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chemical engineering research and design 9 4 ( 2 0 1 5 ) 549564
Contents lists available at ScienceDirect
Chemical Engineering Research and Design
j ourna l h omepage: www.elsev ier .com/ locate /cherd
CFD s g pnon-i
Amir HeComputation nginScience and
a
In as i
pr DA)
co erph
CFD model to predict the reactor performance at non-isothermal conditions. The effects of feed inlet temperature,
gas and liquid velocities, operational pressure and hydrogen sulde concentration of the gas phase were investigated
to calculate the reactions conversions and the bed temperature distribution. Also, the inuence of bed porosity and
adiabatic operational conditions on the reactor temperature and HDS reaction conversion was discussed. The results
showed at adiabatic reactor, HDS reaction conversion increased about 9% compared to constant wall temperature
co
in
ab
Ke
G
1. Int
Hydrodesuare the wesil fuels improcesses ators knownmajority ofin the co-cbed (Meder2013). Durigas to liquireduce oil imlow pressuparts and TOn the oth
CorresponE-mail aReceivedAvailable
http://dx.do0263-8762/ndition. Furthermore, it was found that neglecting the gasliquid interphase heat transfer effect in the CFD model
creases the average relative error between numerical and the experimental data at prediction of HDS conversion
out 5% and also affects the bed temperature pattern.
2014 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
ywords: Computational uid dynamics (CFD); Hydrotreating; Non-isothermal condition; Trickle bed reactor;
asliquid heat transfer
roduction
lfurization (HDS) and hydrodearomatization (HDA)ll-known hydrotreatment (HDT) processes of fos-purities reduction in the oil industries. The HDTre generally performed in the packed bed reac-
as trickle bed reactor (TBR) (Ranade et al., 2011). In the TBRs, gas and liquid phases move continuouslyurrent downow mode through the high pressureos et al., 2009b; Ranade et al., 2011; Wang et al.,ng the HDT process, hydrogen transfers from thed phase and reacts with the target components to
purities. TBRs are generally characterized to havere drop and low catalyst loss. There are no movingBRs have comparatively lower maintenance costs.er hand, issues such as catalyst deactivation and
ding author. Tel.: +98 21 77240376; fax: +98 21 77240495.ddress: [email protected] (S.H. Hashemabadi).
8 April 2014; Received in revised form 16 August 2014; Accepted 22 September 2014 online 30 September 2014
cementations are also TBRs main characteristics (Mederosand Ancheyta, 2007; Sattereld, 1975).
In the past, many attempts were made to nd out about dif-ferent aspects of TBR performance using numerical methods.Reviewing published studies shows that most of the researchworks were focused on development of appropriate models topredict bed hydrodynamic properties by means of CFD tech-nique. Investigating the effect of pressure drop (Atta et al.,2010; Attou and Ferschneider, 2000; Aydin and Larachi, 2005,2008; Bazmi et al., 2011, 2012; Boyer et al., 2007; Brkljac et al.,2007; Iliuta et al., 2002; Iliuta and Larachi, 2002, 2005; Iliutaet al., 2000a,b; Lopes and Quinta-Ferreira, 2008, 2009b; Proppet al., 2000; Salimi et al., 2013; van der Merwe et al., 2007),mal-distribution and liquid holdup (Bazmi et al., 2012; Gunjalet al., 2003; Lappalainen et al., 2009; Lopes and Quinta-Ferreira,2009a; Martnez et al., 2012; Mederos et al., 2009a; Strasser,
i.org/10.1016/j.cherd.2014.09.016 2014 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.tudy of diesel oil hydrotreatinsothermal trickle bed reactor
idari, Seyed Hassan Hashemabadi
al Fluid Dynamics (CFD) Research Laboratory, School of Chemical ETechnology (IUST), Narmak, Tehran 16846-13114, Iran
b s t r a c t
the present study, the EulerianEulerian multiphase approach w
ocesses (hydrodesulfurization (HDS) and hydrodearomatization (H
mputational uid dynamics (CFD) technique. A new gasliquid introcess in the
eering, Iran University of
mplemented to simulate the hydrotreating
) in the trickle bed reactor (TBR) by means of
ase heat transfer coefcient was used in the
550 chemical engineering research and design 9 4 ( 2 0 1 5 ) 549564
Nomenclature
a, b and C constants (dimensionless)aGL specic gasliquid interface (m1)as specic surface of a particle (m1)CL,i concentration of ith species at liquid phase
(mol/m3)Cp heat capacity (J/kg K)D diffusion coefcient (m2/s)dp, dh, dr particle, hydraulic and reactor diameter (m)E1, E2 Ergun constantsEo Etvs number Eo = Lg(dh)2/ in Eq. (14)
(dimensionless)Eo modied Etvs number (dimensionless)F interphase momentum exchange coefcient
(kg/m3 s)fe wetting efciency (dimensionless)Fr Froude number (dimensionless)g gravity (m/s2)H Henrys coefcient (MPa cm3/mol)h specic enthalpy (W/m3)hG,L gasliquid interphase heat transfer (W/m2 K)Ga modied Galileo number (dimensionless)K mass transfer coefcient (m/s)KPoly/Di/Mono dynamic equilibrium constant (dimension-
less)Kw Watson characterization factor (dimensionless)k thermal conductivity (W/m K)ks HDS reaction constant (((m3)2.16)/kg(kmol)1.16 s)k,k forward and backward reaction rate constants
(m3/kg s)kad HDS reaction adsorption coefcient (m3/kmol)LHSV liquid hourly supercial velocity (h1)m interphase mass transfer rate (kg/m3 s)Nu Nusselt number (dimensionless)Pr Prandtl number (dimensionless)Re Reynolds number, Re = Udh/ in Eq. (14)
(dimensionless)Re modied Reynolds number (dimensionless)P pressure (Pa)q heat ux (W/m2)R universal gas constant (J/mol K)Ri reaction rate of ith species (kg/m3 s)r radius (m)S source term (kg/m3 s)SG specic gravity (dimensionless)T temperature (K)TCABP cubic average boiling point (K)TMABP molal average boiling point (K)TMeABP mean average boiling point (K)t time (s)u velocity (m/s)v molar volume (m3/mol)x mass fraction (dimensionless)xmi molar fraction (dimensionless)
Greek symbols, and constants (dimensionless), and constants (dimensionless)HR heat of reaction (J/mol) volume fraction (dimensionless) average bed porosity (dimensionless)
Subscriptb G i int k L P r S T
2010; ZeiseDudukovicKundu et aFerreira, 20Ring and Mthe main reactors. ToperationaHashemabFerreira, 202010), scaleand Krishn(Alvarez anet al., 2012aMurali et alems (Kalli2011; Skalamany reseapublished oheat transfreported. Tcan be sumfer (Flvio Pet al., 2003;ticles to uet al., 2006heat transftive axial (FconductivitLamine et a
In this cwas simulagasliquid iby Heidari phase momimplementreported Hnd the beiors of reacExtensive seffects of gtemperaturdynamic viscosity (N s/m2)solubility coefcient (N l/kg MPa)ratio of catalyst volume to summation of inertand catalyst volume (dimensionless)density (kg/m3)surface tension (N/m)
sboiling point or bulk porositygasith speciesinteractionkth phaseliquid phasepressurerth phasesolid phasetemperature
r et al., 2001) and wetting efciency (Al-Dahhan and, 1995; Baussaron et al., 2007a,b; Cheng et al., 2012;l., 2003; Lappalainen et al., 2008; Lopes and Quinta-10c; Mills and Dudukovic, 1981; Pironti et al., 1999;issen, 1991; van Houwelingen et al., 2006) were
subjects on the numerical study of trickle bedhe investigations of TBR performance at differentl conditions (Gunjal and Ranade, 2007; Heidari andadi, 2014; Jarullah et al., 2011; Lopes and Quinta-07, 2010a,b,c; Lopes et al., 2007; Mapiour et al.,
up challenges of TBRs (Hickman et al., 2013; Siea, 1998), reactor performance in the industrial scaled Ancheyta, 2008; Alvarez et al., 2007; Jarullah,b; Mederos and Ancheyta, 2007; Munoz et al., 2005;l., 2007) and study of catalysts deactivation prob-nikos et al., 2008; Kam et al., 2005; Pacheco et al.,
et al., 1991) were also other interesting subjects forrchers. Despite the fact that many researches weren hydrodynamics and yield of TBRs, studies abouter in the trickle ow regime have not been widely
he available researches about heat transfer at TBRsmarized in four categories; wall to bed heat trans-into Moreira et al., 2006; Habtu et al., 2011; Larachi
Mariani et al., 2003; Mousazadeh et al., 2012), par-ids heat transfer (Borremans et al., 2004; Guardo, 2007; Larachi et al., 2003), gasliquid interphaseer (Heidari and Hashemabadi, 2013) and the effec-lvio Pinto Moreira et al., 2006) and radial thermaly (Babu et al., 2007; Flvio Pinto Moreira et al., 2006;l., 1996; Larachi et al., 2003).ontribution, the non-isothermal trickle bed reactorted by CFD method and implementation of a newnterphase heat transfer model that was developedand Hashemabadi (2013). The appropriate inter-entum, mass and heat interaction models were
ed in EulerianEulerian multiphase approach. TheDS and HDA reactions kinetics were optimized tost values that present intrinsic chemical behav-tions mechanisms based on the reactor real model.imulation works were conducted to examine theas and liquid velocities, operational pressure, feede and gas phase hydrogen sulde concentration on
chemical engineering research and design 9 4 ( 2 0 1 5 ) 549564 551
the reactor performance. The CFD results were compared withreported eximportanceaccuracy ofand bed tem
2. Go
2.1. Mo
To develop lowing assu
1. Catalyst2. Vaporiza
to their 3. Two-lm
fer betw4. Mass tra
uid interesistan
5. The solporosity
6. Accordinet al. (20ow regthe simuforce wa
2.2. Hy
In the prapproach wuid (discretfollows:
(kk)t
+
(kkuk)t
+k
i=r(u
The lastbetween phciency, fe, is
Fint,G = fe
Fint,L = fe(
In orderAttou and model. In tin the derivtion to accoin the three
forms:
GG +
+E2
GG +
+E2
1
G +
le 1 pties,
Spe
Eulen be
xk,i +
k
i=r(m
corrffusile 1. n infthe e mdisp(2011sion on, p
havrs. Thn (digatios govchey
the ity d) are
oveanc
ith la fullyriatel deses sizCFD
abition rese
et aperimental data (Chowdhury et al., 2002). Also, the of gasliquid interphase heat transfer effect on the
CFD model at prediction of reactions conversionsperature distribution were studied.
verning equations
deling assumption
the momentum, mass and heat equations the fol-mptions were regarded as:
s deactivation was ignored in the bed.tions of diesel oil components were neglected duehigh molecular weights.
theory was used to dene interphase mass trans-een gas and liquid phases.nsfer resistance is controlled by the gas and liq-rface and consequently it was assumed that noce exists between other phases.id phase was taken as third phase with known
distribution and zero velocity in the domain.g to Lopes and Quinta-Ferreira (2007) and Atta07a,b), due to low gasliquid interaction at trickleime, capillary pressure force can be neglected inlation of TBRs. Accordingly, in this work, capillarys ignored in the CFD model.
drodynamics equations
esent study, an EulerianEulerian multiphaseas used to present gas (continuous phase) and liq-e phase) continuity and momentum equations as
(kkuk) =k
i=r(mrk mkr) + Sq (1)
+ (kkuk2) = kPk + (kuk) + kkg
rkmrk ukrmkr) + Fint,k(uk ur) (2)
term in Eq. (2), Fint,k, shows momentum exchangeases and with considering effect of wetting ef-
evaluated by (Lappalainen et al., 2009):
FGL (1 fe)FGS (3)
FLG FLS) (4)
to develop interphase momentum exchanges, Fkr,Ferschneider (1999) model was applied in the CFDhis model, effective diameter of particles was usedation of interphase interaction terms as a correc-unt for the presence of the liquid lm. Their model
phase system can be expressed by the following
FGL =
FGS =
FLS =
Tabproper
2.3.
In the tion ca
kkt
+
Theular diin Tabtillatio
In describradial et al. dispertributifactorsreactopersioinvestispecieand Anfore, in(porosnelingcausesperformbeds wnot beappropmaticaparticlin the
Theevaluaferent GunjalL
(E1G(1 G)2
G2dp2
[S
(1 G)]0.667
G(uG uL)(1 G)Gdp
[S
(1 G)]0.333)
(5)
L
(E1G(1 G)2
G2dp2
[S
(1 G)]0.667
GuG(1 G)Gdp
[S
(1 G)]0.333)
(6)
L
(E1G(S)
2
L2dp2
+ E2LuL(S)Ldp
)(7)
resents supplementary correlations to estimate oil wetting efciency and porosity distribution.
cies conservation equations
rianEulerian multiphase approach, species equa- written as follows:
(kkxk,iUk) = (kkDi,kxk,i)
rk,i mkr,i) + fekRk,i (8)
elations required for calculation of species molec-on, Di, and interphase mass transfer are presentedAlso, diesel oil component concentration and dis-ormation are tabulated in Table 2.current work, molecular diffusion was used toass diffusion instead of packed beds axial andersion coefcients, Eq. (8). According to Ranade) main factors contributing to mass and liquidin the packed beds are non-uniform porosity dis-artial wetting, dead-zones and channeling. Thesee the vital effects on dispersion in the trickle bede main idea to develop axial and radial mass dis-
ffusive term) models in the packed beds is then of hydrodynamics and porous media effects onerning equations (Jarullah et al., 2012b; Mederosta, 2007; Mederos et al., 2006, 2009a, 2012). There-
models in which hydrodynamic and bed propertiesistribution, partial wetting, dead-zones and chan-regarded, using axial or radial dispersion coefcientr prediction of species diffusion terms and reactore. Here, it should be noticed that in the packedrge particles diameter, mechanical dispersion can-
explained by porosity distribution functions and models need to be used to improve the mathe-cription of the reactor. In this work, due to smalle, the effect of mechanical dispersion was ignoredmodel.lity of EulerianEulerian multiphase approach onof axial and radial dispersion was studied by dif-archers (Atta et al., 2007a; Bazmi et al., 2012;l., 2003). They found a good agreement between
552
chem
ical
engin
eering
research
and
desig
n
9 4
(
2 0
1 5
)
549564
Table 1 Correlations to estimate diesel oil properties, bed characteristics and interphase mass transfer correlations.
Parameter Correlation
Liquid density (Ahmed, 2007)L = 0 + P + TP = ([0.167 + 16.181 100.04250 ][P 1.450 107] 0.01 [0.2999 + 263 100.06030 ] [P 1.450 107]2) 16.018T = ([0.0133 + 152.4(0 + P)2.54](T 1.8 520) [8.1 106 0.0622 100.764(0+P )](T 1.8 520)2) 16.018
Liquid viscosity (Ahmed, 2007)
L = 3.141 107(T 1.8 460)3.444[log10(API)]aa = 10.313[log10(T 1.8 460)] 36.447API = 141.5
SG15.6 131.5
Surface tension (Tsonopoulos et al., 1986) = (0.0017237 T0.05873b
SG0.64927(L G))4/1000Wetting efciency (Lappalainen et al.,
2008)fe = 0.335Re0.185L Eo0.188Ga0.025G (1 + FrG)0.014
Diffusion coefcient (Ahmed, 2007; Perryand Green, 2008; Reid et al., 1987; Riazi,2005)
DL,i = 8.93 108v0.267Lv0.433i
T
L
vi = 0.285v1.048ci or L , vcL = 0.5567T0.2896MeABPSG
0.766615.6
TMeABP = TMABP + TCABP2 , TMABP =n
i=1
xmiTbi
TCABP =(
11.8
)[ ni=1
i(1.8Tbi 459.67)1/3]3
Interphase mass transfer (Goto andSmith, 1975; Korsten and Hoffmann,1996)
mGL,i = KL,iaGL(
PG,iHi
CL,i)
, mLG,i = mGL,i i : H2 or H2SKL,iaLDL,i
= 1.8(
LuLL
)2(L
LDL,i
)0.5 i : H2 or H2S
Hi =vi
iL i : H2 or H2S
H2 =(
0.5597 0.4294 103(T 273.15) + 3.0753 109 (T 273.15)20 C
+ 1.944 106(T 273.15)2 + 0.835 103(
120 C
)2) 106
H2S = exp(3.3670 0.00847(T 273.15)) 103
Liquid thermal conductivity (Riazi andFaghri, 1985)
k = 1.7307(1.8 TMeABP)SG15.5 C = exp(21.78 8.07986t + 1.12981t2 0.05309t3) = 4.13948 + 1.29924t 0.17813t2 + 0.00833t3 = 0.19876 0.0312t 0.00567t2t = (1.8T 460)/100
Liquid heat capacity (Kesler and Lee, 1976)
Cp = ( + T) = 1.4651 + 0.2302 Kw = 0.306469 0.16734 SG15.5 C = 0.001467 0.000551 SG15.5 CKw = ((1.8 TMeABP)1/3)/SG15.5 C
Bed porosityfunction (Bazmiet al., 2011)(constants wereselected for sockbed)
= (b + D) + (1 (b + D))
[(exp
(C r
dp
))2 + 3i=1
(ai (r/dp )
2
(r/dp )(3+2(i1))+bi
)]i a b C D1 1.803 0.0479 0.1252 0.0452 1.185 0.3566 3 0.02649 0.001925
chemical engineering research and design 9 4 ( 2 0 1 5 ) 549564 553
Table 2 (Chowdhu
Distillatio(ASTM D2
IBP (0.5 vol.50 vol.%: 33FBP (99.5 vo434 CSulfur: 16 2Nitride: 218
CFD and radial dispusing moledynamics consideringtive TBR pegood agreethe same mused in thconsidered
2.3.1. ReaThe last teduction of ireaction raHDA reactio
Ar S + 2H2
Poly-aroma
Di-aromati
Mono-arom
The reashould be nrate constakMono) canet al., 2002)
2.4. Ene
In the curreuated for tpacked bedent researcpractical reshould be le(2001) stateisothermalIn this wolent diamedoes not saied TBR. Futhe producels is quitecurrent stubed is necereactor pereach phasemultiphase
khk)
k
i=r(Q
, , heat
term
Ga correweennge
at trishem
2.18
hG,LkG
dh is
4 s(1
Liquwed tor. In ndits ans:
(1
fe
Waansf
senariaunt
part
= Re
ULDiesel oil (liquid phase) specicationsry et al., 2002).
n curve887)
Components xwt 100 (wt%)
%): 180 C Monoaromatics 17.967 C Diaromatics 8.77l.%): Triaromatics 1.64
98 ppm Tetraaromatics 0.95 ppm Naphthenes 19.25
Parafn 49.78
experimental data for prediction of axial andersion. Gunjal and Ranade (2007) indicated thatcular diffusion coefcient with appropriate hydro-model (EulerianEulerian multiphase model and
porosity distribution) can properly describe reac-rformance. The results of their CFD model showedment with experimental data. In the current work,odel proposed by Gunjal and Ranade (2007) was
e CFD model. Furthermore, wetting effects were on the CFD model to improve model accuracy.
ction kineticsrm in Eq. (8), Rk,i, stands for consumption or pro-th species due to chemical reactions. The followingte expressions were used to describe the HDS andns (Chowdhury et al., 2002):
Aromat + H2S (9)
tics + H2 Di-aromatics (10)
cs + 2H2 Mono-aromatics (11)
atics + 3H2 Naphthene (12)
ctions rate equations are tabulated in Table 3. Itoticed that HDA reactions are reversible and thents for the backward reactions (kPoly, kDi and
be estimated by vant Hoff equation (Chowdhury.
rgy conservation equation
nt work, the non-isothermal conditions were eval-he reactor CFD model. The criteria for study a
at isothermal condition were reported by differ-hers. Doraiswamy and Tajbl (1974) showed that theactor diameter-to-particles diameter ratio (dR/dp)ss than 4 for ignoring radial temperature. Carberryd that the maximum value for assumption of
t(k
+
wherephase source
2.4.1. A newfer betwide raerties and Ha
NuGL =
NuGL =
where
dh = a
2.4.2. Boelhoof solireactoting cothe gafollow
NuGS =
NuLS =
2.4.3. Heat tricantlydata, Mto accobed toas
Nuwall temperature in the radial direction is dR/dp < 6.rk, the ratio of dR/dp based on catalysts equiva-ter is about 13.6 (dR = 19 mm and dp = 1.4 mm) thattisfy criteria of isothermal operation for the stud-rthermore, according to Carberry and White (1969)t yield in the packed bed reactors using 2D mod-
sensitive to temperature effects. Therefore, in thedy, evaluation of temperature distribution in thessary to achieve the best results for prediction offormance. The energy conservation equation for
(gas, liquid and solid) based on EulerianEulerian approach can be developed in the following form:
ReLsu =
where ULc abed and pa
3. CF
In this stuexperimendeveloped diction of hhydrodesul + (kkUkhk) = (k Tk) + k uk kPkt
rk + mrkhrk mkrhkr) + Sk (13)
Qrk and S are thermal conductivity, viscosity, inter- transfer according to Eqs. (14) and (18) and the
due to reactions heat, respectively.
sliquid interphase heat transferlation was used to account interphase heat trans-
gas and liquid phases. The correlation covers the of operational conditions and uids physical prop-ckle ow regime with the following form (Heidariabadi, 2013):
5(
ReGReL
)0.378(PrGPrL
)0.499Eo0.627 (14)
dh (15)
the packed bed hydraulic diameter and dened as
) (16)
uidsolid and gassolid interphase heat transferr et al. (2001) derived a correlation to evaluate rate
liquid heat transfer at fully wetted trickle bedthe current study, due to catalysts partial wet-ion, their correlation was modied to account ford liquid phases heat transfer with solid phase as
fe) 0.111Re0.8G Pr1/3G (17)
0.111Re0.8L Pr1/3L (18)
ll to bed heat transferer from the reactor wall to the bed at TBRs is signif-sitive to the liquid ow rate. Based on experimentalni et al. (2003) proposed the following correlation
wall to bed Nusselt number, Nuwall, for differenticle diameter aspect ratios (4.7, 8.2, 17.2 and 34.3)
0.76Lsu
Pr1/3L (19)
c dp
L(20)
nd dp are liquid supercial velocity at core of therticle equivalent diameter, respectively.
D model and numerical algorithms
dy, as a benchmark, Chowdhury et al. (2002)tal work was used to consider the effect ofinterphase heat transfer correlations in the pre-ydrotreating reactions conversions. They studiedfurization and hydrodearomatization of diesel oil
554 chemical engineering research and design 9 4 ( 2 0 1 5 ) 549564
Table 3 Hydrodesulfurization and hydrodearomatization reactions kinetics.
Reactions (Chowdhury et al., 2002) Heat of reactions (HR) (Stanislaus andCooper, 1994; Chowdhury et al., 2002)
HDS RAr S = ksC
1.6Ar S
C0.56H2
1+50,000CH2S67 000
HDA (polyaromatics) RPoly = kPolyCPoly + kPolyCDi 66 462HDA (diaromatics) RDi = kDiCDi + kDiCMono 133 024HDA (monoaromatics) RMono = kMonoCMono + kMonoCNaph 199 203
in a tubular reactor with 500 mm length and 19 mm diame-ter, Fig. 1. The reactor consisted of two non-reactive zones attwo ends lled by inert particles with 0.2 mm average diame-ter. In the reactive zone, the trilobe catalysts (1.6 mm averagediameter and 3.5 mm average length) and inert spherical par-ticles were mixed with ratio of 1:1.25 (vol/vol). In this study, theequivalent diameter of particles was evaluated about 1.4 mmon the basis of Sauter Mean Diameter (SMD) of trilobe cata-lysts. The more detail about effect of particles different size onCFD model results of Chowdhury et al. (2002) reactor was pre-sented by Gunjal and Ranade (2007). The thermal conductivityof the solid phase on the basis of volumetric average of cat-alysts and inert particles thermal conductivity was evaluatedabout 58 W/m K. The reactor wall temperature was controlledby thermal system to prevent high increase in reactor temper-ature. Table 4 shows 18 different operational conditions usedat CFD simulations. The boundary conditions at the inlet zoneare equal with operational conditions, Table 4; furthermore,
the wall temperature is equal with the bed inlet temperature.Fig. 1 shows other boundary conditions of the CFD model. Theinitial conditions of the simulations were adjusted based onTable 4 data. In order to reduce divergence at the beginning ofthe simulation, the initial hydrogen concentration in the gasphase was dened to zero.
Due to reactor shape and uniform ow through the bed,a two dimensional (2D) axisymmetric computational domainwas used for CFD simulations, Fig. 1. Governing equations(Eqs. (1), (2), (8) and (13)) were solved by nite volume method(Patankar, 1980). Semi-Implicit Method for Pressure LinkedEquations (SIMPLE) was implemented for evaluating pressureand velocity coupling in the computational domain. In orderto achieve more accurate simulations, all of the convectiveterms in the transport equations were discretized by QUICK(Quadratic Upwind Interpolation for Convective Kinematics)scheme (Patankar, 1980). The simulations were performed atunsteady state conditions with time step of 0.01 s. The energyFig. 1 Reactor dimensions, computational domain and boundary conditions.
chemical engineering research and design 9 4 ( 2 0 1 5 ) 549564 555
Table 4 Operational and boundary conditions in the CFD simulation.
Parameter Cases Tinlet, Twall (K) P (MPa) LHSV (h1) QG,NTP/QL xvH2S
Temperature
sim-T1 573 4 2 200 0.014sim-T2 593 4 2 200 0.014sim-T3 613 4 2 200 0.014sim-T4 653 4 2 200 0.014
Pressuresim-P1 593 2 2 200 0.014sim-P2 593 4 2 200 0.014sim-P3 593 8 2 200 0.014
LHSVsim-L1 593 4 sim-L2 593 4 sim-L3 593 4
Gas ow rate
sim-Q1 593 4 sim-Q2 593 4 sim-Q3 593 4 sim-Q4 593 4
Hydrogensuldeconcentration
sim-H2S1 593 4 sim-H2S2 593 4 sim-H2S3 593 4
equations prevent nuulations weand averagof solutionsimultaneosteady stattions were 960 (8M Ca
4. Re
4.1. CFD
The hydrodin the authconcisenesIn order totions that rdeveloped,tures (sim-in a model
Fig.
rmalith
relat (Che dev
with
Me
diffeor Ce nnd nondentism m
denson th
Mosim-H2S4 593 4
relaxation factors were dened small enough tomerical instability during the solution. The sim-re terminated when the bed average temperaturee mass fraction of sulfur components at the entire
domain have no signicant change with the time,usly. The average time that was required to reache conditions was about 10 000 s. All of the simula-done on a PC with 8 GB RAM and Intel CoreTM i7che, 3.20 GHz) processor.
sults and discussion
model validation
ynamic correlations of CFD model were validatedors previous work (Salimi et al., 2013) and for
s, validation procedure was not presented here. validation of the CFD model based on the condi-eactions kinetics by Chowdhury et al. (2002) were
the CFD simulations at different inlet tempera-
isothetrast wmean resultsthat thmance
4.2.
Three mesh fing thtime aindepetype saoptimumesh effect
4.3.
T1, sim-T2, sim-T3 and sim-T4, Table 4) were done
with uniform porosity, fully wetted particles and
2 Validation of HDS reactor CFD model.
In this invbed non-isoting effect w(ks,Poly,Di,Monkinetics. Aeffects are tion rates wcalculated (2011) poinevaluation tions shou
Table 5 operation
Mesh typ
1 2 3 1 200 0.0142 200 0.0144 200 0.014
2 100 0.0142 200 0.0142 300 0.0142 500 0.014
2 200 02 200 0.0142 200 0.032 200 0.08
bed. Fig. 2 depicts CFD simulations results in con-Chowdhury et al. (2002) experimental data. Theive error of 5.5% between CFD and experimentalowdhury et al., 2002) was obtained which showseloped CFD model can predict HDS reactor perfor-
appropriate accuracy.
sh independency
rent mesh sizes were examined to nd optimumFD simulations. In this sensitivity analysis, achiev-al HDS reaction conversion at the minimum run
signicant change on its value were used as meshcy criteria. As shown in Table 5, the second mesh
es the mentioned criteria and was selected as theesh for numerical simulations. Additionally, the
ity was rened near the bed wall to account walle radial porosity distribution, Fig. 1.
died reaction kineticsestigation, the inuence of porosity distribution,thermal conditions and also particles partial wet-ere accounted in the reactions kinetics constants
o Table 3) to nd intrinsic HDS and HDA reactionsccording to Mederos et al. (2009a) if temperatureneglected in the reactor model, it leads to the reac-ith several orders of magnitude greater than thoseat non-isothermal conditions. Also, Ranade et al.ted out that for development of rate equations andof kinetic parameters, all aspect of reactor condi-ld be considered in the mathematical model. To
Mesh independency results at sim-T1al condition of Table 4.
e Cellnumbers
HDS reactionconversion (%)
Run time(h)
9000 40 1022 000 42.6 4588 000 42.7 115
556 chemical engineering research and design 9 4 ( 2 0 1 5 ) 549564
Table 6 New values of reactions kinetic constants fornon-isothermal conditions and partially wettedcatalysts.
Reaction Isothermal andfully wettedcatalysts
(Chowdhury etal., 2002)
Non-isothermaland partially
wetted catalysts
HDS (ks), Eq. (9) 2.5 1012 7.166 1012HDA (polyaromatics
kPoly), Eq. (10)2.66 105 4.23 105
HDA (diaromatics kDi),Eq. (11)
8.5 102 1.33 103
HDA (monoaromatics kMono), Eq. (12)
6.04 102 9.62 102
this aim, new values of reactions constants were estimatedby comparing of HDS conversion obtained from numerical(this work) and experimental data (Chowdhury et al., 2002)at different operational temperatures (sim-T1, sim-T2, sim-T3and sim-T4, Table 4). The best values were evaluated by usingbisection mconstants f
4.4. Fee
Fig. 3 showperatures (can be inferments withrelative errmodel withabout 1.8%reactions koperationaties of the H
4.4.1. TemThe axial teHDA reactipresented zone, the bheat by theperature in
Fig. 3 HDtemperatur
Fig. 4 Axthe total reTable 4.
HDS reaction conversion at different operationalres (sim-P1, sim-P2 and sim-P3, Table 4).
imately at z = 0.31 m and then begins to decreaseh the bed. The reason of reduction in the bed temper-after z = 0.31 m can be found at reactor constant wallrature which was xed at 613 K. When the reactantsthe reactive zone, great amounts of thermal energy
due to high reaction rates at the beginning of reactivet the same time, increase in the bed temperature accel-
reactions rates and the bed temperature rises much On the other hand, the bed constant wall temperatureethod. Table 6 presents the new values of reactionsor the HDS and HDA reactions.
d inlet temperature effect
s HDS reaction conversion at different inlet tem-sim-T1, sim-T2, sim-T3 and sim-T4, Table 4). As itred, the CFD simulation results show proper agree-
experimental data (Chowdhury et al., 2002). Theor between the experimental and optimized CFD
new reactions constants (Section 4.3) was found. Therefore, it can be concluded that the modiedinetics can be used to study the effects of differentl parameters on the performance and local proper-DS reactor, more accurately.
perature distributionmperature distribution and total heat of HDS andons at sim-T3 operational condition (Table 4) arein Fig. 4. As shown in this gure, in the reactiveed temperature increases rapidly due to generated
hydrotreating reactions (Eqs. (9)(12)). The tem-creases to the highest value (a hot spot with 623 K)
Fig. 5 pressu
approxthrougature tempeenter releasezone. Aeratesfaster.S reaction conversion at different inletes (sim-T1, sim-T2, sim-T3 and sim-T4, Table 4).
which was shown in Fafter the inin the reactthe heat thperature derate of redz > 0.4 m, wenergy equ
4.5. Th
Fig. 5 depicsim-P2 andtion. The rial temperature distribution (at r = 0) and heat ofactions through the bed at sim-T3 conditions,set at 613 K eliminates generated heat in the bed. Asig. 4, the total heat of reactions begins to decreaselet part of reactive zone which is due to reductionants concentrations. On the other hand, removingrough the reactors wall nally causes the bed tem-creases through the bed at z > 0.31 m. Lastly, the
uction in the temperature occurs more rapidly athere the reactive zone reaches to its end and theation (Eq. (13)) is solved with no heat source terms.
e bed operational pressure effect
ts the effect of the bed operational pressure (sim-P1, sim-P3, Table 4) on the conversion of HDS reac-esults show a good agreement between reported
chemical engineering research and design 9 4 ( 2 0 1 5 ) 549564 557
Fig. 6 (A) mass fractiat constantsim-P1 con
experimenlation resuat constantimproves win the convwhen the opresses anthe same tliquid phasbed, whichresidence thydrogen cfore the hygives rise toa result, grohigh operat
4.5.1. PerFig. 6 compwall tempeture and sucondition. observed bperature anabout 16 K
HDS reaction conversion at different LHSV values1, sim-L2 and sim-L3, Table 4).
d condition compared to constant wall temperature,ratestly, com
reacFig. 7 (sim-L
isolateaccelesequensulfur than aAxial temperature distribution (at r = 0) and (B)on of desulfurized components through the bed
wall temperature and isolated wall in theditions, Table 4.
tal data (Chowdhury et al., 2002) and CFD simu-lts with 4.9% relative error. As it can be observed,
gas and liquid ow rates, the reaction conversionith an increase in the bed pressure. Enhancementersion rate can be caused by two reasons; rst,perational pressure increases, the gas phase com-d thus its velocity decreases through the bed. Atime, the momentum interaction between gas andes causes the liquid velocity to reduce through the, in turn, brings about increase in the liquid phaseime. Second, in the high reactor pressures, theoncentration increases in the gas phase and there-drogen interphase mass transfer enhances which
more conversion in the liquid phase reactants. Aswth in the HDS conversion rate can be observed ational pressures.
formance of adiabatic reactorares the effect of isolated reactor wall and constantrature on axial distribution of liquid tempera-lfur components concentration at sim-P1 (Table 4)According to Fig. 6A, an ascending difference isetween temperature values at constant wall tem-d isolated conditions with maximum difference
. The more increase in the bed temperature at
version for78% while iture condit
As Fig. decreases constants ain the liquiliquidsolidphase heatspecic timlibrium. Asobserved in
4.6. Eff
Fig. 7 showSupercial ric ow rate
Fig. 8 Axand sim-L3 the reactions rates and reactants conversion. Con-as it can be seen in Fig. 6B, the mass fraction ofponents in the adiabatic reactor decreases moretor with constant wall temperature. The nal con-
HDS reaction in the adiabatic condition was aboutt is obtained about 69% at constant wall tempera-ion.6A illustrates, the liquid phase temperature
about 0.5 K after the reactive zone and remainsfter z=0.41 m. The reason of this small reductiond temperature can be found in the liquidgas and
interphase heat transfer rates. In effect, the inter- transfer is not a phenomenon with innite rate ande is required that phases reach the thermal equi-
a result, after the reactive zone a small decrease is the liquid phase temperature.
ect of LHSV on HDS reaction conversion
s HDS reaction conversion versus Liquid HourlyVelocity (LHSV LHSV is ratio of liquid volumet-
per reactor volume) at sim-L1, sim-L2 and sim-L3ial temperature distribution at r = 0 in the sim-L1 conditions, Table 4.
558 chemical engineering research and design 9 4 ( 2 0 1 5 ) 549564
Fig. 9 Totvalues (sim
conditions,and experiwhich showimental resincreases, chigher valuand accordThe differeLHSV valuemass transinterphaseincrease inmass transtration in tseems thatreal conditdiction in Hto experim
In Fig. is depictedTable 4). Ashows highof such behand subseqL3. Accordthe sim-L1case, sim-L
Fig. 10 H (sim
tive ot pon theoughf cond th-L3.
the nce t
HDllusteter se inreasetwe2002lative
of d dueard rs ovbed non-isothermal condition and vant Hoff equation,
Fig. 11 (Aal HDA reaction conversion at different LHSV-L1, sim-L2 and sim-L3, Table 4).
Table 4. The relative error between CFD resultsmental data (Chowdhury et al., 2002) is about 3.8%s good agreement between numerical and exper-ults. As it can be inferred from Fig. 7 when LHSVonversion of HDS reaction decreases. Actually, ates of LHSV the liquid residence time decreaseingly, reaction conversion reduces in the reactor.nce between CFD and experimental data at highs can be explained by effect of hydrogen interphasefer rate on HDS reaction conversion. According to
mass transfer coefcient term, KL,iaL (Table 1), an the liquid velocity enhances the rate of interphasefer. Therefore, at high LHSVs the hydrogen concen-he liquid phase increases. Based on CFD results, it
hydrogen concentration is predicted more thanions at higher LHSVs and consequently, more pre-DS conversion occurs at numerical results respectental data.8, axial distribution of temperature in the TBR
at two different conditions (sim-L1 and sim-L3,s shown, the temperature of the bed at sim-L1er values in comparison with sim-L3. The reasonavior can be found in more conversion at sim-L1uently, more heat generation compared to sim-
values
of reachot sptime. Iity thrmost ozone athe simmovesreside
4.6.1. Fig. 9 iparamincreato dection beet al., age rereasoncan bebackwreduceing to ing to Fig. 8, the bed maximum temperature in condition occurs at z = 0.35 m while in the other3, the highest temperature happens at the outlet
at high temas forwardconversion
) Radial temperature distribution at z = 0.4 m and (B) contour of teDS reaction conversion at different gas ow rate-Q1, sim-Q2, sim-Q3 and sim-Q4, Table 4).
zone, z = 0.4 m. The cause of this difference in thesitions can be found in the liquid phase residence
sim-L1, the liquid phase moves with lower veloc- the bed than that of sim-L3. As a result, in sim-L1nversion happens at the entrance of the reactivee hot spot occurs closer to the inlet compared with
In contrast, the higher velocity at sim-L3 conditionhot spot to the end of the reactive zone due to lowime of reactants.
A reactions conversionrates the effect of liquid velocity in terms of LHSVon the total HDA conversion. As the gure shows,
the LHSV values reduces reaction conversion due in reactants residence time. Moreover, the devia-en numerical and experimental data (Chowdhury) is high and CFD results show about 45% aver-
error with respect to the experimental data. Theeviation between CFD and experimental results
to inuence of temperature on the rate of HDAeactions which damps forward reactions rates anderall conversion of aromatic components. Accord-peratures HDA backward reactions become as fast reactions. Therefore, reduction in the total HDA
can be observed in the numerical results.
mperature in the sim-Q1 condition (Table 4).
chemical engineering research and design 9 4 ( 2 0 1 5 ) 549564 559
4.7. Gas ow rate effect
In Fig. 10, gas ow raAccording tHDS reactiment can brelative erret al., 2002)
Increaseuid phase subsequenTherefore, higher gas Such inconvelocities oIn comparities the bedcondition. Cenhances bhydrogen cin Fig. 10, mgas ow rat
The radzone (z = 0.4nal cross s(Table 4). Aaffected bythe porositin the vicinporosity, duphase masslocations aTable 1. Contration in treactions. in the catations leadstemperaturof the localysts volumand the beity positionwhere the perature shheat transfity to the r(Twall = 593
In Fig. 11Q1 conditioapproximaposition ofthe bed pothe center and r < 4 mboring locato reduce treactor engcess.
4.8. Eff
Fig. 12 illussulde con
HDS reaction conversion at different hydrogen concentrations (sim-H2S1, sim-H2S2, sim-H2S3 and2S4, Table 4).
S3 and sim-H2S4, Table 4). The inuence of increase gas phase hydrogen sulde can be seen in the formuction of hydrogen concentration in the gas phaserrespondingly, in the liquid phase. Actually, at lower
(A) Reactive zone average temperature and (B) totalenerated by HDS and HDA reactions (sim-H2S1,2S2, sim-H2S3 and sim-H2S4, Table 4).the HDS reaction conversion is plotted againstte (sim-Q1, sim-Q2, sim-Q3 and sim-Q4, Table 4).o the gure, increase in the gas ow rate improveson conversion, although no remarkable enhance-e observed. The numerical results show about 6.4%or versus available experimental data (Chowdhury.
in the gas velocity affects directly on the liq-velocity due to interphase momentum coupling;tly, reactants residence time reduces in the bed.it is expected that reaction conversion decreases atow rates while the reverse behavior is observed.sistency can be explained by inuence of higher gasn increase of hydrogen interphase mass transfer.son with low velocity condition, at higher veloci-
hydrogen concentration remains close to the inletonsequently, the rate of interphase mass transferetween gas and liquid phases which causes moreoncentration in the liquid phase. Hence, as shownore conversion in the HDS reaction occurs at higheres.ial temperature distribution at the end of reactive
m) and the contour of temperature on longitudi-ection are shown in Fig. 11 for sim-Q1 conditions Fig. 11A suggests, the temperature prole is
the bed porosity distribution so that wherevery is high, the bed temperature increases exceptity of the wall. In the locations with high locale to more velocity of liquid phase, hydrogen inter-
transfer increases about 4% respect to neighboringccording to interphase mass transfer correlation ofsequently, enhancement in the hydrogen concen-he liquid phase increases rates and heat of theOn the other hand, it is expected that decreaselysts volume fraction at high local porosity posi-
to reduction of the reactions rates and the bede. As a result, it can be concluded that formationl hot spots due to small changes in the cata-e fraction is affected by interphase mass transferd temperatures increases in the high local poros-s far from the wall. In the vicinity of the wall,bed porosity is at the highest value, the bed tem-arply decreases. In this region, the maximumer from the bed occurs because of the proxim-eactor wall which is set at constant temperatureK).B, the contour of bed temperature is shown at sim-n. According to this gure, the hottest region is
tely formed at the end of the reactive zone. The hot spot depends on velocity of the phases androsity distribution. It forms in the location nearof the bed axis located in the range of r > 2 mmm where the local porosity is more than neigh-tions. The estimation of hot spot position helpshermal runaway problems in the bed and enablesineers to have an appropriate control over the pro-
ect of gas phase H2S concentration
trates the HDS conversion at different hydrogencentrations of the gas phase (sim-H2S1, sim-H2S2,
Fig. 12suldesim-H
sim-H2in theof redand co
Fig. 13heat gsim-H
560 chemical engineering research and design 9 4 ( 2 0 1 5 ) 549564
Fig. 14 Mass fraction of Poly-, Di- and Mono-aromaticsalong the bed at sim-H2S1 conditions, Table 4.
values of hydrogen mole fraction in the gas phase, rateof interphase mass transfer reduces which causes smallerhydrogen concentration in the liquid phase and thereforereduction in the conversion of reactions. As it is depictedin Fig. 12, the current CFD model which considers for the
Fig. 15 (Athe CFD prsim-P2 andtemperatur
effect of interphase heat transfer, provides a better matchto the expresults (GuThe averagtal data (Chstudy and between nof HDS coof adsorptperature inreaction kismall chancient has nmain reasoical resultsHDS reactiocentrations
Fig. 13 zone and hto Fig. 13Awith incredue to decheat by theshould be dthe releasecomputed,heat by theure shows fraction intion decrearate, the retrend at hiconcentratconsumptiHDA reactitration, thedeclines wsumption bhydrogen c
utioses. Teat bso aperaghydrcontribincreaated hand albed avferent ) Effect of gasliquid interphase heat transfer inediction of HDS reaction conversion (sim-P1,
sim-P3, Table 4) and (B) axial (r = 0) bede at sim-P3 conditions.
4.8.1. DisfractionIn Fig. 14,matic comsim-H2S1 cand di-aromono-arominlet of thereactions kthe case osion of di-increase inoccurs alonAfter that,tion and cofraction ofreactor.erimental data in comparison with other CFDnjal and Ranade, 2007) at isothermal conditions.e of relative error between CFD and experimen-owdhury et al., 2002) is about 13% for the current21% for Gunjal and Ranade (2007). The deviationumerical and experimental results at predictionnversion might be attributed to independencyion coefcient of hydrogen sulde to the tem-
the HDS reaction kinetics and also developednetics constants. However, it seems that due toges in the bed temperature, adsorption coef-o signicant effect on the errors. Therefore, then of deviation between experimental and numer-
might be related to the undesired dependency ofn kinetic from hydrogen and hydrogen sulde con-.depicts the average temperature of the reactiveeat of HDS and total HDA reactions. According, the temperature shows no signicant changesase in the hydrogen sulde concentration whilerease in HDS conversion (Fig. 12) and produced
HDS reaction, it seems that the bed temperatureecreased. To explain constant temperature trend,d heat by HDS and total HDA reactions should be
simultaneously. In Fig. 13B, values of generated reactions are shown at individual bars. The g-that with increase in the hydrogen sulde volume
the gas phase, the produced heat by HDS reac-ses. In contrast, due to reduction in HDS reactionleased heat by total HDA reactions takes ascendinggher hydrogen sulde concentrations. At the highion of hydrogen in the bed, the rate of hydrogenon by the HDS reaction is considerably more thanons. On the other hand, at low hydrogen concen-
rate of hydrogen consumption by HDS reactionhich causes growth in the rate of hydrogen con-y the HDA reactions. With more decrease in theoncentration (sim-H2S1 to sim-H2S4, Table 4), then of HDA reactions to consumption of hydrogenherefore, as seen in Fig. 13B, due to higher gener-y HDA reactions in comparison with HDS reactionproximately constant overall produced heat, the
e temperature shows no signicant changes at dif-ogen sulde concentration, Fig. 13A.
tribution of aromatic components axial mass
distribution of average mass fraction of aro-ponents is shown along the reactor length atonditions. As observed, mass fractions of poly-
matics components continuously decrease whileatics mass fraction shows a maximum at the
reactive zone. According to Eqs. (10)(12), HDAsinetics are presented by a chain mechanism. Inf mono-aromatics reaction, due to high conver-aromatics species respect to mono-aromatics, an
the concentration of mono-aromatics componentsg the bed with a maximum point at z = 0.17 m.
due to reduction in the di-aromatics concentra-nsumption of mono-aromatics components, mass
mono-aromatics begins to decrease through the
chemical engineering research and design 9 4 ( 2 0 1 5 ) 549564 561
Fig. 16 Co e heheat transf
4.9. Gasimulation
In order toeffect in thtemperatursim-P2 andgasliquid case of noversion preconditions.and liquid pto only excheat loss inalong the bsion showstemperaturinterphaseAs it can bethermal intture distribchange in tas interphatants convdistributioninterphaseTBR perform
5. Co
CFD simulby means main objenon-isotheinterphase
ansfr moonve
CFD
reaclopebest ntour of the bed temperature: (A) with gasliquid interphaser at sim-P3 conditions, Table 4.
sliquid interphase heat transfer effect onresults
demonstrate gasliquid interphase coefciente prediction of HDS reaction conversion and bede distribution, the CFD simulations at sim-P1,
sim-P3 (Table 4) were repeated with eliminatinginterfacial heat transfer. As Fig. 15 shows, in the
heat trtransfetions con the
Thedevethe gasliquid heat transfer, Fig. 15A, the HDS con-diction is about 5% higher than non-isothermal
In effect, neglecting the heat transfer between gashases causes the reaction heat in the liquid phasehange with the solid phase. Thus, due to lower
the liquid phase, the phase temperature increasesed (Fig. 15B) which leads to the reaction conver-
higher values than expected. In Fig. 16, contour ofe is shown with and without effect of gasliquid
heat transfer during the CFD simulation at sim-P3. inferred from the gure, neglecting the gasliquideraction affects signicantly on the local tempera-ution, so that the location and values of hot spotshe bed. Subsequently, the entire phenomena suchse mass transfer, phases properties and local reac-ersion are affected by difference at temperature. Therefore, it is safe to say that utilizing gasliquid
heat transfer signicantly improves the accuracy ofance prediction.
nclusion
ations of hydrotreating TBR were carried outof EulerianEulerian multiphase approach. Thective of this work was the CFD simulation ofrmal reactor by implementation of appropriate
heat transfer coefcient. The modied solid-uids
reactionsand realcomprom
It was shby the beat positiomaximuthis zonetemperat
At the adifferencwas showmaximumtemperatment wacondition
Finally, iphase heconversioThereforinterpha
Acknowle
The author(POGC - Islthis work (Gat transfer and (B) without gasliquid interphase
er coefcient and a new gasliquid interphase heatdel were developed to accurately predict the reac-rsions and local properties through the bed. Based
simulations, the following results can be inferred:
tion kinetics constants were optimized based ond CFD model. The optimization was done to ndvalues that present intrinsic chemical behavior of on the basis of appropriate mathematical model conditions of studied TBR. Results showed goodise between numerical and experimental results.
own that the radial temperature of the bed affectedd porosity and the highest temperature occurredns near the bed center. Results showed that the
m heat loss occurs at the vicinity of the wall; in, high velocities of the phases and constant wallure cause the maximum heat loss in the bed.diabatic and constant wall temperature, a largee was observed between the bed temperatures. Itn that there is a difference about 16 K between
bed temperatures at adiabatic and constant wallure conditions. In addition, about 16% improve-s observed in HDS reaction conversion at adiabatics.
t was shown that neglecting the gasliquid inter-at transfer affects on the prediction of reactionsn and local parameters such as bed temperature.
e, using appropriate model to describe gasliquidse heat transfer seems inevitable.
dgment
s would like to thank Pars Oil and Gas Companyamic Republic of Iran) for the nancial support ofrant No. 91-203/TP).
562 chemical engineering research and design 9 4 ( 2 0 1 5 ) 549564
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CFD study of diesel oil hydrotreating process in the non-isothermal trickle bed reactor1 Introduction2 Governing equations2.1 Modeling assumption2.2 Hydrodynamics equations2.3 Species conservation equations2.3.1 Reaction kinetics
2.4 Energy conservation equation2.4.1 Gasliquid interphase heat transfer2.4.2 Liquidsolid and gassolid interphase heat transfer2.4.3 Wall to bed heat transfer
3 CFD model and numerical algorithms4 Results and discussion4.1 CFD model validation4.2 Mesh independency4.3 Modified reaction kinetics4.4 Feed inlet temperature effect4.4.1 Temperature distribution
4.5 The bed operational pressure effect4.5.1 Performance of adiabatic reactor
4.6 Effect of LHSV on HDS reaction conversion4.6.1 HDA reactions conversion
4.7 Gas flow rate effect4.8 Effect of gas phase H2S concentration4.8.1 Distribution of aromatic components axial mass fraction
4.9 Gasliquid interphase heat transfer effect on simulation results
5 ConclusionAcknowledgmentReferences