I n d . Eng. C h e m . Res. 1989, 28, 564-572
564
SEPARATIONS Optimal Design and Synthesis of Homogeneous Azeotropic Distillation Sequences Jennifer R. Knight? and Michael F. Doherty* Department of Chemical Engineering, Goessmann Laboratory, University of Massachusetts, Amherst. Massachusetts 01003
A systematic procedure for optimizing homogeneous azeotropic separation sequences has been developed. T h e procedure uses an explicit design technique which eliminates the need for recycle convergence schemes. The separation of ethanol from water using ethylene glycol as the entrainer is used t o illustrate the optimization procedure. Comparisons are made with competing designs from the literature, illustrating the need to properly optimize flow sheets before drawing conclusions on the relative merits of various separation technologies. The optimization of a chemical process is an extremely important and yet often neglected step in process design. It is clearly impossible to make a rational choice among competing entrainer, sequence, and/or separation technologies unless they are compared at or near their optimal design and operating conditions. There is extensive literature on the optimization of distillation sequences for ideal mixtures, and it is standard practice to compare optimal process alternatives. In contrast, there is almost nothing available in the literature on the optimization of azeotropic distillation systems. These systems present new optimization variables such as entrainer recycle purity and entrainer-to-feed ratio, which have no counterparts in ideal systems. It is not even known whether such heuristics as using operating reflux ratios of l.2rminremain valid for azeotropic mixtures. Thus, there is a real need for optimization studies in this area so that both systematic procedures and heuristics may be developed. As an example of the poor situation that prevails in azeotropic separation technology, we note that many articles have made claims about the relative merits of competing designs for the ethanollwater separation with little regard to the fact that these designs are not being compared on an equitable basis (Barba et al., 1985; Ladisch et al., 1984; Essien and Pyle, 1983; Robertson et al., 1983; Whitcraft et al., 1983; Leeper and Wankat, 1982; Mehta, 1982; Black, 1980). Black's (1980) paper has become the standard reference for improved distillation designs against which other separation technologies are being compared. Later in the article we will compare the costs and energy requirements of our optimized sequences with those reported by Barba et al. (1985) and Black (1980), whereupon it will become clear that some of the claims made about competitive technologies should be viewed with caution. In all likelihood, the practice of comparing unoptimized process flow sheets for azeotropic separations is due, in part, to the difficulty in designing and optimizing nonideal separation sequences by the traditional methods (i.e., by simulation). In this paper we present an optimization procedure for homogeneous azeotropic separation se'Present address: Tennessee Eastman Company, P.O. Box 511, Kingsport, T N 37660.
0888-5855/89/2628-0564$01.50/0
quences which bypasses most of the difficulties associated with the simulation-based design and optimization techniques. The method is simple to implement and gives informative results. The theories and procedures developed in this article apply quite generally to nonideal and azeotropic separations. The optimization is illustrated using the separation of ethanol from water as the primary example. The separation of ethanol from water has been chosen because of the importance of ethanol as both a commodity chemical and as a blend in gasoline (Klingebiel and Coughenour, 1985; Anderson, 1985,1986; Keller, 1979) and also because there is a lot of published information that we can compare our results against. Ethanol can be separated from water to produce fuelgrade ethanol by several means. The separation by classical extractive distillation using ethylene glycol as the entrainer is discussed in this paper (see also Knight and Doherty (19861, Levy and Doherty (1986a), Doherty and Caldarola (1985), Lee and Pahl (1985), Black (1980), and Black and Ditsler (1972)). The separation can also be performed by using heterogeneous azeotropic distillation with benzene as the entrainer (Pham and Doherty, 1989; Prokopakis and Seider, 1983) or with pentane as the entrainer (Black et al., 1972). Tedder et al. (1985) propose using a combination of solvent extraction and extractive distillation. Barba et al. (1985) consider the theoretical and experimental aspects of salting out ethanol using calcium chloride. Adsorption processes have been proposed by Ladisch et al. (1984) and Robertson et al. (1983). Direct catalytic conversion of ethanol in fermentation broth to gasoline has also been proposed (Aldridge et al., 1984; Whitcraft et al., 1983).
Optimization Variables Typically, a binary azeotropic mixture can be separated in a two-column sequence using a homogeneous entrainer (Doherty and Caldarola, 1985). A preliminary column might be used to concentrate the binary mixture to near its azeotropic composition. In this section, we consider the case of an ethanol-rich feed (i.e., near the binary azeotrope) being separated in a two-column sequence in order to establish the most important aspects of the optimization 0 1989 American Chemical Society
Ind. Eng. Chem. Res., Vol. 28, No. 5 , 1989 565
!I
Table I. ODtimization Variables optimization variable symbol specification column 1 HFu secondary optimization variable enthalpy (subcooled liquid near feed-plate temperature) F, primary optimization variable feed ratio secondary optimization variable (rl = reflux ratio @mi",,)
column 2 composition composition reflux ratio
specified by design engineer secondary optimization variable (must be very high purity entrainer) rert,2 secondary optimization variable (r2 = brmin,d
Figure 1. Separation sequence flow sheet.
analysis. In addition, Black and Ditsler (1972) studied this case and we can therefore compare our results to theirs. Later in the article we consider more dilute feeds and the influence of various sequence options on the total annualized cost of the separation. For the two-column sequence shown in Figure 1, independent material and energy balances can be performed on the entire separation system, the recycle heat exchanger, each column, each condenser, and each reboiler. For a ternary mixture, the balance equations reduce to a set of 18 equations in 39 variables (Knight, 1986). Therefore, 21 variables must be specified for the system of equations to have an isolated solution. The variables chosen to be specified can be characterized as either design variables or optimization variables. Design variables are those whose values are set by market demands or the physical situation (i.e., the primary product purity or the enthalpy of a bottoms stream set to that of a saturated liquid, respectively). Once design variables are specified, their values remain constant throughout the optimization procedure. Conversely, optimization variables are ones that must be arbitrarily assigned a value (within physical limitations, of course). The values are subject to change as we proceed from the base case to the optimal design. The design of the separation sequence is carried out for a specified flow rate, enthalpy, and composition of the lower feed to the extractive column ( F L , H F L , xFL). The enthalpic states of the bottoms are set to that for saturated liquids and the enthalpic states of the distillates are set to that for subcooled liquids 10 OF above the cooling water temperature (HB,l,HB,2, HD,l,H D , 2 ) . The entrainer makeup stream is taken to be pure entrainer at ambient conditions (xE,HE), and the distillate purity for each column must be specified ( x ~ x, ~ , ~All ) .the foregoing variables are taken as the design variables in the problem. If a product purity is not dictated by market demands, however, then it is an optimization variable. The other optimization variables that must be specified are the feed ratio and recycle purity (Fr,x8,J,the reflux ratio in each column (reGI,rew), and the heat recovered from the recycle stream (Q,,or equivalently, HFu(TFu)).The optimization variables are summarized in Table I. When a preconcentrator column is used, the distillate and bottoms purity and the reflux ratio for that column are also optimization variables. With the appropriate variables specified, the overall material and energy balance equations are solved to determine the remaining dependent compositions, flows, and enthalpies.
Once the balance equations are solved, the individual columns in the sequence must be designed to meet the product specifications. Minimum reflux ratios are calculated by using the algebraic algorithm of Knight and Doherty (1986) and Knight (1986). Having calculated the minimum reflux ratio, an operating reflux ratio of say 1.2rmincan be chosen. The column design is completed by using a boundary value procedure to calculate the number of plates in each column section. It should be noted that, in contrast to performance calculations, the recycle stream in the design of extractive separation sequences poses no convergence problems. In performance calculations, the composition of the upper feed to the extractive column must be known in order to calculate the bottoms composition of the entrainer recovery column. The upper feed composition to the first column, however, depends upon the bottoms composition from the second column. Thus, a recycle-convergence scheme is necessary. This is embedded in higher level convergence schemes which are needed to determine the correct number of trays in each section of the column in order to satisfy product quality requirements (i.e., ethanol purity in the distillate). I n contrast, none of these convergence schemes are needed i n t h e design procedure presented here, thus greatly simplifying t h e problem.
Ranking of Optimization Variables As the set of optimization variables given in Table I indicates, a multivariable optimization must be performed on the separation sequence to obtain the "true" optimum. However, this level of detail is excessive for the screening out of economically unattractive sequences. Also, the accuracy to which the optimization is carried out should not exceed the accuracy of the design and economic models (Fisher et al., 1985a). In order to perform an approximate optimization of the sequence, we must first determine the set of dominant optimization variables. Consider the optimization variables listed in Table I. Because we have a reliable method for calculating the minimum reflux ratio for these separations, the heuristic rop = 1.2rmincan be applied to give a good approximation to the optimal reflux ratio. It should be kept in mind that the minimum reflux ratio may need to be multiplied by a larger factor when the minimum reflux is caused by a tangent pinch (Levy and Doherty, 1986b). A reasonable value for the temperature of the upper feed is that it approximates the temperature of the distillate. The composition of the distillate from the second column should not be a very significant variable since the separation between the water and ethylene glycol is easy. This leaves the recycle composition and the feed ratio to be considered.
566 c
Ind. Eng. Chem. Res., Vol. 28, No. 5 , 1989
2
75;
or=12*r,,
055I
,'k
\
3 r = 1 3 *
'he O f s-ea-
0 5 0 L-
1
1
35
*enperature
O
. 5
1
n
1
eo
r T n
IC
2 5
3 0
3 5
FEED RATIO
Figure 2. Total annualized cost versus feed ratio for concentrating ethanol from 85.64 to 99.8 mol 70.
----
t
0998
Table 11. Size and Cost Information for the Ethanol/Water Seoaration Given in Figure 3 annualized cost, x 106 size $/year column 1 (extractive column) shell 4.3-ft diam 0.084 80 trays 0.007 trays (actual) 2750 ft2 0.053 condenser reboiler 1635 ft2 0.042 cooling water 526540 lbjh 0.067 steam (50 psia) 13350 lb/h 0.206 column 2 (entrainer recovery column) 1.8-ft diam 0.015 shell 30 trays 0.001 trays (actual) 190 f t 2 0.009 condenser 0.019 490 ft2 reboiler 0.006 47 580 lb/h cooling water 0.058 2700 lb/h steam (300 psia) recycle exchanger 320 ft2 0.013 exchanger 2880 lb/h -0.033 steam (50 psia)
TAC Table 111. Rank and Proximity Parameters optimization variable rank Fr 5.0 7.34 XB,H~O 0.001 0.81 0.1 0.76 XD,EG 0.3 0.68 (r/rmin)l 30 F 0.13 TFC 0.3 0.05 (r/rmin)2
t
Figure 3. Flow sheet for the fuel-grade purification scheme at F , = 1.0.
For classical extractive distillation, the recycle composition is not simply an optimization between the increased cost of more trays in the second column for higher purity entrainer versus increased processing costs (due to higher recycle flow rate) for lower purity entrainer, as is the case for ideal distillations (Fisher et al., 1985b). The very high purity ethylene glycol recycle composition in the examples presented in this paper is required to meet the product specifications in the extractive column. Because the rectifying section of the extractive column operates at ethanol concentrations above the azeotrope, the water composition increases from the upper feed plate to the distillate. Therefore, low ethylene glycol purity in the recycle stream (Le,,higher water composition) is not feasible for the given product specification. A required entrainer purity of 99.99% or higher is not unrealistic. The feed ratio is suspected to be the dominant optimization variable because flow rates are often the most significant optimization variables in process flow sheets (Douglas, 1985). Figure 2 shows the importance of the feed ratio for the separation of ethanol and water to produce fuel-grade ethanol (the specifications for this sequence are given in Figure 3). The detailed equipment design equations are given in the Appendix. The cost models are taken from Douglas (1988) and are also given in the Appendix. The total annualized cost is plotted for feed ratios ranging from 0.4 to 3.5. A t each feed ratio, the minimum reflux ratio was calculated for both columns and detailed costing was done at operating reflux ratios of 1.15, 1.2, and 1.3 times the minimum. For each case, the upper feed temperature to the first column was held constant at 78 "C and the
0.547
proximity 0.35 1.00 0.84 0.28 0.33 0.25
lower feed temperature at 44 "C. The sequence produced approximately 13.5 X lo6 gal/year of ethanol product. The effect on the total annualized cost for these variations in reflux ratio is small compared to the effect caused by the variations in the feed ratio. The curve in Figure 2 is discontinuous because steam is considered to be available only at the discrete levels given in Table V. The rank-order and proximity parameters developed by Fisher et. al. (1985a) can be used to determine the dominant variables for an approximate optimization of the azeotropic separation process. The rank-order parameter is defined as
This parameter is usually insensitive to the base case design and indicates the relative importance of the various optimization parameters. The proximity parameter is defined as
and ranges from zero at the optimal value to unity far from the optimal value. It can be viewed as a well-scaled stopping criterion for the optimization procedure, since values of p , 5 0.3 frequently correspond to designs that are very close to optimal. The rank of each optimization variable was calculated by using eq 1. The base case design was performed at the specifications given in Figure 3 (recall, F, = 1.0, recycle purity = 99.999 mol 70 ethylene glycol, rOp= 1.2rmin,and other specifications as given in the figure). The size and cost information for the base case design is given in Table 11. The results of the calculations are given in Table 111.
Ind. Eng. Chem. Res., Vol. 28, No. 5, 1989 567
I:
c751 F;
';hJ 0
I
0.650
05
210
IC
2,5
~c
45
FEED RATIO
Figure 4. Total annualized cost and proximity parameter versus feed ratio for concentrating ethanol from 85.64 to 99.8 mol %.
The rank of the feed ratio is an order of magnitude greater than the rank of all other optimization variables. Therefore, we anticipate that a single-variable optimization with respect to the feed ratio should give a good approximation to the optimal design. The proximity parameters for each of the optimization variables were calculated by using eq 2 and are also shown in Table 111. The proximity parameters for the reflux ratios are small, thus showing the merit of the heuristic r = L2r- Also, the proximity parameter for the feed ratio is reasonably small because the optimal feed ratio is 0.5 (see Figure 2). However, unlike the case of the reflux ratios, this did not come about by the use of a good heuristic so much as by a good guess. Figure 4 shows the total annualized cost versus feed ratio, again for the separation of ethanol and water into fuel-grade ethanol. This curve is continuous since steam is considered to be available at continuous levels in these calculations (see Appendix). The proximity parameter for the feed ratio is also plotted. If the optimizations were carried out until the proximity parameter was less than 0.3, the sequence would be very near its minimum total annualized cost. The proximity parameter for the recycle purity in Table I11 is unity, its worst possible value. Figure 5 shows how the total annualized cost varies as a function of the recycle purity with all other parameters held constant at their base case values. Although the proximity parameter is unity, the total annualized cost of the sequence is still very close to its optimal value. The proximity parameter is so high because the total annualized cost rapidly approaches infinity as the ethylene glycol purity in the recycle approaches unity (i.e., for recycle ethylene glycol purity >99.999 mol %). As indicated by its low ranking, the total annualized cost varies little over a wide range of recycle purity. Calculating the minimum recycle purity required for a feasible separation sequence would allow the design engineer to specify a recycle purity near its optimal value (this is analogous to calculating rminand setting rOp= 1.2rmIn).The purity requirement can easily be estimated using approximate material balances. For the extractive column, assume that all the water that enters in the upper feed and that all the ethanol that enters in the lower feed leave in the distillate and that all the water that enters in
0 525
L-2 I
09975 09980 09985 09990 09995 10000
RECYCLE PURITY
Figure 5. Total annualized cost versus recycle ethylene glycol purity for concentrating ethanol from 85.64 to 99.8 mol % a t F, = 1.0.
the lower feed and all the ethylene glycol that enters in the upper feed leave in the bottoms. By use of these approximations, together with the definition of the feed ratio, the following equations are readily derived: = [XU,H2$r -k
XL,ETOHIFL
(3)
These equations rearrange to give 'U,H*O
-
XD,H~O~L,ETOH
Fr[l - XD,H201
(5)
Correspondingly, XU,EG
= 1- X U , H ~ O
(6)
For the feed ratio of unity, the equations yield 99.77 mol % as the minimum ethylene glycol recycle purity. Case studies show that the sequence is infeasible for a recycle purity of 99.75 mol % ethylene glycol but feasible for a recycle purity of 99.80 mol %, showing the validity of the estimation.
Results As well as showing the importance of the feed ratio, Figures 2 and 4 give the opitmal design for fuel-grade ethanol from a near-azeotropic feed composition. The optimal design occurs at Fr = 0.5. Comparison with Black and Ditsler's (1972) Design. Figure 6 shows the total annualized cost versus feed ratio for high-purity ethanol production (ethanol purity of 99.998 mol % at a production rate of 13.5 X lo6 gal/year). When our design and cost procedures are used on the product specifications and operating conditions given by Black and Ditsler (i.e., Fr = 3.5, rl = 1.814, r2 = 33.89), the total annualized cost of the sequence is $1.93 X 106/year. This is over 3 times the total annualized cost for the optimal design in Figure 6. Note that a large improvement
568
Ind. Eng. Chem. Res., Vol. 28, No. 5 , 1989
t I
185 -
o
/
r=12*rm,n
/
Or:j3*rm,,
I
/
/
I
/
N
I
,
)
CHANGE IN STEAM REBOILER TEMPERATURE
/
1.25
0
0.5
1.0
1.5
2.0
2.5
FEED RATIO
Figure 7. Total annualized cost versus feed ratio for concentrating ethanol from 4.2 to 99.8 mol 70 in a three-column sequence. 0 60 0
05
10
15
I
I
I
I
20
25
30
35
FEED RATIO
Figure 6. Total annualized cost versus feed ratio for concentrating ethanol from 85.64 to 99.998 mol 70.
can be made in Black and Ditsler's design by doing "good design" (i.e., calculating the minimum reflux ratio and operating reasonably close to it). Further improvement is made by optimizing over the feed ratio. On the basis of our calculations, the following algorithm is recommended for the optimal design of homogeneous azeotropic distillations. Algorithm. 1. Specify the composition, temperature, and flow rate of the process feed to the sequence. 2. Set the entrainer-to-process feed ratio, F,, in the extractive column to unity. This is often a good initial guess. 3. Set the main product purities in the distillate streams leaving the extractive column and the entrainer recovery column (e.g., ethanol and water, respectively, in our example). Normally these are determined by product quality requirements, environmental regulations, etc. 4. Set the remaining distillate compositions according to the rules given by Levy et al. (1985). 5. Set the compositions in the bottoms stream from the extractive column by taking 99.5-99.99% fractional recovery of main product (e.g., ethanol) in the distillate. Further refinement is given by Fisher et al. (1985b). 6. Set the entrainer recycle purity (Le., the bottoms composition from the entrainer recovery column) half-way between the minimum value calculated from eq 6 and unity. 7 . Set the entrainer recycle temperature to be a few degrees (about 5-15 " C ) Zielow the boiling temperature of the distillate stream leaving the extractive column. 8. Set the operating reflux ratios in each column at 1.2-1.5rmia,. Minimum reflux ratios are calculated by the method described in Knight and Doherty (1986), suitably
extended to multiple feed columns (Knight, 1986). 9. Each column in the sequence can now be designed independently by the boundary value method proposed by Levy et al. (1985), Levy and Doherty (1986a,b), and Knight and Doherty (1986). No recycle convergence scheme is required since the method allows us to make the state of the entrainer recycle stream the same at its origin and destination. 10. Cost each unit in the sequence and optimize the total annualized cost of the sequence with respect to the dominant optimization variables, which for the example studied was F, alone. Fermentation Broth to Fuel-Grade Ethanol. The feed to the separation sequence for Figures 2-5 is 85.64 mol % ethanol. In order to produce fuel-grade ethanol from fermentation broth, however, a feed stream composition of say 4.2 mol % (10 wt %) ethanol must be considered. For such dilute feeds, it is always more economical to preconcentrate the process stream up to the binary azeotrope and feed this to the two-column sequence shown in Figure 3 than to feed the dilute stream directly to the two-column sequence. The resulting three-column sequence removes most of the water as a bottoms stream rather than a distillate stream, thereby saving substantial amounts of energy. The total annualized cost as a function of feed ratio for the three-column sequence is shown in Figure 7 . The two-column sequence is about 400% more costly (see Knight (1986)). An increasing interest is being paid to the amount of energy (i.e., heat input to the reboilers) necessary to purify ethanol. The impetus for attention for the energy requirement arises from the use of ethanol as a fuel extender in ethanol-gasoline blends. For this reason, Figure 8 is included to show the energy input to the reboilers versus the feed ratio for the three-column configuration. Note that the minimum in the heat required corresponds to the minimum in the total annualized cost (i.e., they occur at the same feed ratio).
Ind. Eng. Chem. Res., Vol. 28, No. 5, 1989 569 Table IV. Comparison of Processes from the Energy Requirement Point of View specific energy consumption, concn range, type of process Btu/aal EtOH wt % Black (1980) distillation processes 6.4-98 36 370 low-press dist. azeotropic dist. 6.4-dry EtOH pentane 30 910 6.4-dry EtOH benzene 34 690 6.4-dry EtOH diethyl ether 38 720 extractive dist. 29 060 6.4-dry EtOH gasoline 6.4-dry EtOH ethylene glycol 96 600 Barba et al. (1985) salting out 14 200 7.5-99 Douglas and Feinberg (1983) nondistillation processes 10-98 solvent extraction 17 800 8-99.5 membrane pervaporation 13 000 optimized extractive distillation designa 10-99.9 3-column sequence 19 000 6.4-99.9 22 400 3-column sequence 6.4-99.9 3-column sequence at rmin 19 800 10-99.9 2-column sequence 83 000 DEnergy input to the reboilers minus the heat recovered from the recycle stream heat exchanger.
t
22,000
19,OOOL 0
I
I
I
I
I
0.5
1.0
1.5
2.0
2.5
FEED RATIO
Table V. Utility Costs steam, psia 50 100 300 500 cooling water
temp, O 740 787 877 926
R
cost (1985), $/lo00 lb 1.43 1.95 2.73 2.86 0.016
Barba et al. (1985) present a table comparing the energy requirements of their separation with those reported by Black (1980) and the Department of Energy (Douglas and Feinberg, 1983). These results as well as the energy requirements for the optimal two- and three-column sequences are summarized in Table IV. As stated previously, these comparisons should be viewed cautiously since we do not know how close to optimal the competing designs are. However, our optimal design, using ethylene glycol as an entrainer, is much more competitive (on an energy basis) with the other separation schemes than is Black's (1980) design. The energy requirement for the optimal three-column sequence at minimum reflux is reported in order to give the minimum energy requirement (i.e., without energy integration) for the ethylene glycol entrainer. On a cost basis, we expect our design to be quite competitive with the other technologies since they require expensive capital equipment such as crystallizers and membranes. Effect of Ethanol Purity. A major concern about alcohol blended with gasoline is that water will preferentially absorb in the alcohol. This can cause a phase separation into a water-rich alcohol phase and a gasoline phase. The tolerance for water depends upon such things as the alcohol used and the temperature. Figure 9 shows the effect of ethanol purity on the total annualized costs. These designs are for the three-column configuration operating at a feed ratio of 1.0. The total annualized cost increases sharply as the purity changes from 99.8 to 99.998 mol % . The corresponding energy input requirements are plotted in Figure 10. The energy requirements are almost linear as the ethanol purity ranges from 96.0 to 99.998 mol %; hence, the sharp rise in the total annualized costs at
Figure 8. Energy requirements versus feed ratio for concentrating ethanol from 4.2 to 99.8 mol % in a three-column sequence. 1.401
1.35
-
1.151 0.95
I
I
I
I
I
0.96
0.97
0.98
0.99
1.00
ETHANOL PURITY (Mole Fraction)
Figure 9. Total annualized cost versus ethanol purity for concentrating ethanol from 4.2 to 99.8 mol % in a three-column sequence with F, = 1.0.
high purity is due to the rapidly increasing number of plates required to achieve the separation.
Conclusions A systematic optimization procedure for separating azeotropic mixtures has been developed. The procedure is an integral part of the synthesis and design scheme
570 Ind. Eng. Chem. Res., Vol. 28, No. 5, 1989 20,000
1
95
L
19,500
0 \
5
t
18,500
Q
z
5W
I
3
-k
851
5i W
I
I-
z
W
18,000
2 J
1
75’
17,500
1
17,000 0.95
0.96 0.97 0.98 0.99 1.00 ETHANOL PURITY (Mole Fraction)
65
I
1
Figure 10. Energy requirements versus ethanol purity for concentrating ethanol from 4.2 to 99.8 mol 70 in a three-column sequence with F, = 1.0.
30-
25-
2.0 -
I
750
I
I
I
850
I
I
950
TEMPERATURE ( R )
Figure 12. Latent heat versus steam temperature.
simplify the optimization procedure. Second, the use of an explicit design technique simplifies the calculations necessary when proceeding from the base case to the optimal design. The separation of ethanol from water was studied in detail because of its importance as a commodity chemical and fuel blend. The feed ratio is the most significant optimization variable for this system, and it is expected to be for most other systems. The importance of doing good design and optimization was shown through the marked improvement on Black and Ditsler’s (1972) separation sequence and the corresponding merit of this design relative to comparisons previously reported.
Acknowledgment The authors are grateful for research support provided by the National Science Foundation (Grant CPE-8406983). Nomenclature
05t
O
650
750
850
950
T
TEMPERATURE ( R )
Figure 11. Cost versus steam temperature.
because it is clearly impossible to make a rational choice among several candidate entrainers and/or sequences unless they are compared a t their optimal design and operating conditions. The major advantages of the design and optimization procedure proposed in this work are 2-fold. First, by knowing the physical limits of the process (i.e., rmin), reasonable heuristics can be implemented to
A = area B = bottoms flow rate C = number of components in a mixture or cost D = distillate flow rate or column diameter f = cost function F = feed flow rate F, = molar feed flow rate ratio (entrainer feed flow rate/ process feed flow rate) H = molar enthalpy or column height M&S = current cost index p = proximity parameter (eq 2) Q = heat duty r = reflux ratio or rank-order parameter (eq 1) TAC = total annualized cost T L M = log mean temperature difference V = vapor flow rate (not necessarily constant) V, = maximum vapor velocity, ft/s U = overall heat-transfer coefficient xi = composition of species i in the liquid phase or optimization variable y i = composition of species i in the vapor phase
Ind. Eng. Chem. Res., Vol. 28, No. 5, 1989 571
A=-
Greek Symbol p = density
(A-5) UATLM The cooling water inlet temperature is 85 O F and outlet temperature is 105 O F . The distillate (and reflux stream) temperature is taken to be 104 O F in these examples. The overall heat-transfer coefficient is 100 Btu/(ft2 h O F ) for the condensers and 150 Btu/(ft2 h O F ) for the reboilers. The cost of the heat exchangers is given by
Subscripts B = bottoms product CAP = capital cond = condenser cw = cooling water D = distillate product E = entrainer EG = ethylene glycol ETOH = ethanol ex = recycle heat exchanger ext = external F = overall feed FL = lower feed FU = upper feed HE = heat exchanger H20 = water L = lower or liquid max = maximum min = minimum OP = operating reb = reboiler S = column shell st = steam T = trays U = upper V = vapor
CHE
7) PL - Pv
112
The cost equations used throughout the separation system are simplified versions of Guthrie's (1969) correlations (Douglas, 1988). For atmospheric pressure, a carbon steel construction, and sieve plates, the installed cost of a column's shell and trays is given as
cs = M&S 101.9D'
[email protected] 280
=
M&S 101.3A0.65(2.29+ Fc) 280
(A-6)
where F, = 1.0 for a floating head condenser and Fc= 1.35 for a kettle reboiler. The utilities available and their costs are given in Table V. Figures 11 and 12 show the cost and latent heat of vaporization versus temperature for steam available over a continuous range. Recycle Exchanger. The heat load of the recycle exchanger has been determined by specifying the temperature of the recycle feed to the double-feed column (at 351 K) and calculating the enthalpic difference between the subcooled and saturated liquids. The area of the exchanger has been calculated using an overall heat-transfer coefficient of 100 Btu/(ft2 h O F ) . A credit for an equivalent amount of low-pressure steam has been given. Total Annualized Cost. The TAC for the separation system is given by TAC = C c ~ p / 3+ Cop (A-7)
Appendix: Design and Costing Information In order to determine the most economical separation system (or a handful of separation systems of roughly equivalent economic merit), detailed design and costing must been done. The design and costing procedures and equations used in this work are summarized below. Distillation Columns. The number of trays in each distillation column is calculated by determining the intersection of the column profiles and dividing the total number of trays by an overall tray efficiency equal to 0.6. The double-feed column is designed by assuming lower feed tray locations and determining the intersection of the middle section profile with the rectifying section profile. The lower feed plate location is varied until the lowest number of plates is needed to accomplish the separation. The column is designed to operate at 80% of the maximum vapor velocity with a 24-in. tray spacing. The maximum vapor velocity is given by (Peters and Timmerhaus; 1980, p 718) V, = 0.3(
Q
(-4-3) (A-4)
Condensers and Reboilers. The exchanger areas are determined by
where CCAP
= cS,l +
CT,l
+ Ccond.l +
Creb,l
Ccond,2
+ c S , 2 + CT,2 + + Creb,2 + cex (A-8)
COP = Ccw,l + C s t , l + C c w , ~+ C s t , ~- Cst,ex (-4-9) An example of the detailed design and costing results is given in Table I1 for the fuel-grade ethanol separation at a feed ratio of 1.0. Registry No. EtOH, 64-17-5; ethylene glycol, 107-21-1.
Literature Cited Aldridge, G. A.; Verykios, X. E.; Mutharasan, R. Ind. Eng. Chem. Process Des. Deu. 1984,23,733. Anderson, E. V. Chem. Eng. News 1985,63(16), 9. Anderson, E. V. Chem. Eng. News 1986,64(11), 14. Barba, D.; Brandani, V.; Di Giacomo, G. Chem. Eng. Sci. 1985,40, 2287. Black, C. Chem. Eng. Prog. 1980, 76(9), 78. Black, C.; Ditsler, D. E. Azeotropic and Ertractiue Distillation; Advances in Chemistry Series 115; Gould, R. F., Ed.; American Chemical Society: Washington, DC, 1972; p 1. Black, C.; Golding, R. A.; Ditsler, D. E. Azeotropic and Extractive Distillation; Advances in Chemistry Series 115; Gould, R. F., Ed.; American Chemical Society: Washington, DC, 1972; p 64. Doherty, M. F.; Caldarola, G . A. Ind. Eng. Chem. Fundam. 1985,24, 474. Douglas, J. M. AIChE J . 1985,31,353. Douglas, J. M. Conceptual Design of Chemical Processes; McGrawHill: New York, 1988. Douglas, L.; Feinberg, D. Evaluation of Nondistillation Ethanol Separation Process. SERI/TR-231-1887, DE 83011994, 1983; US. Department of Energy, Washington, DC. Essien, D.; Pyle, D. L. Process. Biochem. 1983, 18, 31. Fisher, W. R.; Doherty, M. F.; Douglas, J. M. AIChE J . 1985a,31, 1538. Fisher, W. R.; Doherty, M. F.; Douglas, J. M. Ind. Eng. Chem. Process Des. Deu. 1985b,24,955. Guthrie, K. M. Chem. Eng. 1969, 76(6), 114. Keller, J. L. Hydrocarbon Process. 1979,58(5), 127. Klingebiel, W. J.; Coughenour, G. E. AIChE Annual Meeting, Chicago, IL, Nov 1985. Knight, J. R. Ph.D. Dissertation, University of Massachusetts, Amherst, MA, 1986.
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Peters, M. S.; Timmerhaus, K. D. Plant Design and Economics f o r Chemical Engineers, 3rd. ed.; McGraw-Hill: New York, 1980. Pham, H. N.; Doherty, M. F. Chem. Eng. Sci. 1989, in press. Prokopakis, G. J.; Seider, W. D. AIChE J . 1983, 29, 49. Robertson, G. H.; Doyle, L. R.; Pavlath, A. E. Biotechnol. Bioeng. 1983, 25, 3133. Tedder, D. W.; Taefik, W. Y.; Poehlein, S. R. 4th Symposium of Energy Conservation and Technology, Knoxville, TN, Oct 1985. Whitcraft, D. R.; Verykios, X. E.; Mutharasan, R. Znd. Eng. Chem. Process Des. Deu. 1983, 22, 452.
Received for review August 1, 1988 Accepted December 5, 1988
Separation of p -Xylene and Ethylbenzene from C8 Aromatics Using Medium-Pore Zeolites Tsoung Y. Yan Central Research Laboratory, Mobil Research and Development Corporation, P.O. Box 1025, Princeton, New Jersey 08540
Medium-pore ZSM-5 zeolites were found t o be excellent for the separation of p-xylene and ethylbenzene from C8 aromatics. Their adsorption capacity and selectivity for p-xylene were high. T h e selectivity for p-xylene over ethylbenzene, Pple,was 5.5 at the optimum Si02/A1203of 700. The competitive adsorption capacity for p-xylene from a simulated reformer product was 120 mg/g. The p-xylene selectivity, Pple, increased sharply and then leveled off when p-xylene loadings reached 50 and 90 mg/g, respectively. T h e high p-xylene selectivity and its dependence on p-xylene loading are believed to be related to the unique packing of p-xylene in the crystalline cavities. The C8 aromatics are important raw materials for petrochemicals. The most important isomer is p-xylene for terephthalic ester production. o-Xylene, m-xylene, and ethylbenzene are raw materials for phthalic anhydride, isophthalic acid, and styrene, respectively. Because of their close boiling points, their separation by distillation is impractical and uneconomical. Separation processes based on other principles have been developed and reviewed (Wada, 1974; Milewski, 1981). Selective adsorption by the use of a zeolitic adsorbent is generally considered to be the most economical among the industrial processes for separation of Ca aromatics. The Parex process by UOP (Boughton, 1983) and the Asahi process by Asahi Chemicals (Seko et al., 1979) are both based on zeolitic adsorbents. The Parex process has been successfully operated since 1971; 34 Parex units have been licensed throughout the world (Boughton, 1983). Seko et al. (1979) pointed out that, for the separation of xylenes that have large molecular diameters, it is essential to use large-pore-size crystals of natural faujasite, zeolite X, or zeolite Y. On the basis of the patent literature, the zeolite used in the Parex process appears to be metalion-exchanged Y (Neuzil, 1976). Santacesaria et al. (1982) also found that potassium-exchanged Y is a good material for the separation of p - and m-xylenes. Milewski and Berak (1982) have studied the effects of preparation procedures on the selectivity for xylene isomer separation of potassium-barium-exchanged natural faujasite. Due to a disproportionately large demand, p-xylene is removed from the Caaromatic mixtures and the rest of the stream is recycled to the isomerization unit for reequilibration. In the typical isomerization process, ethylbenzene conversion is more difficult and less selective to p-xylene than o- and m-xylenes. Some processes have been developed to overcome this problem. On the other hand, ethylbenzene has a ready market for styrene production. Unfortunately, it has been difficult to separate ethyl-
benzene from the mixtures along with the p-xylene. In fact, p-xylene separation is limited by ethylbenzene contamination in the conventional separation based on elution chromatography. Thus, in order to improve xylene separation and to separate ethylbenzene from the mixture, an adsorbent of high p-xylene selectivity relative to ethylbenzene is required. The characteristics of improved adsorbents for xylene separations are high selectivity for p-xylene over ethylbenzene, high adsorption capacity, and insensitivity to variation in feed composition and impurities. Much progress has been made in the industry to improve natural faujasite and zeolite Y through modification and preparation procedures. Venuto and Cattanach (1971) of Mobil Oil discovered that p-xylene can be separated from the mixtures of o-, p - , and m-xylenes using ZSM-5 zeolites as a selective adsorbent. Dessau (1980) also showed that the ZSM-5 zeolite selectively adsorbs p-xylene in the mixtures of o- and p-xylenes with a para-to-ortho selectivity of about 5. In this study, the potential of using medium-pore-size zeolites, instead of large-pore zeolites, for xylene separation was explored. On the basis of the equilibrium adsorption data, the proprietary zeolite ZSM-5 was found to be an excellent adsorbent for xylene separation.
Experimental Section Chemicals. The chemicals p-xylene, o-xylene, ethylbenzene, mesitylene, and 1,2,3,5-tetramethylbenzene were the finest commercial grades and were pretreated over fresh ZSM-5 catalyst before use. Adsorbents. ZSM-5 zeolites were prepared according to the general procedure of Argauer and Landolt (1972). The zeolites were crystallized from mixtures containing a tetrapropyl ammonium compound, sodium oxide, alumina, silica, and water. Through synthesis, the Si02/A1203 ratios varied between 70 and 1600 (Table I). The synthesized ZSM-5 was calcined in Nz at 1 OC/min to 500 "C
0888-5885/89/2628-0572$01.50/0 0 1989 American Chemical Society
