Ind. Eng. Chem. Res. 1991,30, 1023-1032
formance for each catalyst starting material; the optimal conversion, yield, and selectively clearly would likely correspond to different reaction conditions. However, such a determination would be useful for the practical selection of a catalyst. Acknowledgment This work was conducted through the Ames Laboratory, which is operated for the U S . Department of Energy by Iowa State University under Contract W-7405-Eng-82. This work was supported by the Office of Basic Energy Sciences, Chemical Sciences Division. Literature Cited Alvero, R.; Carrizosa, J. A,; Odriozola, J. A,; Trillo, J. M. Activation of Rare Earth Oxide Catalysts. J. Less-Common Met. 1983,94, 139-144. Bernal, S.; Botana, F. J.; Rodriguez-Izquierdo, J. M. Thermal Evolution of a Sample of La203 Exposed to the Atmosphere. Thermochim. Acta 1983a,66, 139-145. Bernal, S.;Garcia, R.; Lopez, J. M.; Rodriguez-Izquierdo, J. M. TPD-MS Study of Carbonation and Hydration of Yb203(C). Collect. Czech. Chem. Commun. 1983b,48,2205-2212. Bernal, S.;Diaz, J. A.; Garcia, R.; Rodriguez-Izquierdo, J. M. Study of Some Aspects of the Reactivity of La203with COz and HzO. J. Mater. Sci. 1985,20,537-541. Burch, R.; Squire, G. D.; Tsang, S. C. Comparative Study of Catalysts for the Oxidative Coupling of Methane. Appl. Catal. 1988, 43,105-116. Campbell, K. D.; Zhang, H.; Lunsford, J. H. Methane Activation by the Lanthanide Oxides. J. Phys. Chem. 1988,92,750-753. Carrizosa, I.; Odriozola, J. A.; Trillo, J. M. Lanthanide Oxides: Yb203 Hydration. Znorg. Chim. Acta 1984,94,114-116. Deboy, J. M.; Hicks, R. F. The Oxidative Coupling of Methane over Alkali, Alkaline Earth, and Rare Earth Oxides. Znd. Eng. Chem. Res. 1988a,27, 1577-1582. Deboy, J. M.; Hicks, R. F. Kinetics of the Oxidative Coupling of Methane over 1 wt% Sr/La203. J. Catal. 1988b,113,517-524. Hinsen, W.; Bytyn, W.; Baerns, M. Oxidative Dehydrogenation and Coupling of Methane. h o c . 8th Znt. Congr. Catal. 1984,581-592.
1023
Hutchings, G. J.; Scurrell, M. S.; Woodhouse, R. J. Partial Oxidation of Methane over Samarium and Lanthanum Oxides: A Study of the Reaction Mechanism. Catal. Today 1989,4,371-381. Jones, C. A.; Leonard, J. J.; Sofranko, J. A. Fuels for the Future: Remote Gas Conversion. Energy Fuels 1987,1, 12-16. Lee, J. S.; Oyama, S. T. Oxidative Coupling of Methane to Higher Hydrocarbons. Catal. Rev.-Sci. Eng. 1988,30, 249-280. Lin, H. C.; Campbell, K. D.; Wang, J. X.; Lunsford, J. H. Oxidative Dimerization of Methane over Lanthanum Oxide. J.Phys. Chem. 1986,90,534-537. Otsuka, K.; Jinno, K. Kinetic Studies on Partial Oxidation of Methane over Samarium Oxides. Znorg. Chim. Acta 1986,121, 237-241. Otsuka, K.; Nakajima, T. Partial Oxidation of Methane over Rare Earth Metal Oxides using NzO and O2 as Oxidants. Znorg. Chim. Acta 1986,120,L27-L28. Otsuka, K.; Komatsu, T. Active Catalysts in Oxidative Coupling of Chem. Commun. 1987a,388-389. Methane. J. Chem. SOC., Otsuka, K.; Komatsu, T. High Catalytic Activity of Sm203for Oxidative Coupling of Methane into Ethane and Ethylene. Chem. Lett. 1987b,483-484. Otsuka, K.; Jinno, K.; Morikawa, A. The Catalysts Active and Selective in Oxidative Coupling of Methane. Chem. Lett. 1985, 499-500. Otsuka, K.; Jinno, K.; Morikawa, A. Active and Selective Catalysts for the Synthesis of CzH6 and C2H, via Oxidative Coupling of Methane. J. Catal. 1986,100,353-359. Pitchai, R.; Klier, K. Partial Oxidation of Methane. Catal. Rev.SC~ Eng. . 1986,28, 13-88. Rosynek, M. P.; Magnuson, D. T. Preparation and Characterization of Catalytic Lanthanum Oxide. J. Catal. 1977,46,402-413. Scurrell, M. S. Prospects for the Direct Conversion of Light Alkanes to Petrochemical Feedstocks and Liquid Fuels-A Review. Appl. Catal. 1987,32,1-22. Taylor, R. P. M.S. Thesis, Iowa State University, 1989. Turcotte, R. P.; Sawyer, J. D.; Eyring, L. On the Rare Earth Dioxymonocarbonates and Their Decomposition. Znorg. Chem. 1969,8,238-246. Wendlandt, W. W.; George, T. D. The Thermal Decomposition of Inorganic Compounds IV. Rare Earth Carbonates. Tex. J. Sci. 1961,13,316-323. Received for review July 23, 1990 Revised manuscript received December 26, 1990 Accepted January 8,1991
Pressure Swing Adsorption: Experimental and Theoretical Study on Air Purification and Vapor Recovery James A. Rittert and Ralph T. Yang* Department of Chemical Engineering, S t a t e University of New York a t Buffalo, Buffalo, New York 14260
Pressure swing adsorption (PSA) air purification/vapor recovery was studied by experiments and model simulations using dimethyl methylphosphonate (DMMP) vapor and activated carbon. The most significant result was that complete cleanup of the product effluent resulted when starting from a saturated bed even for the very strongly adsorbed vapor, DMMP. Furthermore, at the same time, a concentrated DMMP vapor was produced at the exhaust effluent. Therefore, PSA cannot only be used to purify air, it can also concentrate the vapor for more efficient recovery or abatement. Also, two cyclic steady states were demonstrated both experimentally and theoretically. When starting from a clean bed, the concentration wave penetrated the bed very slowly while a cyclic steady state was being approached and much of the bed remained unused acting as a guard against product effluent contamination. However, when starting from a saturated bed, a different cyclic steady state was approached where a "heel" existed in the bed a t the product effluent end. Introduction Although fixed bed adsorption processes have existed for a very long time (see Mantell (1951)),cyclic adsorption 'Present address: Westinghouse Savannah River Company, Savannah River Laboratory, Aiken, S C 29802.
0888-5885/91/2630-lO23$02.50/0
processes are relatively new. It was not until 1959 that the first truly cyclic adsorption process was invented by Skarstrom (1959) for air drying, referred to as heatless adsorption or pressure swing adsorption (PSA). This paper is concerned with a PSA process similar to that invented by Skarstrom (1959); however, in this study PSA is used for air purification instead of dehydration. The significant 0 1991 American Chemical Society
1024 Ind. Eng. Chem. Res., Vol. 30, No. 5, 1991
difference is made clear below. But first a brief review of two other cyclic adsorption processes is given since they are also applicable to air purification and/or vapor recovery applications. The PSA process is limited to gas separations because a pressure change has little effect on changing the composition of a liquid in the presence of an adsorbent. Nevertheless, Wilhelm et al. (1966) developed parametric pumping (PP) for both gas and liquid separations. The original parametric pump operates in a batch mode, where a liquid is periodically heated and cooled while, at the same time, being pumped up and down through a fixed bed of adsorbent that has a reservoir attached to each end. This idea was further extended by Pigford et al. (1969), who developed a process referred to as cycling zone adsorption (CZA). They realized that continuous, cyclic operation was possible with the parametric pump if flow reversal was not employed. Moreover, CZA allowed pressure, composition, or any other thermodynamic variable of a gas or liquid to be cycled and thus cause a separation. Excellent reviews of these three processes (PSA, parametric pumping, and CZA) along with some industrial applications have been given by Ruthven (1984), Tondeur and Wankat (19851, Wankat (1986), Yang (1987), and Suzuki (1990). The purification of air by removing low concentrations of noxious gases or vapors, or the concentration of vapors for recovery or abatement, has generally been accomplished by adsorption technology (Mantell, 1951). The primary difference between these kinds of adsorption processes is the way the beds are regenerated. Three modes of regeneration are commonly employed: steam, hot air (gas) purge, or pressure swing. Each mode has inherent advantages and disadvantages as outlined by Turk (1977) but only for steam and hot purge gas. A few advantages of pressure swing over steam or hot purge gas are when the vapor has the ability to react with adsorbed water since many adsorbents make effective catalysts, corrosion of equipment may result in the presence of moisture, and the vapor decomposes upon heating. Moreover, the first two methods require cycle steps for steaming or heating, and drying or cooling. This results in long cycle times (hours); thus large beds are required to achieve high feed throughputs. In contrast, PSA processes are unique because the beds are rapidly regenerated by decreasing the total pressure and purging at low pressure. This results in short cycle times (minutes) which give rise to high feed throughputs even for small beds. Nevertheless, PSA has only within the past three decades become an established adsorption process for purification and only within the last decade has it become increasingly popular for concentrating vapors for recovery or abatement. Several monographs are available (Ruthven, 1984; Tondeur and Wankat, 1985; Wankat, 1986; Yang, 1987; Suzuki, 1990) that discuss the principles of PSA and its industrial applications which include gas dehydration, hydrogen purification, and air separation. It should be noted that PSA gas dehydration (Skarstrom, 1959; Carter and Wyszynski, 1983; Chihara and Suzuki, 1983a,b) and PSA air purification processes, although similar in some respects, have one significant difference. Gas dehydration involves the removal of low concentrations of moisture that has a relatively high vapor pressure and is easily desorbed, whereas air purification may involve the removal of low concentrations of compounds that have low vapor pressures and are difficult to desorb. This difference has apparently discouraged the use of PSA for air purification/vapor recovery applications. Thus, air purification (White, 1988) and vapor recovery (Lovett and Cunniff,
PROD
+
?
‘f
2
1
EXH
?
-r
FEED Figure 1. Typical two-bed PSA air purification or solvent concentration process.
1974; Kenson, 1979; Parmele et al., 1979; Cantrell, 1982) have received comparatively little attention. Therefore, the objective of this study is to present a comprehensive analysis of air purification and vapor recovery by PSA. A PSA apparatus, utilizing BPL activated carbon, was designed for this purpose and tested with a low vapor pressure compound (dimethyl methylphosphonate (DMMP); P, = 1Torr at 303 K), which is of interest to defense and the chemical industry since it is a simulant for chemical agent, e.g., nerve gas. A model was also developed to determine the bed profiles and associated concentration wave fronts. Results are presented for both transient and cyclic steady-state operations which demonstrate the feasibility of PSA for air purification and vapor recovery and which ascertain the effects of important process variables on the process performance.
Process Description A typical PSA air (gas) purification and/or vapor recovery system consists of two beds operating in tandem. A two-bed PSA process and its valving are displayed in Figure 1. During every cycle each bed undergoes the following cycle steps: (I) feed pressurization, (11) highpressure feed, (111) countercurrent blowdown, and (IV) countercurrent purge with product. Purified product (air) is withdrawn during cycle step I1 essentially at the feed pressure, and regeneration (or vapor concentration) is accomplished during cycle step IV by using a fraction of expanded product from one bed as purge for the other bed. The PSA air purification process performance is judged mainly by the product purity and, to a lesser extent, the feed throughput and air (product) recovery, whereas the PSA vapor recovery process performance is judged mainly by the enrichment of the vapor (i.e., the ratio of exhaust to feed concentrations). Note that, depending on the specific application, both air purification and vapor recovery can be accomplished simultaneously with a single PSA process. Compared to other adsorption processes, PSA purification/vapor recovery processes rarely utilize all the adsorbent and the beds are never completely regenerated. A cyclic steady state is attained where the amount ad-
w
Ind. Eng. Chem. Res., Vol. 30, No. 5, 1991 1025
PT
U PT
VAC
MFC
Table I. PSA Process Characteristics and Conditions bed length (L) 12.8 cm 1.1 cm bed i.d. (dB) 5.25 g dry weight BPL carbon particle diameter (dp) 0.06-0.08 cm 0.43 bed porosity ( 6 ) feed throughput 75 cm3(STP)/(min g) 4.5 cm/s superficial velocity (CU)' 0.4s residence time' feed concentration range 100-400 ppm 0.12-3 atm pressure range (PL- P H ) pressure ratio range (PHIPL) 3-25 20-240 min cycle time range (t,) ambient temperature 294 K
0 b5yMvq "p,
4
PR
AIR
PT
SP
sv
BPR
sv
Figure 2. Schematic of PSA apparatus: BPR, back-pressure regulator; CB, calibration bed; MFC,mass flow controller; nv, needle valve; PR, pressure regulator; PT, pressure tap; SP, sampling port; sv, solenoid valve; v, valve.
sorbed in each bed decreases little, comparing the end of cycle step IV to the end of cycle step II; and for either step, it monotonically decreases from near saturation at the feed end to essentially zero (complete cleanup) at the product end. Thus, the unused portion of the bed acts as a guard and is needed to maintain the gas- and adsorbed-phase axial distribution. Experimental Apparatus and Procedure A schematic of the single-bed PSA apparatus is displayed in Figure 2. The stainless steel system was designed to simulate the four steps of the aforementioned two-bed PSA process and to operate at pressures up to 7 atm, air flow rates up to 70 cm3(STP)/s, vapor concentrations from saturation down to parts per billion, and cycle times from 2 s to days. Laboratory air, used for feed and purge, was cleaned with activated carbon and dried with CaS04and 13X zeolite. The saturator contained 97% pure DMMP (Stauffer Chemical Company) and was maintained at 293 f 0.5 K. The adsorbent was commercial grade BPL activated carbon (Calgon Corporation) regenerated at 413 K in a dry air purge for 12 h. High pressure was controlled by a back-pressure regulator, and low pressure was atmospheric (not controlled) or vacuum (controlled with a needle valve). Pressure was monitored at the top and bottom of the column with a pressure transducer. Mass flow controllers regulated feed and purge influents, and product and exhaust effluents were intermittently measured with a wet test meter. Cycle sequencing was controlled by an electronic timer which operated four solenoid valves. The system was completely automated except for gas sampling and DMMP analysis. Septa were located at the top and bottom of the column to obtain gas samples with pressure-tight syringes. These syringes also allowed sampling below atmospheric pressure. The DMMP was analyzed with a flame ionization detector (FID) calibrated by the following method. The feed stream was diverted to a cleaned and dried carbon bed during cycle steps I11 and IV. The weight gained by this bed (assuming no breakthrough) was converted to DMMP concentration and calibrated against the FID output. The calibration was linear, the lower detection limit was 10 ppb, and the standard deviation was less than 5%. All PSA runs were performed at ambient temperature and at a constant feed throughput. Refer to Table I for the PSA process characteristics and conditions. The cycle time was estimated by taking 1% of the time necessary to saturate the bed at the process conditions (Chihara and Suzuki, 1983a,b). The duration of cycle steps I and I11 was very short compared to the cycle time; therefore, the length
'Relative to the feed pressure
(PH).
of time for cycle steps I and I1 and that for cycle steps I11 and IV were combined where equal lengths of time (10 min) were allotted for each set. Prior to each PSA run,the bed was saturated at the feed conditions. To obtain DMMP product concentration histories, process conditions were chosen to ensure a contaminated product. Process conditions were also chosen to ensure complete cleanup of the product. Also, because of the single-bed experimental design, clean air was used for purge instead of actual product effluent. Nevertheless, a two-bed process starting with clean beds also uses purified (clean) product for purge, and the single-bed apparatus was designed only to simulate the cycle steps of a two-bed PSA process. For each PSA run, 2-3 days was required to reach cyclic-steady-state operation. Cleaned and dried carbon beds were placed at the product and exhaust (atmospheric pressure only) ends of the bed to verify cyclic steady state and complete cleanup of the product effluent. Cyclic steady state was realized when the DMMP in the effluent streams remained constant for more than 12 h. Material balances based on the results from using the clean and dried carbon beds closed to within 2 4 % . Theory
LDF Model Assumptions and Equations. The PSA model was based on the following assumptions: inert carrier gas and adsorbent; dilute, single-component feed; isothermality; constant bed void fraction; negligible bed pressure drop; constant superficial velocity during cycle steps I1 and IV; ideal gas behavior; no radial gradients or axial dispersion; linear driving force (LDF) approximation to account for the "lumped" effects of mass-transfer resistances and deviations from plug flow; and frozen gas and adsorbed phases during cycle steps I and 111. With these assumptions, a mass balance over a differential portion of the bed for cycle steps I1 and IV led to ay ay PRT dq - + €U% = -P at at The LDF approximation gave dq/at as E
aq/at = K(q* - 9)
(1)
(2)
where q* was the amount adsorbed in equilibrium with Y and calculated from the Langmuir isotherm: V,,,b YP q* = (3) 1 + bYP Initial and Boundary Conditions. The initial and boundary conditions for each cycle step are listed below and applied to every cycle. Note that cycle steps I and I1 of the first cycle corresponded to complete saturation of
1026 Ind. Eng. Chem. Res., Vol. 30, No. 5 , 199r 0.6
0
n
Y e, Y
m
w
5: U e, 5: U e,
0.3
I/ I
c
Hexane
0
0.25
0
.
1
,
1.0
r
P/F
- 0.54
1
0.50
P ~ m p(TORR)
Figure 3. DMMP adsorption isotherm at 294 K on BPL activated carbon (Ritter, 1989). Upper solid lines: Langmuir model isotherms (parameters are given in Table 11; the lower of the two curves is obtained by fitting the model to the PSA data and is associated with a smaller b value). Lower solid line: hexane isotherm included for comparison. Table 11. DMMP Isotherm and LDF Model Parameters DMMP Isotherm Parameters4 0.490 g/g 9.87 X lo6 atm-'
0
bvm
300
600
TIME (SEC)
Parameters Employed in LDF Model vm 0.490 g/g b 9.87 X lo4 atm-' K 5.0 x 10-3 s-1
Figure 4. Effect of LDF coefficient on the cyclic-steady-state product effluent concentration history for PSA run 4 (see Table I11 for process conditions).
Parameters obtained by nonlinear regression from the data given elsewhere (Ritter, 1989).
saved considerable CPU time. Correlation of the LDF Model with Experiments. There were three parameters in the LDF model. The parameters from eq 3 ( b and V,) were obtained (as a first approximation) from the DMMP adsorption isotherm (Ritter, 1989) by using nonlinear regression, and K was used strictly as a fitting parameter. The data points are plotted in Figure 3 along with the Langmuir isotherm (upper curve) predicted from b and V, (see Table II). The hexane isotherm on activated carbon was included in this figure to exemplify the rectangular nature of the DMMP isotherm. The LDF model was fitted to one experiment (PSA run 4) that had a significant amount of DMMP in the product effluent. With these values of b and V,, and for different K , the LDF model predicted a higher average DMMP product concentration at the cyclic steady state compared to experiment. The average product concentration was also independent of K. Therefore, as a first guess, b was decreased by a factor of 10. This b is also given in Table I1 and the corresponding Langmuir isotherm is shown in Figure 3 (middle curve). With this b, along with the same V,, the LDF model was able to predict the average product concentration; however, the product concentration history depended on K. Figure 4 displays the effect of K on the DMMP product concentration history for PSA run 4. The areas under the curves were nearly the same which verified that K had little effect on the average product concentration. However, the vapor concentration wave broadened as K decreased and gave rise to a more contaminated product at t = 0. A K = 0.005 s-l described PSA run 4 quite well; therefore, this K was used to predict the other PSA runs. In general, the predictions were good (see below). This model was therefore used to ascertain the gas- and adsorbed-phase bed profiles corresponding to the experimental PSA runs. It should be noted that the two correlated Langmuir isotherms leveled off (see Figure 3) while the experimental DMMP isotherm gradually increased. This may explain why the LDF model required a less
a clean bed and the PSA process was started with cycle step IV of the first cycle. cycle step I (pressurization) t = 0: Y p = (PL/PH)YD and qp = qD for 0 I z I L (4)
cycle step I1 (adsorption) z = 0:
Y = YF and q = q* fort I O (54 t = 0: YA = Yp and qA = qp for 0 I z I L (5b) cycle step I11 (blowdown): t = 0: YB = (PH/PL)YA and q B = qA for 0 I z I L (6)
cycle step IV (desorption):
z=L: Y = O and q = O fort10 (74 t = 0: YD' YB and qD= Q B f o r o 5 Z I L (7b) Solution Method. Equations 1, 2 and 3 were solved numerically by use of an explicit, backward finite difference algorithm with At = 0.5 s and Az = 0.5 mm. These At and Az resulted in 1200 time steps (for t, = 20 min) and 256 distance steps for each half cycle. Nevertheless, because of the strictly explicit nature of the model, less than 40 CPU s per cycle was required. The model was written in Fortran code and implimented on a VAX-780 computer. This model was slightly different from other models in the literature (Yang, 1987) because the partial pressure of the vapor was frozen during cycle steps I and 111. This was a reasonable assumption since the flow rates of cycle steps I1 and IV corresponded to many bed volumes of gas. Moreover, it utilized the Langmuir isotherm as it was the simplest nonlinear model to use because it allowed Y to be solved explicitly at each time and position step. This
Ind. Eng. Chem. Res., Vol. 30, No. 5, 1991 1027 Table 111. Results of the Experimental and Modeling PSA Runs"
PSA run lb
t,, min
20
PHIatm 3.07
PL,atm 0.12
PH/PL 25.12
Y
YF,ppm
11.39
218
YE,ppm
RP,?&
0
56
(0) 0 (0) 25
2c
20
3.06
1.07
2.87
1.19
236
3
20
3.07
1.08
2.89
0.93
217
4
20
3.08
1.04
2.95
0.54
193
5
20
3.06
0.65
4.70
0.54
240
6
20
3.06
0.32
9.62
0.54
219
7
20
1.49
0.49
3.02
0.56
403
8
20
1.48
0.50
2.99
0.56
210 -
9
20
1.48
0.49
2.99
0.55
105 -
10
40
3.08
1.08
2.86
0.93
226
11
240 -
3.08
1.08
2.87
0.94
232
~
YP,ppm
(1156) 526 (577) 507 (601) 467 (569) 1265 (1122) 3250 (2097) 1324 (1207) 627 (626) 342 (315) 647 (620) 595 (523)
59 68 82
88 94 82 81 82 68 67
Yp and YE correspond to average product and exhaust concentrations, respectively. Modeling results are given in parentheses. bTransient results at cycle number 20 from startup of a saturated bed. cTransient results very near cyclic steady state at cycle number 881 from startup of a saturated bed. favorable isotherm to fit the experimental PSA runs.
Results and Discussion The results for 11experimental PSA runs are displayed in Table 111. They demonstrate the effects of four important process variables on the product purity and recovery and the exhaust (vapor) concentration. The effect of a particular variable is ascertained by comparing the PSA runs with the parameter underlined. Table I11 also lists the results from the LDF model for the 11PSA runs. Note that PSA runs 1and 2 were not at cyclic steady state (see below), whereas all the other PSA runs were. Transient Process Behavior. The unsteady-state results of PSA run 1 (Table 111)correspond to cycle number 20 and were obtained to demonstrate the cleanup of a saturated bed. Figure 5 displays the experimental product effluent concentration at 0,5, and 10 min during cycle step I1 from startup to cycle number 20 and also the prediction of the average product effluent concentration from the LDF model. Note that Yp/YF = 1.0 at cycle number 1. It is seen from Figure 5 that cycle number 20 was where DMMP could not be detected in the product effluent. This was observed experimentally as well as from the modeling results, although the LDF model (compared to experiment) initially predicted a much faster cleanup of the product effluent. The origin for the fast approach to the cyclic steady state lies in the deficiency of the LDF approximation: it overestimates the amount adsorbed during adsorption and underestimates the amount adsorbed during desorption and it gets worse when the cycle time gets shorter (Buzanowski and Yang,1989). The same phenomenon has also been observed and explained by Nakao and Suzuki (1983). These results show that even a very strongly adsorbed vapor like DMMP can be desorbed by using only PSA technology. It should be noted that the PSA process conditions for PSA run 1were drastic (see Table 111). Nevertheless, complete cleanup was also achieved at conditions much more typical of PSA purification processes. The results of PSA run 2, based on a material balance, correspond to near cyclic steady state, although slightly more DMMP was present in the exhaust effluent compared to the feed and no DMMP was detected
0.4,
.
.
.
.
.
.
!
.
.
.
.
0
-
.
.
.
.
.
.
.
.
.
0 mln
0 -
5
-
10
----
0
'
'. '
'
'7 -'
.
avg. model
1
\\ 0
.
1
STEP I I
A
.
-'
- ' - I -
11
" 22
WWER OF CYCLES
Figure 5. Transient cleanup of the product effluent for PSA run 1starting from a saturated bed (see Table I11 for process conditions).
in the product effluent, indicating the bed was still desorbing DMMP. It is seen from Table I11 that y and PH/PLfor this PSA run were considerably less than those for PSA run 1, yet complete cleanup of the product effluent was achieved. The transient bed profiles of PSA run 2 starting from a saturated bed and corresponding to the end of cycle step I1 are shown in Figure 6 (solid lines) for different cycle numbers. Clearly, a cyclic steady state was being approached. Moreover, at z = 128 mm, Y/YF decreased nearly to zero indicating complete cleanup. This profile was markedly different, however, when starting from a clean bed. The transient bed profiles for this case (Figure 6, dashed lines) were also converging to a cyclic steady state which was seemingly different than that obtained from an initially saturated bed. The major difference in these two sets of bed profiles was where they changed curvature. For the case of an initially saturated bed, the region over which the bed profile changed shape (between z = 90 and 128 mm) was quite large indicating the presence of a "heel", whereas for the case of an initially clean bed, this region was very small. Clearly, in this case, the "heel" was caused
1028 Ind. Eng. Chem. Res., Vol. 30, No. 5, 1991
1
1.o
"O
I " " ' P/ F
c
\\
-
\\\
-
Y
&'
0.5
0.54
-0
0.93 -
0
1.19 - Yp :0.0
model
-
-
BED LENGTH (MM)
Figure 6. Transient gas-phase bed profiles a t the end of cycle step I1 for PSA run 2 starting from a clean bed [dashed lines correspond to cycle number (from left to right) 185,462,916, 1279, 1665,and 19361 and a saturated bed [solid lines correspond to cycle number (from right to left) 261,610,1186,and 13601 (see Table I11 for process conditions).
by the very nonlinear (rectangular) DMMP isotherm (see Figure 3). Similar results, i.e., multiple cyclic steady states in PSA processes, have been reported by Farooq et al. (1988). They suggested that the only unique cyclic steady state in PSA occurs under isothermal conditions and for feed concentrations where a linear isotherm exists. Their results are further verified in the study by Ritter and Yang (1990). Multiple cyclic steady states have been also observed in other cyclic adsorption processes, e.g., thermal swing adsorption (LeVan, 1990). These results show that if the product end of the bed becomes contaminated, it will remain contaminated. Nevertheless, they also show that when starting from a clean bed, the wave front at the end of cycle step I1 is fairly sharp and gives rise to a very clean product. Also, even for these moderate PSA process conditions, the wave front takes a long time to penetrate the bed as a result of the cyclic nature of PSA, whereas at the feed conditions of PSA run 2, a constant flow of feed to the bed would saturate it in approximately 2.5 days (180 cycles). This feature of PSA is important to defense applications as a PSA air purification process can be safely operated for a considerably longer time compared to a single-pass purification system. Effects of Process Variables on Purification: Effect of Volumetric Purge to Feed Ratio. The effect of the volumetric purge to feed ratio on the process performance was determined from the results of PSA runs 2, 3, and 4, presented in Table 111. The volumetric purge to feed ratio was varied by decreasing the purge flow rate. All other variables were unchanged. Figure 7 and Table I11 show that the product purity increased and the product recovery decreased as the volumetric purge to feed ratio increased. Purge decreased the DMMP partial pressure in the bed voids which caused DMMP to desorb. Higher purge flow rates therefore flushed more DMMP out of the bed per cycle and consumed more product. Moreover, for PSA run 2 slightly more DMMP left the column during cycle steps I11 and IV compared to what entered during cycle steps I and 11, and no DMMP was detected in the product effluent. These results agreed with results in the literature (Shendalman and Mitchell, 1972; Weaver and Hamrin, 1974); i.e., a critical volumetric purge to feed ratio (y > 1.0) exists where a larger volume of purge (compared to the feed) is necessary for complete cleanup of the product effluent. However, a small high to low pressure ratio was used which
0
300
600
TIME (SEC) Figure 7. Effect of volumetric purge to feed ratio on the cyclicsteady-state product effluent concentration history (seeTable III for process conditions).
resulted in a low product recovery for PSA run 2. It is also seen from Figure 7 that the LDF model was able to predict the cyclic-steady-state product effluent concentration history for PSA runs 3 and 4 as well as the average product concentration (see Table 111). It also predicted the complete cleanup of the product effluent for PSA run 2. Figure 8 displays the gas- and adsorbed-phase bed profiles for PSA runs 2 and 4 (PSA run 4 was at cyclic steady state). For the gas or adsorbed phases, the lower and upper profiles respectively pertain to the condition of the bed at the beginning and end of cycle step 11. Note that the adsorbed-phase bed profiles are represented by a single curve due to the irreversible isotherm. It is seen that for a small y (Figure 8B),the DMMP gasand adsorbed-phase bed profiles maintained the same general shape throughout the PSA cycle, and for z < 64 mm the bed remained saturated at the feed conditions. Also, very little desorption occurred at the cyclic steady state and considerable DMMP remained in the bed even at z = 128 mm. However, for a large y (Figure 8A), the bed profiles show that, at near cyclic steady state, DMMP was being removed from the bed where only a trace (
