Extraction of Aromatics from Middle Distillate Using ... - ACS Publications

literature values.12 The reported experimental values conformed closely to their corresponding literature values, to an average absolute value of devi...
2 downloads 0 Views 161KB Size
5686

Ind. Eng. Chem. Res. 2007, 46, 5686-5696

SEPARATIONS Extraction of Aromatics from Middle Distillate Using N-Methyl-2-pyrrolidone: Experiment, Modeling, and Optimization Adel S. Al-Jimaz,* Mohamed S. Fandary, Khaled H. A. E Alkhaldi, Jasem A. Al-Kandary, and Mohamed A. Fahim† Chemical Engineering Department, College of Technological Studies, PAAET P.O. Box 42325, Shuwaikh 70654, Kuwait

The phase equilibria of aromatics separation from the multicomponent system [paraffins: (tetradecane + hexadecane + heptadecane) and aromatics (ethylbenzene + 1,3,5-trimethylbenzene + butylbenzene)] using N-methyl-2-pyrrolidone (NMP), as an extracting agent, have been studied. The aromatics in the multicomponent mixture were extracted at different temperatures (293-323 K) and different solvent to feed ratios (0.991.89). Such a system is found in the removal of aromatics from middle distillates in petroleum processing. The effects of temperature, solute concentration in the feed, and solvent to feed ratio on solubility, distribution coefficient, selectivity, and yield were investigated. The abilities of nonrandom two liquid (NRTL) and universal quasi-chemical (UNIQUAC) models to predict liquid-liquid equilibria were evaluated. The experimental data of the studied system were regressed to estimate the interaction parameters between each of the seven pairs of components using the two models as a function of temperature. The calculated results were comparable with the experimental data. Minimum major cost parameters and maximum yield of operation were analyzed through an optimization model to investigate the effects of temperature and solvent to feed ratio. Optimum operating conditions for enhanced aromatic extraction were unveiled. Introduction Liquid-liquid extraction is the most economical process for separating aromatics from middle distillates. Liquid-liquid extraction is an important analytical tool in research and industrial laboratories, as well as a commercial unit for selective separation and recovery of different types of aromatics from multicomponent liquid mixtures. Separation of aromatics from middle distillates by direct distillation is not feasible because of the limitations raised by many homogeneous binary azeotropes existing between aliphatic and aromatic hydrocarbons. These limitations make distillation ineffective for separating aromatics. Extraction processes are a better choice. The extractive distillation and solvent extraction processes are carried out using selective solvents. N-Methyl-2-pyrrolidone (NMP) is a dipolar aprotic basic solvent used in the well-established AROSOLVAN process as a highly selective extractant for the recovery of aromatics from petroleum fractions. Experimental data on liquid-liquid equilibria (LLE) published for n-alkanes + aromatics + NMP systems containing carbon greater than nine in number for the alkanes and/or aromatics are limited.1-4 Reliable prediction of these data from limited experimental information is of vital importance for the design and analysis of aromatic extraction systems. * To whom correspondence should be addressed. Tel.: +965 231 4400. Fax: +965 481 1568. E-mail: [email protected]. † Present address: Chemical Engineering Department, University of Kuwait, P.O. Box 5969, Safat 13060, Kuwait.

The performance of an extractive solvent was evaluated through its solvency and selectivity properties. Solubilities, distribution coefficients, and selectivities were known operating conditions of the proposed extraction processes. Various thermodynamic models, such as nonrandom two liquid (NRTL) and universal quasi-chemical (UNIQUAC), are available for the prediction of LLE. The estimation of the NRTL or UNIQUAC binary interaction parameters also requires the availability of experimental LLE, vapor-liquid equilibria, or infinite dilution activity coefficient data. Multicomponent systems are difficult to represent graphically. In many such systems of industrial importance, the number of components is so large that they cannot be conveniently identified. In the case of multicomponent mixtures to be separated by one or mixed solvents, a simplification to a pseudoternary mixture and a single ternary diagram is constructed.5-9 This paper continues our previous work,2-4 which dealt with the liquid-liquid-phase equilibria for de-aromatization of Kuwait middle distillate. The objective of this work was to study LLE of the multicomponent system: paraffins (1) + aromatics (2) + NMP (3). A multicomponent mixture of three major paraffins {tetradecane, 22%; hexadecane, 35%; and heptadecane, 43%, on a mass basis} and three major aromatics {ethylbenzene, 36%; 1,3,5-trimethylbenzene, 30%; and butylbenzene, 34%, on a mass basis} represented the main hydrocarbon groups in Kuwait middle distillate. The measured LLE data for the studied multicomponent system were used to determine the distribution coefficient, selectivity, and yield at different temperatures (293, 303, 313, and 323 K) and different solvent to feed ratios (0.99-

10.1021/ie060960f CCC: $37.00 © 2007 American Chemical Society Published on Web 07/25/2007

Ind. Eng. Chem. Res., Vol. 46, No. 17, 2007 5687 Table 1. Details of the Chemicals: Purities, UNIQUAC Structural Parameters, and Refractive Indices

compound

supplier

GC purity (%)

tetradecane hexadecane heptadecane ethylbenzene mesitylene butylbenzene NMP

Fluka Aldrich Sigma Aldrich Sigma Aldrich Fluka

99.5 99.3 99.2 99.3 99.5 99.3 99.5

a

UNIQUAC structural parameter

nD20

R

q

exptl

lit.a

9.8950 11.2440 11.9184 4.5970 5.393 5.946 3.981

8.1759 9.256 9.7959 3.5078 4.014 4.588 3.200

1.4289 1.4344 1.4371 1.4962 1.4992 1.4895 1.4686

1.4290 1.4345 1.4369 1.4959 1.4994 1.4898 1.4684

Reference 12.

1.89). Data were correlated by the NRTL model of Renon and Prausnitz10 and the UNIQUAC model of Abrams and Prausnitz.11 This study presented an optimization model to investigate the economics and performance efficiency of the extraction of aromatics from middle distillates against the extraction temperature and solvent to feed ratio. The model investigated the effects of soaring energy prices on the economics of the extraction process. Experimental Section Chemicals. The determined purity of the chemicals (Table 1) was ascertained by comparing the measured refractive indices of the pure components at 293 K with the available literature values.12 The reported experimental values conformed closely to their corresponding literature values, to an average absolute value of deviation of the order of 10-4. The purity of the chemicals was also determined by gas chromatograph. NMP and aromatic compounds were stored under a 0.4 nm molecular sieve. All chemicals were used without further purification. Apparatus and Experimental Procedure. The experimental apparatus used for extraction consisted of a 60 cm3 glass cell with a water jacket to maintain a constant temperature. The temperature was controlled within +0.2 K. The cell was connected to a Haake K15 water bath fitted with a Haake DC1 thermostat. Mixtures comprised of 20 g of NMP, 20 g of paraffins mixture, and different known masses (0-8 g) of aromatics mixture were placed in the extraction vessels. The mass measurements were performed using an electronic balance (Mettler AT460) with a stated precision of (10-4 g. The mixtures were vigorously stirred for 1 h and then left to settle for 4 h. Samples were taken by syringe from both the upper and the lower layers. A series of LLE measurements for the multicomponent system: (tetradecane, hexadecane, and heptadecane) + (ethylbenzene, 1,3,5-trimethylbenzene, and butylbenzene) + NMP over a temperature range of 293-323 K and at atmospheric pressure were performed. Analyses. The paraffins (1), aromatics (2), and NMP (3) were analyzed using a Chrompack CP 9000 gas chromatograph equipped with an on-column injector, flame ionization detector (FID), and a data processor system. The column used was CP SIL 8CB (30 m × 3.2 × 10-4 m × 2.5 × 10-7 m film thickness). The column temperature was programmed for initial temperature of 383 K maintained for 2 min, and a final temperature of 673 K was maintained for 5 min. The heating rate was 10 K/min, and the carrier gas (Helium, grade 5.6) flow rate was maintained at 3 × 10-5 m3/min. The injection temperature was 523 K, and the detector temperature was 573

K. The temperature was controlled with practical accuracy of apparatus of +0.03 K. Each mole fraction was repeatedly measured four times, and the average mole fraction was recorded. The average mole fraction experimental uncertainty was (0.0005. Models and Correlations Our experimental data were correlated with the NRTL model of Renon and Prausnitz10 and the UNIQUAC model of Abrams and Prausnitz.11 Interaction Parameters. The LLE experimental data were used to determine the optimum NRTL and UNIQUAC binary interaction parameters between tetradecane, hexadecane, heptadecane, ethylbenzene, 1,3,5-trimethylbenzene, butylbenzene, and NMP. The same data were used to determine the optimum NRTL and UNIQUAC binary interaction parameters of the pseudoternary system {paraffins (1), aromatics (2), and NMP (3)}. The NRTL and the UNIQUAC models were fitted to experimental data using an iterative computer program, based on the flash calculation method, developed by SLrensen and Arlt.13 The objective function (F) used in this case was determined by minimizing the square of the difference between the mole fractions correlated by the respective method; these were experimentally measured over all the tie lines in the multicomponent system. For the UNIQUAC correlation, the structural parameters (r and q) for pure compounds are listed in Table 1. These parameters were calculated from the data published by Magnussen et al.14 For pseudo-paraffins, r and q were 11.176 and 9.202, respectively; for pseudo-aromatics, r and q were 5.335 and 3.981, respectively. These parameters were calculated from the data published by Al-Jimaz et al.5 The objective function (F) used was

F ) min

∑k ∑j ∑i (xijk,exp - xijk,cal)2

(1)

where x is the mole fraction and subscripts exp, cal, i, j, and k are experimental, calculated, components, phases, and tie lines, respectively. The NRTL model was fitted with fixed values of the nonrandomness parameter (Rij) for each pair of components. A fixed value of Rij ) 0.2 between each pair of components was satisfactory. The optimization results were judged by calculating the corresponding root mean square deviation (rmsd) values using the following equation:

rmsd ) 100

x

∑k ∑j ∑i (xijk,exp - xijk,cal)2 n-p

(2)

where n is the number of the experimental data and p is the number of the NRTL or the UNIQUAC interaction parameters. The distribution coefficient of aromatics (K) for the system {paraffins (1) + aromatics (2) + NMP (3)}, which is the measure of the solvent power or capacity of the NMP (3), is given by

K)

(x2)NMP-rich phase (x2)paraffins-rich phase

(3)

5688

Ind. Eng. Chem. Res., Vol. 46, No. 17, 2007

Figure 1. Schematic diagram of the extraction process.

Table 2. Experimental Equilibrium Mole Fraction (xi), Distribution Coefficient (K), and Selectivity (S) for the Multicomponent System {Paraffins (1) + Aromatics (2) + NMP (3) }at Different Temperatures paraffins-rich phase x1

NMP-rich phase x2

x1

x2

T (K)

xtetra

xhexa

xhepta

xethyl

xmethyl

xbutyl

xtetra

xhexa

xhepta

xethyl

xmethyl

xbutyl

S

K

293

0.2441 0.2211 0.2117 0.1969 0.1805 0.1676 0.1412 0.1163

0.3417 0.3073 0.2950 0.2729 0.2527 0.2317 0.1948 0.1614

0.3706 0.3495 0.3361 0.3098 0.2888 0.2628 0.2206 0.1835

0.0000 0.0293 0.0429 0.0627 0.0772 0.0945 0.1183 0.1357

0.0000 0.0226 0.0333 0.0485 0.0597 0.0732 0.0916 0.1051

0.0000 0.0212 0.0308 0.0454 0.0558 0.0683 0.0856 0.0981

0.0066 0.0081 0.0092 0.0108 0.0117 0.0131 0.0145 0.0201

0.0093 0.0113 0.0129 0.0152 0.0164 0.0183 0.0202 0.0281

0.0106 0.0129 0.0148 0.0173 0.0188 0.0209 0.0231 0.0321

0.0000 0.0191 0.0282 0.0420 0.0521 0.0648 0.0834 0.1002

0.0000 0.0148 0.0219 0.0326 0.0404 0.0502 0.0646 0.0777

0.0000 0.0139 0.0204 0.0305 0.0378 0.0470 0.0605 0.0726

17.83 15.05 12.08 10.40 8.69 6.79 4.25

0.654 0.659 0.671 0.676 0.686 0.706 0.739

0.2164 0.1942 0.1809 0.1641 0.1531 0.1348 0.1160 0.1003

0.2999 0.2705 0.2521 0.2282 0.2114 0.1872 0.1610 0.1391

0.3409 0.3082 0.2871 0.2601 0.2397 0.2131 0.1829 0.1579

0.0000 0.0288 0.0411 0.0618 0.0737 0.0921 0.1088 0.1234

0.0000 0.0221 0.0317 0.0476 0.0570 0.0713 0.0841 0.0955

0.0000 0.0204 0.0295 0.0444 0.0531 0.0665 0.0784 0.0892

0.0070 0.0087 0.0097 0.0111 0.0121 0.0136 0.0152 0.0172

0.0098 0.0121 0.0136 0.0155 0.0170 0.0190 0.0212 0.0240

0.0112 0.0139 0.0156 0.0177 0.0194 0.0218 0.0243 0.0275

0.0000 0.0195 0.0284 0.0436 0.0532 0.0687 0.0843 0.1014

0.0000 0.0151 0.0220 0.0338 0.0412 0.0533 0.0653 0.0786

0.0000 0.0141 0.0206 0.0316 0.0385 0.0498 0.0611 0.0735

15.21 12.87 10.45 9.01 7.35 5.89 4.76

0.683 0.695 0.709 0.723 0.747 0.777 0.822

0.1911 0.1696 0.1582 0.1406 0.1274 0.1069 0.0879 0.0846

0.2675 0.2360 0.2201 0.1942 0.1769 0.1483 0.1217 0.1171

0.3058 0.2687 0.2506 0.2201 0.2012 0.1684 0.1381 0.1328

0.0000 0.0279 0.0398 0.0583 0.0697 0.0861 0.0991 0.1089

0.0000 0.0216 0.0307 0.0451 0.0540 0.0665 0.0768 0.0844

0.0000 0.0201 0.0286 0.0421 0.0504 0.0623 0.0717 0.0789

0.0074 0.0089 0.0102 0.0115 0.0126 0.0149 0.0167 0.0244

0.0104 0.0125 0.0143 0.0161 0.0176 0.0209 0.0234 0.0342

0.0119 0.0143 0.0164 0.0184 0.0201 0.0238 0.0268 0.0391

0.0000 0.0199 0.0288 0.0439 0.0538 0.0697 0.0863 0.0992

0.0000 0.0154 0.0224 0.0340 0.0417 0.0540 0.0669 0.0768

0.0000 0.0144 0.0209 0.0318 0.0390 0.0505 0.0626 0.0719

13.51 11.19 9.08 7.76 5.76 4.53 3.12

0.716 0.728 0.755 0.772 0.811 0.871 0.911

0.1634 0.1423 0.1276 0.1107 0.0959 0.0803 0.0611

0.2274 0.1979 0.1772 0.1536 0.1329 0.1117 0.0839

0.2589 0.2251 0.2014 0.1746 0.1508 0.1271 0.0951

0.0000 0.0265 0.0376 0.0547 0.0669 0.0789 0.0899

0.0000 0.0205 0.0291 0.0423 0.0517 0.0611 0.0695

0.0000 0.0191 0.0271 0.0394 0.0483 0.0571 0.0649

0.0077 0.0101 0.0109 0.0122 0.0134 0.0157 0.0194

0.0108 0.0141 0.0152 0.0171 0.0187 0.0220 0.0271

0.0124 0.0161 0.0174 0.0196 0.0214 0.0251 0.0310

0.0000 0.0202 0.0292 0.0445 0.0564 0.0696 0.0840

0.0000 0.0156 0.0227 0.0345 0.0437 0.0539 0.0651

0.0000 0.0146 0.0212 0.0322 0.0409 0.0504 0.0609

10.71 9.09 7.32 6.00 4.48 2.91

0.7636 0.7793 0.8152 0.8454 0.8823 0.9367

303

313

323

The effectiveness of a solvent can be expressed by the selectivity (S) of the solvent. The selectivity of the NMP (3), which is a measure of the solvent’s ability to separate aromatics (2) from paraffins (1), is given by

S)

(x2/x1)NMP-rich phase (x2/x1)paraffins-rich phase

(4)

Optimization Model. The experimental results and NRTL and UIQUAC model simulations illustrated the significant effect of solvent to feed ratio and operating temperature on the extraction process. Both affected the major cost parameters of the extraction process. In an effort to optimize the performance of the extraction process, this work analyzed the major cost parameters and performance variables of the extraction of aromatics from middle distillates using NMP solvent.

Ind. Eng. Chem. Res., Vol. 46, No. 17, 2007 5689

Figure 2. Experimental and predicted LLE data for the system: paraffins (1) + aromatics (2) + NMP (3) at T ) 293 K: B, experimental; dashed line, NRTL; solid line, bimodal curve, UNIQUAC.

Figure 4. Experimental and predicted LLE data for the system: paraffins (1) + aromatics (2) + NMP (3) at T ) 313 K: B, experimental; dashed line, NRTL; solid line, bimodal curve, UNIQUAC.

the extract phase. The total molar amount required of the solvent (FTS) was

FTS ) FMRstf

(5)

where FM is the molar flow rate of the middle distillates and Rstf is the solvent to feed ratio. The recovered solvent and recycled flow (FR) is

FR ) FM(1 + Rstf)θ(x3)NMP-rich phase

(6)

where θ is the fraction of the extract phase. Hence, the makeup solvent flow (FS) is

Fs ) FM[Rstf - (1 + Rstf)θ(x3)NMP-rich phase]

(7)

The cost of makeup solvent15,16 (Cs) was then calculated by

Cs )

Figure 3. Experimental and predicted LLE data for the system: paraffins (1) + aromatics (2) + NMP (3) at T ) 303 K: B, experimental; dashed line, NRTL; solid line, bimodal curve, UNIQUAC.

The optimization cost objective function could be formulated through the following cost analysis. Fresh feed of middle distillates {paraffins (1) and aromatics (2)} was mixed with NMP solvent (3) to form the combined feed to the extraction process. At equilibrium, the raffinate (rich in paraffins) phase was taken as a product, while the extract (rich in aromatics and NMP solvent) phase was heated to the heaviest hydrocarbon boiling point, at which aromatics and paraffins separate as a vapor, and the NMP solvent emerges as a liquid. The NMP solvent was then cooled and mixed with the makeup solvent to form the extraction solvent. Figure 1 shows a schematic diagram of the extraction process. The major cost parameters in this process description were the following: 1. Cost of solvent makeup. Solvent makeup was determined as the total amount demanded less the amounts recovered from

λs F Fs S

(8)

where λs is a cost parameter ($/m3) and Fs is the molar density of the solvent. 2. Cost of solvent recovery. The solvent was recovered from the extract phase through flash separation by heating to the boiling temperature of the heaviest aromatic hydrocarbon. The solvent was recovered as a liquid and was then cooled down. The cooling fluid cost was a constant, while the heating cost remained variable to investigate the effect of the continuously increasing value of energy. The solvent recovery cost16 (CR) was

CR )

λR (F θ(1 + Rstf))[βR1 + βR2(x3)NMP-rich phase] FM M

(9)

where λR is a cost scaling factor for the solvent recovery and FM is the molar density of the middle distillates. βR1 and βR2 are the heating and cooling costs. The cooling cost was assumed to be $2.5/m3 of recovered solvent, while the heating cost varied between $4 and $16/m3 of feed to the flash unit.

5690

Ind. Eng. Chem. Res., Vol. 46, No. 17, 2007 Table 3. UNIQUAC and NRTL Interaction Parameters for the Multicomponent System According to the Equation aij ) a0ij + bij(T(K) - 273) UNIQUAC i

Figure 5. Experimental and predicted LLE data for the system: paraffins (1) + aromatics (2) + NMP (3) at T ) 323 K: B, experimental; dashed line, NRTL; solid line, bimodal curve, UNIQUAC.

On the other hand, in this analysis, the cost of lost paraffins in the extract phase was not investigated. Operation at high extraction efficiency caused only minor transport of middle distillates (paraffins) to the extract phase; hence, this cost can be neglected. On the basis of this analysis, the major cost parameters could be coupled to form the optimization cost objective function:

Minimize cost (C) defined as C ) C s + CR C)

λs F [R - (1 + Rstf)θ(x3)NMP-rich phase] + Fs M stf λR (F θ(1 + Rstf))[βR1 + βR2(x3)NMP-rich phase] FM M C ) f{Rstf, T, βR1}

(10)

On the other hand, optimization of extraction efficiency can be approached using the following analysis. The objective of the extraction process is the removal of aromatics from the middle distillates using the NMP solvent. These aromatics transport to the extract phase, leaving the higher quality raffinate (middle distillates) phase. The major extraction performance parameters are the distribution coefficient (K), the selectivity (S), and the extract phase fraction (θ). A parameter that couples the effect of both variables (S and K) can better be used as a tool to investigate the performance of the extraction process. This coupling parameter is the yield of aromatics removal to the extract phase. Yield of aromatics (Yld) is defined as the molar ratio of aromatic components in the extract phase to that in the feed. This yield represents the goal to extract as much aromatic as possible to enhance the properties of middle distillates:

Yld )

E(x2)NMP-rich phase FT(x2)Combined feed



(x2)NMP-rich phase (x2)Combined feed

a0ij

j

bij

(K)

bij

tetra tetra tetra tetra tetra tetra

hexa hepta ethyl methyl butyl NMP

-98.510 -92.000 9.370 6.770 -33.210 560.130

-3.594 -7.710 0.153 -23.937 -0.644 -7.073

-4.649 -1.552 1.115 1.363 1.432 1.600

-0.074 0.092 0.250 -0.107 -0.045 0.561

hexa hexa hexa hexa hexa hexa

tetra hepta ethyl methyl butyl NMP

-30.500 3.420 46.300 -47.780 29.800 672.890

17.800 -8.087 -3.200 -12.287 -4.940 -5.144

0.218 -3.935 0.224 -0.440 0.335 2.430

0.166 0.320 0.124 -0.039 -0.011 -0.012

hepta hepta hepta hepta hepta hepta

tetra hexa ethyl methyl butyl NMP

85.610 268.770 -121.180 -13.704 -46.270 656.070

15.394 0.643 2.433 -23.464 -1.863 -5.787

-2.506 -0.966 1.140 -0.369 0.678 6.549

0.072 0.024 -0.023 0.157 -0.031 -0.058

ethyl ethyl ethyl ethyl ethyl ethyl

tetra hexa hepta methyl butyl NMP

-17.770 -70.390 -163.100 49.330 15.500 -7.800

8.557 4.364 18.120 -24.423 17.930 0.100

0.713 3.154 3.316 -1.303 -2.880 2.307

0.026 -0.148 -0.043 0.143 0.384 -0.059

methyl methyl methyl methyl methyl methyl

tetra hexa hepta ethyl butyl NMP

-59.280 -96.730 -222.380 18.990 63.090 1.090

4.013 6.783 17.313 0.576 -10.054 -1.194

-4.823 -0.140 -1.233 -3.020 0.539 1.221

0.112 -0.085 0.135 -0.027 1.237 0.009

butyl butyl butyl butyl butyl butyl

tetra hexa hepta ethyl methyl NMP

-26.300 -23.910 -137.200 63.590 23.210 46.900

12.110 4.126 15.780 46.636 -16.416 6.070

0.428 0.139 -0.746 -2.388 -1.420 0.627

-0.005 -0.004 0.102 -0.059 -0.095 0.127

NMP NMP NMP NMP NMP NMP

tetra hexa hepta ethyle methyl butyl

-124.320 -83.710 -42.810 -3.910 -36.900 -58.520

2.777 0.156 -2.594 2.516 -18.290 -1.473

3.955 12.990 2.685 2.208 -0.522 0.567

0.113 -0.020 0.024 0.003 -0.018 -0.003

Table 4. UNIQUAC and NRTL Interaction Parameters for the Pseudoternary System {Paraffins (1), Aromatics (2), and NMP (3)} According to the Equation aij ) a0ij + bij(T(K) - 273) UNIQUAC

NRTL

i

j

a0ij (K)

bij

a0ij (K)

bij

1 1 2 2 3 3

2 3 1 3 1 2

106.460 321.935 -137.036 295.250 -34.594 -171.000

-54.776 -2.604 2.721 2.105 0.954 -54.400

80.488 3.076 -57.971 11.353 4.049 82.138

-4.559 0.005 3.025 3.640 -0.015 -4.578

Performing a mole balance of the extraction process for both paraffins and aromatics reveals the following expression for extraction selectivity:

(x2)Combined feed S)

(11)

(K)

NRTL a0ij

(x2)paraffins-rich phase (x1)Combined feed (x1)paraffins-rich phase

- (1 - θ) (12) - (1 - θ)

Ind. Eng. Chem. Res., Vol. 46, No. 17, 2007 5691

Figure 6. Effect of temperature on measured and correlated distribution coefficient (K) at O, 293; 3, 303; 0, 313; ], 323 K; solid line, UNIQUAC.

Figure 7. Effect of temperature on measured and correlated selectivity (S) at: O, 293; 3, 303; 0, 313; ], 323 K; solid line, UNIQUAC.

Similarly, the definition of K can be rewritten by substituting eq 11 with

( )(

Yld (x2)combined-feed K) θ (x2)paraffins-rich phase

)

[(

S

Kθ (x1)combined-feed

(x1)paraffins-rich phase

)

S

(13)

Finally, substituting eq 13 into eq 12 reveals

Yld )

Yld )

(x1)paraffins-rich phase

)

]

- (1 - θ) + (1 - θ)

Yld ) f{Rstf, T} Results and Discussion

]

- (1 - θ) + (1 - θ) (14)

Distribution Coefficient and Selectivity. The experimental results of K and S are presented in Table 2. These results were compared to the correlated results of K and S by calculating the corresponding coefficient of determination (r2) values using the following equation:

Equation 14 clearly illustrates that yield does reflect the coupling effect of selectivity and distribution coefficient on the yield of aromatic removal from middle distillates. Thus, yield was used as the objective function of the optimization of extraction efficiency.

Maximize yield (Yld):

[(

Kθ (x1)combined-feed

r2 )

where

σexp2 - σexp,cal2 σexp2

(15)

5692

Ind. Eng. Chem. Res., Vol. 46, No. 17, 2007

x x

n

∑(yk,exp - yjexp)

σexp )

σexp,cal )

2

k)1

n-1

(16)

n

(yk,exp - yk,cal)2 ∑ k)1

yjexp )

n-1 1

(17)

n

∑yk,exp

n k)1

(18)

and y represents distribution coefficient (K) or selectivity (S), yj is the arithmetic mean, n is the number of experimental data, σ is the standard deviation, and subscripts exp, cal, and k are experimental, calculated, and tie lines, respectively.

The measured equilibrium mole fractions (x), distribution coefficients (K), and selectivities (S) for the studied system are given in Table 2. As the temperature increased, the solubility of NMP in the paraffins-rich phase increased; temperature, however, had little effect upon the solubility of paraffins in the NMP-rich phase. The selectivity and the distribution coefficient values were not constant for the two-phase region. While the selectivity decreased, the distribution coefficient increased as the temperature and/or the solute in the feed increased (Table 2). The experimental and the correlated tie lines for the studied system at (293, 303, 313, and 323 K) are shown in Figures 2-5, respectively. The studied system exhibited a type I liquid-liquid phase diagram. The mutual paraffin-NMP solubility increased as the concentration of aromatics in the feed increased. The size of the two-phase region decreased with an increase in temperature and/or aromatics concentration in the feed.

Figure 8. Distribution coefficient (K) against selectivity (S) at different temperatures: O, 293; 3, 303; 0, 313; ], 323 K; solid line, UNIQUAC.

Figure 9. Cost optimization function (C) against solvent to feed ratio (Rstf) at different temperatures: O, 293; 3, 303; 0, 313; ], 323 K; at heating cost βR1 ) $4/m3.

Ind. Eng. Chem. Res., Vol. 46, No. 17, 2007 5693

Figure 10. Cost optimization function (C) against solvent to feed ratio (Rstf) at different temperatures: O, 293; 3, 303; 0, 313; ], 323 K; at heating cost βR1 ) $8/m3.

Figure 11. Cost optimization function (C) against solvent to feed ratio (Rstf) at different temperatures: O, 293; 3, 303; 0, 313; ], 323 K; at heating cost βR1 ) $12/m3.

Data Correlation. The interaction parameters for the NRTL and the UNIQUAC models as a function of temperature based on multicomponent and pseudoternary data are shown in Tables 3 and 4, respectively. These parameters were used to calculate LLE tie lines for the present system. The calculations based on both models adequately represented the tie lines data for this system. On the basis of analysis of the rmsd for the multicomponent system (the average rmsd was 0.25 for NRTL and 0.36 for UNIQUAC), both NRTL and UNIQUAC models accurately correlated the LLE experimental data of the multicomponent system. The UNIQUAC model, however, gave a better correlation for the pseudoternary system (the average rmsd was 1.58 for NRTL and 0.42 for UNIQUAC). The distribution coefficients and selectivities were correlated from calculated LLE data by the UNIQUAC model using the interaction parameters generated in Tables 3 and 4 at different temperatures. The correlated distribution coefficient and selec-

tivity values based on the multicomponent data agreed more strongly with the corresponding experimental values than the values based on the pseudoternary data according to the coefficient of determination (r2). For the multicomponent system, r2 was 0.98 and 0.99 for K and S, respectively; for the pseudoternary system, r2 was 0.95 and 0.96 for K and S, respectively. Figure 6 represents the relationship of the solvent to feed ratio (Rstf) with the measured and correlated distribution coefficients (K) for the studied system at a temperature range of 293-323 K. The distribution coefficient values increased as the temperature increased and/or the solvent to feed ratio (Rstf) decreased. The same behavior was also correctly correlated from calculated LLE data using the UNIQUAC model, as shown in the same figure. Figure 7 represents the relationship of the solvent to feed ratio (Rstf) with the measured and correlated selectivity (S) for

5694

Ind. Eng. Chem. Res., Vol. 46, No. 17, 2007

Figure 12. Cost Optimization function (C) against solvent to feed ratio (Rstf) at different temperatures: O, 293; 3, 303; 0, 313; ], 323 K; at heating cost βR1 ) $16/m3.

Figure 13. Yield of aromatics removal (Yld) against solvent to feed ratio (Rstf) at different temperatures: O, 293;3, 303; 0, 313; ], 323 K.

the studied system at a temperature range of 293-323 K. The selectivity increased as the solvent to feed ratio (Rstf) increased. Temperature and selectivity, however, were inversely related. The same behavior was also correctly correlated from calculated LLE data using the UNIQUAC model, as shown in the same figure. Because the selectivity in all cases was greater than 1, the extraction was possible. As shown in Figure 8, the selectivities (S) and distribution coefficients (K) reflected opposing behavior; that is, a solvent with particularly high selectivity often had only a limited distribution coefficient, and vice versa. While at low temperatures, selectivity was high and distribution coefficients were low; at high temperatures, selectivity was low and distribution coefficients were high. The operation of liquid-liquid extraction was significantly affected by variations in the operating temperature and solvent to feed ratio. Thus, the determination of the effects of temper-

ature and solvent to feed ratio on the values of distribution coefficient (K) was quite crucial for optimum operation of the liquid-liquid extraction process. The extraction process cost optimization function (C) was investigated in the operating temperature range of 293-323 K and solvent to feed ratio range of 0.99-1.89, using the following parameters: λs/Fs ) $0.650/kmol, λR/FM ) $0.025/kmol, βR2 ) $2.5/m3; βR1 varied between $4-16/m3 (Figures 9-12). The objective cost function was plotted against the solvent to feed ratio at temperatures 293, 303, 313, and 323 K for heating costs of $4/m3 in Figure 9, $8/m3 in Figure 10, $12/m3 in Figure 11, and $16/m3 in Figure 12. At low-energy prices, βR1 ) $4/m3 the lowest operation costs were obtained at the lowest temperatures. At these temperatures, it was preferable to operate at the lowest solvent to feed ratio. However, the effect of solvent to feed ratio was not significant.

Ind. Eng. Chem. Res., Vol. 46, No. 17, 2007 5695

Figure 14. Effect of solvent to feed ratio (Rstf) on measured distribution coefficient (K) and measured selectivity (S); 2, K at 293 K; B, S at 293 K; 4, K at 303 K; and O, S at 303 K.

As energy prices increased, the lower temperatures still showed minimum costs; however, the effect of temperature became less significant as the solvent to feed ratio became more important. The smallest possible solvent to feed ratio should be used. Figure 13 shows a plot of the yield of aromatics removal (Yld) against the solvent to feed ratio (Rstf) at temperatures 293, 303, 313, and 323 K. The maximum yield was obtained by operating at the lowest temperatures (293 or 303 K). Operating at a Rstf ratio higher than 1.5 had no added effect, as the aromatic yield remained constant at Rstf > 1.5. A final preview of the extraction efficiency parameters (S and K) against the solvent to feed ratio is shown in Figure 14 at temperatures 293 and 303 K. Operation at Rstf < 1.0 was not favorable because S was less than 5.0. Conclusions An experimental investigation of LLE behavior for the multicomponent system paraffins (tetradecane, hexadecane, and heptadecane) + aromatics (ethylbenzene, 1,3,5-trimethylbenzene, and butylbenzene) + NMP was carried out at temperatures ranging from 293 to 323 K and different solvent to feed ratios. The solubility of NMP in a paraffins-rich phase increased as the temperature increased but had little effect on the solubility of paraffins in the NMP-rich phase. The mutual NMP-paraffins solubility increased as the concentration of aromatics increased. Both the NRTL and the UNIQUAC models satisfactorily and equally correlated with the LLE experimental data (the average rmsd was 0.25 for NRTL and 0.36 for UNIQUAC). The effect of temperature upon distribution coefficient and selectivity was correlated using the UNIQUAC model. While the distribution coefficient increased as the temperature increased and/or the solvent to feed ratio decreased, the selectivity increased as the temperature decreased and/or the solvent to feed ratio increased. The distribution coefficient increased, but the selectivity decreased as the concentration of aromatics in the feed increased. On the basis of the selectivity data, the separation of aromatics from paraffins by liquid extraction with NMP is feasible. Optimized extraction process

cost and efficient performance were attained at temperatures of 293-303 K and an Rstf ratio of 1.1-1.5. Increasing energy prices shrank the optimal region of solvent to feed ratio toward the 1.1 end. Acknowledgment The authors thank the Public Authority for Applied Education and Training (PAAET) for the financial support of this work (PAAET-TS-01-001). Literature Cited (1) Lin, W. Studies on the Extraction of aromatics from C9+ Oil. J. Chem. Eng. Jpn. 2002, 35, 1257-1262. (2) Al-Jimaz, A. S.; Fandary, M. S.; Al-Kandary, J. A.; Fahim, M. A. Liquid-liquid equilibria for n-alkanes (C12, C14, C17) + propylbenzene + NMP mixtures at temperatures between 298 and 328 K. Fluid Phase Equilib. 2005, 231 (2), 163-170. (3) Fandary, M. S.; Al-Jimaz, A. S.; Al-Kandary, J. A.; Fahim, M. A. Extraction of pentylbenzene from high molar mass alkanes (C14 & C17) by N-methyl-2-Pyrrolidone. J. Chem. Thermody. 2006, 38 (4), 455-460. (4) Al-Jimaz, A. S.; Fandary, M. S.; Al-Kandary, J. A.; Fahim, M. Measurement and Correlation of Phase Equilibria for Dodecane + secButylbenzene + N-Methyl-2-Pyrrolidone. J. Chem. Eng. Data 2005, 50 (5), 1740-1746. (5) Al-Jimaz, A. S.; Fandary, M. S.; Al-Kandary, J. A.; Fahim, M. A. Isopropanol-Enhanced Solubility of Water in Reformate. J. Chem. Eng. Jpn. 2002, 35, 319-323. (6) Fandary, M. S.; Al-Jimaz, A. S.; Al-Kandary, J. A.; Fahim M. A. Liquid-Liquid Equilibria of Water + Ethanol + Reformate at Different Temperatures. J. Chem. Eng. Data 2002, 47 (3), 487-491. (7) Al-Kandary, J. A.; Al-Jimaz, A. S.; Fandary, M. S.; Fahim M. A. Liquid - Liquid Equilibria of Water + MTBE + Reformate. Fluid Phase Equilib. 2001, 187-188, 131-138. (8) Lo, T. C.; Baird, M. H.; Hanson, C. Handbook of SolVent Extraction; Wiley & Sons: New York, 1983; pp 10-14. (9) Treybal, R. E. Liquid Extraction; McGraw Hill: New York, 1963; pp 50-52. (10) Renon, H.; Prausnitz, J. M. Local Compositions in Thermodynamic Excess Functions for Liquid Mixtures. AIChE J. 1968, 14, 135-144. (11) Abrams, D. S.; Prausnitz, J. M. Statistical Thermodynamics of liquid Mixtures: A New Expression for the Excess Gibbs Energy of Party or Completely Miscible Systems. AIChE J. 1975, 21, 116-128. (12) CRC Handbook of Chemistry and Physics, 86th ed.; CRC Press: Boca Raton, FL, 2005-2006.

5696

Ind. Eng. Chem. Res., Vol. 46, No. 17, 2007

(13) SLrensen, J. M.; Arlt, W. Liquid-Liquid Equilibrium Collection Data; Dechema Chemistry Data Series; Frankfort/Main, Germany, 1980; Vol. V, Part 2. (14) Magnussen, T.; Rasmussen, P.; Fredenslund, A. UNIFAC parameter table for prediction of liquid-liquid equilibriums. Ind. Eng. Chem. Proc. Des. DeV. 1981, 20, 331-339. (15) Aldrich. Handbook for Fine Chemicals and Laboratory equipment; Germany, 2003.

(16) Lababidi, Haytham M. S.; Ali, Sami H.; Fahim Mohammed, A. Optimization of Aromatics Extraction of Naphtha Reformate by Propylene carbonate/Diethylene Glycol Mixed Solvent. Ind. Eng. Chem. Res 2006, 45 (14), 5086-5097.

ReceiVed for reView July 24, 2006 ReVised manuscript receiVed June 6, 2007 Accepted June 14, 2007 IE060960F