I n d . Eng. Chem. Res. 1990,29, 1072-1075
1072 t = time, s T = temperature, “C u = superficial gas velocity, m/s x =
benzene conversion
xB, xT, xH2= mole fractions of benzene, thiophene, and hy-
drogen xB0,xT0 = inlet mole fractions of benzene and thiophene z = length variable, m Greek Symbols (Y = relative activity for poison adsorption e = bed voidage
eA, OB = fractional occupancy of hydrogenation-active and pc pg
-inactive sites by thiophene (two-site model) = bulk density of catalyst, kg/m3 = gas density, kg/m3 Registry No. Ni, 7440-02-0; benzene, 71-43-2; thiophene,
110-02-1.
Literature Cited
Bourne, K. H.; Holmes, P. D.; Pitkethly, R. C. h o c . 3rd Znt. Congr. Catal. 1965,2, 1400. Butt, J. B.; Joyal, C. L.; Megiris, C. E. The Poisoning of Catalysts: Experimental Observations and Modeling. In Catalyst Deactivation; Petersen, E. E., Bell, A. T., Eds.; Marcel Dekker: New York, 1987. Frycek, G. J. Experiment and Modeling of Poisoning Effects in Temperature-Increased Fixed Bed Reactor Operation. Ph.D Dissertation, Northwestern University, Evanston, IL, 1984. Available from University Microfilms, Inc. Kehoe, J. P. G.; Butt, J. B. J. Appl. Chem. Biotechnol. 1972,22,23. Lyubarskii, G . D.;Andeeva, L. G.; Kul’kova, N. V. Kinet. Catal. 1962,3, 102. Megiris, C. E. Effects of Poisoning on the Dynamics of Fixed Bed Reactors. Ph.D Dissertation, Northwestem University, Evanston, IL, 1987. Available from University Microfilms, Inc. Megiris, C. E.; Butt, J. B. Znd. Eng. Chem. Res. 1990,following paper in this issue. Price, T. H.; Butt, J. B. Chem. Eng. Sci. 1977,32, 393. Richardson, J. T. J. Catal. 1971,21,130. Weng, H. S.; Eigenberger, G.; Butt, J. B. Chem. Eng. Sci. 1975,30, 1341. Zrncevic, S.; Gomzi, Z. Chem. Eng. Sci 1983,38, 1351.
Ahmed. K.: Chadwick. D.: Kershenbaum, L. S. Stud. Surf. Sci. Catal. iwi,34,513. Baiker, A.; Epple, D.; Wokaun, A. Chem. Eng. Sci. 1986,41, 779. Billimoria, R. M.; Butt, J. B. Chem. Eng. J . 1981,22,71.
Received for review November 1, 1988 Revised manuscript received May 10, 1989 Accepted May 23, 1989
Effects of Poisoning on the Dynamics of Fixed Bed Reactors. 2. Constant Conversion Policy of Operation Constantin
E.Megirist and John B. B u t t *
Department of Chemical Engineering, Northwestern University, Evanston, Illinois 60208-3120
The dynamic behavior of a fixed bed reactor subject to strong, irreversible poisoning has been investigated. In this work, the nature of the reaction and reactor and deactivation characteristics have been incorporated into a study of fixed bed operation a t constant conversion. Experiments and simulation results are presented, showing in a severe test that the variable capacity model for chemisorption of thiophene on Ni can explain the results. The constant conversion, temperature increased requirement (TIR) experiment is quite sensitive to the energetics of deactivation and, overall, provides a good measure of the worth of both the reactor simulation model and the approach to poisoning kinetics. Simulation of transients under TIR further illustrates the wavelike propagation of activity and concentration profiles through the bed. These resemble the cyclic operation of part 1 but differ importantly in end-of-bed behavior because of the constant-conversion requirement. Guard-bed behavior is observed but is modified by the constant conversion requirement and concomitant increase in bed temperature. Many instances of catalyst deactivation require reactor operation at constant conversion conditions accomplished by increasing the reactor temperature with time to compensate for deactivation while there is a constant feed rate to the reactor. The result is a temperature-time history, often called the “temperature increased requirement” (TIR), that represents a measure of the resistance of the catalyst to deactivation. Krishnaswamy and Kittrel (1979) and Sadana (1980, 1982) have presented simple mathematical models based on two different criteria for optimum reactor operation and the assumption that at any instant the reador is isothermal and the deactivation rate is concentration independent. Subsequently, both groups of investigators extended their approach to include severely intraparticle diffusion-limited systems (Krishnaswamy and Kittrell, 1982; Henley and Sadana, 1986; Sadana, 1987). Gonzalez-Velasco et al.
* Author to whom correspondence should be addressed.
t Present address:
Koninklijke/Shell Laboratorium, 1003 AA Amsterdam, T h e Netherlands. 0888-5885/90/2629-1072$02.50/0
(1984) and Romero et al. (1981) applied the analysis of Krishnaswamy and Kittrell(1979) to the dehydrogenation of benzyl alcohol to benzaldehyde on Cu/Si02 with good results. However, the assumption of concentration independence of deactivation is often a serious limitation to the general applicability of such models. In cases where the deactivation rate is a concentrationdependent function, the analysis of Butt and Rohan (1968) applies. That approach is based on the fixed bed modeling via a series of perfect mixing cells and was later extended (Butt, 1970,1971) to poisoning of bifunctional catalysts. Recently, Hong and Lee (1985, 1986) presented a new approach for estimating the extent of catalyst deactivation and maintaining the exit conversion within a band about the desired level from on-line measurements of inlet temperature and outlet concentration. The method is a feedback control scheme and does not require knowledge of the deactivation kinetics to maintain the desired conversion. This work follows part 1 (Megiris and Butt, 1990) in an extension to TIR operation. Such operation can be con0 1990 American Chemical Society
Ind. Eng. Chem. Res., Vol. 29, No. 6, 1990 1073 sidered as a limit of the cyclic technique with an infinite number of infinitesimal cycles. In the present work, the variable poison adsorption capacity model used previously is employed to predict the temperature-time history required to maintain constant conversion in a TIR. Predicted temperature-time trajectories are applied experimentally as a severe test of the validity of the simulation model.
Experimental Section The general experimental conditions, procedures, materials, and apparatus have been given in part l. For TIR operation, the temperature-time (7'4) history required to maintain constant conversion under preset experimental conditions was first predicted by numerical solution of the simulation model. The reactor was established isothermal at the initial temperature of the run, and then, the pure benzene/hydrogen stream was fed to the bed until steady-state conversion was established. After the reactor had attained steady state, the feed was switched to introduce the thiophene-containing mixture into the bed. At the same time, the predicted T-t schedule was applied to the catalyst bed with the help of a computerized temperature control system (Megiris, 1987,1988) and the reactor temperature was continuously increased to keep the conversion invariant with time. However, the reactor was kept isothermal at any instant. When the final temperature of the T-t trajectory was reached, the feed was switched back to the pure benzene stream and the reactor temperature was stabilized at its final value. The exit conversion was monitored at periodic intervals along the duration of a run.
, n I
; u ; c
170160150140130120110118-
-
90 80-
78-
-
got
40 38 50
O
20-
18
-
0
;
0'
I
I
I
31
60
9@
I
I
I
I
120
150
le0
218
TlnK ttllM)
Figure 1. Comparison of time-temperature trajectories required for constant conversion; conditions of run C2. Single-site model versus variable adsorption capacity model. Target conversion (model) of benzene is 69.7%. Space velocity = 510 cmS/(mimg).
P E
178 168 158 110 -
R
130
[UTt nadcll
198
188
Simulation The variable poison adsorption capacity model (Table VI, part 1) is used in the TIR simulation, with the additional requirement to specify T(z,O)= Tofor initial conversion. As before, MT is a composite linear function of temperature in the range 65-200 "C:
MT = 0.03 X 10-4T + 1.94 X
MT = 7.06
X
lo4
(65-170 "C)
T E
n A
T U
R
E C
38 80 70 60
(170-200 "C)
-
120 118100 -
-
58
'
I
I
I
I
where MT is in kmol of poison/kg of catalyst, and T i s in
"C. The other major correlations involved in the simulation, for kinetics and deactivation rate, are as given also in part 1, together with their corresponding parameters. For purposes of comparison, the single-site model has also been included here, with the formulation as given in Table IV, part 1.
C 0
I U
E R S I 0
n
"1-
7 4 58
'I
--
. --
. *
..*
. . - . * . . ..
38 r(
Results The experimental conditions for runs under constant conversion conditions were similar to those for the cyclic runs of part 1. The predicted time-temperature histories comparable to run C2 are shown in Figure 1,together with the conversion results obtained from operation according to the schedules requires by both one-site and variable adsorption capacity models. Differences between the schedules demanded by the two models are quite apparent as far as time-temperature profiles are concerned, and the superiority of the variable capacity model in maintenance of constant conversion is demonstrated. To pursue the point a bit further, we show some additional results in Figures 2 and 3. Figure 2 gives the results for a run at similar conditions to Figure 1except for the space velocity, which has been increased from 510 to 765
18 0
30
68
98
128
158
TIHE tnlN)
Figure 2. Comparison as for Figure 1. Space velocity increased from 510 to 765 cms/(min.g). Target conversion = 54.5%.
cm3/ (min-g). Figure 3 is the same as for Figure 2 except the catalyst size has been changed from 60-70 to 80-100 mesh. The results similar to the base case of run C2 (Figure 1)are seen, so the model appears capable of setting operational policies both over a range of conversions and in the demonstrated absence of significant diffusional effects. It should be kept in mind that the temperature-time profiles shown in Figures 1-3 are those determined by
REL#IIUE ACTIUITY FOR POISON ADSORPTION
i.a
8.7
a.6
a.5
a. 4 8.3 8.2
a. i 8.8 B
24 38 DISTANCE (Q1)
12
6
36
18
42
48
Figure 5. Variation of relative activity for poison adsorption, constant conversion operation. BEK4MR CONCEMRATION 2.2
; C
E
n 8
3n
60
90
TINE
izn
2.8
1.8 1.6 1.4
158
(NIM)
Figure 3. Comparison BB for Figure 2. Catalyst particle size changed from 60-70 to 90-100 mesh. Space velocity = 765 cm3/ (min-g). Target conversion = 50.5%. WDROCENATION ACTIUIW 1.a 8.9
8.8
0.7
a . a i ' d Figure 6. Benzene concentration response profiles within the reactor. 8
POISON C O N C E M R M I O N
8.6 8.5 128
a.4
P
8.3
n
a. 2 a. i
T
8.a
Figure 4. Hydrogenation activity response under constant conversion conditions. Run C2 simulation.
simulation but that are then imposed upon the reactor in operation to obtain the experimental conversion results shown. Thus, the temperature schedules predicted by the model determine operational policy. It is clear from these experiments, which are surely a severe test of the deactivation model, that the variable capacity formulation is correct. Slight cycling in the conversion-time results is an inevitable result of finite time lags in the control scheme (Megiris, 1987).
Simulation of Dynamics: Activity and Concentration Profiles We should now examine the insight provided by the variable poison adsorption capacity model on the dynamic behavior of activity and concentration profiles developed along the catalyst bed in response to poisoning under TIR operation. A reasonable example is provided by the simulation results corresponding to Figure 1 as presented in Figures 4-7. The reactor dynamics resemble the wave behavior reported for the first cycle in the isothermal cyclic mode of operation and are composed of three distinct time domains. The first domain is a first concentration response (FCR)
opre
IkE.fw
1-11
0-I)
iaa
H
I 0 P H
68
E
"
E
28
n
P
"a
6
12
18
24
38
36
42
48
DISTANCE ( U I O
Figure 7. Poison concentration profiles in TIR operation,
of thiophene, which very rapidly establishes a quasi-steady profile from its zero initial condition. This time domain is not shown in Figure 7 because the quasi-steady profile (curve 1) is established in less than two residence times of reactor operation. During the FCR time period, the activity and benzene concentration profiles do not change significantly from their initial steady-state values. The other two domains are composed of two different types of slow concentration response (SCR) periods. Profiles plotted for SCR region 1 are 3 min apart, while those plotted for SCR region 2 are 10 min apart. During the first SCR (0-30 min), the activity and concentration profiles slowly develop a characteristic shape. During the second SCR period (30-140 min), the profiles travel through the catalyst bed, but the speed of wave propagation continuously decreases with poison time on stream. In this case, no clear distinction can be made between a
Ind. Eng. Chem. Res., Vol. 29, No. 6, 1990 1075 small guard bed formed a t the entrance of the bed and a main bed (bed exit) active for the hydrogenation reaction as in the cyclic mode of operation shown in part 1. However, the fact that the profiles of relative activity for poison adsorption never go to zero (Figure 5) is a clear indication of the existence of the guard-bed effect. This is driven by the continuous increase of the poison adsorption capacity of the Ni catalyst with temperature (Le., time on stream), and although not clearly visible in Figure 5, this dominates the dynamic behavior of the reactor. The bed entrance, although inactive for hydrogenation, always retains a residual activity for thiophene chemisorption,stripping some of the poison from the feed before it reaches the active part of the bed. The residual poison then contributes to the slowdown of the wave propagation through the catalyst bed. The guard-bed effect is also responsible for the complex structure of Figure 5. The poison concentration profiles form a characteristic net. At the last stages of each run, the bed temperature increases quickly, and therefore, the value of MT follows the same path. The fast rise in the poison chemisorption capacity at the entrance to the bed leads then to enhanced adsorption of poison from the feed (Figure 5,1W140 min), although that part of the bed is inactive for the hydrogenation reaction (Figure 4,100-140 min). Thus, even though the guard bed may be small in dimension, its effect becomes increasingly important and "pulls down" the poison concentration profiles in Figure 7. The final concentration profiles, as shown in Figure 7, are almost linear. No intuition in the world would lead to this, as far as we know. However, the linear profile, thus developed, means that overall observations of temperature versus time in a TIR experiment could possibly give indirect evidence as to deactivation kinetics. Finally, the benzene concentration profiles in Figure 6 develop a characteristic triangular shape caused by the square-wave type of hydrogenation activity profiles and the zero-order kinetics with respect to benzene concentration of the hydrogenation reaction in the 60-120 OC range. They all converge to the same point because of the constant conversion operation of the reactor and demonstrate the internal consistency of the experiment and interpretation.
Conclusions The extreme transient behavior characteristic of temperature-time experiments constitutes a severe test of all aspects of the simulation. We conclude that the variable poison adsorption capacity model is correct for this type of deactivation of an hydrogenation catalyst and, further, that the combination of cyclic operation and temperature increase requirement experiments is remarkably effective in the identification of the mechanism of poisoning. In simulation, the dominance of the guard-bed effect is striking. While this might be expected to be important
in cyclic operation-and so it is-it is also responsible for the complexity of the wavelike propagation of concentration and activity profles through the bed in TIR operation, even though in dimension this may be relatively small. The use of constant conversion operation in industrial practice for the determination of intrinsic deactivation parameters is a risky business and can lead to painfully poor conclusions. The constant conversion operation is an "averaging" procedure and masks the effects of all the important parameters that influence the dynamics of the reaction system. This is shown clearly in the analysis of the present experiments. From both the results of simulation and experiment, it would appear that, while temperature-increased operation is often employed commercially, the cyclic policy of operation may be the single most efficient tool for obtaining information on the specifics of deactivation and determining the appropriate catalyst activity maintenance scheme. However, the TIR policy gives a severe test of this.
Acknowledgment Support of CM via the National Science Foundation and the Murphy Fund of Northwestern University is gratefully acknowledged, as well as that of the Alexander von Humboldt-Stiftung support for J.B.B.for both parts of this study. Registry No. Ni, 7440-02-0; benzene, 71-43-2; thiophene, 110-02-1.
Literature Cited Butt, J. B. Chem. Eng. Sci. 1970, 25, 801. Butt, J. B. Proc. 4th Europ. Symp. Catal. React. Engr.; Pergamon Press: Elmsford, NY, 1971; p 255. Butt, J. B.; Rohan, D. M. Chem. Eng. Sci. 1968,23,489. Gonzalez-Velasco,J. R.; Gutierrez-Ortiz, M. A,; Gutierrez-Ortiz, J. I.; Romero, A. Chem. Eng. J. 1984,28, 13. Henley, J. P.; Sadana, A. Chem. Eng. Commun. 1986,46, 281. Hong, J. C.; Lee, H. H. AZChE J. 1985,31, 302. Hong, J. C.; Lee, H. H. Chem. Eng. Sci. 1986,41,1783. Krishnaswamy, S.; Kittrell, J. R. Znd. Eng. Chem. Process Des. Dev. 1979, 18, 399.
Krishnaswamy, S.; Kittrell, J. R. Znd. Eng. Chem. Fundam. 1982,21, 95.
Megiris, C. E. Effects of Poisoning on the Dynamics of Fixed Bed Reactors. Ph.D. Dissertation, Northweatem University, Evanston, IL, 1987. Available from University Microfilms, Inc. Megiris, C. E. Chem. Eng. Sci. 1988, 43, 2239. Megiris, C. E.; Butt, J. B. Znd. Eng. Chem. Res. 1990, preceding paper in this issue. Romero, A.; Bilbao, J.; Gonzalez-Velasco,J. R. Chem. Erg.Sci. 1981, 36, 797.
Sadana, S. Chem. Eng. Commun. 1980,4,51. Sadana, S. Chem. Eng. Sci. 1982,37,492. Sadana, S. Chem. Eng. Commun. 1987,49, 291.
Receiued for reuiew November 1, 1988 Revised manuscript received May 10, 1989 Accepted May 23, 1989
