Ind. Eng. Chem. Process Des. Dev. 1986, 25, 687-693
687
of NPAM (Figure 2) was effective in mixing fine particles. In an attempt to find a way of improving the mixing efficiency, the mixing vessel was divided into two sections, a column and an air tank, and they were connected to each other with a flexible pipe to simulate the effect of through flow. Comparison of mixing efficiency was made between the separate type (column and air tank) and a single column type mixer of the same volume. Observation with the eye as well as the quantitative study revealed that for a given volume, it is more advantageous to have a separate air tank than to have a single column when particles of large cohesiveness are to be mixed, but the effect of the separate tank is rather small when particles of small cohesiveness are to be mixed. A new stochastic model was developed to simulate the mixing process. It was found that the model can describe the mixing process qualitatively provided that the average air velocity was below 0.20 m/s.
S = cross-sectional area of the column, m2 t o = time span during which mixing effectively occurred, s ii = average superficial velocity (eq l), m/s V = volume of column minus particles, m3 V, = volume of column plus flexible pipe, m3 Vb = volume of separate air tank, m3 V, = V, + v b , m3 W = mass of particles, kg W , = maximum mixable mass of particles, kg x = volume fraction of undyed particles in the upper bed x, = x when perfect mixing is achieved
Nomenclature
Akiyama, T.; Peters, L. K.; Kageyama, S.; Hosoi, M.; Yokota, I.; Kono, M. Ind. Eng. Chem. Process Des. Dev. 1982. 2 1 , 664. Akiyama, T.; Tada, I. Ind. Eng. Chem. Process Des. Dev. 1984, 2 3 , 737. Akiyama, T.; Tada, I. Ind. Eng. Chem. Process Des. Dev. 1985, 2 4 , 961. Akiyama, T.; Zhang, J.; Egawa, M.; Kojima. H. Funfa; Kogaku Kaishi 1985, 22, 215. Carr, R. L., Jr. Chem. Eng. 1985, 18, 163. Cox, D. R.; Mlller, H. D. "The Theory of Stochastic Processes"; Wiley: New York, 1965; Chapter 3. Howard, R. A. "Dynamic Probabilistic Systems"; Wiley: New York, 1971; Chapter 10.
= flowability plus floodability k = volume ratio of the lower bed to the upper bed IZ = number of sampling points N = number of air injections P = transition matrix defined by eq 3 P = atmospheric pressure, Pa APi = Pi - Po, Pa AF', = Pf- Po, Pa Pi, Pf= initial and final pressures, respectively, Pa P,, = probability that a process in the initial state i will occupy state j in its next transition fwd
Greek Letters a = probability, PI2 /3 = probability, PZl y = probability, P32 Pb = bulk density of particles, kg/m3 u = variance defined by eq 3 = probability matrix defined by eq 5 L i t e r a t u r e Cited
Received for review March 11, 1985 Revised manuscript received November 1, 1985 Accepted November 15, 1985
Plant Design and Optimization for the Production of Furfural from Xylose Solutions Manuel Lbzaro, JosQ Marther-Benet, and LUISPulgjaner E.T.S.I . I.& Universidad Polit6cnica de Cataluiia, Diagonal, 647-08028 Barcelona, Spain
A general plant design experiment-based methodology is proposed, which minimizes costly pilot tests, thus ensuring the reliability and minimum cost of the design. The method described is applied to the design and optimization of a plant for the production of furfural from xylose solutions available as byproducts from various wood-processing industries. Critical variables are the type and concentration of catalyst, temperature and pressure of operation, initial concentration of xylose, furfural yield, and residence time in the reactor. The plant design is carried out by simulation based on the conditions obtained from the minimized experimental set. Further refinement of the design allows for the processing at high temperature without simultaneous removal of the product. The minimum operation and investment costs are also considered for optimized final plant design, which includes furfural recovery by liquid-liquid extraction with substantial improvement in the overall process economics.
The interest in furfural production has increased in recent years because of the multiplicity of products that can be derived from the furans, specially the difunctional aliphatic and olefinic types and lysine, because of the refining of rare earths and other metals, and because furfural is still the most economical source of furans. Furthermore, the production of furfural might be economically expanded by using as prime materials agricultural wastes, similar to those now used, from various xylose-containing solutions that are byproduct streams from industries using hardwoods, as already reported by Harris and Smuk (1961). 0196-4305/86/1125-0687$01.50/0
However, the processing profitability of many crude xylose solutions to furfural is questionable due to the uncertainty of many factors involved in the process economics evaluation and to poor estimates in the overall operating conditions required for maximum yield and energy costs minimization. The design problems start with a complex reaction mechanism that involves furfural destruction in acidic aqueous media, which is commonly used as the catalyst (Williams and Dunlop, 1948). Although further studies report a more detailed analysis on xylose in acidic solutions reacting under isothermal conditions over a broad range of concentration, acidity, and temperature (Root et 0 1986 American Chemical Society
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Ind. Eng. Chem. Process Des. Dev., Vol. 25, No. 3, 1986
al., 1959), plant design and optimization have been restricted by limited data and design tools currently available. Even the Quaker Oats process, which dominates the US market and uses a direct conversion of biomass residue to furfural, suffers from low yield. To overcome this situation, the present study has undertaken a different approach to plant design and optimization which includes both experimental optimization of reaction conditions and selection of the optimum separation process taking into account the overall investment and operation costs. Experimental design includes a modified Evolutionary Operation method (EVOP) (La War0 et al., 1983) that ensures the adjustment to the optimum range of operating conditions with a minimum set of experiments. Final plant optimization has been carried out by u+ng C%mpui,T-&+Dwiig,. id
General Comments on the Process Production of furfural from agricultural wastes consisting on xylose-containing solutions that are byproduct streams from some industries using hardwoods has been reported by several authors (Williams and Dunlop, 1948; Kirby, 1948; Kobayashi, 1952). Throughout the discussion that follows, it is,assumed that the aqueous xylose solution would be derived by the prehydrolysis of hardwood with dilute acidic solution, the purpose of this hydrolysis being to separate the xylosecontaining hemicellulose from the resistant cellulose and lignin. The resulting solution contains many constituents, primarily xylose, glucose, and water. This study concentrates in the economic evaluation of obtaining a maximum yield of furfural from such a solution. The most important production costs, other than xylose (which strongly depends on the form used, as byproduct solution, or on the form of pentosan), are acid and process steam costs. Increasing the acid concentration a t low acidity levels results in significantly higher yields, but this effect levels off rapidly a t higher acidity concentrations. This increase means also a decrease in reactor size, although with little effect on the overall plant cost. But higher acidity levels tend to increase the percentage of solid byproducts. There is an economic acid-to-solid ratio to be determined by balancing higher acid cost against greater product return and associated operating conditions (Harris and Smuk, 1961). The importance of incorporating efficient heat utilization into the plant design becomes apparent from the fact that increasing yields of furfural correspond to the decreasing xylose concentration and increasing temperature, both factors resulting in increased steam consumption due to a nearly proportional increase in the plant and reactor sizings. An additional problem to efficient heat recovery is the fouling character of reacting sugar solutions which requires that the plant be designed to transmit heat only across surfaces that are noncontacted by the reacting solution. The use of isothermal batch reactors with direct-injected steam for heating has been proposed to be within economical limits by selecting a recovery process in which low-pressure steam can be utilized to satisfy the total steam requirements of the process. However the solution presented in this work chooses a continuous process, with a direct-injected steam-heatingsystem, characterized by high throughput and low reaction equipment costs, thanks to a proper temperature selection and careful design of the heat recovery and separation systems. Amongst the various methods proposed for the recovery of furfural from aqueous solutions are solvent extraction, distillation, and selective adsorption on solids. Here again,
Y
8
-v
Y
U
0 BALL VALVE da STOP-COCK
ADJUST-COCK
L.1 NOKRETURN VALVE FILTER
Figure 1. Diagram of experimental apparatus.
although distillation has been proposed as the most practical, the economical and technical evaluation carried out in this study shows that it may not be the most adequate when processing at low xylose concentrations. Liquid-liquid extraction has been preferred and found to be technically more appropriate and within economically attractive fringe benefits.
Experimental Procedure It was a research objective to study both experimentally and mathematically the furfural production from xylosecontaining solutions over an specific range of operating conditions. The kinetics of the acid-catalyzed conversion of xylose to furfural were studied by Root et al. (1959) over a broad range of selected variables. In this work, the specific range of operating conditions of commercial use were chosen to further investigate and optimize the kinetic model, using modified evolutionary operation methods for planning experiment design procedures. Thus, it was hoped to gain sufficient understanding of the complex physical and chemical phenomena to allow for the development of suitable models for final plant design and optimization. Materials and Methods. Furfural production was experimentally studied in a versatile microplant CATATEST (Geomechanique, Paris) which was specifically modified and highly automatized in our laboratory to allow for precise high-pressure liquid-phase operation. The microplant is equipped with a 180-cm3 inox (AIS1 316) tubular reactor, high-pressure feeding pump operating within the range 25-750 cm3/h, and separation unit. There is also auxiliary equipment for temperature control in the reactor by microcomputer, fluid level, and pressure control systems. Figure 1shows the diagram of the experimental setup and Figure 2 a general view of the modified microplant. Xylose solutions were prepared from commercial-grade xylose (Panreac).
Ind. Eng. Chem. Process Des. Dev., Vol. 25, No. 3. 1986
I Variable
change
Surface
response
689
I
calculation
Figure 2. Modified microplant view. Table I. Experimental Values Used in the Tests set T, K CH+,equiv g/L Q,L/min CXO,mol/L 0.35-0.4 0.006-0.008 1 473-483 0.02-0.05 0.0055-0.007 0.4 0.02-0.03 2 486-493 0.004-0.006 0.4 0.015-0.025 3 483-489 0.4 0.005 4 485 0.02
Although initially six variables were considered (type and concentration of catalyst, temperature and pressure operating conditions, initial concentration of xylose, furfural yield, and residence time), preliminary studies reduced the number of critical design variables to the following four: initial xylose concentration, Cxo (mol/L), feed flow or residence time, Q (L/min), catalyzer concentration, CH+(equiv g/L) and reactor temperature, T (K). Reactor size was reduced to 130 cm3 by filling it with inert material (Raschig rings) to widen the operational range of the residence time. Table I shows the range of values used in each set of experiments. As stated before, the boundaries for each variable were established from data reported in the literature (Root et al., 1959; Harris and Smuk, 1961) restricted to the range of industrial use commonly found a t present. Experimental design toward the best operating conditions involves an optimizing procedure that uses surface response search techniques incorporating Ridge Analysis, thus restricting the searching to spherical bounded regions. The sphere radius is calculated as
@ = S X
(1)
where
x i being the value of variable i, fithe mean, and aithe associated standard deviation. The method ensures the extraction of useful information in a minimum number of steps. Detailed information on this procedure has been published elsewhere (LBzaro et al., 1983). The algorithm used can be summarized in the following steps: (1)A two-dimensional surface response is obtained from the experimental data, and its accuracy is verified by regression analysis. (2) The eigenvalues and eigenvectors of the surface response equation are found by the Jacobi method and ordered by increasing value. (3) The interval is calculated where a valid surface response is obtained. (4) Lagrange multipliers are used to locate the constrained maxima toward the optimum operating conditions. For an specific radius, the maximum of the surface response is evaluated. (5) Once the sequence of values of variables as a function of the sphere radius is obtained, a new cycle is started moving toward the optimum. The computation sequence is shown in Figure 3.
1 Eigenvalues calculation
I
Ridge analysis
I
Find next cicle values
O L & 1
ata in
Figure 3. General logic flow chart.
Sampling Procedure and Analysis. Reaction rate data were obtained from solutions reacting isothermally in a continuous process a t 5-min intervals. The selected sampling period proved to be adequate to study the transient phenomena in the conversion mechanism toward xylose formation and at the same time provided an accurate evaluation of the steady-state operating conditions. To avoid the acid-catalyzed destruction products formation, a heat exchange was incorporated at the exit of the reactor to cool down the product stream. A hypodermic calibrated syringe was used to remove an exact amount from the well-shaken ampules containing the sampled solutions from the reactor. Gas chromatography (DAN1 6800), equipped with a flame detector, was used to determine the concentration of furfural. Component separation was good using a column filled with Carbowax 20M (15%) in Chromosob W80-100 mesh with 2% (wt) KOH, at 423 K operating temperature. The residence time for the appearance of furfural was 5 min, the total analysis time being less than 15 min. Plant Modeling and Simulation. The final objective of this study is to develop a commercial process with an optimum arrangement and sizing of process units operating at their best performanceto ensure the optimization of the overall investment and operating costs of the plant. This calls for the calculation of the complete mass and energy balance (heat recovery taken into account) and eventually the recycle loops that would recover valuable solvents or unreacted materials. The solution approach to this problem has been the mathematical model building of the entire process, which includes (a) linear and nonlinear programming techniques that will ensure high product yield (module RIDGE), (b) separation and energy recovery calculations (PROCESSby Simulation Sciences), and (c) a
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Ind. Eng. Chem. Process Des. Dev., Vol. 25, No. 3, 1986 I
I
I
I
u
1
1
-
1.0
1 .o
2.0
Figure 4. Variation of the objective function (a) and operating Conditions (b) in the optimum ridges for set 1.
investment and operational cost evaluation module (COST, FuROPTI, FUROPTID, FURREX, and FURREC). Modeling and optimization programs have been run in a VAX 780 series computer.
Results and Discussions Experimental Optimization of Reactor Operating Conditions. The first stage consisted in selecting the initial operation conditions. For the reasons stated before, the boundaries used for each variable are reported in Table I (set 1). The objective function was to maximize the gross profit (B)per xylose amount in the feed (W) S=B/W (3) were B is defined as the furfural sale - cost of reactants - energy cost - pumping cost. After 20 experiments, the objective function was in the range of 0.0304036$/mol of xylose. The values obtained indicate significant variations with respect to those reported in the literature. Therefore, an experimental design was developed to ensure the optimum operating conditions. The methodology uses a modified EVOP and Ridge analysis (Liizaro et al., 1983). Results obtained (Figure 4) indicate that the direction of the optimum moves toward an increase in T and CX,, while CH+and Q should decrease. Further experiments at smaller intervals and increasing values of the sphere radius over 2 indicate that a better objective function is always obtained at the upper limit of Cxo. Therefore, the xylose concentration is set at its maximum. This reduces the number of variables to 3. The progress toward the optimum at this stage is shown in Figure 5. There is a slight improvementin the objective function, and the new direction sets the boundaries as shown in Table I (set 3). The results of this set are shown in Figure 6. Now the objective function is practically constant which means that the accuracy of the method with the restrictions imposed cannot discriminate further, reaching the final operating conditions indicated in set 4. Considerations on the Tubular Beactor Conversion Rate. The results obtained after experimentation, as described before, in general agree with the mechanism proposed by Root et al. (1959) as follows: the reaction path can be described as II
xylose -!-
intermediate products
4 Dz
-I
-2.01
-
furfural
"
D,
I
where all the components are in the liquid phase, D1and
2.0
R
Figure 6. Variation of the objective function (a) and operating conditions (b) in the optimum ridges for set 2. 3.84,
1
I
I I
I
1
4
3.761 2.0
-
I
I
b
-
-LO/-
,
I
1 .o
,
, 2 .o
1 R
Figure 6. Variation of the objective function (a) and operating conditions (b) in the optimum ridges for set 3.
Dzare destruction products, and the reaction takes place in the presence of sulfuric acid as the catalyst. The overall kinetics can be represented by the general correlation equation (4)
where = Ci/Cxodenotes the concentration of component i related to the initial concentration of xylose (Cxo)in the d b are correlation coefficients for the reaction destruction and intermediate products, respectively, which are temperature and xylose concentration dependent,
b = f2(T,Cx)
(6)
and d is a correlation coefficient which is temperature and acid concentration dependent d = f3(T,CH+)
(7)
The experimental results obtained show that a furfural yield higher than that predicted in previous studies could be obtained, as it appears in Table 11. Therefore, an improved correlation equation was considered by introducing in eq 4 a new correction factor d l dl = f4(tR,T)
(8)
Ind. Eng. Chem. Process Des. Dev., Vol. 25, No. 3, 1986 691 Table 11. Accuracy Test for the Kinetic Model" CH,equiv 4,mol/L g/L Cp, mol/L t , min T, K 0.116 0.02 0.145 18 487 0.132 0.05 0.132 10 482 0.160 0.02 0.206 13 474 0.176 0.130 12 491 0.02 0.173 0.02 0.151 6 490
-
12
C&, mol/L 0.126 0.129 0.175 0.130 0.155
" C" = theoretical concentration obtained from the mechanism proposed by Root et al. (1959). C = experimental concentration. C' = theoretical concentration obtained by using parameter dl. 1.4
1
d
2
3 4 PRODUCTION. ( t / h )
Figure 9. Capital investment vs. furfural production.
10
a
0.2 0.0
w c
1
z 4 -
2 -
I
1
0
5
10
I
I
0 -
15
I
TfME,lMINUTESl
Figure 7. Correlation coefficient vs. residence time and temperature. AZEOTROPE COLlMN
REACTOR
~
9
J -
2
4
3
PRODUCTION
I
(t/hl
Figure 10. Net profit at various furfural production levels. A 10% uncertainty (prime materials costa, production performance, stock level, diverse supplies, etc.) has been allowed to calculate curve b. c Z
OMYDRATINC,
I
1
1.0
c
I
FURFUR& WASTE SLURRY
Figure 8. Flow sheet of the process using azeotrope distillation. 0
which depends on the reactor temperature and residence time (Figure 7) to obtain 0
I
The value of dl was adjusted experimentally and proven to give substantially higher accuracy when introduced in eq 9. The precision of the results obtained by the improved model equation against a set of experimental data is shown in Table 11. Concentration and Purification Stage. The furfural recovery process includes various methods proposed by several authors as reported by Harris and Smuk (1961). In any case, the aqueous solution leaving the reactor with 0.15-0.2 mol/L furfural content requires a concentration stage that depends on the conditions set in the reactor. Plant simulation has been carried out by using alternative schemes which have also been economically evaluated, leading to two basically different configurations: one uses azeotrope distillation with flash separation, while the other employs liquid-liquid extraction which substantially improves the overall design. Both alternatives are analyzed and discussed in what follows. Azeotrope Distillation with Flash Separation. This method was proposed as the most practical by Harris and
1
2
P R O3O U C T I O N ,
( t4/ h l
Figure 11. Profitability of the plant ab various furfural production levels. Curve b has been calculated assuming a 10% uncertainty as in Figure 10. The broken line indicates the break-even profit level.
Smuk (1961). Recovery is carried out in two towers: an azeotrope tower and dehydrating tower. The azeotrope can be broken by condensing the distilled solution, the condensate separating into two phases, one containing 8% and the other 84% furfural. The dilute phase is returned to the azeotrope tower as reflux, and the furfural-rich phase is passed to the dehydrating tower where it is concentrated to anhydrous furfural (Figure 8). The economic evaluation of this method shows that azeotrope distillation is very expensive. This equipment accounts for about 50% of the total installed plant equipment cost. Furthermore, the azeotrope tower is very demanding energy-wise since it uses 11times more steam than is needed by the other column. Heat requirements for the azeotrope tower are, however, very dependent on the feed concentration. Therefore, the column design was optimized by looking for net return on the investment and minimum operation costs. Distillation column operation was modeled, simulated, and optimized together with the complete plant (procedure FUROPT2). The operating temperature obtained for the
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Ind. Eng. Chem. Process Des. Dev., Vol. 25, No. 3, 1986
Table 111. Design Data Comparison between Alternative Recovery Systems for a Production of 2 tons/h liquid-liquid extract. azeotrope dist. method method azeotrope dehydrating recovering purifying QR
Qc AR AC
NT
NS NF RR
D TB TD PD
total QR material
94.00 70.76 995.0 450.0 20 20 16 24.3 3.4 381 372 780 95.12
AIS1 316
1.12 6.9 10
10 2.7 1.0 445 377 780
17.33 15.07 220.17 159.5 10
3.06 2.93 32.4 25.8 10
4
6 36.2 1.0 435 354 780
1.7 2.4
400 343 780 20.38
LlOUlD -LIOUID EXTRACTION
RECOVERING
REACTOR
ATER- BENCENE
SLURRY
Figure 12. Flow sheet of the process using liquid-liquid extraction.
carbon steel
Table IV. Energy and Benzene Requirements for Alternative Designs liquid-liquid distillation extraction energy, kJ/kg of furfural 69 090 37 700 benzene, kg/kg of furfural 0.02
flash was 349 K, and the optimized column heat requirement was 41 800 kJ/kg of furfural produced. The study of the investment costs vs. production of the plant at the above conditions is shown in Figure 9. Then the net annual return on the investment can be calculated when the total production costs and financing expenses are taken into account. Figure 10 gives the net profit evaluation and Figure 11 the net annual return of the plant a t various production levels (program COST and procedures FUROPTI and FUROFTID). The analysis of the process economics shows clearly that at optimum operating conditions, the total investment cost of the plant is relatively small when compared with the cost of utilities (essentially heat supply) as it will be emphasized later (Tables I11 and IV). On the basis of 5 years payout time, the annual amortization cost plus the financial expenses represent about 20% of total production costs. It can also be observed that there is a break-even return on investment a t about 20%,which corresponds to a plant producing 500 kg/h of furfural, or 3500 tons/year calculated on a basis of 7000 h of total production time per year. It is also interesting to observe that the net profit rate increases almost linearly with the plant size, reaching values up to a desirable 75% return on the investment costs, which correspond to an approximate production size of 3500 kg/h, when the investment costs of the plant start to weigh more heavily on production costa. Liquid-Liquid Extraction Method. Previous considerations on heat and size requirements of the azeotrope column used in the concentration and purification stage of the design led us to consider the possibility of better alternatives in the process design. Furfural recovery by liquid-liquid extraction was carefully examined and found to be very promising from the beginning. We summarize the results obtained from our study in what follows. The initial process arrangement is shown in Figure 12, where it can be observed that the azeotrope column has been removed, and a liquid-liquid extraction column that uses benzene as the solvent replaces it. Complete furfural recovery is accomplished in this arrangement by placing a distillation column next to the liquid-liquid extraction unit and separating the exit stream into two streams, one with a high content on furfural and
t 1
I
I
-j ACICIC WASTE SLUPRY
I
3
I
SEPARATOHy&CANTER
-
l
LlOUlD - LIOUlS EXTRACTION
l
_-LA
- A_-' f , A - E 9 - BENZEUE
Figure 13. Improved design with decanter and energy recovery optimization.
the other benzene rich with water traces. A purifying column is used to remove the residual benzene to obtain a high-quality furfural as the final product. Process operation has been simulated and optimized (procedures FURREX and FURREC), and the detailed results of the process design can be obtained from the authors. An improved alternative was considered later (Figure 13) which optimizes the energy and benzene recovery of the system and introduces a three-phase flash to recuperate the benzene from the aqueous stream at the bottom of the liquid-liquid extractor. Regaining the energy from the exit stream of the reactor means, besides a benzene loss reduction to one-tenth of the previous design, a substantial economy in heat supply, making this configuration a very attractive alternative, since the additional cost introduced in the equipment and installation is relatively small. A detailed comparison for relevant design data between this option and the azeotrope column recovery system is given in Table I11 on the basis of 2 tons/h production level. A reserve stock level has been foreseen, which is equivalent to 3-day production in the case of xylose and to 1week in the case of furfural. Our extensive design studies show that the most critical design variable in the process is the ratio between the benzene flow and the furfural aqueous stream entering the liquid-liquid extraction column. This ratio will determine the size of the latter and that of the purifying column and will also affect essentially the overall material and energy balances of the plant. We can summarize the advantages found with this approach as compared with previous designs as follows: The initial investment costs are of the order of 15% less for productions over 1 ton/h. This is shown in Figure 14 as compared with results obtained in previous designs (Figure 9).
Ind. Eng. Chem. Process Des. Dev., Vol. 25, No. 3, 1986 693
observed that the return on the investment is still good at low levels of production. The results obtained in this study are being applied to the design of a commercial plant.
Acknowledgment We are thankful to the Instituto de Ciberngtica for free access to their computing facilities and to Simulation Sciences Inc. for the facilities given to the use of PROCESS. 0 1
1
2
I
I
3
4
PROOUCTION , ( f /h)
Figure 14. Investment at various plant sizes for improved plant design.
1
2
3
4
PRODUCTION , ( f / h l
Figure 15. Net profit at various furfural production levels for improved plant design. Curve b has been calculated assuming a 10% uncertainty as in Figures 10 and 11. c
z
w 10
E
W
> 08
z c
5n 0.6
a
t; 0 . 4 z
0.2
0.0
t
I
/
t
I-
2
PRODUCTION. ( t / h l
Figure 16. Profitability of the new plant design at various furfural production levels. Curve b has been calculated assuming a 10% uncertainty as in Figure 13. Again the broken line indicates the break-even profit level.
Energy requireinents have been optimized to a minimum: just the energy required to maintain the operating temperature of the reactor and the correct operation of the purifying column. Table IV shows the substantial energy improvement attained. Although the benzene-water solubility coefficient is very low, benzene losses could be still high due to the large flow involved, but these losses have been dramatically reduced to one-tenth by introducing an extremely efficient recovery system. The net profit obtained with the improved design (Figure 15) is 15% higher than previous designs (Figure 10). Therefore, the ratio net profit/investment is improved over 30% (compare Figures 16 and 11). It can also be
Nomenclature Ac = condenser area, m2 AR = reboiler area, m2 a = K 2 / K 1= rate constant ratio B = gross profit, $ b = correlation constant C = experimental concentration, mol/L C' = theoretical concentration obtained from eq 6, mol/L C" = theoretical concentration obtained from eq 1, mol/L C* = concentration related to the initial xylose concentration CH+ = catalyst concentration, equiv g/L Cxo = initial xylose concentration, mol/L D1,D2 = destruction products d = correlation constant d, = correlation constant K , = rate of xylose disappearance constant, min-' K 2 = rate of furfural disappearance constant, min-' NF = feed stream tray NS = side-stream tray NT = total number of trays PD= distillate pressure (pressure at the condenser), mmHg Q = feed flow, L/min Qc = heat duty of the condenser, GJ/h (1 GJ/h = 109J/h) Q R = heat duty of the reboiler, GJ/h RR = reflux ratio S = objective function, $/mol T = reactor temperature, K T B = bottoms product temperature, K T D= distillate temperature, K t = reaction time, min t R = residence time, min W = xylose amount in the feed, mol X = standardized variables vector Xi = standardized value of variable ith x i = value of variable ith Ti = mean value of variable ith Subscripts F = furfural X = xylose Greek Letters ci = standard deviation for variable ith Registry No. Furfural, 98-01-1; D-xylose, 58-86-6.
Literature Cited Harris, J. F.; Smuk, J. M. Forest Prod. J . , 1861, 1 1 , 303. Kirby, A. M. Ph.D. Thesis, University of Wisconsin, Madison, 1948. Kobayashi, T. "Research on the Kinetics of Wood Sacharification at Lower Temperatures with Dilute and Strong Sulfuric Acid"; Forest Product Research Institute: Hokkaido, Japan, 1952. Uzaro, M.; Puigjaner, L.; Martinez-Benet, J. M.; Recasens, F. "Process Modeling and Optimization with Evolution-Operation Techniques": SpringerVerlag; Hamburg, 1983; Informatik-Fachberichte ESC.83, pp 549-55. Root, D. F.; Saeman, J. F.; Harris, J. F.; Neil, W. R. Forest Rod. J . , 1958, 9 , 158. Williams, D. L.; Dunlop, A. P. Ind. Eng. Chem. 1848, 4 0 , 239.
Received for review July 16, 1984 Revised manuscript received October 31, 1985 Accepted November 14, 1985
