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Analysis and simulation of an industrialvegetable oil refining process
ARTICLE in JOURNAL OF FOOD ENGINEERING · JUNE 2013
Impact Factor: 2.77 · DOI: 10.1016/j.jfoodeng.2013.01.034
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Università di Pisa
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Analysis and simulation of an industrial vegetable oil refining process
Gabriele Landucci a,⇑, Gabriele Pannocchia a, Luigi Pelagagge b, Cristiano Nicolella a
a 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 2012
Received in revised form 1 November 2012
Accepted 27 January 2013
Available online 4 February 2013
Keywords:
Vegetable oil refining
Process simulation
Advanced thermodynamic models
Formation of flammable mixtures
a b s t r a c t
This work focuses on the performance analysis of an industrial vegetable oil refinery. Using a commercial
process simulator, a process model was developed and validated against actual vegetable oil refinery field
data. 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 nodes
for hexane accumulation in the process were evaluated, both considering ordinary operative conditions
and undesired process deviations due to increase of the hexane content. In this latter case, the control
actions 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 operating
conditions. Finally, the possibility of flammable mixtures formation inside process vent pipes, caused by
the entrainment of air due strong vacuum conditions, was also investigated.
2013 Elsevier Ltd. All rights reserved.
1. Introduction
Edible oil production by extraction processes greatly increased
in the last century due to both higher request and consumption
(FAO, 2011) and the progressive availability of more efficient pro-
cess technologies and equipment (Bockisch, 1998; Mielke, 1990;
Shahidi, 2005; Veloso et al., 2005; Calliauw et al., 2008; Cuevas
et al., 2009; Haslenda and Jamaludin, 2011; Szydłowska-Czerniak
et al., 2011; Zulkurnain et al., 2012). A critical phase of the edible
oil production chain is the final refining aimed at removing free
fatty acids, which, in too high concentrations, lead to the rancidity
of the oil (Cavanagh, 1976; Sullivan, 1976; Keurentjes et al., 1991;
Bhosle and Subramanian, 2005; Martinello et al., 2007; Calliauw
et 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 refining for removing thementioned components are degumming, neutralization, washing,
drying, bleaching, deodorization and filtration (Gunstone et al.,
1994; Mag, 1990; Loft, 1990; Shahidi, 2005; Santori et al., 2012).
This stage of the production chain is crucial for the quality
enhancement of the final product.
Onethe more criticalaspectsof vegetable oil refining is relatedto
the presence of residual volatile solvent used for the extraction. In
particular, due to the low vapor pressure, the residual solvent may
cause a loss of efficiency in high temperature vacuum operations
(such as drying, bleaching and deodorization). In these operations,
vacuum conditions are often 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 and
cooling water for condensation. A possible increase of the residual
solvent concentration has a negative impact on these costs, besides
worseningthe environmental impact relateddue to higheremission
factors (odors, pollutant, etc.) (MRI, 1995; Muth et al., 1998).
Another criticality is due to the fact that the extraction solvent is
typically technical hexane (extraction grade hexane) (Dunford and
Zhang, 2003; MRI, 1995) a highly flammable liquid and vapor (GHS
hazard statement, Shell, 2012). In some critical nodes of the process,
the solvent accumulates in the vapor phase and mixing with air may
occur, potentiallyleadingto theformationof flammable mixturesand
confined explosion of the equipment in case of accidental ignition
(NFPA, 2007; Lees, 1996; Tugnoli et 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; Santori
et al., 2012), a low but significant amount of atmospheric air is en-
trained by seals or gaskets mixing with the process vents. This may
lead to the formation of flammable mixtures also in process lines.
Even if the vegetable oil refining process is well known, the
industrial facilities are continuously subjected to modifications,
revamping and new technologies implementation in order to
achievea higher process efficiency (Shahidi, 2005). In the literature,
several examples of simulation and experimental analysis of each
0260-8774/$ - see front matter 2013 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.jfoodeng.2013.01.034
⇑ 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
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single stage of the refining 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 been
extensively applied in the framework of process/chemical industry
(Motard et al., 1975; Shaw, 1992; Biegler et al., 1997; Vadapalli and
Seader, 2001; Hoyer et al., 2005; Towler and Sinnott, 2013) and
aimed at taking into account the mentioned critical aspects, is still
lacking.
The present analysis was therefore addressed at investigating
the vegetable oil refining process by the development of detailed
simulation model using the commercial software ‘‘Honeywell Uni-
Sim Design’’ (Honeywell, 2010a,b). The analysis was aimed at
identifying the main process streams, the reference substances,
and quantifying the mass and energy fluxes among the refining
plant. The process simulator was applied to case studies represen-
tative of the current industrial applications, deriving the input data
from inlet conditions of an actual vegetable oil refinery. In
particular, the vegetable oil refinery of SALOV S.p.A., located in
San Rocchino (Massarosa) (Italy), was considered in the analysis.
The simulation model was validated against actual field data of
the same plant and a sensitivity analysis was performed in order to
evaluate 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 the
whole process efficiency.
2. Materials and methods
2.1. Methodological approach
The flowchart of the methodology is reported in Fig. 1, and is
based on the approach followed in a previous work by Landucci
et al. (2011) for the analysis of crude vegetable oil storage systems.
The first 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 during
plant grow and farming soil characteristics. A reference composi-
tion representative of different types of oil was used to perform
the further steps of the methodology. The second step (see Fig. 1)
consisted in the schematization of the typical process operations
for oil refining, with definition of operative conditions for process
equipment and evaluation of energy requirements (steam con-
sumption and other utilities). Then, a thermodynamic model was
applied in order to reproduce the vapor/liquid equilibrium of the
crude vegetable oil system (step 3 in Fig. 1), implementing the
presence of water and residual solvent content. The model was val-
idated against available experimental data.
Next (step 4 in Fig. 1), the refining process was simulated with
Honeywell UniSim Design. Specific subroutines were imple-
mented for the simulation of non-standard utilities such as the
ejectors used for keeping vacuum conditions in process vessels
and 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 in
Fig. 1). A sensitivity analysis was performed (step 6 in Fig. 1) aimed
at identifying the system response to the increasing residual sol-
vent content in the feedstock and possible restoration control mea-
sures. Finally, the possibility of formation of flammable mixtures
inside 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. Recent
studies were focused on the detailed experimental or numerical
characterization 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 modeling
tools were implemented for the analysis of the refining process
taking into account different relevant triacylglycerols (TAGs), par-
tial acylglycerols (monoacylglycerols MAGs, diacylglycerols DAGs),
and the possible residual acid components, such as free fatty acids
of 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 present
study was to evaluate the effect of residual hexane content on
the safety and energy performance of process equipment, a simpli-
fied reference composition was considered. The same approach
was followed in several studies on edible oil processing available
in the literature (Zhang et al., 2003; Ruiz-Mendez and Dobarganes,
2007; Cerutti et al., 2012).
The reference composition implemented in the simulation mod-
el is reported in Table 1. Such composition is based on the typical
crude sunflower oil feedstock used in SALOV S.p.A. vegetable oil
refinery, as already considered by Landucci et al. (2011). The oil
phase of the edible oil was schematized as pure triolein (reference
TAG), 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 list
of components as ‘‘hypo component’’ (Honeywell, 2010a). The hex-
ane residual content (schematized as pure n-hexane) was taken as
Characterization of the
crude vegetable oil
composition1
Thermodynamic modelfor the estimation of
vapor/liquid equilibrium3
Validation with
experimental data
Schematization of the oil
refining process2
Collection of typical
operations and
process conditions
from actual plants
Software implementation
of the refining process4
UniSim tool
Analysis of a case study
and optimization of
process conditions5
Sensitivity analysis6
Assessment of
utilities requirement
Set up of optimal
equipment operative
conditions
Increase of residual
solvent concentration
7 Safety aspects
Fig. 1. Flowchart of the methodology.
Table 1
Reference composition of the crude vegetable oil
considered in the present study based on SALOV
refinery data.
Components Mass fraction (%)
Triolein 97.29
Oleic acid 2.00
n-Hexane 0.10
n-C29H60 0.15
Sterols 0.40
Tocopherols 0.06
G. Landucci et al. / Journal of Food Engineering 116 (2013) 840–851 841
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elsewhere (Honeywell, 2010b), while Appendix A summarizes the
key parameters and equations used to predict enthalpy, entropy,
the fugacity coefficients for each component of the mixture and
thus the vapor/liquid equilibrium.
In order to test the validity of the model, a comparison with
available experimental data was carried out. A significant number
of literature studies focuses on vegetable oil/hexane mixtures at
high 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 diluted
solutions, which are significant 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 range
0.2–1.32% by weight. The hexane vapor pressure is measured in the
experiments as a function of the temperature. The model was fitted
on the experimental results by setting the triolein–hexane binary
interaction coefficient to 0.095 (Honeywell, 2010b). Notice that
for all other pairs of compounds, the default values of binary inter-
action coefficients were used. All binary interaction coefficients are
reported 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 in
the vapor phase as a function of temperature and hexane concen-
tration in the oil phase. As can be observed in this figure, the model
gives a quite accurate prediction with major deviations on the safe
side (e.g., 17% overprediction of n-hexane vapor pressure). The datawere linearly extrapolated for temperatures lower than 75 C asal-
ready performed in a recent publication (Landucci et al., 2011), in
which, however, the effect of water on the vapor phase composi-
tion was neglected and the model was set up only for the analysis
of storage conditions.
2.5. Simulation model implementation
The process simulation model, implemented in the UniSim
Design software, was aimed at evaluating the energy consumption
of the plant and the more critical nodes in which hexane is
accumulated, both in ordinary process conditions and following
unexpectedprocess deviations. Forthe sakeof brevityonly themain
issues related to vegetable oil refining simulator and innovative as-
pects connected with theanalysisof themore importantequipment
are summarized in the following sections. In order to highlight the
complexity of the developed process simulation model and the
potentialities of themethod, theSupplementaryinformation filere-
ports samples of the UniSim Design process flow diagrams (PFDs).
2.5.1. Condensers
The condensers are critical units under the point of view of
energetic efficiency of the process. These units are aimed at con-
densing the steam outlets from the ejectors connected to the main
process equipment to keep vacuum conditions (see specific
description in Section 2.5.3) by the use of cooling water available
in the refinery plant. Fig. 2 shows the condensers associated to
the ejector of the drying section (E5), bleaching (E6) and deodor-
ization (E7 for the first and second stage ejectors, E8 for the third
stage ejector). The sample UniSim Design PFD for the condenser
E5 is shown in Supplementary information.
The cooling water flowrate is the variable manipulated by the
software (ADJ 1 operator) which determines its value by imposing
a fixed temperature of 20 C for the condensate. This implementa-
tion allows for a better stability of the model in presence of input
deviations on the crude oil composition. The condenser parameters
were determined after a preliminary rating operation. The typical
range of cooling water flowrates, derived from actual plant design
data, 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 average
value for the pressure drops and heat transfer coefficient.
Then, condensers are implemented in the overall simulation
model by imposing thepressure drops on both tubes andshell sides,
and the product of the geometry area times the overall heat transfer
coefficient (‘‘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 already
used in condenser E7, associated to ejectors EJ3a and EJ3b (see
Fig. 2), its modeling using an a priori fixed value for the overall
transfer coefficient may be inaccurate. In fact, the cooling water
is manipulated to satisfy specifications on other upstream units
and may vary significantly. Therefore, the so-called ‘‘rating mode’’
(see Honeywell (2010a) for more details on this procedure) was
used, in which one specifies the exchanger geometry (number/
dimensions/arrangements of tubes, shell passes, etc.) and appro-
priate correlations are internally used to evaluate the heat transfer
coefficients and pressure drops on the basis of actual flowrates.
2.5.2. Deodorization column
The deodorization stage is aimed at removing minor compo-nents (e.g., squalene and polycyclic aromatic compounds) which
cause odor and the loss of quality of the final product. The deodor-
ization column (C1 in Fig. 2) is a stripping column made of five
chambers, each fed with low pressure steam (LPS, at 1.5 bar). The
total LPS mass flowrate is set as the 1.8% of the total refined oil
flowrate. The hot exhausted vapors from each chamber are col-
lected and fed to a water scrubber (C2 in Fig. 2), where the fatty
acids are removed and purged.
In order to reach the requiredstrong vacuum conditions (in par-
ticular, 0.2 kPa pressure and temperature higher than 220 C) the
ejector system depicted in Fig. 2 is required.
The column was modeled in the UniSim Design software by
implementing six separators in series, aimed at representing the
five 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 refining process.
Process section Operative temperature (C) Operative pressure (kPa)
Neutralization 20 100
Degumming 60–70 100
Washing 90 100
Drying 90 5
Bleaching 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).
G. Landucci et al. / Journal of Food Engineering 116 (2013) 840–851 843
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vapor/liquid equilibrium conditions. For the first four separators an
energy stream is added in addition to the LPS stripping stream in
order to simulate the presence of high pressure steam (saturated
steam at 40 bar) fed to internal heating coils inside the C1 column
chambers in order to keep high temperature conditions. The Uni-
sim Design PFD is reported in Supplementary information.
2.5.3. Ejectors
Several steam driven ejectors are used in the refinery to obtain
the needed vacuum conditions in the process equipment. As evi-
denced in Section 2.5.1 these pieces of equipment are critical for
the energy performance assessment of the refinery plant. However,
no dedicated model is available in the process simulator for ejec-
tors. Thus, a specific modeling tool was implemented in the soft-
ware in order to achieve an accurate performance evaluation
exploiting 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 flow related to air at 20 C respect to the motive steam flow, as
a 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 is
extensively described in the technical literature (Meherwan,
1999; Akterian, 2011).
Hence, by setting the pressures of the equipment in vacuum
conditions (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 the
entrainment ratio and calculating the necessary mass flows as
follows:
1
l¼ maMS
1
K ejð1Þ
where ma is the entrained flow of air at 20 C, MS is the flow of mo-
tive steam and K ej is a correction factor for suction flows other than
air, expressed as follows:
K ej ¼
ffiffiffiffiffiffiffiffiffiffiRS T S RLT L
s ð2Þ
where RS is the gas constant of suction flow, RL the gas constant of
air (=287 J kg1 K1), T S the temperature (in K) of suction flow, T Lthe reference air temperature for the ejector (=293 K).
Table 3
Fitting parameters for the approximation of the ejectors
design curves (see Eq. (3)).
Parameter (P s/P m) X 1 X 2
0.001 4.14 0.983
0.002 3.81 0.910
0.005 3.38 0.732
0.010 3.03 0.673
0.020 2.70 0.615
0.050 2.26 0.489
Table 4
Comparison between the process parameters evaluated by the model and the available field data. For tags locations, see Fig. 4.
TAG Description Units Model results Field data
FI1 Refined oil exit flow kg/h 14,558 14,075
PI1 Pressure in the deodorization column kPa 0.2 0.22
TI1 Temperature of the bleaching reactor C 104.8 110.1
TI2 Temperature of crude oil at the deodorization inlet C 231.7 230.7
TI3 Refined oil exit temperature C 160.9 154.8
TI4 Temperature of the deodorization column top side C 135.8 153.0
Drying
Bleaching
Deodorization
Crude oil from
neutralization
Refined oil
to storage
2
3
4
1
CW1
CW2
CW3
CW4
CW5
CW6
H1 H2 H3Bleaching
earth &
activated
carbon
5
C1 C2 V1
C3 V2
C5 V3E5 E6
H4 H5 H6 E2
H7 H8 H9 E3 E4
W1
E1
W2
LEGEND:
C
CW
E
H
V
W
Condensed steam
Cooling water
Energy stream
Low or medium pressure steam
Vent
Process waste
Material stream tag
C4
E7
Fig. 4. Schematic representation of the heat and material balance on the analyzed plant sections.
844 G. Landucci et al. / Journal of Food Engineering 116 (2013) 840–851
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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 curves
as follows:
maMS
¼ X 1P d=P s
X 2ð3Þ
where X 1 and X 2 are fitting 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 specified as input parameters;hence the software applies Eqs. (1)–(3) to evaluate the motive
steam flow which is necessary to keep an imposed discharge
pressure.
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 flow), the energetic consumptions are
evaluated by calculating the necessary motive steam flow needed
to 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 field data werederived from SALOV S.p.A. refinery during typical working
Table 5
Heat and material balance on the plant sections analyzed in the present study. For the identification of the streams, refer to Fig. 4. Composition is expressed in percentages by
weight basis.
Item Material streams
1 2 3 4 5b W1 W2
Temperature (C) 90.0a 84.3 105.2 20.0a 25.0a 105.0 48.4
Pressure (kPa) 195.0 200.0a 210.0a 186.0 200.0a 8.0 0.2
Flowrate (kg/h) 14,887.5 14,795.2 14,695.0 14,558.4 14.8 97.8 133.0a
Triolein (%) 98.14 98.74 98.75 99.62 0.0 100.0 5.2
Water (%) 0.55 0.01 0.01 0.0 100.0 0.0 0.0
n-Hexane (%) 0.10 0.02 0.01 0.0 0.0 0.0 67.3
Oleic acid (%) 0.60 0.61 0.61 0.0 0.0 0.0 0.0
Other (%) 0.61 0.62 0.62 0.38 0.0 0.0 27.5c
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 identification of the streams, refer to Fig. 4. C = steam condensate; CW = cooling water; E = energy stream; H = steam;
V = vent.
ID Physical
state
Description Thermal power
(kW)
Flowrate
(kg/h)
Temp.
(C)
Pressure
(kPa)
Drying sectionC1 Liquid Steam condensate associated to ejector EJ1a 150.1 19.0 16.5
C2 Liquid Steam condensate associated to ejector EJ1b 1153.0 127.5 250.0
CW1 Liquid Cooling water fed to the drying section condensers 9282.0 8.0 150.0
CW2 Liquid Cooling water exiting the drying section condensers 9282.0 18.0 149.9
H1 Vapor Motive steam fed to first stage ejector EJ1a 70.1 175.5 900.0
H2 Vapor Motive steam fed to second stage ejector EJ1b 53.4 175.5 900.0
H3 Vapor Drying steam pre-heating in E1a 1153.0 127.5 250.0
V1 Vapor Vent exiting from drying section 70.6 123.2 108.0
E1 – Heat removed in downstream degumming section with heat exchanger 142.0
Bleaching section
C3 Liquid Steam condensate associated to ejector EJ1a 301.0 127.5 250.0
C4 Liquid Steam condensate associated to ejector EJ1b 30.4 19.8 16.5
CW3 Liquid Cooling water fed to the bleaching section condensers 1180.8 8.0 150.0
CW4 Liquid Cooling water exiting the bleaching section condensers 1180.8 20.0 150.0
H4 Vapor Motive steam fed to first stage ejector EJ2a 15.6 175.5 900.0
H5 Vapor Motive steam fed to second stage ejector EJ2b 27.6 175.5 900.0
H6 Vapor Bleaching steam pre-heating in E1b 301.0 127.5 250.0V2 Vapor Vent exiting from bleaching section 35.4 134.0 108.0
E2 – Bleaching pre-heating 11.0
Deodorization section
C5 Liquid Steam condensate associated to ejector EJ3 1537.0 19.8 102.5
CW5 Liquid Cooling water fed to the deodorization section condensers 240,000.0 8.0 150.0
CW6 Liquid Cooling water exiting the deodorization section condensers 240,000.0 12.0 140.9
H7 Vapor Motive steam fed to first stage ejector EJ3a 1100.1 175.5 900.0
H8 Vapor Motive steam fed to second stage ejector EJ3b 157.1 175.5 900.0
H9 Vapor Motive steam fed to third stage ejector EJ3c 26.0 175.5 900.0
V3 Vapor Total ventflowrateexiting from deodorization section condensers (E7 and
E8)
33.8 132.4 108.0
E3 – C1 chambers external coil heating 89.0
E4 – Steam (40 bar) for oil preheating 448.0
E5 – Cooling of scrubber C2 recycle 53.0
E6 – Air cooler 1055.0
E7 – Cooling unit 163.0
G. Landucci et al. / Journal of Food Engineering 116 (2013) 840–851 845
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deodorization. Both steam and cooling water utilities have the
highest 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 Table 6) carried out with high pressure steam.
Besides, additional heat exchangers are needed for cooling the
scrubber C2 (see Fig. 2) recycle and the vents before the treatment
and the discharge in the atmosphere.
3.2. Process optimization and sensitivity analysis
The analysis of the refinery in the baseline case (0.1% hexane by
weight basis in the inlet crude oil) highlighted the criticalities re-
lated to the energy consumptions in the refinery lowpressure units
(e.g., drying, bleaching and deodorization). Since the ejector sys-
tems operative conditions affect the whole refinery energetic per-formance, the process simulator was applied in order to optimize
the operating conditions for the minimization of motive steam
consumption. The optimization was carried out on the three ejec-
tor systems considering that the motive steam is available in the
plant at the same pressure (medium pressure steam, MPS at 9 bar).
Fig. 5a reports an example of optimization, in particular related
to the ejector system connected to the drying flash drum (EJ1a/b
with condenser E5, see Fig. 2). As can be seen in the scheme, the
ejector is constituted by two different sections in which P s
is the
suction pressure, representative of the equipment operative
conditions, P out the system discharge pressure, MSA and MSB the
motive steam streams respectively for the first 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 MSA and MSB and finally obtaining the P intwhich minimizes the overall steam consumption (e.g., the sum of
MSA and MSB), as shown in Fig. 5a. Determining the intermediate
ejectors pressure allows for the process energetic efficiency
enhancement.
The described optimization method can be performed also by
considering a possible increase of the inlet residual hexane con-
tent, as reported in Fig. 5b. In particular the figure shows the opti-
mized intermediate pressure for all the considered ejector systems
(see Fig. 2 for tags and equipment representation). These outcomes
might be potentially applied when a different feedstock quality is
accepted and processed by the refinery for a mid- or long-term
period, with the need of a systematic improvement of the operat-
ing conditions. As shown in Fig. 5b, the increase of the residual
hexane content has a stronger influence on the drying and bleach-
ing sections respect to the deodorization, since in these sections
the major part of hexane is removed (see Section 3.1). This results
in the increase of the intermediate pressure for optimizing the mo-
tive steam consumption.
The results of the sensitivity analysis carried out by varying the
inlet hexane concentration and optimizing the operating condi-
tions and process variables are reported in Table B1 of Appendix
B. 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. 6a shows
the increase of the overall motive steam and cooling water con-
sumption by varying the inlet hexane concentration of one order
of magnitude (e.g., ranging from 0.1% to 1.5% by weight basis). Mo-
tive steam consumption is increased by 40%, showing a more sig-
nificant variation respect to cooling water utility, which increase
is limited to 1%. This is due to the fact that the highest flowrate
of cooling water is a fixed simulation parameter, since it is fed to
the condenser of the third ejector (EJ3c, see detailed description
of simulation set up in Section 2.5.1). This flowrate is almost
twenty 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. 6b pre-
sents the change in the hexane removal percentage (thus,
starting from the values evaluated at 0.1% residual hexane content,
see Section 3.1) in each process section. The results highlight that
the excess hexane is mainly removed in the drying section, due to
the oversizing of the equipment. Hence, this allows decreasing the
hexane amount fed to the downstream units, which hexane re-
moval decreases as shown in Fig. 6b.
Therefore, the sensitivity analysis allowed determining the
change 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 refining process.
Fig. 7. Comparison between the flammability range of hexane considering two
inert reference gases (carbon dioxide and nitrogen) and vapor concentration in the
venting line for (a) drying, (b) bleaching and (c) deodorization considering a
residual hexane content of 0.1% by weight basis in the inlet crude oil. For air
infiltration types characterization, see Table 7.
G. Landucci et al. / Journal of Food Engineering 116 (2013) 840–851 847
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3.3. Formation of flammable mixtures inside process streams
The process simulator pointed out the more critical nodes for
hexane 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 process
pipes, 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 flammable mixtures
in confined spaces. This might lead to fire and explosion hazards
in case of accidental ignition of the flammable mixture, already
highlighted for the storage equipment in a previous work (Land-
ucci et al., 2011).
Therefore, the process simulator was employed to investigate
this problem, considering an additional air flow in the three vent
lines (V1, V2 and V3, see Fig. 4) given a reference air entrainment
value, specified by the ejector manufacturer (Körting Hannover
AG,1994) for the vent discharge line. Table 7 reports the considered
entrainment value (infiltration type 2), also considering a possible
negative or positive variations respect to this reference value
(respectively, infiltration types 1 and 3 in Table 7).
Fig. 7 reports the evaluated residual hexane concentration in
the vent lines evidencing the possibility of formation of flammable
mixtures in the drying (Fig. 7a), bleaching (Fig. 7b) and deodoriza-
tion (Fig. 7c) sections as a function of the different air entrainment
rates given a fixed hexane residual content in crude oil feed (e.g.,
0.1% by weight basis). A flammable mixture is potentially formed
if the calculated concentration point enters inside the flammable
range, i.e. the region of the chart included inside the reference con-
tinuous lines. In absence of data for water as inerting fluid, the ef-
fect of nitrogen (bright lines in Fig. 7) and carbon dioxide (dark
lines in Fig. 7) as diluents was taken into account in order to obtain
preliminary indications for the methodology (Mashuga and Crowl,
1998; Zabetakis, 1965). Furthermore, the flammability range is af-
fected by operative pressure and temperature, but the use of data
referred to 25 C temperature and 1.01 bar allows for evaluation of
the flammability hazards on the safe side in the considered process
sections (Lees, 1996).
The results make clear that in the case of higher hexane concen-
tration in the vent line, the entrained air is not sufficient to form
flammable 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. 7a, and in which none
of the calculated points fall under the flammable region even for
high air entrainment rates. On the contrary, for the other two sec-
tions, the hexane vent content is lower and some points calculated
for high air entrainment rates especially in the deodorization sec-
tion vent (see Fig. 7c), fall into the hazardous zone. This evidences a
safety criticality for strong vacuum operating equipment in pres-
ence of flammable vapors.
Hence, this type of hazard might be taken into account during
the 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 þbÞþbðV bÞ Peng–Robinson state equation P = Pressure (Pa)
R = 8314(J kmol1 K1) universal gas
constant
T = Temperature (K)
V = Volume (m3)
a = see Eq. (6)b = see Eq. (5)
Eq. (2) Z 3 - ( 1 - B) Z 2 + ( A - 2B - 3B2) 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 0:077796RT c ;iP c ;i
1st Peng–Robinson equation
coefficient for mixtures
xi = mass fraction of the ith
component of the mixture of N
components.
T c ,i = critical temperature of the ith
component
P c ,i = critical pressure of the ith
component
Eq. (6) a ¼ PN
i¼1
PN j¼1 xi x jðaia j Þ
0:5ð1 kijÞ; ai ¼ ac ;iai
ac ;i ¼ 0:457235ðRT c ;i Þ
2
P c ;i; a0:5i ¼ 1 þ mið1 T
0:5r ;i Þ
2nd Peng–Robinson equation
coefficient for mixtures – original
formulation
T r ,i = T /T c ,ikij = system specific experimental
binary interaction factor
mi = see Eq. (7)
Eq. (7) mi ¼ 0:37464 þ 1:5422xi 0:26992x2i ; xi 6 0:49
mi ¼ 0:379642 þ ð1:48503 ð0:164423 0:016666xiÞxiÞxi ; xi > 0:49
Polynomial factor for Eq. (6) –
original formulation
xi = Acentric factor of the ithcomponent
Eq. (8) ai ¼ T N i=ðM i 1Þr ;i expðLið1 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 ith
substance (see details in Honeywell
(2010b))
Eq. (9) H H IDRT ¼ Z 1
121:5bRT
a T dadT
ln
V þð20:5þ1Þb
V þð20:51Þb
Enthalpy equation H = predicted enthalpy
H ID = reference enthalpy evaluated
at 25 C and 1.01 bar
Eq. (10) S S IDR ¼ lnð Z bÞ lnðP =P
Þ A21:5bRT
T a
dadT
ln
V þð20:5þ1Þb
V þð20:51Þb
Entropy equation S = predicted entropy
S ID = reference entropy evaluated at
25 C and 1.01 bar
P pressure in the reference state
(1.01 bar)
Eq. (11) ln/i ¼ ln Z PbRT
þ ð Z 1Þ bib
a21:5bRT
1a 2a
0:5i
PN j¼1 x ja
0:5 j ð1 kijÞ
bib
ln V þð20:5 þ1Þb
V þð20:5 1Þb
Evaluation of fugacity coefficient / = mixture fugacity coefficient of
for the ith component
848 G. Landucci et al. / Journal of Food Engineering 116 (2013) 840–851
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4. Conclusions
In the present work a quantitative methodology was developed
for the performance analysis of the vegetable oil refining process.
An advanced thermodynamic model was implemented in order
to 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 refining processsimulator, developed on the Honeywell UniSim Design software.
The simulator allowed for a detailed performance analysis of
the process. The results were compared with field data obtained
from an actual vegetable oil refinery showing good agreement in
reproducing the refining process in the reference conditions.
The effect of the residual solvent content increase on the pro-
cess efficiency was investigated, determining the most significant
nodes of solvent accumulation among the plant process operations
and evaluating its influence on the global energy requirements. In
particular, the ejector systems, aimed at keeping vacuum operating
conditions, were deeply investigated, evaluating the utility con-
sumption increment. Both motive steam and cooling water for con-
densers were analyzed by varying the residual hexane content in
the input crude oil and determining the modification in the opera-
tive conditions for minimizing the energy costs. The study evi-
denced the criticalities related to the management of inlet crude
oil quality, in terms of residual solvent content control, for the
enhancement of the global process efficiency.
Finally, the simulator also allowed investigating the potential
hazards due to formation of flammable mixtures inside the process
vent lines, in presence of purged hexane vapors and air entrained
by gaskets and/or seals of vacuum operating pipelines. The results
evidenced the conditions in which flammable mixtures might
potentially be formed inside the process vents, with fire and explo-
sion hazards in presence of accidental ignition.
Acknowledgement
The authors gratefully acknowledge financial support received
from Regione Toscana (Bando Unico R&S n.2009DUA/526090469/
1).
Appendix A
The present section provides details on the thermodynamic
model implemented in Unisim Design (Honeywell, 2010a,b).
The selected model is based on the Peng–Robinsonequations (Peng
and Robinson, 1976) corrected with the Twu Alpha function (Twu
et al., 1995; Honeywell, 2010b), which takes into account the ex-
cess free energy in order to have more accurate prediction of vapor
pressure. Table A1 summarizes the key parameters and equations
used to predict enthalpy, entropy, the fugacity coefficients for each
component of the mixture and thus the vapor/liquid equilibrium.
Tables A2 and A3 report the specific parameters selected for each
substance considered in the present study.
Appendix B
Table B1 reports the results of the process optimization and
sensitivity analysis, comparing the baseline case results (BC) and
the optimized cases (OCs) by varying the residual hexane content
(HEX in the following, expressed in % by weight basis) up to one
order of magnitude respect to the BC, which features HEX = 0.1%.
The first column of the table reports the process variable of
interest (EJ: ejector, MS: motive steam, CW: cooling water, see
Figs. 4 and 5). The second column report the results obtained for
the baseline case with HEX = 0.1%, while the third column shows
the correspondent optimization of process variables aimed at
Table A3
Determination of system specific 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 0
Oleic acid 0 – 0 0 0 0 0
n-Hexane 0.095 0 – 0.031 0 0 0.48
n-C29H60 0 0 0.031 – 0 0 0.48
Sterols 0 0 0 0 – 0 0
Tocopherols 0 0 0 0 0 – 0
Water 0 0 0.48 0.48 0 0 –
Table A2
Main parameters selected for the present analysis (Honeywell, 2010b). For parameters definition 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-C29H60 Sterols Tocopherols Water
T c ,i 5 C 680.9 496.9 234.7 564.9 668.1 646.7 374.1
P c ,i 5 kPa 360.2 1390 3032 826 999.7 945.9 22,120
Li 8 – –a 0.7760 0.1363 0.3688 –a –a 0.3831
M i 8 – –a 0.8235 0.8620 0.8247 –a –a 0.8701
N i 8 – –a 0.8235 0.8620 0.8247 –a –a 0.8701
L0 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 –
xi see note (a) – 1.6862 – – – 0.9863 0.9624 –
a
The 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, fornon-library compounds, the Twu alpha function can be estimated by the following expressions: ai ¼ a
ð0Þi ðT Þ þ xiða
ð1Þi ðT Þ a
ð0Þi ðT ÞÞ where a
ð0Þi ¼T
N 0=ðM 01Þr ;i
expðL0ð1 T N 0M 0r ;i ÞÞ; að1Þi ¼ T
N 1=ðM 11Þr ;i expðL1ð1 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 xi).
G. Landucci et al. / Journal of Food Engineering 116 (2013) 840–851 849
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keeping the same operative condition in process equipment. The
other 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 reports
the correspondent optimized process variables and operative con-
ditions. The same type of results are shown in the fifth and sixth
column for HEX = 1.0%.
Appendix C. Supplementary material
Supplementary data associated with this article can be found, in
the online version, at http://dx.doi.org/10.1016/j.jfoodeng.2013.
01.034.
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EJ2a/b operative pressure (kPa) 16.5 20.0 16.5 22.5 16.5 24.0
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