Residence reactor performance

The distribution of residence times of reactants or tracers in a flow vessel, the RTD, is a key datum for determining reactor performance, either the expected conversion or the range in which the conversion must fall. In this section it is shown how tracer tests may be used to estabhsh how nearly a particular vessel approaches some standard ideal behavior, or what its efficiency is. The most useful comparisons are with complete mixing and with plug flow. A glossary of special terms is given in Table 23-3, and major relations of tracer response functions are shown in Table 23-4. 

If the pilot reactor is turbulent and closely approximates piston flow, the larger unit will as well. In isothermal piston flow, reactor performance is determined by the feed composition, feed temperature, and the mean residence time in the reactor. Even when piston flow is a poor approximation, these parameters are rarely, if ever, varied in the scaleup of a tubular reactor. The scaleup factor for throughput is S. To keep t constant, the inventory of mass in the system must also scale as S. When the fluid is incompressible, the volume scales with S. The general case allows the number of tubes, the tube radius, and the tube length to be changed upon scaleup ... 

When the residence time distribution is known, the uncertainty about reactor performance is greatly reduced. A real system must lie somewhere along a vertical line in Figure 15.14. The upper point on this line corresponds to maximum mixedness and usually provides one bound limit on reactor performance. Whether it is an upper or lower bound depends on the reaction mechanism. The lower point on the line corresponds to complete segregation and provides the opposite bound on reactor performance. The complete segregation limit can be calculated from Equation (15.48). The maximum mixedness limit is found by solving Zwietering s differential equation. ... 

Simulation studies are also conducted for a dispersed PFR and a recycle reactor at 260 °C, 500 psig and feed with DCPD=0.32 mol/min, CPD=0.96mol/min and ethylene=3.2mol/min. Peclet number (Pe) or the recycle ratio is selected as a variable parameter for the dispersed PFR or for the recycle reactor, respectively. Conversion approaches to that of PFR over Pe=50 as can be seen in Fig.4. It is also worth mentioning that the reactor performance is improved with recycle if the residence time is low. 

GL 13] [R 1] [P 12] As a function of residence time, conversion increases linearly from 30 to 81% at selectivities from 79 to 67% [6]. The associated yield increase is non-linear and seems to approach a plateau (Figure 5.21). Hence residence times much larger than 14 s are not suited to increase reactor performance. 

Figure 5.29 Special-type multi-purpose micro devices and mixing tee used for investigation of CO2 absorption. Comparison of their reactor performance as a function of the residence time. Micro bubble columns ( ) 1100 pm x 170 pm, (A) 300 pm x 100 pm and (T) 50 pm x 50 pm Interdigital mixer ( ) (40 pm) caterpillar mixer (A) (850 pm ramp) mixing tee (0) (1 mm) [5],...

Study the effect of varying residence time x, feed concentration, and rate constants on reactor performance. 

As with continuous processes, the heart of a batch chemical process is its reactor. Idealized reactor models were considered in Chapter 5. In an ideal-batch reactor, all fluid elements have the same residence time. There is thus an analogy between ideal-batch reactors and plug-flow reactors. There are four major factors that effect batch reactor performance ... 

Different reactor networks can give rise to the same residence time distribution function. For example, a CSTR characterized by a space time Tj followed by a PFR characterized by a space time t2 has an F(t) curve that is identical to that of these two reactors operated in the reverse order. Consequently, the F(t) curve alone is not sufficient, in general, to permit one to determine the conversion in a nonideal reactor. As a result, several mathematical models of reactor performance have been developed to provide estimates of the conversion levels in nonideal reactors. These models vary in their degree of complexity and range of applicability. In this textbook we will confine the discussion to models in which a single parameter is used to characterize the nonideal flow pattern. Multiparameter models have been developed for handling more complex situations (e.g., that which prevails in a fluidized bed reactor), but these are beyond the scope of this textbook. [See Levenspiel (2) and Himmelblau and Bischoff (4).]... 

These two types of deviations occur simultaneously in actual reactors, but the mathematical models we will develop assume that the residence time distribution function may be attributed to one or the other of these flow situations. The first class of nonideal flow conditions leads to the segregated flow model of reactor performance. This model may be used... 

In Section 11.1.3.2 we considered a model of reactor performance in which the actual reactor is simulated by a cascade of equal-sized continuous stirred tank reactors operating in series. We indicated how the residence time distribution function can be used to determine the number of tanks that best model the tracer measurement data. Once this parameter has been determined, the techniques discussed in Section 8.3.2 can be used to determine the effluent conversion level. 

In the previous section we indicated how various mathematical models may be used to simulate the performance of a reactor in which the flow patterns do not fit the ideal CSTR or PFR conditions. The models treated represent only a small fraction of the large number that have been proposed by various authors. However, they are among the simplest and most widely used models, and they permit one to bracket the expected performance of an isothermal reactor. However, small variations in temperature can lead to much more significant changes in the reactor performance than do reasonably large deviations inflow patterns from idealized conditions. Because the rate constant depends exponentially on temperature, uncertainties in this parameter can lead to design uncertainties that will make any quantitative analysis of performance in terms of the residence time distribution function little more than an academic exercise. Nonetheless, there are many situations where such analyses are useful. 

The maintenance of uniform flow distribution in fixed bed reactors is frequently a problem. Maldistribution leads to an excessive spread in the distribution of residence times with adverse effects on the reactor performance, particularly when consecutive reactions are involved. It may aggravate problems of hot-spot formation and lead to regions of the reactor where undesired reactions predominate. Disintegration or attrition of the catalyst may lead to or may aggravate flow distribution problems. 

Residence-time distribution (RTD) relative times taken by different elements of fluid to flow through a vessel a spread in residence times leads to a statistical treatment, in the form of a distribution whether or not there is a spread in residence times has important implications for reactor performance. 

In this chapter, we consider nonideal flow, as distinct from ideal flow (Chapter 13), of which BMF, PF, and LF are examples. By its nature, nonideal flow cannot be described exactly, but the statistical methods introduced in Chapter 13, particularly for residence time distribution (RTD), provide useful approximations both to characterize the flow and ultimately to help assess the performance of a reactor. We focus on the former here, and defer the latter to Chapter 20. However, even at this stage, it is important to realize that ignorance of the details of nonideal flow and inability to predict accurately its effect on reactor performance are major reasons for having to do physical scale-up (bench —> pilot plant - semi-works -> commercial scale) in the design of a new reactor. This is in contrast to most other types of process equipment. 

Study the effect of varying residence time r (by changing feed rate), feed concentration, and rate constants on reactor performance. This can be done using Parametric Runs to obtain plots of the steady state concentrations as final values versus the corresponding change in parameter. 

A system of N continuous stirred-tank reactors is used to carry out a first-order isothermal reaction. A simulated pulse tracer experiment can be made on the reactor system, and the results can be used to evaluate the steady state conversion from the residence time distribution function (E-curve). A comparison can be made between reactor performance and that calculated from the simulated tracer data. 

In a variable-density reactor the residence time depends on the conversion (and on the selectivity in a multiple-reaction system). Also, in ary reactor involving gases, the density is also a function of reactor pressure and temperature, even if there is no change in number of moles in the reaction. Therefore, we frequently base reactor performance on the number of moles or mass of reactants processed per unit time, based on the molar or mass flow rates of the feed into the reactor. These feed variables can be kept constant as reactor parameters such as conversion, T, and P are varied. 

Whenever the density of the fluid in the reactor varies as the reaction proceeds, the reactor residence time r is not a simple independent variable to describe reactor performance. Typically, we stiU know the inlet variables such as Uq, Tq, Fjo, and Co, and these are independent of conversion. 

In addition to using different catalyst flow patterns in packed and slurry reactors, the flow can be varied to attain different catalyst contacting patterns. As shown in Figure 7-27, many flow patterns such as radial flow and fluid recirculation can be used. These allow variation of the flow velocity u for a given reactor size and residence time x. These recirculation flow patterns approach the flow of recycle reactors so the reactor performance approaches that of a CSTR at high recirculation. 

In Chapter 1 two new sections have been added. In the first of these is a discussion of non-ideal flow conditions in reactors and their effect on residence time distribution and reactor performance. In the second section an important class of chemical reactions—that in which a solid and a gas react non-catalytically—is treated. Together, these two additions to the chapter considerably increase the value of the book in this area. 

Continuous reactors are not always beneficial to achievement of good reactor performance (Woltinger, 2002) in the asymmetric opening of meso-anhydrides, due to product inhibition of the cinchona alkaloid catalyst the conversion and enantiomeric excess decreased rapidly during a continuous reaction. Even optimization of reaction parameters to decrease residence time to a very low value (1 h) did not improve the situation sufficiently. In contrast, performing the reaction in repetitive batch mode allowed a modest 60% e.e. to be sustained over 18 cycles. 

As previously discussed, one possibility of increasing the reactor performance resides in the use of multiple feeds. In Figure 4dan example is presented of a "split-feed" condition the same amount of monomer and initiators considered in the example of Figure 3 was supposed to be fed part at the reactor inlet, part in a reactor zone immediately after the temperature peak as shown by the computed temperature and conversion profiles, a small increase in the monomer conversion can be obtained. 

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