Analysis and Simulation of an Industrial Vegetable Oil Refining Process

8/17/2019 Analysis and Simulation of an Industrial Vegetable Oil Refining Process

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Analysis and simulation of an industrial vegetable oil rening process

Gabriele Landucci a ,⇑ , Gabriele Pannocchia a , Luigi Pelagagge b , Cristiano Nicolella aa Dipartimento di Ingegneria Civile e Industriale, Università di Pisa, Largo Lucio Lazzarino, 56126 Pisa, Italyb SALOV – Società Alimentare Lucchese Oli E Vini S.p.A. 1582, Via Montramito, San Rocchino 55054, Italy

a r t i c l e i n f o

Article history:Received 10 August 2012Received in revised form 1 November 2012Accepted 27 January 2013Available online 4 February 2013

Keywords:Vegetable oil reningProcess simulationAdvanced thermodynamic modelsFormation of ammable mixtures

a b s t r a c t

This work focuses on the performance analysis of an industrial vegetable oil renery. Using a commercialprocess simulator, a process model was developed and validated against actual vegetable oil reneryelddata. The simulator allowed investigating both energy and safety aspects related to the presence of resid-ual extraction solvent (extraction grade hexane) in the processed crude vegetable oil. The critical nodesfor hexane accumulation in the process were evaluated, both considering ordinary operative conditionsand undesired process deviations due to increase of the hexane content. In this latter case, the controlactions able to restore the normal operation were simulated, in terms of increased utility consumption(e.g., motive steam for ejectors and cooling water) or by modifying and optimizing equipment operatingconditions. Finally, the possibility of ammable mixtures formation inside process vent pipes, caused bythe entrainment of air due strong vacuum conditions, was also investigated.

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1. Introduction

Edible oil production by extraction processes greatly increasedin the last century due to both higher request and consumption(FAO, 2011 ) and the progressive availability of more efcient pro-cess technologies and equipment ( Bockisch, 1998; Mielke, 1990;Shahidi, 2005; Veloso et al., 2005; Calliauw et al., 2008; Cuevaset al., 2009; Haslenda and Jamaludin, 2011; Szydłowska-Czerniaket al., 2011; Zulkurnain et al., 2012 ). A critical phase of the edibleoil production chain is the nal rening aimed at removing freefatty acids, which, in too high concentrations, lead to the rancidityof the oil ( Cavanagh, 1976; Sullivan, 1976; Keurentjes et al., 1991;Bhosle and Subramanian, 2005; Martinello et al., 2007; Calliauwet al., 2008; Cuevas et al., 2009; Carmona et al., 2010; Akterian,2011 ), and other minor components such as phospholipids, pig-ments, proteins, oxidation products and the possible residual con-tent of the solvent used for the extraction process. The main

operations involved in conventional rening for removing thementioned components are degumming, neutralization, washing,drying, bleaching, deodorization and ltration ( Gunstone et al.,1994; Mag, 1990; Loft, 1990; Shahidi, 2005; Santori et al., 2012 ).This stage of the production chain is crucial for the qualityenhancement of the nal product.

Onethe morecriticalaspectsof vegetable oil rening is relatedtothe presence of residual volatile solvent used for the extraction. Inparticular, due to the low vapor pressure, the residual solvent maycause a loss of efciency in high temperature vacuum operations

(such as drying, bleaching and deodorization). In these operations,vacuumconditions areoften obtained by ejector systems ( Bockisch,1998; Mag, 1990; Loft, 1990; Muth et al., 1998; Akterian, 2011 ),whose costs are mainly related to the consumption of steam andcooling water for condensation. A possible increase of the residualsolvent concentration has a negative impact on these costs, besidesworseningthe environmental impactrelateddue to higheremissionfactors (odors, pollutant, etc.) ( MRI, 1995; Muth et al., 1998 ).

Another criticality is due to the fact that the extraction solvent istypically technical hexane (extraction grade hexane) ( Dunford andZhang, 2003; MRI, 1995 ) a highly ammable liquid and vapor ( GHShazard statement, Shell, 2012 ). In some critical nodes of the process,thesolvent accumulates in the vapor phaseandmixing with air mayoccur, potentiallyleadingto theformationofammablemixturesandconned explosion of the equipment in case of accidental ignition(NFPA, 2007; Lees, 1996; Tugnoliet al., 2012 ). As reported in a previ-ous work ( Landucci et al., 2011 ) this mainly affects crude oil storage

tanks, as also experienced in two recent severe accidents which in-volved several fatalities ( La Repubblica, 2006; El Economista, 2007 ).Nevertheless, since very low pressure vacuum operations character-ize several stages of the process ( Bockisch, 1998; Mag, 1990; Loft,1990; Shahidi, 2005; Muth et al., 1998; Akterian, 2011; Santoriet al., 2012 ), a low but signicant amount of atmospheric air is en-trained by seals or gaskets mixing with the process vents. This maylead to the formation of ammablemixtures also in process lines.

Even if the vegetable oil rening process is well known, theindustrial facilities are continuously subjected to modications,revamping and new technologies implementation in order toachievea higherprocess efciency ( Shahidi, 2005 ). In the literature,several examples of simulation and experimental analysis of each

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⇑ Corresponding author. Tel.: +39 050 2217907; fax: +39 050 2217866.E-mail address: [email protected] (G. Landucci).

Journal of Food Engineering 116 (2013) 840–851

Contents lists available at SciVerse ScienceDirect

Journal of Food Engineering

j ou rna l homepage : www.e l sev i e r. com/ loca t e / j foodeng

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single stage of the rening process are available ( Keurentjes et al.,1991; Wills and Heath, 2005; Zin, 2006; Ceriani and Meirelles,2006; Didi et al., 2009; Farhoosh et al., 2009; Sampaio et al.,2011 ), while a systematic performance analysis, which has beenextensively applied in the framework of process/chemical industry(Motard et al., 1975; Shaw, 1992; Biegleret al., 1997; Vadapalli andSeader, 2001; Hoyer et al., 2005; Towler and Sinnott, 2013 ) andaimed at taking into account the mentioned critical aspects, is stilllacking.

The present analysis was therefore addressed at investigatingthe vegetable oil rening process by the development of detailedsimulation model using the commercial software ‘‘Honeywell Uni-Sim Design’’ ( Honeywell, 2010a,b ). The analysis was aimed atidentifying the main process streams, the reference substances,and quantifying the mass and energy uxes among the reningplant. The process simulator was applied to case studies represen-tative of the current industrial applications, deriving the input datafrom inlet conditions of an actual vegetable oil renery. Inparticular, the vegetable oil renery of SALOV S.p.A., located inSan Rocchino (Massarosa) (Italy), was considered in the analysis.

The simulation model was validated against actual eld data of the same plant and a sensitivity analysis was performed in order toevaluate the utility consumption and potential safety relevant sit-uations depending on the quality of the input feedstock, in partic-ular evidencing the effect of the residual solvent content on thewhole process efciency.

2. Materials and methods

2.1. Methodological approach

The owchart of the methodology is reported in Fig. 1 , and isbased on the approach followed in a previous work by Landucciet al. (2011) for the analysis of crude vegetable oil storage systems.

The rst step of the methodology was related to characteriza-

tion of the crude vegetable oil composition, which, for each typeof seed or fruit, is determined by environmental conditions duringplant grow and farming soil characteristics. A reference composi-tion representative of different types of oil was used to performthe further steps of the methodology. The second step (see Fig. 1 )

consisted in the schematization of the typical process operationsfor oil rening, with denition of operative conditions for processequipment and evaluation of energy requirements (steam con-sumption and other utilities). Then, a thermodynamic model wasapplied in order to reproduce the vapor/liquid equilibrium of thecrude vegetable oil system (step 3 in Fig. 1 ), implementing thepresence of water and residual solvent content. The model was val-idated against available experimental data.

Next (step 4 in Fig. 1 ), the rening process was simulated withHoneywell UniSim Design. Specic subroutines were imple-mented for the simulation of non-standard utilities such as theejectors used for keeping vacuum conditions in process vesselsand the deodorization operation.

The process simulator was used to perform the optimization of operative conditions given the optimal composition of the feed-stock, in order to minimize the costs related to utilities (step 5 inFig. 1 ). A sensitivity analysis was performed (step 6 in Fig. 1 ) aimedat identifying the system response to the increasing residual sol-vent content in the feedstock and possible restorationcontrol mea-sures. Finally, the possibility of formation of ammable mixturesinside process lines was investigated (step 7 in Fig. 1 ).

2.2. Characterization of the crude vegetable oil

Crude edible oil is a complex multicomponent system. Recentstudies were focused on the detailed experimental or numericalcharacterization of the vapor/liquid equilibrium of this system(Christov and Dohrn, 2002; Rodrigues et al., 2004; Calliauw et al.,2008; Ceriani et al., in press ). Furthermore, advanced modelingtools were implemented for the analysis of the rening processtaking into account different relevant triacylglycerols (TAGs), par-tial acylglycerols (monoacylglycerols MAGs, diacylglycerols DAGs),and the possible residual acid components, such as free fatty acidsof different type ( Rodrigues et al., 2004; Farhoosh et al., 2009; Chi-yoda et al., 2010; Silva et al., 2011; Sampaio et al., 2011; Gera-

simenko and Tur’yan, 2012; Teles dos Santos et al., in press;Ceriani et al., in press ). Nevertheless, since the aim of the presentstudy was to evaluate the effect of residual hexane content onthe safety and energy performance of process equipment, a simpli-ed reference composition was considered. The same approachwas followed in several studies on edible oil processing availablein the literature ( Zhang et al., 2003; Ruiz-Mendez and Dobarganes,2007; Cerutti et al., 2012 ).

Thereference composition implemented in thesimulationmod-el is reported in Table 1 . Such composition is based on the typicalcrude sunower oil feedstock used in SALOV S.p.A. vegetable oilrenery, as already considered by Landucci et al. (2011) . The oilphase of the edible oil was schematized as pure triolein (referenceTAG), while the free fatty acids content is assumed as pure oleic

acid. Minor components such as sterols, tocopherols and squaleneare also present and were implemented in the UniSim Design listof components as ‘‘hypo component’’ ( Honeywell, 2010a ). The hex-ane residual content (schematized as pure n-hexane) was taken as

Characterization of thecrude vegetable oilcomposition

1

Thermodynamic modelfor the estimation ofvapor/liquid equilibrium

3

Validation withexperimental data

Schematization of the oilrefining process

2

Collection of typicaloperations and

process conditionsfrom actual plants

Software implementationof the refining process

4

UniSim tool

Analysis of a case studyand optimization ofprocess conditions

5

Sensitivity analysis6

Assessment ofutilities requirement

Set up of optimalequipment operative

conditions

Increase of residualsolvent concentration

7 Safety aspects

Fig. 1. Flowchart of the methodology.

Table 1

Reference composition of the crude vegetable oilconsidered in the present study based on SALOVrenery data.

Components Mass fraction (%)

Triolein 97.29Oleic acid 2.00n-Hexane 0.10n-C 29 H60 0.15Sterols 0.40Tocopherols 0.06

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0.1% in the baseline case, the maximumvalue allowed for the crudeoil processed by SALOV S.p.A. Nevertheless, this valuemay be high-er, up to 8–10 times the reference value, depending on the type of seed and oil origin. Moreover, the presence of residual and/or pro-cess water was also taken into account in the evaluation of vapor/liquid equilibrium (see Section 2.4 ).

2.3. Schematization of the oil rening process

In order to consider typical rening process conditions, thepurication of sunower oil was simulated assuming a free fattyacid content of 2% to be reduced up to 0.04% (percentages are ex-pressed on a weight basis). A schematization of SALOV process isreported in the Process Flow Diagram (PFD) shown in Fig. 2 . Thisprocess is similar to others reported in the literature ( Bockisch,1998; Ceriani and Meirelles, 2006; Mag, 1990; Loft, 1990; Muthet al., 1998; Shahidi, 2005; Santori et al., 2012 ). The oil is rst neu-tralized by adding sodium hydroxide to an intermediate grade of acidity removing the neutralized soaps and waxes with a centrifu-gal separator. Next, the oil is degummed by adding water and sub-sequently it is sent to centrifugal separation to split the oil fraction

from the solid waste. During this step, the oil is washed with waterand consequently it is dried in a ash separator under vacuumcon-ditions. Next the oil is sent to the bleachingtreatment, aimed at theremoval of color-producing substances and further impurities. Inthis operation the oil is mixed with bleaching earth and activatedcarbon in a stirred reactor operating under vacuum conditionsfor the adsorptionof the mentionedcontaminants. Thestream con-taining bleaching earth and activated carbon is modeled as purewater in the process simulator.

Next the oil is ltered and sent to the deodorization treatment.This section consists of a ‘‘physical neutralization’’ with low pres-sure steam at high temperature under vacuum conditions. The free

fatty acids are stripped by steam in a tray tower and then con-densed in a spray tower, while steam with non-condensable vaporsare sent to the ejectors section. Ejectors are also used to keep therequired vacuum conditions in other low-pressure sections (ashseparator and bleaching reactor, see Fig. 2 ).

Table 2 provides the detailed operative conditions used in eachsection of the rening process.

2.4. Thermodynamic model

The choice and the software implementation of the thermody-namic model is a crucial step for a sound modeling of the reningprocess, since it allows determining the operative conditions ineach equipment unit. The UniSim Design software can implementthe thermodynamic model with different ‘‘property-packages’’(Honeywell, 2010b ) for determining the correct vapor/liquid equi-librium of complex mixtures. The use of the process simulator forthe thermodynamic modeling of complex multicomponent sys-tems is extensively diffused in both scientic and technical studies(Harwardt et al., 2008; Szabo et al., 2011; Towler and Sinnott,2013 ). It is worth mentioning that equation of state models, in gen-

eral, and the Peng–Robinson one and its variants, in particular, arerecommended models in most commercial simulators for hydro-carbon mixtures, also in the presence of water, over a wide rangeof pressure and temperature combinations. More details on theUniSim Design code validation are reported elsewhere ( Honey-well, 2010a,b ).

In the present study, the selected Property Package is based onthe Peng–Robinson equations ( Peng and Robinson, 1976 ) correctedwith the Twu Alpha function ( Twu et al., 1995; Honeywell, 2010b ),which takes into account the excess free energy in order to havemore accurate prediction of vapor pressure. More details on thethermodynamic model implemented in software are reported

NEUTRALIZATION

DEGUMMING WASHING

Equipment items: C: column; E: heat exchanger/condenser; EJ : steam ejector; F: filter; G: pump; P: centrifugal sepa rator; R: reactor; S: flash separator.

Material streams : EA: bleaching earth & activated carbon; EE: exhausted earth; FFA: free fatty acids; FO: feedstock oil; LPS: low pressure steam; MPS:medium pressure steam; RO: refined oil; SH: sodium hydroxide; SW: soaps & waxes; V: vents; WW: Waste water; W: Water.

FO

SH

W

EA

LPS

MPS

V

RO

FFA

SW WW

EER1 R2R3

P1 P2 F1E1a E2

E4

E3

EJ1a/b EJ2a/b EJ3a/b

S1

G1 G2 G3 G4

C1

C2

G5

TI2

TI3 FI1

TI4

PI1

TI1

DRYING BLEACHING DEODORIZATION

E5 E6 E8

W WW

EJ3c

E7

W

E1b

Fig. 2. Schematization of the vegetable oil rening process. Tags represent the process variables used for model validation.

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elsewhere ( Honeywell, 2010b ), while Appendix A summarizes thekey parameters and equations used to predict enthalpy, entropy,the fugacity coefcients for each component of the mixture andthus the vapor/liquid equilibrium.

In order to test the validity of the model, a comparison withavailable experimental data was carried out. A signicant numberof literature studies focuses on vegetable oil/hexane mixtures athigh concentrations of hexane in the liquid phase ( Fornari et al.,1994; Ceriani and Meirelles, 2004; Smith and Florence, 1951 ), typ-ical of extraction processes. The only available data for dilutedsolutions, which are signicant in the present case, are reported

by Smith and Wechter (1950) . Data are referred to the soybeanoil/n-hexane solutions with a residual solvent content in the range0.2–1.32% by weight. The hexane vapor pressure is measured in theexperiments as a function of the temperature. The model was ttedon the experimental results by setting the triolein–hexane binaryinteraction coefcient to 0.095 ( Honeywell, 2010b ). Notice thatfor all other pairs of compounds, the default values of binary inter-action coefcients were used. All binary interaction coefcients arereported for completeness of exposition in Appendix A.

Fig. 3 reports a comparison between experimental data and val-ues calculated with Unisim Design of n-hexane partial pressure inthe vapor phase as a function of temperature and hexane concen-tration in the oil phase. As can be observed in this gure, the modelgives a quite accurate prediction with major deviations on the safe

side (e.g., 17% overpredictionof n-hexane vapor pressure). Thedatawere linearly extrapolated for temperatures lower than 75 C asal-ready performed in a recent publication ( Landucci et al., 2011 ), inwhich, however, the effect of water on the vapor phase composi-tion was neglected and the model was set up only for the analysisof storage conditions.

2.5. Simulation model implementation

The process simulation model, implemented in the UniSimDesign software, was aimed at evaluating the energy consumptionof the plant and the more critical nodes in which hexane is

accumulated, both in ordinary process conditions and followingunexpectedprocess deviations. Forthe sakeof brevityonly themainissues related to vegetable oil rening simulator and innovative as-pects connectedwith theanalysisof themore importantequipmentare summarized in the following sections. In order to highlight thecomplexity of the developed process simulation model and thepotentialitiesof themethod, the Supplementaryinformation lere-ports samples of the UniSim Design process owdiagrams (PFDs).

2.5.1. CondensersThe condensers are critical units under the point of view of

energetic efciency of the process. These units are aimed at con-densing the steam outlets from the ejectors connected to the mainprocess equipment to keep vacuum conditions (see specicdescription in Section 2.5.3 ) by the use of cooling water availablein the renery plant. Fig. 2 shows the condensers associated tothe ejector of the drying section (E5), bleaching (E6) and deodor-ization (E7 for the rst and second stage ejectors, E8 for the thirdstage ejector). The sample UniSim Design PFD for the condenserE5 is shown in Supplementary information .

The cooling water owrate is the variable manipulated by thesoftware (ADJ 1 operator) which determines its value by imposinga xed temperature of 20 C for the condensate. This implementa-tion allows for a better stability of the model in presence of inputdeviations on the crude oil composition. The condenser parameterswere determined after a preliminary rating operation. The typicalrange of cooling water owrates, derived from actual plant designdata, was imposed in a preliminary dedicated simulation model to-gether with the geometry documented in the equipment data-sheets, thus calculating in the so-called rating mode an averagevalue for the pressure drops and heat transfer coefcient.

Then, condensers are implemented in the overall simulationmodelby imposing thepressure drops onboth tubes andshell sides,and the product of the geometry area times the overall heat transfercoefcient (‘‘designmode’’, see Honeywell(2010a) formoredetails).

This modeling approach was associated to the condensers E5,E6 and E7 (see Fig. 2 ), while for condenser E8 a different approachwas followed. Since this unit receives the cooling water alreadyused in condenser E7, associated to ejectors EJ3a and EJ3b (seeFig. 2 ), its modeling using an a priori xed value for the overalltransfer coefcient may be inaccurate. In fact, the cooling wateris manipulated to satisfy specications on other upstream unitsand may vary signicantly. Therefore, the so-called ‘‘rating mode’’(see Honeywell (2010a) for more details on this procedure) wasused, in which one species the exchanger geometry (number/dimensions/arrangements of tubes, shell passes, etc.) and appro-priate correlations are internally used to evaluate the heat transfercoefcients and pressure drops on the basis of actual owrates.

2.5.2. Deodorization column

The deodorization stage is aimed at removing minor compo-nents (e.g., squalene and polycyclic aromatic compounds) whichcause odor and the loss of quality of the nal product. The deodor-ization column (C1 in Fig. 2 ) is a stripping column made of vechambers, each fed with low pressure steam (LPS, at 1.5 bar). Thetotal LPS mass owrate is set as the 1.8% of the total rened oilowrate. The hot exhausted vapors from each chamber are col-lected and fed to a water scrubber (C2 in Fig. 2 ), where the fattyacids are removed and purged.

In order to reach the requiredstrong vacuumconditions (inpar-ticular, 0.2 kPa pressure and temperature higher than 220 C) theejector system depicted in Fig. 2 is required.

The column was modeled in the UniSim Design software byimplementing six separators in series, aimed at representing the

ve chambers of the column C1 plus the bottom of the column,in which the separation is also carried out thus reaching the

Table 2

Operative conditions of the main sections of the rening process.

Process section Operative temperature ( C) Operative pressure (kPa)

Neutralization 20 100Degumming 60–70 100Washing 90 100Drying 90 5Bleaching 105 6

Deodorization 230 0.2

Fig. 3. Validation of the thermodynamic model developed in UniSim Design. HEX:

residual hexane content in thecrudevegetable oil(% by weight basis).Experimentaldata were derived from Smith and Wechter (1950) .


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vapor/liquid equilibriumconditions. For the rst four separators anenergy stream is added in addition to the LPS stripping stream inorder to simulate the presence of high pressure steam (saturatedsteam at 40 bar) fed to internal heating coils inside the C1 columnchambers in order to keep high temperature conditions. The Uni-sim Design PFD is reported in Supplementary information .

2.5.3. EjectorsSeveral steam driven ejectors are used in the renery to obtain

the needed vacuum conditions in the process equipment. As evi-denced in Section 2.5.1 these pieces of equipment are critical forthe energy performance assessment of the renery plant. However,no dedicated model is available in the process simulator for ejec-tors. Thus, a specic modeling tool was implemented in the soft-ware in order to achieve an accurate performance evaluationexploiting the UniSim Design software ‘‘User Unit Operation’’

function. The function allows inserting the data derived from ac-tual ejector systems datasheets, in particular the design curves.These curves report the entrainment ratio (1/ l ), given by the suc-tion ow related to air at 20 C respect to the motive steam ow, asa function of the ratio between the discharge and suction pressures(P d/P s). The curves vary according to the parameter given by the ra-tio between suction and motive steam pressures ( P s/P m). The anal-ysis of the design curves and optimization of ejector systems isextensively described in the technical literature ( Meherwan,1999; Akterian, 2011 ).

Hence, by setting the pressures of the equipment in vacuumconditions (e.g., P s), of the motive steam (e.g. P m) and of the dis-charge ( P d) it is possible to derive by reading on the curves theentrainment ratio and calculating the necessary mass ows asfollows:

1

l¼

maMS

1

K ejð1 Þ

where ma is the entrained ow of air at 20 C, MS is the ow of mo-tive steam and K ej is a correction factor for suction ows other thanair, expressed as follows:

K ej ¼ ffiffiffiffiffiffiffiffiffiffiRS T S RLT Ls ð2 Þwhere RS is the gas constant of suction ow, RL the gas constant of air (=287 J kg 1 K 1), T S the temperature (in K) of suction ow, T Lthe reference air temperature for the ejector (=293 K).

Table 3

Fitting parameters for the approximation of the ejectorsdesign curves (see Eq. (3)).

Parameter ( P s/P m) X 1 X 20.001 4.14 0.9830.002 3.81 0.9100.005 3.38 0.7320.010 3.03 0.6730.020 2.70 0.6150.050 2.26 0.489

Table 4

Comparison between the process parameters evaluated by the model and the available eld data. For tags locations, see Fig. 4.

TAG Description Units Model results Field data

FI1 Rened oil exit ow kg/h 14,558 14,075PI1 Pressure in the deodorization column kPa 0.2 0.22TI1 Temperature of the bleaching reactor C 104.8 110.1TI2 Temperature of crude oil at the deodorization inlet C 231.7 230.7TI3 Rened oil exit temperature C 160.9 154.8TI4 Temperature of the deodorization column top side C 135.8 153.0

Drying

Bleaching

Deodorization

Crude oil fromneutralization

Refined oilto storage

2

3

4

1

CW1

CW2

CW3

CW4

CW5

CW6

H1 H2 H3Bleaching

earth &activatedcarbon

5

C1 C2 V1

C3 V2

C5 V3E5 E6

H4 H5 H6 E2

H7 H8 H9 E3 E4

W1

E1

W2

LEGEND:

CCWEHVW

Condensed steamCooling water Energy streamLow or medium pressure steamVentProcess wasteMaterial stream tag

C4

E7

Fig. 4. Schematic representation of the heat and material balance on the analyzed plant sections.


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In order to obtain more realistic results, the actual datasheet of industrial ejector systems were obtained ( Körting Hannover AG,1994 ) inserting in the UniSim Design software ‘‘Unit Operation’’function the numerical interpolation of the design chart curvesas follows:

maMS

¼ X 1P d=P s

X 2

ð3 Þ

where X 1 and X 2 are tting constants reported in Table 3 for differ-ent values of the parameter P s/P m .

In the process simulator, for each equipment operating in vac-uum conditions the suction temperature, the suction pressure

and the motive steam pressure are specied as input parameters;hence the software applies Eqs. (1)–(3) to evaluate the motive

steam ow which is necessary to keep an imposed dischargepressure.

Therefore, by varying the input conditions, e.g. due to devia-tions in the process (in particular, the increase of volatile com-pounds affect the suction ow), the energetic consumptions areevaluated by calculating the necessary motive steam ow neededto restore the optimum process conditions.

3. Results and discussion

3.1. Model validation and case study analysis

In order to validate the process simulator, actual eld data werederived from SALOV S.p.A. renery during typical working

Table 5

Heat and material balance on the plant sections analyzed in the present study. For the identication of the streams, refer to Fig. 4. Composition is expressed in percentages byweight basis.

Item Material streams

1 2 3 4 5 b W1 W2

Temperature ( C) 90.0 a 84.3 105.2 20.0 a 25.0 a 105.0 48.4Pressure (kPa) 195.0 200.0 a 210.0 a 186.0 200.0 a 8.0 0.2Flowrate (kg/h) 14,887.5 14,795.2 14,695.0 14,558.4 14.8 97.8 133.0 a

Triolein (%) 98.14 98.74 98.75 99.62 0.0 100.0 5.2Water (%) 0.55 0.01 0.01 0.0 100.0 0.0 0.0n-Hexane (%) 0.10 0.02 0.01 0.0 0.0 0.0 67.3Oleic acid (%) 0.60 0.61 0.61 0.0 0.0 0.0 0.0Other (%) 0.61 0.62 0.62 0.38 0.0 0.0 27.5 c

a Value imposed to process simulator.b The stream containing bleaching earth and activated carbon is modeled as pure water.c Spent bleaching earth.

Table 6

Heat and material balance on the plant utilities. For the identication of the streams, refer to Fig. 4. C = steam condensate; CW = cooling water; E = energy stream; H = steam;V = vent.

ID Physicalstate

Description Thermal power(kW)

Flowrate(kg/h)

Temp.( C)

Pressure(kPa)

Drying sectionC1 Liquid Steam condensate associated to ejector EJ1a 150.1 19.0 16.5C2 Liquid Steam condensate associated to ejector EJ1b 1153.0 127.5 250.0CW1 Liquid Cooling water fed to the drying section condensers 9282.0 8.0 150.0CW2 Liquid Cooling water exiting the drying section condensers 9282.0 18.0 149.9H1 Vapor Motive steam fed to rst stage ejector EJ1a 70.1 175.5 900.0H2 Vapor Motive steam fed to second stage ejector EJ1b 53.4 175.5 900.0H3 Vapor Drying steam pre-heating in E1a 1153.0 127.5 250.0V1 Vapor Vent exiting from drying section 70.6 123.2 108.0E1 – Heat removed in downstream degumming section with heat exchanger 142.0

Bleaching sectionC3 Liquid Steam condensate associated to ejector EJ1a 301.0 127.5 250.0C4 Liquid Steam condensate associated to ejector EJ1b 30.4 19.8 16.5CW3 Liquid Cooling water fed to the bleaching section condensers 1180.8 8.0 150.0CW4 Liquid Cooling water exiting the bleaching section condensers 1180.8 20.0 150.0H4 Vapor Motive steam fed to rst stage ejector EJ2a 15.6 175.5 900.0H5 Vapor Motive steam fed to second stage ejector EJ2b 27.6 175.5 900.0H6 Vapor Bleaching steam pre-heating in E1b 301.0 127.5 250.0V2 Vapor Vent exiting from bleaching section 35.4 134.0 108.0E2 – Bleaching pre-heating 11.0

Deodorization sectionC5 Liquid Steam condensate associated to ejector EJ3 1537.0 19.8 102.5CW5 Liquid Cooling water fed to the deodorization section condensers 240,000.0 8.0 150.0CW6 Liquid Cooling water exiting the deodorization section condensers 240,000.0 12.0 140.9H7 Vapor Motive steam fed to rst stage ejector EJ3a 1100.1 175.5 900.0H8 Vapor Motive steam fed to second stage ejector EJ3b 157.1 175.5 900.0H9 Vapor Motive steam fed to third stage ejector EJ3c 26.0 175.5 900.0V3 Vapor Total ventowrateexiting from deodorization section condensers (E7 and

E8)33.8 132.4 108.0

E3 – C1 chambers external coil heating 89.0E4 – Steam (40 bar) for oil preheating 448.0E5 – Cooling of scrubber C2 recycle 53.0E6 – Air cooler 1055.0E7 – Cooling unit 163.0



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operations, and compared with the ones predicted by the model inthe correspondent locations. The results of the validation are re-ported in Table 4 , in which the tags of the monitored process vari-ables are indicated in the PFD shown in Fig. 2 . As shown in thetable, the simulator allows for a good reproducibility of actual pro-cess conditions, such as temperature, pressure and materialstreams, with a maximum relative error of 11%.

The simulator was used to investigate the criticalities of the veg-etable oil rening process and the inuence of the residual solventcontent on the process efciency. In particular, the simulator al-lowed identifying the more critical nodes in which the solvent isaccumulated and tracing the different sections respect to the initialcrude oil content. Themain hexaneaccumulation node is thedryingash, in which 76.6% of hexaneis removed, while minor residual areaccumulated in the other sections, in particular 12.7% and 10.7%respectively in bleaching and deodorization sections. Thus, a possi-ble increaseof hexaneresidual maylead to processefciency decre-ment, in terms of motivesteam consumption for theejector system.

In order to systematically quantify the renery energy con-sumption and to determine the critical factors affecting the ef-ciency, the process simulator results were analyzed.

Fig. 4 reports the block diagram of the process evidencing themain material streams together with the energy and utility lines.The main product streams are marked together with the possibleprocess vent and wastes/residuals (respectively labeled with ‘‘V’’and ‘‘W’’ in Fig. 4 ). The cooling utility is mainly water (‘‘CW’’ inFig. 4 ), while steam at different pressures is the heating utility, also

employed in the mentioned ejector system. The steam enteringeach block are labeled with ‘‘H’’ in Fig. 4 , while the exit condensateis labeled with ‘‘C’’. In order to simulate further heat exchanges inand out of the simulator boundaries and passing between unitoperations (steam coils, air coolers, etc.) several ‘‘energy streams’’were added to the scheme (labeled with ‘‘E’’ in Fig. 4 ) using a spe-cic UniSim Design software function.

The quantication of the heat and material balance for thescheme ( Fig. 4 ) is reported in Tables 5 and 6 , respectively for pro-cess streams and utilities.

As can be seen in Table 5 , the oil content (schematized as puretriolein) increases passing through the different sections. The major part of water is eliminated in the drying section, as expected,while the acid fats content, residual of the upstream neutralizationis totally removed in the deodorization section.

Considering the energy consumptions, synthetically repre-sented by the results shown in Table 6 , the bleaching section fea-tures the lowest thermal requirements, both in terms of hot andcold utilities. On the contrary, it clearly appears that the most crit-ical section, under the point of view of energy requirements, is the

Fig. 5. (a) Example of optimization for ejector EJ1a/b for the base case with hexaneresidual content of 0.1% by weight basis; (b) optimization of intermediate pressure(P int ) as a function of different hexane residual content in the inlet crude oil (% by

weight basis) for the three ejectors groups reported in Fig. 2. MS = motive steam.

Fig. 6. Variation of the main process parameters as a function of the increasinghexane concentration in the inlet crude oil: (a) cooling utility (water) and heatingutility (ejectors motive steam) consumption; (b) hexane removal (% of the initialresidual content in the crude oil) in the different renery sections.

Table 7

Air inltration considered in the process vents of the different plant sections

operating under vacuum conditions.

Type of inltration Air inltration (kg/h)

Drying Bleaching Deodorization

Type 1 3 3 3Type 2 a 5 5 6Type 3 8 8 10

a Value derived from manufacturer data ( Körting Hannover AG,1994 ).



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deodorization. Both steam and cooling water utilities have thehighest requirements in order to keep the severe operative condi-tions imposed by the process. In particular, low pressure (0.2 kPa)leads to major motive steam consumption and associated cooling

water for condensation, while the high operative temperature of the column (230 C) is kept also by the use of additional heating(energy streamE4 in Table6 ) carried out with high pressure steam.Besides, additional heat exchangers are needed for cooling thescrubber C2 (see Fig. 2 ) recycle and the vents before the treatmentand the discharge in the atmosphere.

3.2. Process optimization and sensitivity analysis

The analysis of the renery in the baseline case (0.1% hexane byweight basis in the inlet crude oil) highlighted the criticalities re-lated to the energy consumptions in the renery lowpressure units(e.g., drying, bleaching and deodorization). Since the ejector sys-

tems operative conditions affect the whole renery energetic per-formance, the process simulator was applied in order to optimize

the operating conditions for the minimization of motive steamconsumption. The optimization was carried out on the three ejec-tor systems considering that the motive steam is available in theplant at the same pressure (medium pressure steam, MPS at 9 bar).

Fig. 5 a reports an example of optimization, in particular relatedto the ejector system connected to the drying ash drum (EJ1a/bwith condenser E5, see Fig. 2 ). As can be seen in the scheme, theejector is constituted by two different sections in which P

s is the

suction pressure, representative of the equipment operativeconditions, P out the system discharge pressure, MS A and MS B themotive steam streams respectively for the rst and second stage,and P int is the intermediate pressure, which is the degree of free-dom (DOF) to specify for the optimization. The optimization is car-ried out by varying both MS A and MS B and nally obtaining the P intwhich minimizes the overall steam consumption (e.g., the sum of MSA and MS B), as shown in Fig. 5 a. Determining the intermediateejectors pressure allows for the process energetic efciencyenhancement.

The described optimization method can be performed also byconsidering a possible increase of the inlet residual hexane con-tent, as reported in Fig. 5 b. In particular the gure shows the opti-mized intermediate pressure for all the considered ejector systems(see Fig. 2 for tags and equipment representation). These outcomesmight be potentially applied when a different feedstock quality isaccepted and processed by the renery for a mid- or long-termperiod, with the need of a systematic improvement of the operat-ing conditions. As shown in Fig. 5 b, the increase of the residualhexane content has a stronger inuence on the drying and bleach-ing sections respect to the deodorization, since in these sectionsthe major part of hexane is removed (see Section 3.1 ). This resultsin the increase of the intermediate pressure for optimizing the mo-tive steam consumption.

The results of the sensitivity analysis carried out by varying theinlet hexane concentration and optimizing the operating condi-tions and process variables are reported in Table B1 of AppendixB. The table allows determining the optimized operating condi-tions referring to the base case discussed in Section 3.1 .

On the basis of the sensitivity analysis results, the overall utili-ties requirements were derived and shown in Fig. 6 . Fig. 6 a showsthe increase of the overall motive steam and cooling water con-sumption by varying the inlet hexane concentration of one orderof magnitude (e.g., ranging from0.1% to 1.5% by weight basis). Mo-tive steam consumption is increased by 40%, showing a more sig-nicant variation respect to cooling water utility, which increaseis limited to 1%. This is due to the fact that the highest owrateof cooling water is a xed simulation parameter, since it is fed tothe condenser of the third ejector (EJ3c, see detailed descriptionof simulation set up in Section 2.5.1 ). This owrate is almosttwenty times higher than the sum of the other cooling water util-ities, which can be varied in order to control the condensate tem-

perature (see Section 2.5.1 ).In order to determine the variation in the process vents behav-

ior due to the increase of inlet hexane concentration, Fig. 6 b pre-sents the change in the hexane removal percentage (thus,startingfrom the values evaluated at 0.1% residual hexane content,see Section 3.1 ) in each process section. The results highlight thatthe excess hexane is mainly removed in the drying section, due tothe oversizing of the equipment. Hence, this allows decreasing thehexane amount fed to the downstream units, which hexane re-moval decreases as shown in Fig. 6 b.

Therefore, the sensitivity analysis allowed determining thechange in process parameters and utility requirements for restor-ing the process operating conditions given unforeseen changes of the inlet feedstock. It clearly appears that the increase of volatile

solvent residual has a negative impact on the energetic costs of the rening process.

Fig. 7. Comparison between the ammability range of hexane considering twoinert reference gases (carbon dioxide and nitrogen) and vapor concentration in theventing line for (a) drying, (b) bleaching and (c) deodorization considering aresidual hexane content of 0.1% by weight basis in the inlet crude oil. For airinltration types characterization, see Table 7 .



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3.3. Formation of ammable mixtures inside process streams

The process simulator pointed out the more critical nodes forhexane accumulation, also considering the potential variation of the initial hexane residual in the process feed. Among the possi-ble hazards related to the presence of hexane inside processpipes, one of the critical issues is related to the possibility of air entrainment from gaskets and seals in strong vacuum operat-ing pipes, thus leading to the formation of ammable mixturesin conned spaces. This might lead to re and explosion hazardsin case of accidental ignition of the ammable mixture, alreadyhighlighted for the storage equipment in a previous work ( Land-ucci et al., 2011 ).

Therefore, the process simulator was employed to investigatethis problem, considering an additional air ow in the three ventlines (V1, V2 and V3, see Fig. 4 ) given a reference air entrainmentvalue, specied by the ejector manufacturer ( Körting HannoverAG,1994 ) for the vent discharge line. Table 7 reports the consideredentrainment value (inltration type 2), also considering a possiblenegative or positive variations respect to this reference value(respectively, inltration types 1 and 3 in Table 7 ).

Fig. 7 reports the evaluated residual hexane concentration inthe vent lines evidencing the possibility of formation of ammablemixtures in the drying ( Fig. 7 a), bleaching ( Fig. 7 b) and deodoriza-tion ( Fig. 7 c) sections as a function of the different air entrainmentrates given a xed hexane residual content in crude oil feed (e.g.,

0.1% by weight basis). A ammable mixture is potentially formedif the calculated concentration point enters inside the ammablerange, i.e. the region of the chart included inside the reference con-tinuous lines. In absence of data for water as inerting uid, the ef-fect of nitrogen (bright lines in Fig. 7 ) and carbon dioxide (darklines in Fig. 7 ) as diluents was taken into account in order to obtainpreliminary indications for the methodology ( Mashuga and Crowl,1998; Zabetakis, 1965 ). Furthermore, the ammability range is af-fected by operative pressure and temperature, but the use of datareferred to 25 C temperature and 1.01 bar allows for evaluation of the ammability hazards on the safe side in the considered processsections ( Lees, 1996 ).

The results make clear that in the case of higher hexane concen-tration in the vent line, the entrained air is not sufcient to formammable mixtures, thus leading to a less hazardous situation.This is the case of the drying section, in which the major part of hexane is removed and, as shown in Fig. 7 a, and in which noneof the calculated points fall under the ammable region even forhigh air entrainment rates. On the contrary, for the other two sec-tions, the hexane vent content is lower and some points calculatedfor high air entrainment rates especially in the deodorization sec-tion vent (see Fig. 7 c), fall into the hazardous zone. This evidences asafety criticality for strong vacuum operating equipment in pres-ence of ammable vapors.

Hence, this type of hazard might be taken into account duringthe vent pipeline design and in maintenance operations.

Table A1

Main parameters and equations implemented in the thermodynamic model ( Honeywell, 2010b ).

ID Equation Description Parameters

Eq. (1) P ¼ RT V b a

V ðV þ bÞþ bðV bÞ Peng–Robinson state equation P = Pressure (Pa)

R = 8314(J kmol 1 K 1) universal gasconstantT = Temperature (K)V = Volume (m 3)

a = see Eq. (6)b = see Eq. (5)Eq. (2) Z 3 - ( 1 - B) Z 2 + ( A - 2 B - 3 B2 ) Z - ( AB - B2 - B3) = 0 Peng–Robinson expressed in terms

of the compressibility factor Z Z = Compressibility factor = (PV)/(RT) A = see Eq. (3)B = see Eq. (4)

Eq. (3) A = aP /( RT )2 Parameter in Eq. (2) a = see Eq. (6)Eq. (4) B = bP /( RT )2 Parameter in Eq. (2) b = see Eq. (5)Eq. (5) b ¼ PN i¼1 xibi ; bi ¼ 0:077796

RT c ;iP c ;i

1st Peng–Robinson equationcoefcient for mixtures

xi = mass fraction of the ithcomponent of the mixture of N components.T c ,i = critical temperature of the ithcomponentP c ,i = critical pressure of the ithcomponent

Eq. (6) a ¼ PN i¼1P

N j¼1 xi x jða ia jÞ

0:5 ð1 kijÞ; ai ¼ ac ;ia ia c ;i ¼ 0:457235

ðRT c ;i Þ2

P c ;i ; a0:5i ¼ 1 þ mið1 T

0:5r ;i Þ

2nd Peng–Robinson equationcoefcient for mixtures – originalformulation

T r ,i = T /T c ,ikij = system specic experimentalbinary interaction factorm i = see Eq. (7)

Eq. (7) mi ¼ 0:37464 þ 1 :5422 x i 0 :26992 x 2i ; x i 6 0 :49m i ¼ 0:379642 þ ð 1:48503 ð0 :164423 0 :016666 x iÞx iÞx i ; x i > 0:49

Polynomial factor for Eq. (6) –original formulation

x i = Acentric factor of the ithcomponent

Eq. (8) a i ¼ T N i =ðM i 1Þr ;i exp ðLið1 T N i M ir ;i ÞÞ

Twu Alpha function for Peng–Robinson correction for Eq. (6)

Li, M i, N i = Parameters of pure ithsubstance (see details in Honeywell(2010b) )

Eq. (9) H H IDRT ¼ Z 1

12 1:5 bRT

a T d adT ln V þð 20:5 þ 1Þb

V þð 20:5 1Þb Enthalpy equation H = predicted enthalpyH ID = reference enthalpy evaluatedat 25 C and 1.01 bar

Eq. (10) S S IDR ¼ ln ð Z bÞ ln ðP =P Þ

A21:5 bRT

T a

dadT ln V þð 2

0:5 þ 1ÞbV þð 20:5 1Þb Entropy equation S = predicted entropyS ID = reference entropy evaluated at

25 C and 1.01 barP pressure in the reference state(1.01 bar)

Eq. (11) ln / i ¼ ln Z PbRT þ ð Z 1Þbib a21:5 bRT 1a 2a0:5i PN j¼1 x ja0:5 j ð1 kijÞ bib

ln V þð 20 :5 þ 1Þb

V þð 20 :5 1Þb

Evaluation of fugacity coefcient / = mixture fugacity coefcient of for the ith component



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4. Conclusions

In the present work a quantitative methodology was developedfor the performance analysis of the vegetable oil rening process.

An advanced thermodynamic model was implemented in orderto reproduce the vapor/liquid equilibrium of crude vegetable oil –residual solvent system. The model was validated against available

experimental data and was implemented in the rening processsimulator, developed on the Honeywell UniSim Design software.The simulator allowed for a detailed performance analysis of

the process. The results were compared with eld data obtainedfrom an actual vegetable oil renery showing good agreement inreproducing the rening process in the reference conditions.

The effect of the residual solvent content increase on the pro-cess efciency was investigated, determining the most signicantnodes of solvent accumulation among the plant process operationsand evaluating its inuence on the global energy requirements. Inparticular, the ejector systems, aimed at keeping vacuumoperatingconditions, were deeply investigated, evaluating the utility con-sumption increment. Both motive steam andcooling water for con-densers were analyzed by varying the residual hexane content inthe input crude oil and determining the modication in the opera-tive conditions for minimizing the energy costs. The study evi-denced the criticalities related to the management of inlet crudeoil quality, in terms of residual solvent content control, for theenhancement of the global process efciency.

Finally, the simulator also allowed investigating the potentialhazards due to formation of ammable mixtures inside the processvent lines, in presence of purged hexane vapors and air entrainedby gaskets and/or seals of vacuum operating pipelines. The resultsevidenced the conditions in which ammable mixtures mightpotentially be formed inside the process vents, with re and explo-sion hazards in presence of accidental ignition.

Acknowledgement

The authors gratefully acknowledge nancial support receivedfrom Regione Toscana (Bando Unico R&S n.2009DUA/526090469/1).

Appendix A

The present section provides details on the thermodynamicmodel implemented in Unisim Design ( Honeywell, 2010a,b ).The selected model is based on the Peng–Robinsonequations ( Pengand Robinson, 1976 ) corrected with the Twu Alpha function ( Twuet al., 1995; Honeywell, 2010b ), which takes into account the ex-cess free energy in order to have more accurate prediction of vaporpressure. Table A1 summarizes the key parameters and equationsused to predict enthalpy, entropy, the fugacity coefcients for eachcomponent of the mixture and thus the vapor/liquid equilibrium.Tables A2 and A3 report the specic parameters selected for eachsubstance considered in the present study.

Appendix B

Table B1 reports the results of the process optimization andsensitivity analysis, comparing the baseline case results (BC) andthe optimized cases (OCs) by varying the residual hexane content(HEX in the following, expressed in % by weight basis) up to oneorder of magnitude respect to the BC, which features HEX= 0.1%.

The rst column of the table reports the process variable of interest (EJ: ejector, MS: motive steam, CW: cooling water, seeFigs. 4 and 5 ). The second column report the results obtained forthe baseline case with HEX = 0.1%, while the third column showsthe correspondent optimization of process variables aimed at

Table A3

Determination of system specic binary interaction factor ki, j (i: columns; j: rows) (see Eq. (11) in Table A1 ).

ki, j i ? j; Triolein Oleic acid n-Hexane n-C29H60 Sterols Tocopherols Water

Triolein – 0 0.095 0 0 0 0Oleic acid 0 – 0 0 0 0 0n-Hexane 0.095 0 – 0.031 0 0 0.48n-C29H60 0 0 0.031 – 0 0 0.48Sterols 0 0 0 0 – 0 0Tocopherols 0 0 0 0 0 – 0Water 0 0 0.48 0.48 0 0 –

Table A2

Main parameters selected for the present analysis ( Honeywell, 2010b ). For parameters denition see Table A1 .

Parameter (see Table A1 ) Equation (see Table A1 ) Units (SI) Assigned parameter for each component – Unisim Design library

Triolein Oleic acid n-Hexane n-C 29 H60 Sterols Tocopherols Water

T c ,i 5 C 680.9 496.9 234.7 564.9 668.1 646.7 374.1P c ,i 5 kPa 360.2 1390 3032 826 999.7 945.9 22,120Li 8 – – a 0.7760 0.1363 0.3688 – a –a 0.3831M i 8 – – a 0.8235 0.8620 0.8247 – a –a 0.8701N i 8 – – a 0.8235 0.8620 0.8247 – a –a 0.8701L0 see note (a) – 0.1253 – – – 0.1253 0.1253 –M0 see note (a) – 0.9118 – – – 0.9118 0.9118 –N0 see note (a) – 1.9482 – – – 1.9482 1.9482 –L1 see note (a) – 0.5116 – – – 0.5116 0.5116 –M1 see note (a) – 0.7841 – – – 0.7841 0.7841 –N1 see note (a) – 2.8125 – – – 2.8125 2.8125 –x i see note (a) – 1.6862 – – – 0.9863 0.9624 –

aThe parameters Li, M i and N i depend on individual compounds and were retrieved from UniSim Design library for the application of Eq. (8) of Table A1 . Nevertheless, for

non-library compounds, the Twu alpha function can be estimated by the following expressions: a i ¼ að0Þ

i ðT Þ þ x iðað1Þi ðT Þ a

ð0Þi ðT ÞÞ where a

ð0Þi ¼T

N 0=ðM 0 1Þr ;i

exp ðL0ð1 T N 0M 0r ;i ÞÞ; að1Þi ¼ T

N 1=ðM 1 1Þr ;i exp ðL1ð1 T

N 1M 1r ;i ÞÞ; T r ;i ¼ T =T c ;i .

In this case, Table A2 reports the relevant parameters for the estimation of the Twu alpha function (L0, M0, N0, L1, M1, N1 and x i).



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keeping the same operative condition in process equipment. Theother column of the table shows the results in case of higher

HEX values. In particular, the third column shows the variationof the process variables able to restore the normal operative condi-tions in presence of HEX= 0.5%, while the fourth column reportsthe correspondent optimized process variables and operative con-ditions. The same type of results are shown in the fth and sixthcolumn for HEX = 1.0%.

Appendix C. Supplementary material

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.jfoodeng.2013.01.034 .

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Table B1

Results of the sensitivity analysis. BC = base case; OC: optimized case; RHC: residual hexane content.

Process variable HEX = 0.1% HEX = 0.5% HEX = 1.0%

BC OC BC OC a BC OC a

EJ1a/b operative pressure (kPa) 16.5 14.0 16.5 25.5 16.5 26.0EJ2a/b operative pressure (kPa) 16.5 20.0 16.5 22.5 16.5 24.0EJ3a/b operative pressure (kPa) 2.8 2.9 2.8 3.0 2.8 3.0EJ3c operative pressure (kPa) 20.0 11.0 20.0 12.0 20.0 12.0MSA for EJ1a/b owrate (kg/h) 70.1 55.2 90.4 165.7 115.2 223.1MSB for EJ1a/b owrate (kg/h) 53.4 64.1 177.1 66.0 342.3 63.0MSA for EJ2a/b owrate (kg/h) 15.6 20.7 18.8 28.6 22.2 38.4MSB for EJ2a/b owrate (kg/h) 27.6 21.7 47.5 32.7 68.7 42.5MSA for EJ3a/b owrate (kg/h) 1100.1 1138.3 1113.9 1171.7 1127.3 1205.3MSB for EJ3a/b owrate (kg/h) 157.2 55.0 216.6 78.7 275.4 95.7MSA for EJ3c owrate (kg/h) 26.0 50.3 42.0 69.0 61.3 94.5CW1&CW2 owrate (kg/h) 9282.2 9061.0 10,330.0 12,026.2 11,604.5 14,534.7CW3&CW4 owrate (kg/h) 1180.8 1316.0 1375.0 1664.2 1637.4 2099.6CW5&CW6 owrate (kg/h) 240,000.0 240,000.0 240,000.0 240,000.0 240,000.0 240,000.0

a Respect to the base case.


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Analysis and Simulation of an Industrial Vegetable Oil Refining Process