T = 75 °C. Dispersion Index DI vs. space time. Influence of agitation speed. Curves S (segregated flow) and M (well-micromixed flow) calculated from batch experiments. Initiator PERKAD0X l6, A = 0.033 mol L - -, kd = 5 x 10 5 s-1, f = 0.85 Mq = 6.65 mol L l, SQ = 2.22 mol IT1.

Fio. 19. Influence of micromixing and mass transfer limitations on the yield of competitive-consecutive reactions (of which one reaction is homogeneous and the other is wall-catalyzed) in a tubular reactor. 

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