coilsim1d simulation of steam cracking coilskvangeem/download/coilsim/manual... · 2014-10-20 ·...

Confidential

User manual

COILSIM1D

Simulation of Steam Cracking Coils

Confidential October 2014

Prof. dr. ir. Kevin Van Geem

Universiteit Gent

Laboratorium voor Chemische Technologie

Director : Prof. dr. ir. G. B. Marin

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Executive summary

COILSIM1D is developed at the Laboratory for Chemical Technology of Ghent University to

simulate steam cracking of hydrocarbons in a tubular reactor. The reaction network that it uses is

a radical scheme consisting of two parts:

a monomolecular µ network

a β network

To model the reactors for steam cracking, a reactor model is also required. The model equations

are based on a 1-dimensional reactor model, in which no radial gradients are assumed, except for

the temperature in a very thin film close to the wall in which all resistance to heat transfer is

located. The flow is assumed to be of the plug flow type. The model equations contain the

continuity equations for the different species, an energy balance and a pressure equation. These

equations are integrated along the reactor coil, finally resulting in the product yields and the

pressure and temperature profiles.

To simulate the run length of industrial steam cracking coils, the fundamental simulation model

COILSIM1D incorporates two coking models. The coking model of Plehiers et al. (1992) was

developed for prediction of coking rates for steam cracking of light hydrocarbon feedstocks. The

model of Reyniers et al. (1994) allows to simulate the coking rate of heavier feedstocks, ranging

from light naphtha fractions up to condensates. Both coking models account for the

heterogeneous noncatalytic or so-called asymptotic coking only. The contributions of the

heterogeneous catalytic coking and the homogeneous noncatalytic coking to the total amount of

coke formed during the complete run length are assumed to be negligible. 4,5

The coking kinetics

are coupled to the 1-dimensional reactor model equations solved in COILSIM1D.

October 2014

Prof. dr. ir Kevin Van Geem

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Contents

Chapter 1: Steam Cracking of Hydrocarbons ............................................................................ 8

1.1 Introduction ..................................................................................................................... 8

1.2 Reaction Network .......................................................................................................... 10

1.2.1 Global Reaction Network ...................................................................................... 10

1.2.2 The β network ........................................................................................................ 12

1.2.3 The µ network ........................................................................................................ 13

1.2.3.1 Reaction schemes from C-C scission reactions, hydrogen abstractions and

addition reactions ................................................................................................................. 14

1.2.3.2 Additivity of reaction schemes ........................................................................ 19

1.2.3.3 Calculation of the Pseudo Rate Coefficients .................................................. 21

1.3 Species considered in the Reaction Network ................................................................ 22

1.3.1 Molecules ............................................................................................................... 22

1.3.2 Radicals .................................................................................................................. 27

1.4 Calculation of the reaction rate coefficients .................................................................. 28

1.4.1 Radical additions and reverse scission ............................................................... 29

1.4.2 Hydrogen abstraction reactions .............................................................................. 31

1.4.3 C-C and C-H scission of molecules and recombination of radicals ...................... 32

1.5 References …………………………………………………………………………..32

Chapter 2: COILSIM 1D .......................................................................................................... 35

2.1 Introduction ................................................................................................................... 35

2.2 1-Dimensional Reactor Model Equations ..................................................................... 36

2.2.1 Continuity Equations ............................................................................................. 36

2.2.2 Energy equation ..................................................................................................... 36

2.2.2.1 Basic Equation ................................................................................................ 36

2.2.2.2 Calculation of the convection coefficient hc ................................................... 37

2.2.2.3 Calculation of the conduction coefficient λw .................................................. 39

2.2.2.4 Calculation of the expansion coefficient α ..................................................... 39

2.2.3 Momentum equation .............................................................................................. 40

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2.2.3.1 Basic Equation ................................................................................................ 40

2.2.3.2 Calculation of the friction factor f .................................................................. 41

2.3 Solving the 1-Dimensional Reactor Model Equations .................................................. 43

2.3.1 Integration of balances ........................................................................................... 43

2.3.2 Calculation of the heat flux based on the wall temperature ................................... 45

2.4 COILSIM1D for industrial furnaces ............................................................................. 47

2.4.1 Shooting method .................................................................................................... 48

2.4.2 Shooting technique in COILSIM1D ...................................................................... 50

2.4.3 Iteration procedure ................................................................................................. 54

2.5 Pre-defined standard coils ............................................................................................. 56

2.6 Adiabatic volume .......................................................................................................... 57

2.7 Calculation of the physical and transport properties ..................................................... 59

2.7.1 Specific heat cp ....................................................................................................... 59

2.7.2 Standard enthalpy of formation ΔHf ...................................................................... 59

2.7.3 Viscosity µ ............................................................................................................. 60

2.7.4 Thermal conductivity λ .......................................................................................... 61

2.8 Calculation of the Coking Rate ..................................................................................... 62

2.9 SIMCO .......................................................................................................................... 63

2.9.1 General overview ................................................................................................... 64

2.9.1.1 Neural network ............................................................................................... 67

2.9.1.2 Shannon entropy optimization ........................................................................ 68

2.9.2 Molecular libraries ................................................................................................. 70

2.9.2.1 Input files ........................................................................................................ 71

2.9.3 Boiling point conversion ........................................................................................ 75

2.9.3.1 Conversion of ASTM D86 to TBP distillation at atmospheric pressure......... 75

2.9.3.2 Conversion of ASTM D2887 to TBP distillation at atmospheric pressure..... 77

2.9.3.3 Conversion of ASTM D2887 to ASTMD86 distillation .................................. 78

2.9.4 Calculation of the commercial indices ................................................................... 79

2.9.4.1 Average molecular weight .............................................................................. 79

2.9.4.2 H/C ratio ......................................................................................................... 80

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2.9.4.3 Density ............................................................................................................ 80

2.9.4.4 True boiling point distillation curve ............................................................... 80

2.9.4.5 PIONA analysis .............................................................................................. 81

2.10 References ..................................................................................................................... 81

Chapter 3: Program and Data File Description ........................................................................ 84

3.1 Introduction ................................................................................................................... 84

3.2 Installing COILSIM1D ................................................................................................. 84

3.3 Installing the CodeMeter security key .......................................................................... 87

3.4 Important data files ........................................................................................................ 87

3.4.1 thermochemistry.i .................................................................................................. 87

3.5 Input files ....................................................................................................................... 88

3.5.1 Units.txt .................................................................................................................. 88

3.5.2 reactor.txt ............................................................................................................... 90

3.5.3 nafta.i ..................................................................................................................... 97

3.5.4 cokes.da .................................................................................................................. 99

3.5.5 coke.i ...................................................................................................................... 99

3.5.6 exp.txt ..................................................................................................................... 99

3.5.7 profileshape.i ........................................................................................................ 103

3.5.1 burnerflux.da ........................................................................................................ 103

3.5.2 pitch.da ................................................................................................................. 103

3.5.3 test.da ................................................................................................................... 104

3.5.4 runlength.txt ......................................................................................................... 104

3.5.1 simulation.txt ....................................................................................................... 105

3.6 Output files .................................................................................................................. 106

3.6.1 simulation_overview.txt ....................................................................................... 106

3.6.2 results.txt, general_info.csv, yields.csv, yieldprofiles.csv ................................... 106

3.6.3 SensitivityOverview.csv ...................................................................................... 112

3.6.4 RunlengthOverview.csv ....................................................................................... 112

3.7 Running COILSIM1D ................................................................................................. 112

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3.8 COILSIM1D GUI ....................................................................................................... 113

Chapter 4: Feedstock Definition ............................................................................................ 130

4.1 Introduction ................................................................................................................. 130

4.2 Molecular components ................................................................................................ 130

4.3 Feedstock transformation ............................................................................................ 136

4.4 Influence of feedstock definition on product distribution ........................................... 138

4.4.1 C6, C7 and C8 isoparaffins .................................................................................. 144

4.4.2 C7 naphthenes ...................................................................................................... 154

4.4.3 C9 aromatics ........................................................................................................ 154

4.5 Conclusions ................................................................................................................. 155

4.6 References ................................................................................................................... 155

Appendix A ………………………………………………………………………………………. I

Appendix B ……………………………………………………………………………………… X

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List of symbols

A frequency factor for a first order reaction s-1

frequency factor for a second order reaction m3 kmol

-1 s

-1

B : inter-fin distance m

cp heat capacity kJ kmol-1

K-1

cpj heat capacity of component j at temperature T kJ kmol-1

K-1

C concentration kmol m-3

di internal diameter of the finless tube m

dt internal diameter of the tube m

Ea activation energy kJ mol-1

f Fanning friction factor -

Fj molar flow rate of component j kmol s-1

Ft total molar flow rate kmol s-1

G mass flux kg m-2

s-1

hc convection coefficient kJ m-2

K-1

s-1

ΔfHk standard enthalpy of species k kJ kmol-1

k reaction rate coefficient for a first order reaction s-1

reaction rate coefficient for a second order reaction m3 kmol

-1 s

-1

nij stoechiometric coefficient -

nr number of reactions -

M average molecular mass kg kmol-1

pt total pressure Pa

P pitch of the fin m

q heat flux to the process gas kJ m-2

s-1

rb radius of the bend m

rV,k reaction rate of reaction k kmol m-3

s-1

Rv,k net production rate for species k kmol m-3

s-1

T temperature K

v velocity m s-1

x conversion -

z axial reactor coordinate m

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Greek symbols

α conversion factor -

δ steam dilution kg kg-1

ρ density kg m-3

Ω cross sectional surface area m2

λ thermal conductivity of the process gas kJ m-1

K-1

s-1

μ viscosity of the process gas kg m-1

s-1

υkj stoichiometric coefficient of component j. -

Chapter 1: Steam Cracking of Hydrocarbons

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Chapter 1:

Steam Cracking of Hydrocarbons

1.1 Introduction

Steam cracking of hydrocarbons is one of the most important processes of the petrochemical

industry. In this process, hydrocarbons are cracked into commercially more important products

such as light olefins and aromatics. Feedstocks ranging from light alkanes, such as ethane and

propane, up to complex mixtures such as naphthas and heavy gas oils are converted at

temperatures ranging from 900-1200 K in tubular reactors suspended in large gas-fired furnaces.

The importance of the steam cracking process to the petrochemical industry has justified the

continuous interest for developing new and better mathematical simulation models during the

last four decades. Mathematical modeling has the important advantage that, once the model is

developed, results can be easily gathered and computer simulations take only a limited time

(Dente and Ranzi, 1979). Rice and coworkers (1931, 1934, 1943) showed that steam cracking of

hydrocarbons proceeds through a free radical mechanism and that three important reaction

families can be distinguished:

- Carbon-carbon and carbon-hydrogen bond scissions of molecules and the reverse radical-

radical recombinations:

2121 RRRR [1. 1]

- Hydrogen abstraction reactions, both intra- and intermolecular:

HRRRHR

2121 [1. 2]


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- Radical addition to olefins and the reverse scission of radicals, both intra- and

intermolecular:

321 RRR

321 RRR [1. 3]

Although the previous three reaction families are the dominant reaction families for steam

cracking other reaction families can also become important. Electrocyclizations are an example

of such reaction families. An electrocyclic reaction is the concerted interconversion of a

conjugated polyene and a cycloalkene. Consider for example the following electrocyclic reaction

of 1,3,5-hexatriene with the formation of 1,3 cyclohexadiene:

[1. 4]

Electrocyclizations are very fast reactions (Shiess and Dinkel, 1981) and are important routes

towards the formation of aromatic compounds (Jutz, 1978; Kopinke et al., 1987).

Nowadays computers are used not only to solve the simulation numerically, but also to

generate the reaction network, construct the model and calculate the kinetic parameters. A key

difficulty of these mechanism generation programs is that they produce large numbers of

kinetically unimportant reactions and species. Several assumptions help to retain the mechanism

within manageable sizes. The µ radical hypothesis is surely the most important assumption in the

current reaction network. This hypothesis assumes that bimolecular reactions can be neglected

for radicals with more than 5 carbon atoms (Ranzi et al. 1983). The latter are also called µ

radicals. Radicals that are only involved in bimolecular reactions such as the hydrogen radical,

the methyl radical or the benzyl radical are called β radicals [βµ rules of Goldfinger-Letort-

Niclause (Laidler, 1987)]. An intermediate category are βµ radicals such as the ethyl radical,

which have a β character at low temperatures and a µ character at high temperatures. The

distinction between β, βµ and µ radicals allows to reduce the computational cost of the reaction

network without loosing any accuracy. In the following paragraphs the construction of the

reaction network is explained in more detail.


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1.2 Reaction Network

1.2.1 Global Reaction Network

Developing a detailed reaction network is a major challenge. On the one hand the size of the

reaction network can become huge as the number of reactions and species increases

exponentially with the average carbon number of the feedstock (Broadbelt et al., 1994). On the

other hand, developing these reaction networks implies that both the thermo-chemistry and

kinetic parameters are known. Fortunately it can be safely accepted for steam cracking that

monomolecular reactions dominate for species with more than 5 carbon atoms (Ranzi et al.,

1983). This allows distinguishing between two networks: the monomolecular µ network and the

β network.The latter contains both uni- and bimolecular reactions. The kinetics for the former

can be described by analytical expressions based on the pseudo steady state assumption (PSSA)

for the radical reaction intermediates (Hillewaert et al., 1988).

The µ radical hypothesis does not hold for species with 5 or less carbon atoms, making it no

longer possible to use the analytical expressions based on the PSSA. Therefore it is necessary to

store their reactions in a separate sub network, called the β network. It is immediately clear that

the separation of radicals into µ, β and βµ radicals based on the number of carbon atoms is very

rough. Several exceptions to this rule of thumb exist, e.g. the benzyl radical, but according to the

previously defined rule they are not considered in the β network. Also several other radicals can

have both a β and µ character, such as radicals with no possibility of C-C scissions and no

possibility of isomerization followed by a C-C scission. Consider the 3-methyl-3-pentene-2-yl

radical. The radical can only decompose via a slow C-H scission, but this reaction path is not the

dominant disappearance route. Under steam cracking conditions, this radical addition reactions

can be much more important than scission reactions. A similar reasoning also holds for the 1-

phenyl-2-pentene-4-yl radical. Hence, some radicals with more than 5 carbon atoms cannot be

considered as pure µ radicals without introducing errors.


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Figure 1.1: Overview of the construction of the single event microkinetic model. Interaction of

the µ network with the β network

The previous results proved that the separation of radicals into µ, β and βµ radicals based on

the number of carbon atoms is too rough. Therefore, it is necessary to introduce another category

of radicals, the so called C6+ β and βµ radicals. For the latter the bimolecular reactions such as

addition reactions and hydrogen abstraction reactions are not negligible, and consequently these

reactions should be included in the β network. The β network further includes the reactions of the

smaller radicals. In Figure 1.1 an overview of the construction of the complete microkinetic

model is given. In the µ network, reaction schemes are generated for all molecules with 6 or

more carbon atoms. There are 3 primary reactions considered in the µ network: C-C scission

reactions of molecules, hydrogen abstractions by β and βµ radicals and C6+ β and βµ radicals,

and radical addition reactions by β and βµ radicals and C6+ β and βµ radicals. The concentrations

of the intermediate µ radicals are eliminated by assuming the PSSA for these radicals. The β

scission of the formed µ radicals is stopped when only olefins and radicals from the β network

remain.


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1.2.2 The β network

The β network considers all reactions from the three reaction families for species with 5 or

less carbon atoms. This results in a large number of radical intermediates and elementary

reactions. Therefore, a computer program is developed that generates the β network

automatically based on the binary relation matrix concept. In this concept, the cracking rules are

translated into matrix operations performed on the Boolean relation matrix, representing the

species structure (Hillewaert et al., 1988). The construction of the reaction network is shown in

Figure 1.2.

Figure 1.2: Generation of the β network

Starting from an initial pool of molecules, possibilities for scission reactions, hydrogen

abstraction reactions and addition reactions are identified. Cyclization reactions are considered as

intramolecular additions, whereas isomerization reactions are considered as intramolecular

hydrogen abstractions. For every forward reaction introduced in the network, the corresponding

reverse reaction is also incorporated. These reactions result in a number of formed radicals and

molecules. The new radicals are added to the radical pool and the molecules are added to the

molecule pool. In the next iteration the new species react with each other and with other species

of the radical and molecule pool and the network is constructed gradually. To limit the number of

reactions a carbon count stop criterion is applied (Broadbelt et al., 1994), i.e. species are only


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added when they have less than nm carbon atoms for a molecule, and nr carbon atoms for a

radical. Here, both nm and nr are set equal to 5. The resulting β network comprises more than

2000 reactions and over 100 species.

1.2.3 The µ network

The existence of radicals with a pure µ character is essential for the separation of the

reaction network into two parts: a β and a µ network. As stated earlier, for radicals with a µ

character the monomolecular β scission and isomerization reactions are much faster than the

bimolecular hydrogen abstraction and addition reactions. Clymans and Froment (1984) and

Hillewaert et al. (1988) concluded based on experimental results that this assumption surely

holds for heavy paraffinic and iso-paraffinic radicals. These authors observed no saturated

products with a chain length of more than 5 carbon atoms under typical steam cracking

conditions, except for non-converted feedstock molecules. For example during the cracking of n-

decane, neither n-nonane, n-octane, n-heptane nor n-hexane are found in the product spectrum.

Moreover, no 1-decene is experimentally observed. This product could be formed after addition

of a primary decyl radical to ethylene followed by a β scission of the resulting dodecyl radical.

The existence of radicals with a pure µ character enables the generation of reaction schemes

for these radicals, describing their disappearance via a set of monomolecular reaction steps.

Because they are only involved in monomolecular reactions, the resulting set of differential

equations for the µ radicals is linear in their concentrations. These concentrations can then be

easily eliminated of the set of model equations if the pseudo steady state is assumed for the

concentrations of the µ radicals. This hypothesis assumes that the net rate of formation of highly

reactive reaction intermediates in a reaction sequence equals zero (Bodenstein and Lutkemeyer,

1924). The unknown concentrations of the reactive reaction intermediates can then be found as

the solution of the set of linear model equations. In the next few paragraphs, both the generation

of the reaction schemes starting from different primary reactions as well as the elimination of the

concentrations of the intermediate µ radicals are illustrated by some examples. Also important

aspects such as the additivity of the reaction schemes and calculation of the pseudo rate

coefficients are briefly discussed.


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1.2.3.1 Reaction schemes from C-C scission reactions, hydrogen abstractions and addition

reactions

Three primary reactions are considered in the µ network: C-C scission reactions of

molecules, hydrogen abstraction reactions by β and βµ radicals and addition reactions to olefins

by β and βµ radicals. Based on these three primary reactions a reaction network is generated for

each molecule with 6 or more carbon atoms. These three primary reactions all lead ultimately to

the formation of a number of µ radicals which decompose via β scissions and isomerization

reactions to olefins and β and βµ radicals. The set of linear algebraic equations is solved via the

simple Gauss-Jordan elimination algorithm. The reaction scheme for the disappearance of a

component is in fact reduced to a simple format in which only the component and the products,

formed via the monomolecular reactions, are considered. An example of a reaction scheme

generated for n-nonane is shown in Figure 1.3, starting from the C-C scission reactions of this

molecule.

The first step is the cleavage of a C-C bond, resulting in two radicals. These radicals react

further in the propagation reactions. C-H scissions are not considered, since the reaction rate

coefficients for C-H scission reactions of paraffins are much smaller than the reaction rate

coefficients of C-C scission reactions of molecules.


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Figure 1.3: Reaction scheme for n-nonane starting from a C-C scission reaction


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The disappearance rate of n-nonane (M) by C-C scission is, according to the reaction scheme in

Figure 1.3,

M

4

1=i

iV CkMR

[1. 5]

The net formation rate of the 1-octylradical (1) from n-nonane by initiation and the formation

rate of the 3-octylradical (2) by isomerization from 1 can be written as:

111221

CkkCkCkR DIIM11V [1. 6]

22211

CkkCkR DII2V [1. 7]

Taking into account the pseudo steady state approximation, the net formation rates of the

radicals can be set equal to zero:

0RR 2V1V [1. 8]

The set of equations [1.6] – [1.7] can be solved for the concentrations of 1 and 2:

M

IIDIDI

1DIC

kkkkkk

kkkC

212211

22

1

[1. 9]

M

IIDIDI

I1C

kkkkkk

kkC

212211

1

2

[1. 10]

The concentrations of the other radicals can be derived according to a similar procedure. In

general, the following form is obtained:

Mi CFCi

[1. 11]

The factor Fi is a ratio of sums and products of reaction rate coefficients and is temperature

dependent. The 1-octylradical decomposes to an ethylene molecule and a 1-hexylradical (1’).

The formation rates for the descendants by β scission of the 1-octylradical are:


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M

IIDIDI

1DID

1V42V Ck.kkkkk

k.kkk=R=CR

212211

221

H [1. 12]

where kD1 F1 is defined as the pseudo rate coefficient (PRC) of formation of ethylene from n-

nonane. As shown in Figure 1.3, ethylene can also be formed along other reaction paths in the

reaction scheme. The total PRC for formation of ethylene starting from initiation of n-nonane is

thus a sum of terms. These terms originate from the formation rates of ethylene by cleavage of

radicals formed out of n-nonane or by cleavage of other intermediate radicals. The µ radicals

among the descendants, such as n-heptyl and n-hexylradicals, are treated in a similar way. For

each group of isomer µ radicals, the set of continuity equations has to be solved. The rates of

formation of the formed olefins and β radicals can then be written as:

Mj

pseudo

jV COkOR [1. 13]

M

pseudo

V CkR [1. 14]

in which M is the molecule that is initiated, while kpseudo

(Oj) and kpseudo

(Rl) are pseudo rate

coefficients for the formation of an olefin and a β or βµ radical. The scheme in Figure 1.6 can

formally be written as a single global reaction:

radol n

1=l4

1=i

i

pseudo

j

n

1=j4

1=i

i

j

pseudo

209

k

kO

k

OkHC n [1. 15]

Similar to the reaction scheme generated for n-nonane in Figure 1.3, other reaction schemes

can be generated starting from a different primary reaction, such as a hydrogen abstraction

reaction by a β radical or an addition reaction to an olefin. In Figure 1.4 an example is given of a

reaction scheme generated for 1-heptene starting from an addition reaction. The addition of β or

βµ radicals to a double bond almost always yields two different radicals, depending on the

double bonded carbon atom with whom the radical is connected. This implies that the nature of

the radical is of great importance. Next to the addition of hydrogen and methyl radicals, also the

addition of other β and βµ radicals is taken into account.


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Figure 1.4: Reaction scheme for 1-heptene starting from vinyl addition


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In the reaction scheme of Figure 1.4 the β scissions of the cyclic radicals that do not yield

two products are neglected. The cleavage of a C-C bond in the ring requires more energy than

that of an aliphatic C-C bond (Stein and Rabinovitch, 1975). The above hypothesis also implies

that the rate of the reversible reaction:

opening ring closure ring [1. 16]

is smaller than the rate of cleavage of a C-H bond in the ring. For the consecutive reactions

H olefin cyclic radical cyclic radical olefinic [1. 17]

the concept of the rate-determining step can be applied. The above reaction sequence can be

reduced to the simple reaction:

H olefin cyclic radical olefinic [1. 18]

in which the kinetics are determined by the slowest step in the sequence, i.e. the cyclization

reaction. When not a large number of naphthenes are present in the feedstock, the concentration

of the cyclic olefins is much lower than the concentration of the aliphatic olefins and the

concentrations of the cyclic olefins can be eliminated without losing accuracy. However, for a

feedstock containing a significant amount of naphthenes this is no longer true. Therefore, the

formed cyclic olefins are considered as products in the reaction schemes.

1.2.3.2 Additivity of reaction schemes

It is clear from the previous paragraphs that, for a mixture of heavy hydrocarbons, it is very

unlikely that one particular µ radical, e.g. the primary hexyl radical, is considered in only a single

reaction scheme. For example the primary hexyl radical can be formed via a hydrogen

abstraction reaction by a β radical from n-hexane, or via the β scission of a primary octyl radical.

Elimination of these intermediate µ radicals is then only possible when their concentrations are

known for the complete reaction network. This implies that, for almost every new feedstock, a

new reaction network would have to be generated, making the simulation program unattractive

for industrial practice. The question arises if it is not possible to separate the complete reaction


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scheme into smaller sub-schemes where the PSSA is applied for the µ radicals. Consider the

simplified reaction scheme of equation [1.19], where a µ radical is formed via three reactions:

[1. 19]

The continuity equation for the µ radical can be written as follows if the PSSA is assumed:

µVCVBVA CkRRR [1. 20]

Separating the scheme of equation [1.22] in three sub-schemes leads to:

[1. 21]

Applying the PSSA to each of the smaller reaction schemes leads to 3 continuity equations for

the µ radical:

A

µVA CkR

B

µVB CkR [1. 22]

C

µVC CkR

Because the concentration of the µ radical in the global reaction scheme is equal to the sum of

the concentrations of the µ radicals in the different subsystems, equation [1.22] yields:

C

µ

B

µ

A

µµ CCCC [1. 23]

kβ

kβ

A

C

B µ kβ O + β

C

B µ kβ O + β

A µ

µ

O + β

O + β


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Hence, the sum of the rates of formation in the sub-schemes equals the rate of formation of the

global reaction scheme. The previous principle can be extended to the reaction schemes

discussed in the previous sections. Therefore, despite of the reaction schemes being

interconnected via the intermediate µ radicals and olefins, the reaction network describing the

cracking of a hydrocarbon mixture still follows from the sum of the reaction schemes of the

individual components. If the expression for the rate of disappearance of the µ radicals would no

longer be linear in one of the concentrations of the µ radicals, then the additivity of the reaction

schemes would no longer hold (Vercauteren, 1991).

1.2.3.3 Calculation of the Pseudo Rate Coefficients

The pseudo rate coefficients kpseudo

for the formation of the products resulting from a

reaction scheme are a complex function of multiple elementary reaction rate coefficients. Hence,

they are just as temperature dependent as the PRC of a feedstock component. This implies that,

in principle, the PRCs have to be calculated for every temperature that could be observed in the

reactor. By a simple re-scaling operation the temperature dependence can be drastically reduced.

First a reference reaction for the considered primary reaction is chosen. For example for C-C

scission reactions, the formation of 2 methyl radicals from ethane is chosen as reference reaction.

The PRCs in the reaction scheme of disappearance of component M is then equal to the product

of the relative pseudo rate coefficient (RPRC) kpseu,rel

and a reference factor kref:

k )M( k )M( k ref

relpseu,pseudo [1. 24]

The largest temperature dependence is captured by the reference reaction rate coefficient,

whereas the RPRC is only slightly dependent on the temperature, as shown in Figure 1.5. Hence,

it is sufficient to know the RPRC’s for a small number of temperatures. During a reactor

simulation, the RPRC is only calculated if the temperature of the previous calculation of the

RPRCs differs more than 10 K from the temperature at the current axial position. The rate of

formation of the products and the rate of disappearance of the reactants is then calculated by

multiplying the RPRC with the corresponding reference factor. Vercauteren (1991) showed that

the differences for the reaction rates are maximally 1%.


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Figure 1.5: Temperature dependence of the relative pseudo rate coefficient (RPRC) for

disappearance of n-hexane via a C-C scission reaction [■] and hydrogen abstractions [▲].

1.3 Species considered in the Reaction Network

1.3.1 Molecules

The main part of the molecular species considered in the reaction network are molecules

which are traditionally present in cracking feedstocks. These are, for example, n-paraffinic and

iso-paraffinic compounds with less than 34 carbon atoms. Nonetheless, even for single event

microkinetic models, it is not only convenient but also necessary to adopt several simplifications

and lumping procedures in order to avoid an excessive number of chemical species and reactions

(Ranzi et al., 2001).

Table 1.1: List of molecules and lumps considered in the reaction network

0

2

4

6

8

10

12

14

700 750 800 850 900 950 1000 1050 1100

Temperature (K)

RP

RC

fo

r d

iss

ap

ea

ran

ce


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Classes of components Number of

(pseudo-)components Example structure Carbon range

Molecules 727 C0 – C26

hydrogen 1 H2 C0

n-paraffins 33 C1 – C33

iso-paraffins(1)

84

C4 – C33

α-Olefins 31 C2 – C32

Other straight chain olefins 29 C4 – C32

Branched olefins 32

C4 – C32

Straight chain di-olefins 32 C2 – C31

Branched di-olefins 28

C5 – C31

Monocyclic saturates 90

C5 – C33

Endo-mono-cyclic olefins 52

C5 – C32

Exo-mono-cyclic olefins 25

C8 – C32

Mono-cyclic di-olefins 53

C5 – C31

Di-cyclic saturates 24

C10 – C33

Di-cyclic olefins 23

C10 – C32

Di-cyclic di-olefins 22

C10 – C31

Mono-aromatics 51

C6 – C33

Aromatic olefins 25

C8 – C32

Naphtheno-aromatics 24

C10 – C33

Naphtheno-aromatic olefins 23

C10 – C32


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Di-aromatics 25

C10 – C33

Tri-aromatics 20

C14 – C33

β(µ) radicals(2)

43 - C0 – C7

Total 770 C0 – C33 (1)

After lumping of isomers. Some isomers exist both in a lump or as a pure component.

(2) radicals are not explicitly included in the final model by application of the PSSA.

In principle, complete single event modeling of virgin naphthas or gas oils would require a

detailed knowledge of the composition of the feedstock. However, this would be impossible

because, in general, the real detailed composition of these fractions is not experimentally

available and, moreover, the dimensions of the kinetic scheme and its computing times would be

unacceptable. That is one of the main reasons for lumping to be introduced in the reaction

scheme. In Table 1.1 an overview of the components considered in the reaction network is

given. Several components in Table 1.1 are lumped components.

For example all iso-paraffinic compounds with more than 11 carbon atoms are lumped into

one single pseudo-component per carbon number. Consider a mixture of m iso-paraffinic

compounds Ik with the same molecular weight. When these components are lumped into one

single pseudo-component S, the pseudo rate coefficient kpseudo

for disappearance of the lumped

component S is calculated as a weighed sum of the pseudo rate coefficients of the individual

components:

[1. 25]

with wk the weighing factor for component Ik. Only for the lumped component a continuity

equation needs to be considered. Note that the differences in the pseudo rate coefficients of the

different components should remain as small as possible because only then it is allowed to

replace the different components by a single lumped component (Wei and Kuo, 1969; Kuo and

)I(kw)S(kk

pseudom

1kk

pseudo


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Wei, 1969). That is why one lumped component is defined per carbon number and per class of

components. Each lumped component consists then solely of isomers.

Table 1.2: Weighing factors for the iso-paraffinic lumped components

Isomer Weighing Factor

2-methyl 0.207

3-methyl 0.231

4-methyl 0.128

5-methyl 0.157

3-ethyl 0.191

2,3-dimethyl 0.060

2,4-dimethyl 0.026

others 0.000

In principle, the weighing factors wk should be determined from the detailed analytical

composition of the feedstock (Ranzi et al., 2001). This implies that, for each feedstock, new

lumped components need to be defined. Vercauteren (1991) used fixed weighing factors for the

iso-paraffinic compounds. Based on the analysis of a large amount of naphtha and kerosene

fractions he found that the distribution of the different isomers is more or less independent of the

feedstock. This conclusion was confirmed by Ranzi et al. (2001). Of course, it is true that the

lumping procedure restricts the range of validity of the model. For instance, it is no longer

possible to use the existing model to analyze the decomposition of a specific pure component

that has been lumped. However, if there is interest in the behavior of a specific isomer, on

specific demand of a user it is possible to enlarge the kinetic scheme explicitly to include more

detail. This lumping flexibility is one of the relevant advantages of mechanistic kinetic schemes.

In Table 1.2 the values for the weighing factors for iso-paraffinic compounds are given.

Other important compounds are naphthenic compounds. In some cases, e.g. for some

“exotic” naphthas, their mass fractions can be over 50% of the total feedstock mixture. A

distinction is made between naphthenic compounds with a five or six ring and with multiple

rings. Again components with more than 10 carbon atoms are lumped into one single component

per carbon number. Note that still a distinction is made between the type of naphthenic molecule


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(5 or 6 ring or multiple rings; branched and unbranched side chain) as shown in Table 1.1. For

the lumping of the naphthenic compounds, equal weighing factors are used for each constituent.

It is also necessary to lump the intermediate components properly. Ranzi et al. (2001)

distinguished between linear and branched olefins for each carbon number. In the present work

the description for the intermediate olefins is a lot more detailed. A distinction is made between

branched and unbrached olefins, between di and mono olefins and between cyclic, aromatic and

paraffinic olefins. The choice of which lumped component should be selected depends on which

isomers are mostly formed in the reaction schemes. For molecules with a long chain, most of the

C-C scissions and hydrogen abstraction reactions take place in the long chain. This justifies the

choice for the olefins with double bonds on the other side of the chain as lumped components.

The amount of unbranched mono olefins with the double bond not in α position is small.

Therefore, only a distinction between olefins with the double bond 1- and 2-olefins is made. The

2-olefins represent all unbranched olefins for which the double bond is not situated in α position.

Similarly, all unbranched di-olefins are represented by lumped components for which the double

bonds are located at both ends of the chain. These assumptions are introduced because, compared

to the 2-olefins and α,ω di-olefins, the concentrations of the other olefins belonging to these

categories of molecules are almost negligible.

The iso-olefinic compounds with more than 6 carbon atoms are lumped in one single

component per carbon number. Equal weighing factors are used for iso-olefinic compounds

because the exact composition of these branched olefins in the reaction mixture cannot be easily

determined experimentally. Indeed, each branched olefin is formed in the reaction schemes of

several iso-paraffinic compounds, which differ both in size and character. The choice of the

olefins with the double bond in α position of the methyl branches can be explained by the

preferential abstraction of tertiary hydrogen atoms on 3-, 4- and 5-methyl paraffins. Note that in

Table 1.1 no olefins with 3 double bonds are present. This is because the concentrations of the

molecules are eliminated by assuming the pseudo steady state for their concentrations and

assuming that electrocyclizations are the only reaction for the disappearance of these molecules.

Electrocyclizations are very fast reactions (Shiess and Dinkel, 1981) and are important routes

towards the formation of aromatic compounds (Jutz, 1978; Kopinke et al., 1987).

Also for the aromatic compounds, several lump components are implemented. The mono, di,

tri and poly aromatics with a branched side chain are lumped per carbon number. The


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introduction of more di-, tri-, poly- and naphtheno-aromatic compounds is on the one hand

necessary to be able to simulate VGO fractions. On the other hand, these molecules form also an

important part of the pyrolysis fuel oil (PFO) fraction. The PFO fraction is the heavy fraction

(boiling point higher than 473 K) formed during steam cracking of liquid feedstocks. The most

important components of the PFO fraction are: naphthalene, methyl naphthalene, fluorene,

acenaphthalene, anthracene, phenantrene, methyl anthracene, methyl phenantrene, pyrene and

chrysene (Lauer, 1988; Plehiers and Froment, 1991; Nomura et al., 1995; Bolado, 2003).

1.3.2 Radicals

All possible radicals with five or less carbon atoms are considered in the reaction network. It

is important that, in contrast to Dente et al. (1986), no lumping of radicals is allowed. This model

assumption causes strong distortions of the product distribution because some chemical

transformations are considered that are chemically impossible. Introducing the µ radical concept

already drastically reduces the number of radicals for which a continuity equation should be

solved. An overview of the considered radicals is given in Table 1.3.

Table 1.3: List of radicals considered in the single event microkinetic model for steam cracking

hydrogen radical methyl radical

vinyl radical ethyl radical

allyl radical prop-1-en-1-yl radical

prop-1-en-2-yl radical 1-propy radical

2-propyl radical 1-butyl radical

2-butyl radical tert-butyl radical

isobutyl radical 2-methylallyl radical

pent-3-en-1-yl radical 1-penten-3-yl radical

but-3-en-1-yl radical 1,4-pentadien-3-yl radical

neopentyl radical 3-methyl-1-buten-3-yl radical

3-butenyl,2 methylene radical 2-methylbut-2-yl radical

butyl,2-methylene- radical 1-pentyl radical

2-pentyl radical 3-pentyl radical


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3-cyclopentenyl radical 1-buten-3-yl radical

cyclopentadienyl radical 3-butenyl, 2-methyl radical

cyclopentyl radical 2-penten-4-yl radical

cyclohexyl radical 2-cyclopentenyl radical

benzyl radical 1-phenyleth-1-yl radical

2-phenyleth-1-yl radical 1-naphtyl methyl radical

1-phenantryl methyl radical 1-anthracyl methyl radical

1-peryl methyl radical

As can be seen in Table 1.3, several aromatic radicals are considered. The following aromatic

radicals are explicitly accounted for in the reaction network: the benzyl radical, the 2-phenyleth-

1-yl radical, the 1-phenyleth-1-yl radical and the 1-naphtyl methyl radical. If the aromatic

fraction is important, then reactions of these radicals will be partly responsible for components of

the pyrolysis fuel oil (PFO) fraction. This is important because components of the PFO fraction

are believed to be important precursors for coke formation, both in the reactor and in the TLE.

1.4 Calculation of the reaction rate coefficients

The above mentioned reaction network contains only reactions that can be considered

elementary. According to IUPAC (McNaught and Wilkinson, 1997), an elementary reaction is

defined as “a reaction for which no reaction intermediates have been detected or need to be

postulated in order to describe the chemical reaction on a molecule scale. An elementary reaction

is assumed to occur in a single step and to pass through a single transition state.” Hence, in the

rate equation, the order of the reaction coincides with the molecularity of the considered reaction.

The reaction rate coefficient is a temperature-dependent parameter described by the Arrhenius

expression:

[1. 26]

TR

EexpA)T(k a


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with A the pre-exponential factor, Ea the activation energy, R the molar gas constant, and T the

temperature. In the present text, a group contribution method developed by Saeys is used to

calculate the activation energies and the pre-exponential factors (Saeys, 2003; Saeys et al., 2004;

Saeys et al., 2006). Saeys’ method belongs to a category which focuses on the activation energy,

that is, the difference between the standard enthalpy of formation of the transition state and the

standard enthalpy of formation of the reactants, but the results are cast in a format similar to the

structural contribution method of Willems and Froment (1988) [a,b].

The use of structural contributions to calculate the activation energy and the pre-exponential

factor of radical reactions results from the strong analogy that exists between the different

reactions, considering their mechanism (Rice, 1943). Moens (1982) and later on Willems and

Froment (1988a, 1988b) worked out the following procedure: For each reaction family, a

reference reaction is defined. The pre-exponential factor and the activation energy of the

reference reaction serve as a basis for the calculations. For any reaction in the considered family,

the pre-exponential factor and the activation energy are obtained by adding contributions to the

reference values, which account for the structural differences between the mechanism of the

considered reaction and the reference reaction. The activation energy can thus be written as the

activation energy of a well-chosen reference or standard reaction plus perturbation terms which

depend on the primary, secondary and tertiary contributions,

[1. 27]

The perturbation terms take into account the structural difference between the reference reaction

and the studied reaction. This perturbation term is composed of standard activation group

additivity values, Xreaction [Ci], i.e. relative to the activation energy of the reference reaction.

1.4.1 Radical additions and reverse scission

Saeys et al. (2004) showed that to calculate the activation energy for a general addition/

scission reaction, see Figure 1.6, a distinction should be made between three important

contributions: a contribution involving the attacked carbon atom, a contribution involving the

formed radical and a contribution involving the attacking radical.

3reaction2reaction1reactionfRe,aa

CXCXCXEE


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Figure 1.6: General format of an addition/ scission reaction

Hence, the activation energy of this reaction can be calculated with the following equation:

[1. 28]

The pre-exponential factor is calculated by a similar formula:

)nlog(CfCfCf)Alog()Alog(e3add,A2add,A1add,Aaddref,a

[1. 29]

In equation [1.29] Aa,ref add corresponds with the single event pre-exponential factor of the

reference reaction. In the reaction network used in COILSIM1D, the number of single events is

set equal to the redundancy of a reaction. The decomposition of 1-propyl is taken as the reference

reaction for the scission reactions and the methyl addition to ethylene. The reverse reaction is

taken as the reference reaction for the radical addition reactions.

For the hydrogen addition to alkenes and alkynes and the reverse scission reactions,

separate contributions were implemented. Saeys (2003) showed that, although the hydrogen and

carbon-centered radical addition reactions and the reverse β scission reactions are governed by

similar factors, the use of separate contributions is required. The activation energies for reactions

involving hydrogen radicals are not simply shifted by 30 kJ mol-1

from the activation energies for

the reactions involving carbon-centered radicals. The larger separation of the fragments in the

transition state of reactions involving hydrogen radicals makes certain contributions more

important and others less important. This implies also that a new reference should be chosen.

Saeys (2003) proposed to use the addition of a hydrogen radical to ethylene and the reverse β

scission as reference reactions.

3add2add1addaddref,aa

CXCXCXEE


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1.4.2 Hydrogen abstraction reactions

Saeys et al. (2006) consider two important contributions in their group contribution method

for hydrogen abstraction reactions: one being a contribution for the abstracting radical, the other

a contribution for the formed radical.

Figure 1.7: General format of a hydrogen abstraction reaction

This implies that the activation energy for a general hydrogen abstraction, see Figure 1.5, is

calculated with the following formula:

[1. 30]

Similarly, for the pre-exponential factor the following formula is used:

[1. 31]

In equation [1.31] Aa,ref ab corresponds with the single event pre-exponential factor of the

reference reaction.

Intramolecular hydrogen abstraction reactions are isomerization reactions. Both 1,4- and

1,5-isomerizations are considered in the reaction network. The contribution method for

isomerization reactions is completely analogous to the one discussed for the external hydrogen

abstraction reactions. The values for the pre-exponential factor and the activation energy are

calculated by adding the contributions for the attacking and the formed radical to the reference

value.

2ab1ababref,aa

CXCXEE

)nlog(CfCf)Alog()Alog(e2ab,A1ab,Aabref,a


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1.4.3 C-C and C-H scission of molecules and recombination of radicals

For C-C and C-H scission of molecules and the reverse recombination reactions the method of

Willems and Froment (1988a, 1998b) is used. In this case, the C-C scission reaction of butane

yielding two ethyl radicals is selected as reference reaction.

Figure 1.8: General format of a scission/radical recombination reaction

The activation energy of a general scission reaction in Figure 1.8 is calculated using:

[1. 32]

The pre-exponential factor for the scission reaction is given by:

[1. 33]

The activation energy is strongly related to the standard reaction enthalpy, and hence, the

structural contributions can be determined from differences in the latter. To determine the

standard reaction enthalpy the group contribution method of Benson (1976) is used.

The calculation of the activation energy of the recombination reactions requires no

parameters. The pre-exponential factor of the recombination reactions is calculated from

thermodynamic consistency (Willems and Froment, 1988a, 1998b):

T'RlnR1nR

S

A

Aln

scis

rec

[1. 34]

1.5 References

Bodenstein M., Lutkemeyer H. Die Photochemische Bildung von Bromwasserstoff und die

Bildungsgeschwindigkeit der Brommolekel aus den Atomen, Z. Phys. Chem., 114, 208, 1924.

2scis1scisscisref,aa

CXCXEE

)nlog(CfCf)Alog()Alog(e2scisA,1scisA,scisref,a


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Broadbelt L.J., Stark S.M., Klein M.T. Computer-generated Pyrolysis Modeling – on-the-fly

Generation of Species, Reactions, and Rates, Ind. Eng. Chem. Res., 33, 790-799, 1994.

Clymans P.J., Froment G.F. Computer Generation of Rate Equations in the Thermal Cracking of

Normal and Branched Paraffins, Comp. Chem. Eng., 8, 137-142, 1984.

Dente M., Ranzi E., Goossens A.G. Detailed Prediction of Olefin Yields from Hydrocarbon

Pyrolysis trough a Fundamental Simulation-Model (SPYRO), Comp. Chem. Eng., 3, 61-75,

1979.

Dente M., Ranzi E., Barendregt S., Cronin P. Steam Cracking of Heavy Liquid Feedstocks.

Cracking Yields Rigorously Predicted, AIChE Spring National Meeting, New Orleans, USA,

1986.

Hillewaert L.P, Dierickx J.L., Froment GF. Computer-Generation of Reaction Schemes and

Rate-Equations for Thermal-Cracking, AIChE Journal, 34, 17, 1988.

Jutz C., Aromatic and Heteroaromatic Compounds by Electrocyclic Ring Closure with

Elimination, Top. Curr. Chem., 73, 125-130, 1978.

Kopinke F.D., Bach G., Ondruschka B., Zimmerman G. Tendencies of Aromatization in Steam

Cracking of Hydrocarbons, Ind. Eng. Chem. Res., 26, 2393-2397, 1987.

Kopinke F.D., Zimmerman G., Nowak S. On the Mechanism of Coke Formation in Steam

Cracking – Conclusions Obtained from Tracer Experiments, Carbon, 26, 117-124, 1988.

Kossiakoff A., Rice F.O. Thermal Cracking of Hydrocarbons. Resonance Stabilization and

Isomerization of Free Radicals, J. Am. Chem. Soc., 65, 590, 1943.

Kuo J.C.W., Wei J. A Lumping Analysis in Monomolecular Reaction Systems – Analysis of

Approximately Lumpable System, Ind. Eng. Chem. Fund., 8, 124, 1969.

Laidler K.J. Chemical Kinetics, 3rd ed., Harper & Row, New York, 311, 1987.

McNaught A.D., Wilkinson A. Compendium of Chemical Terminology. The Gold Book, 2nd

Edition, Blackwell Science, 1997.

Moens J. Een Rigoureus Kinetisch Model voor de Simulation van de Thermische Kraking van

Lichte Koolwaterstoffen en hun Mengsels, PhD dissertation, UGent, 1982.

Ranzi E., Dente M., Plerucci S., Biardi G. Initial Product Distribution from Pyrolysis of Normal

and Branched Paraffins, Ind. & Eng. Chem. Fund., 22, 132-139, 1983.

Ranzi E., Faravelli T., Gaffuri P., Sogaro A. Low Temperature Combustion – Automatic-

Generation of Oxidation Reactions and Lumping procedures, Combustion & Flame., 102,

179-192, 1995.


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Ranzi E., Dente M., Goldaniga A., Bozzano G., Faravelli T. Lumping procedures in Detailed

Kinetic Modeling of gasification, pyrolysis, partial oxidation and combustion of hydrocarbon

mixtures, Progress in Energy and Combustion Science, 27, 99-139, 2001.

Rice F.O. The Thermal Decomposition of Organic Compounds from the Standpoint of Free

Radicals, J. Am. Chem. Soc., 53, 1959, 1931.

Rice F.O., Herzfeld K.F. The Thermal Decomposition of Organic Compounds from the

Standpoint of Free Radica1s. VI. The Mechanism of Some Chain Reactions, J. Am. Chem.

Soc., 56, 284, 1934.

Saeys M. Ab initio Modelling as a Tool for the Sustainable Development of Chemical processes,

PhD dissertation, UGent, 2003.

Saeys M., Reyniers M.F., Marin G.B., Van Speybroeck V., Waroquier M. Ab initio group

contribution method for activation energies for β scissions and radical additions. AIChE

Journal, 50, 426-444, 2004.

Saeys M., Reyniers M.F., Van Speybroeck V., Waroquier M., Marin G.B. Ab initio group

contribution method for activation energies of hydrogen abstraction reactions

ChemPhysChem, 7, 188-199, 2006.

Shiess P., Dinkel R. Uber den Anteil sigmatroper 1,5-Wanderung von Kohlenwasserstoffgruppen

bei der Thermolytischen Skelettisomerisierung 5,5,-disubstituierter 1,3 cyclohexadiene, Helv.

Chim. Acta, 64, 801-812, 1981.

Stein S.E., Rabinovitch B.S. Ring Opening and Isomerization of a Series of Chemically

Activated Cycloalkyl radicals, J. Phys. Chem., 79, 191-198, 1975.

Vercauteren C. Rigoureuze Kinetische Schema’s voor de Thermische Kraking van

Koolwaterstoffen, PhD dissertation, UGent, 1991.

Wei J., Kuo J.C.W. A Lumping Analysis in Monomolecular Reaction Systems – Analysis of the

Exactly Lumpable System, Ind. Eng. Chem. Fund., 8, 114, 1969.

Willems P.A., Froment G.F. Kinetic modelling of the Thermal Cracking of Hydrocarbons. 1.

Calculation of frequency factors, Ind. Eng. Chem. Res., 27, 1959, 1988 [a].

Willems P.A., Froment, G.F. Kinetic modelling of the Thermal Cracking of Hydrocarbons. 2.

Calculation of Activation Energies, Ind. Eng. Chem. Res., 27, 1966, 1988 [b].

Chapter 2: Reactor Modeling

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Chapter 2:

COILSIM1D

2.1 Introduction

COILSIM1D consist of 2 parts; on the one hand, a solver that solves the reactor model equations,

and on the other hand, the reaction network and the calculation of the physical properties of the

considered species. The general construction of the single event microkinetic simulation model

developed for steam cracking of hydrocarbons is shown in Figure 2.1. This model accounts for

both the chemical reactions and the physical transport phenomena.

Figure 2.1: Illustration of the general construction of a single event microkinetic model for

steam cracking of hydrocarbons

In the next paragraphs the structure of the simulation model, the solver and the calculation of the

physical properties are discussed in more detail.


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2.2 1-Dimensional Reactor Model Equations

Steam cracking is a non-isothermal, non-adiabatic and non-isobaric process. Hence, the 1-

dimensional model equations consist of the transport equations for mass, momentum and energy.

In the next paragraphs the basic equations of the reactor model are presented.

2.2.1 Continuity Equations

The steady state continuity equation for a component j in the process gas mixture over an

infinitesimal volume element with cross sectional surface area Ω, circumference ω and length dz

is:

rn

1k

kV,kj

jr

dz

dF [2. 1]

with Fj : molar flow rate of component j [kmol·s-1]

z : axial position [m]

rV,k : reaction rate of reaction k [kmol·m-3·s-1]

υkj : stoichiometric coefficient of component j [-]

Ω : cross sectional surface area [m2]

nr : number of reactions [-]

2.2.2 Energy equation

2.2.2.1 Basic Equation

The energy equation expresses that heat coming into a volume element with cross section Ω and

length dz equals the amount of heat flowing out of the same volume. Hence the energy equation

is given by:

j k

0

kkV,pjj HRq dz

dTc F f [2. 2]

with


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q : heat flux to the process gas [kJ·m-2·s-1]

T : temperature [K]

cpj : heat capacity of component j at temperature T [kJ·kmol-1·K-1

]

ΔfHk : standard enthalpy of species k [kJ·kmol-1

]

Rv,k : net production rate for species k [kmol·m-3·s-1]

2.2.2.2 Calculation of the convection coefficient hc

The convection coefficient for smooth tubes can be obtained from the Dittus-Boelter correlation:

0.40.8 Pr Re0.023 = Nu [2. 3]

The Reynolds, Nusselt and the Prandtl number are defined as follows:

tdvRe [2. 4]

tc dh

Nu

[2. 5]

pc Pr [2. 6]

The properties used in the above expressions are:

hc : convection coefficient [kJ·m-2·K-1·s-1]

dt : internal diameter of the tube [m]

v : velocity [m·s-1]

ρ : density [kg·m-3]

λ : thermal conductivity of the process gas [kJ·m-1·K-1·s-1]

μ : viscosity of the process gas [kg·m-1·s-1]

cp : heat capacity [kJ·kmol-1·K-1

]

For finned tubes, a distinction is made between spirally finned tubes, for which the fins make a

helix along the wall of the tube, and longitudinal fins, for which straight fins are placed on the


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inner side of the tube wall, oriented in parallel to the longitudinal axis of the tubes. The Reynolds

number Re for finned tubes is also calculated according to equation [2.4], but the internal tube

diameter is replaced by the equivalent diameter deq:

4deq

[2. 7]

where Ω is the cross sectional area, and η is the wetted perimeter of the tube. The convection

coefficient for finned tubes is calculated using the following equations (Reid et al., 1979):

- Spirally finned tubes:

0.5

w

a2

eq

a1

eq

0.40.645

T

T

d

B

d

P Pr Re242.0Nu

[2. 8]

- Longitudinal finned tubes:

i

a3

eq

0.40.326

e

d

d

P Pr Re11.4Nu [2. 9]

with

a1 : -2.95 -0.23

eRe [-]

a2 : 0.0045 0.31

eRe [-]

a3 : -1.4 10-6

1.07

eRe [-]

P : pitch of the fin helix [m]

B : inter-fin distance [m]

di : internal diameter of the finless tube [m]

The pitch P of a helix is the height over which this helix makes a full turn around its axis. B can

be calculated as the length of an arc connecting two consecutive fin center points. These

equations are valid for turbulent flows, i.e. Re higher than 4000.


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2.2.2.3 Calculation of the conduction coefficient λw

The conduction coefficient of the wall depends on the wall material. The materials are

considered to be grey. For stainless steel, the following equation is used (Reid et al., 1979):

T 10 7.216 10 014.2 -6-3

w [2. 10]

For aluminum, the conduction coefficient is calculated from (Reid et al., 1979):

3-122-9-6

wT 10 2.699 T 10 15.778 T 10 33.92 02967.0 [2. 11]

For silicon carbide, the conduction coefficient is calculated from (Reid et al., 1979):

2-9-6

wT 10 7.119 T 10 12.11 00717.0 [2. 12]

Coilsim1D allows the user to add its own materials. The equation used for the conduction

coefficient of new materials has the following form:

[2. 13]

where ka, kb, kc and kd are coefficients that can be supplied by the user.

2.2.2.4 Calculation of the expansion coefficient α

The expansion coefficient is calculated using the following expression:

[2. 14]

where αa, αb and αc are coefficients that depend on the material type.


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2.2.3 Momentum equation

2.2.3.1 Basic Equation

The momentum equation accounting for friction and changes in momentum is given by:

dz

dv v v

r d

f 2

dz

dp 2

bt

t

[2. 15]

with

pt : total pressure [Pa]

α : conversion factor [-]

f : Fanning friction factor [-]

rb : radius of the bend [m]

The momentum equation can be modified to yield a more convenient pressure drop equation by

using the following equation for the process gas velocity using the ideal gas law:

t

2

t

t

p M

T R G

d

FM4v

[2. 16]

with

M : average molecular mass [kg·kmol-1

]

Ft : total molar flow rate [kmol·s-1]

G : mass flux [kg m-2·s-1

]

Applying the chain rule to equation [2.15] makes it possible to rewrite the derivative from v to z

as follows:

dz

dp

p M

T R G

dz

dT

M

1

dz

M

1d

Tp

R G

dz

dvt

2

tt

[2. 17]


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Substitution of equation [2.17] in equation [2.16] and rearranging results into:

f

dz

dT

T

1

M

1

M

1

dz

d

dz

dp

T R G

p

pM

1tt

t

[2. 18]

with

G

dz

dF

G

F

dz

d

M

1

dz

d

n

1j

jn

1jj

[2. 19]

2.2.3.2 Calculation of the friction factor f

Several correlations are available for the calculation of the Fanning friction factor. For rough

straight tubes the friction factor f is obtained from the Colebrook equation (1939):

fRe

256.1

d 7.3log 4

f

1

t

[2. 20]

For smooth straight tubes this equation can be rewritten as follows (Reid et al., 1979):

fRe

256.1log 4

f

1 [2. 21]

Another possible equation for the calculation of the friction factor in smooth tubes is the Blasius

equation (Reid et al., 1979):

25.0Re 0791.0f

[2. 22]:

For the tube bends, the friction factor is calculated as follows (Nekrasov, 1969):

bt

2.0

r d

Re 092.0f

[2. 23]


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With rb (the radius of the bend) and χ (the Nekrasov factor) given by:

b

t

r

d19.0051.017.0

[2. 24]

with κ the angle of the tube bend.

Again, if the tubes are finned, a distinction is made between different types of finned tubes (Reid

et al., 1979):

- Spirally finned tube (Lummus correlation)

cr

0.089

efRe 0.015=f [2. 25]

- Straight finned tube (Watkinson correlation)

cr

0.17

eq

0.29-

ef

d

BRe 0.131=f

[2. 26]

- Spirally finned tube (Watkinson correlation)

cr

-0.24

eq

0.15-

ef

d

PRe 0.0546=f

[2. 27]

The factor fcr is the ratio of the wetted perimeter and the perimeter of the circle drawn to connect

the valleys of consecutive fins. The influence of non-uniformity of the process gas over a cross

section is accounted for by multiplying the friction factor f with:

5.0

w

[2. 28]

where μw is the process gas viscosity calculated at the internal wall temperature.


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2.3 Solving the 1-Dimensional Reactor Model Equations

2.3.1 Integration of balances

The reactor model equations to be solved are given by equations [2.1], [2.2] and [2.15]. The last

two equations only have to be considered when, respectively, the temperature and/or pressure

profile are not imposed. Based on the reactions, rate equations and rate coefficients, the

production rate of each component j by the reaction k, can be expressed as a function of the

concentration of the involved species. The resulting set of continuity equations forms a system of

stiff non-linear first order differential equations. The stiffness is caused by the large difference

(several orders of magnitude) of the eigenvalues related to the molecular species on the one

hand, and the radical species on the other. To overcome the stiffness problem, the numerical

procedure presented by Dente et al. (1979) was applied in the past. In this procedure, the net

production rate of each component is split in a cumulative rate of formation term and a similar

rate of disappearance term. Next, the rate of disappearance is assumed to be quasi-proportional to

the concentration (actually the mass fraction) of the component, leading to the introduction of a

pseudo rate coefficient. The resulting non-homogeneous first order differential equation is then

integrated over a reactor length increment, ∆z, small enough to consider the cumulative rate of

formation and the pseudo rate coefficient to depend on z only. Based on the different magnitude

and behavior of these variables for molecular and radical species, the resulting integral equations

are then further evaluated. The increment ∆z is chosen in such a way that, based on a number of

criteria, the mean values for the cumulative rate of formation and the pseudo rate coefficient can

be used for the molecular species, while a number of terms in the equation approach unity for the

radical species, allowing an analytical integration. Because values of the cumulative rate of

formation and the pseudo rate coefficient at the end of each interval ∆z appear in the resulting

algebraic equations, iteration for each interval is finally required. The calculations proceed until

convergence is reached. More details, as well as the convergence criteria, can be found in

Wauters (2002). Finally, it should be remarked that the method presented by Dente et al. (1979)

for the radical species is a numerical equivalent of the well-known pseudo steady state (also

called the continuously varying steady-state) assumption, i.e. assuming steady state for certain

species in each increment of the integration, leading to a set of algebraic equations to be solved


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simultaneously with the differential equations for the remaining species. De Saegher (1994) has

studied the influence of varioussimplifying steady state approaches on the reactor calculation

results, and concluded that the pseudo steady state assumption actually doesn't hold for allyl-

stabilized radicals. This can have a significant influence on, for example, the accuracy of the

predicted butadiene yield (De Saegher, 1994). Today computational capabilities actually allow

for solving all continuity equations without any steady state assumption to avoid such

inaccuracies. Therefore a new solver, DASSL (Li and Petzold, 1999) is implemented in

COILSIM1D. DASSL uses backward differentiation formula (BDF) methods to solve a system

of Differential Algebraic Equations (DAE) or Ordinary Differential Equations (ODE). The

methods are variable step-size, variable order. The system of equations in DASSL is written in

an implicit ODE form like:

0)'y,y,t(F [2. 29]

where y' denotes the time derivatives of y. The BDF methods used in DASSL require the solution

of a large system of non linear equations on each time step. Here, αn and βn are scalars which

depend on the method and step size. In DASSL, this system is solved by a modified Newton

iteration:

)y,y,t(Fy

F

'y

Fyy

nnnn

1

nn1n

[2. 30]

The set of linear equations [2.29] is solved via a dense or banded solver in DASSL. The iteration

matrix

y

F

'y

FA

n

[2. 31]

is computed and factored, and is then used for as many time steps as possible.

In the new version of COILSIM1D the continuity, energy and momentum equations are solved

simultaneously. Based on the process gas temperature and the (internal tube wall or coke)

interface temperature, the coke formation rate is calculated in a separate step. The effect of coke


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formation on the continuity, energy and pressure equations is neglected because the actual

amount of coke precursors being consumed in the coke formation process is very small (± 0.01

wt%). In case of a run-length simulation, the local cumulating thickness of the deposited coke

layer influences the energy and pressure equations through an additional resistance to heat

transfer over the coke layer, and an increasing pressure drop as a result of the decreasing internal

tube diameter. A coke layer thickness profile can be imposed as an initial boundary condition.

2.3.2 Calculation of the heat flux based on the wall temperature

The first term of the right hand side of the energy equation [2.2] corresponds to the heat flux over

the reactor wall. The second term of the right hand side corresponds to the thermal power

accompanying the endothermic steam cracking process. If the external wall temperature Tw,ext

profile is given, the internal heat flux q should first be calculated. An energy balance over a cross

section of the tube in Figure 2.2 gives:

dr

dTrLddLq twext 22 [2. 32]

Integration of equation [2.30] leads to the internal wall temperature Tw,int:

t

tw

w

twext

extwwd

ddddqTT

2ln

2

2,int,

[2. 33]

with λw the conduction coefficient of the wall.


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Figure 2.2: Energy balance over a cross section of a tube

Also for the temperature at the process gas/coke interface, a similar equation to [2.33] can be

obtained:

coket

t

coke

t

wcdd

ddqTT

2ln

2

int

int,int,

[2. 34]

with λcoke the conduction coefficient of the coke layer. All temperature gradients are eliminated

within the tube, and all resistance to heat transfer is located in a thin film near the wall. Hence,

the temperature of the process gas is given by:

h

qTT

int,c [2. 35]

Tc,int


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where h is the convection coefficient of the process gas. An energy balance over the cross section

of the tube gives:

coketwtextt ddqddqdq 22int [2. 36]

Solving equation [2.35] for the external heat flux qext and [2.33] for the internal heat flux q gives,

after substitution in equation [2.34], the following expression for the internal heat flux q:

coket

t

coke

coket

t

wt

w

coket

extw

dd

ddd

d

dddd

h

TTq

2ln

2

22ln

2

21

,

[2. 37]

which can be substituted in equation [2.2].

2.4 COILSIM1D for industrial furnaces

To perform a simulation of an industrial furnace, the heat flux from the furnace to the radiant

tubes is required. The heat flux profile acts as a set of boundary conditions for the simulation.

However, in industrial cracking units, there is no detailed information available about the heat

flux profile to the reactor coil. Also, the pressure at the reactor outlet of industrial reactors is

traditionally set as low as possible, depending on the separation train following the reactor. The

coil inlet pressure (CIP) is not known. To perform a complete furnace simulation, several options

exist with COILSIM1D. COILSIM1D can be combined with Fluent (Stefanidis et al., 2008),

where Fluent provides the heat flux profile by simulating the fire box. Another possibility is to

obtain the heat flux profile from one of the in house developed software codes FURNACE

(Heynderickx and Nozawa, 2005) or FLOWSIM (Stefanidis et al., 2008). COILSIM1D can also

be used as stand-alone program, where the desired reactor outlet conditions are specified, such as

the propylene/ethylene ratio, the methane/propylene ratio, a key component conversion, or a

fixed yield of ethylene or methane. In order to solve the resulting two point boundary condition

problem, the shooting method (Meade et al., 1996) is applied in an iterative procedure. This

allows the program to determine the inlet pressure and the heat flux profile corresponding to the

requested cracking severity indices at the reactor outlet.


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2.4.1 Shooting method

This is a commonly used numerical method for the solution of two-point boundary value

problems (Meade et al., 1996). As mentioned before, this is an iterative algorithm, which

attempts to identify appropriate initial conditions for a related initial value problem that provides

the solution for the original boundary value problem. The basic idea of the shooting method for

two-point boundary value problems is to reformulate the problem as a nonlinear parameter

estimation problem. This new problem requires a related initial value problem with initial

conditions chosen to approximate the boundary conditions at the other endpoint. When these

boundary conditions are not satisfied to the desired accuracy, the process is repeated with a new

set of initial conditions until the desired accuracy is achieved or an iteration limit is reached

(Meade et al., 1996).

The two-point boundary system for a coupled system of n first order ordinary differential

equations can be expressed as follows:

2

1

,...,2,1,)(

,...,2,1,)(

))(,(

1mjby

miay

zyzfdz

dy

jjm

ii

[2. 38]

The vector y contains the n unknown functions of the independent variable z. The unknown

functions are ordered so that the first components of y have first-kind boundary

conditions at az . The remaining 12 mnm components of the solution have first-kind

boundary conditions defined at a second point, . The shooting method searches for the

vector of parameters 2ms so that the solution to the initial value problem, denoted by );( szy

, agrees with the solution to [2.38].

2

1

,...,2,1,);(

,...,2,1,);(

));(,(

1mjssay

misay

szyzfdz

dy

jjm

ii

[2. 39]

)0( 11 nmm

bz


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Note that [2.39] is simply [2.38] with the boundary conditions at bz replaced with unknown

initial conditions at az . To determine the correct initial values, consider the “objective

function” F with components

2,...,2,1,);()(1

mjsbysF jjmj [2. 40]

Then, [2.38] is solvable if and only if there exists 2ms so that 0)( sF . The success of this

process depends primarily on the iterative procedure used to construct a sequence of parameter

vectors that converges to a zero of )(sF while any numerical root-finding step algorithm could

be employed for this step, one step of the Newton-Raphson method is most commonly used. That

is, given an initial guess 20 ms , define a sequence of initial conditions }{ ks by

[2. 41]

for all 0k . To implement this, note that the vector )( ksF is directly available from the solution

of [2.40], but the Jacobian matrix )( ksF requires the values of );(1 k

j

imsb

s

y

for al

2,...,2,1, mji . These values can be obtained by solving the n initial value problems in [2.40]

together with the 2nm sensitivity equations

2,...,2,1,,...,2,1,)( mjnis

y

y

f

s

y

dz

d

j

i

ij

i

[2. 42]

with corresponding initial conditions

2

21

,...,2,1,

,...,2,1,,...,2,1,0

1 mjiallfors

y

mjmiallfors

y

ij

j

im

j

i

[2. 43]

The above algorithm is known as the simple or single shooting method (Meade et al., 1996).

Some difficulties that appear when non-typical problems are solved can be tackled by replacing

)())(( 11 kkkk sFsFss


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the Newton-Raphson step with another iterative solver with improved convergence properties,

e.g. modified Newton’s method. In the next subparagraph, the boundary condition problem as

defined by the model equations is described and the shooting technique is applied to solve this

problem.

2.4.2 Shooting technique in COILSIM1D

The simulation model consisting of the combination of the reactor model and the reaction

network provides a set of ordinary (non-linear) differential equations that need to be solved. The

boundary conditions determine the solution of this stiff set of differential equations, i.e. the

concentration, temperature and pressure profiles. As discussed before, using the initial pressure

and the heat flux profile as initial and boundary conditions implies several problems for

industrial applications. That is because these parameters are not easily accessible in industrial

steam cracking furnaces. Solving a one point boundary condition problem is quite

straightforward, and any good solver is able to tackle this problem. However, if the process

conditions at the reactor outlet are specified, a two point boundary condition problem is the

result. The boundary (outlet) condition substitutes the initial condition.

For an industrial furnace a pressure related severity index (either COP or the ethylene to ethane

yield ratio), and one of the temperature related severity indices (P/E-ratio, COT, etc.) are the

known boundary conditions at the reactor outlet. The inlet pressure becomes then a settable

variable to obtain the desired outlet specification. Similarly, the heat flux profile is adapted to

meet the set COT or another related commercial index. Replacing the inlet pressure by the

measurable outlet pressure is straightforward: one inlet condition is replaced by one boundary

(outlet) condition. However, the replacement of the heat flux profile by one parameter at the

reactor outlet is not that straightforward. The heat flux profile consists of a number of fluxes that

strongly vary along the reactor coil. This results in an ill posed problem because if, for example,

the reactor is divided in n segments, 1n degrees of freedom remain and hence, an endless

number of solutions can be found that meet the specified outlet condition. Fortunately, the heat

flux profile along the reactor coil has been studied extensively (Heynderickx and Nozawa, 2004;

Stefanidis et al., 2008; Habibi et al., 2007). This allows to predefine the shape of the heat flux

profile depending on the used industrial furnace. Indeed, the value of the heat flux at the reactor


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inlet, combined with the predefined profile shape allows to determine the complete heat flux

profile.

Two predefined profile shapes are retained. The first one is a linear decreasing profile that is, for

example, seen in the Millisecond Furnace (Van Geem et al., 2004). In the first part of the reactor,

the process gas is heated up very fast and the endothermic reactions proceed very fast. Further in

the reactor, most of the feedstock is already cracked, and the heat input decreases. Another

possibility is a sinusoidal shape combined with a linear decrease. The position of the burners in

the furnace often causes a non-homogenous heat flux profile to the coil. The heat flux is higher at

the bottom of the furnace due to the higher temperatures of the flue gasses. Higher in the firebox,

the flue gasses have already given a part of their heat content to the reactor, resulting in a

decrease of the flue gas temperature. This induces a sinusoidal variation of the heat flux with the

height when a coil makes several vertical passes in the furnace. The maxima occur at the lowest

turning points whereas the minima are at the top of the furnace (Heynderickx and Nogazawa,

2004; Habibi et al., 2007; Stefanidies et al., 2008). This is combined with a linear decrease over

the total length of the coil to compensate the reduction of the heat demand towards the end of the

reactor. An example of both heat flux profiles is shown in Figure 2.3, where the full line is the

linear decreasing profile, and the dots show the sinusoidal profile for a coil with 6 passes (5

bends).

Besides these two heat flux profile shapes to the reactor, a third option is included where the heat

flux to the reactor(s) is calculated from the heat release of the floor burners. The heat release

from floor burners has typically a parabolic shape as function of height (Colannino 2007)

because at a certain height (typically 5-6 meters), the combustion is at its maximum, resulting in

maximum heat transfer. This burner heat flux profile can be set by specifying the relative heat

flux at three heights as shown in Figure 2.4. From this burner heat flux profile, the shape of the

heat flux profile to the reactor(s) is calculated depending on the height of the reactor in the

furnace, so a maximum heat transfer to the junctions located at the height where the heat flux

from the burners is maximal. To account for the decrease in heat demand due to higher process

gas temperatures, a linear decreasing profile is combined with this profile, as can be seen in

Figure 2.5. When using floor burners, the profile shape resulting from this method is closer to

reality than the sinusoidal shape.


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The original two points boundary value problem is now translated in a boundary condition

problem that can be solved using the shooting technique. Therefore two parameters need to be

determined at the reactor outlet: one that accounts for temperature effects, and another one that is

related to the pressure. A number of severity indices can be used to define the boundary

condition problem. Table 2.1 gives an overview of the possible severity indices that can be used

as boundary conditions.

Figure 2.3: Typical heat flux profiles (··· sinusoidal decreasing, ― linear decreasing)


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Figure 2.4: Burner heat flux profile defined by three points.

Figure 2.5: Heat flux profile to reactor derived from burner heat flux profile.

0

2

4

6

8

10

12

14

16

18

0 50 100 150 200 250 300

He

igh

t [m

]

Normalized flux [%]

(H1,Q1)

(H2,Q2)

(H3,Q3)

0

5

10

15

20

25

0 5 10 15 20 25 30 35

He

at fl

ux

Axial length [m]


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Table 2.1: Specifications at the reactor outlet and their deviation tolerances

temperature related severity indices deviation tolerance Shooting flag

coil outlet temperature (COT) 1.0 1

propylene/ethylene ratio (P/E) 3100.5 2

methane/propylene ratio (M/P) 3100.5 3

ethane conversion 1100.1 4

propane conversion 1100.1 5

n-butane conversion 1100.1 6

n-pentane conversion 1100.1 7

n-hexane conversion 1100.1 8

yield maximization - 9

ethylene production 2100.1 10

methane production 2100.1 11

pressure related severity indices Pressure flag

coil outlet pressure (COP) 2100.5

1

ethylene/ethane ratio 2100.5

2

2.4.3 Iteration procedure

In 2.4.1 it was stated that the Newton-Raphson method is the most commonly used root finding

algorithm used within the shooting method. The problem with the Newton-Raphson method is

that it requires the evaluation of the Jacobian matrix. Since the values of the target function are

only implicitly known, the Jacobian matrix cannot be calculated directly, and an approximation

method for the Jacobian matrix is necessary. Methods that are similar to the Newton-Raphson

method but use an approximation of the Jacobian matrix or the inverse of the Jacobian matrix are

called quasi-Newton methods. In COILSIM1D, Broyden’s method is used as a root finding

quasi-Newton method. In each step the inverse of the Jacobian is updated directly using the

Sherman-Morisson formula (Amirah,2010):

[2. 44]


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In Formula 2. 44 the following substitutions can be made:

[2. 45]

[2. 46]

[

] = [

] [2. 47]

[

] [

] [2. 48]

With

: the approximation of the Jacobian matrix in step n

: the objective value of the temperature related severity

: the objective value of the pressure related severity

: the temperature related severity in step n

: the pressure related severity in step n

: the flux estimation in step n

: the inlet pressure estimation in step n

In the first step of the algorithm, the Jacobian is calculated using a finite difference approach. For

this reason two initial guesses need to be provided. For the initial heat flux Coilsim1D asks two

guesses. For the coil inlet pressure Coilsim1D calculates the second guess based on the first one.

The Jacobian can then be approximated as in formula 2. 49 (Kelley,2003).

[

(

) (

)

(

) (

)

(

) (

)

(

) (

)

] [2. 49]

After that the initial guess is updated using [2. 50] and the Jacobian is updated using [2. 44]

(Amirah,2010).


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[2. 50]

The iteration is stopped when the value of and

the allowed deviation

from the objective value and respectively. The value of depends on the considered

severity index, the values are tabulated in Table 2.1.

2.5 Pre-defined standard coils

Most reactor configurations used in industrial steam cracking furnaces are standard reactors

provided by 5 companies: ABB Lummus, Technip, Linde, KBR and Stone & Webster, now part

of Technip. For these reactors, it is no longer necessary to determine the number of junctions

needed for the simulation. Instead, the input is reduced to the length, internal diameter and wall

thickness of distinguished sections of the concerned reactor. COILSIM1D will then

automatically generate the number of junctions and will set the correct reactor geometry at all

junctions. This reduces the input significantly. The standard reactors implemented in

COILSIM1D are listed in Table 2.2. Typical ranges for the total length of the coil, the internal

diameter and the wall thickness are provided in this table. Figure 2.5 shows a schematic view of

some of these reactors.

Table 2.2: Standard reactors implemented in COILSIM1D

Reactor length (m) di1 (m) dw

1 (m) coil number

Millisecond 8 - 15 0.03 - 0.05 0.006 - 0.010 2

U-coil 15 - 25 0.04 - 0.07 0.006 - 0.010 3

W-coil 30 - 50 0.04 - 0.07 0.006 - 0.010 4

SRT I 50 - 120 0.06 - 0.13 0.006 - 0.010 5

SRT II 40 - 100 0.06 - 0.15 0.006 - 0.010 6

SRT III 40 - 80 0.06 - 0.15 0.006 - 0.010 6

SRT IV 15 - 30 0.04 -0.19 0.006 - 0.010 7

SRT V 15 - 30 0.04 - 0.19 0.006 - 0.010 11

SRT VI 15 - 30 0.04 - 0.19 0.006 - 0.010 12

1 di: internal diameter of the reactor coil (m), dw: wall thickness of the reactor coil (m)


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Technip GK I 40 - 80 0.03 - 0.11 0.006 - 0.010 8

Technip GK VI 25 - 35 0.04 - 0.20 0.006 - 0.012 9

Linde Pyrocrack 1-1 15 - 25 0.04 - 0.12 0.006 - 0.010 10

Linde Pyrocrack 2-2 30 - 50 0.04 - 0.12 0.006 - 0.010 10

Linde Pyrocrack 4-2

M-Coil

SL-2

40 – 80

50-70

15-30

0.06 - 0.14

0.04 - 0.12

0.04-0.19

0.006 - 0.010

0.006 - 0.010

0.006-0.010

10

14

13

The coil numbers in Table 2.2 are equal for some reactors; the distinction between them is made

by other parameters that are provided in reactor.txt, see Chapter 3.

Figure 2.6: Standard reactors in industrial steam cracking furnaces

2.6 Adiabatic volume

The cracked gas leaving the radiant tubes is rapidly cooled down to temperatures below 400°C

(Froment, 1992). This is accomplished in the transfer line exchanger (TLE), where the heat is


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recovered for the production of high pressure steam. In an ideal set-up, the reactor and the TLE

would succeed each other directly. However, in industrial steam cracker facilities, it is not

possible that the reactor effluent immediately enters the TLE. There is always a connection

necessary that leads the process gas from the reactor exit to the transfer line exchanger. This is

often referred to as the adiabatic volume. The heat transfer from the hot process gas (750 – 900

°C) to the air surrounding the adiabatic volume is negligible compared to the heat transfer in the

following TLE. Therefore this section is as good as adiabatic, and in the simulations this is

considered to be perfectly adiabatic.

For all reactors implemented in COILSIM1D (Table 2.2), it is possible to add an adiabatic

volume. The user must specify 4 parameters in order to do this. First of all, the volume of the

adiabatic section is requested. Also the internal diameter and the wall thickness need to be given.

The last parameter is the number of reactors that are connected with this adiabatic volume. The

process gas of several reactors can flow together in one adiabatic volume before it enters the

TLE. The internal diameter of the adiabatic volume is mostly larger than the diameter of the

radiant tubes in the heater. This expansion of the diameter induces a significant pressure drop,

due to frictional losses. In the current version of COILSIM1D, the Bernoulli law is used to

incorporate the pressure losses due to sharp edge expansions of the diameter along the reactor

and the adiabatic volume. The law of Bernoulli states that the sum of the static pressure and the

dynamic pressure before an expansion is equal to the latter sum after the expansion plus the loss

due to the expansion (Perry and Green, 2006):

2

11

2

222

2

1112

1

2

1

2

1VVPVP [2. 51]

where is defined as

2

2

11

A

A [2. 52]

and A1, A2 the cross sections before and after the expansion, V1 and V2 the velocity before and

after the diameter expansion, ρ1 and ρ2 the density of the process gas before and after the

expansion, as can be seen in Figure 2.6. Using [2.52] and [2.53] the pressure after the expansion


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can be calculated. This was implemented, not only for the expansion to the adiabatic volume, but

also for all sharp edge increases of the tube diameter in the reactor coil.

When an adiabatic volume is incorporated in the simulations, the COT is fixed at the reactor

outlet, not at the outlet of the adiabatic volume. All other severity indices are determined at the

outlet of the adiabatic section. When product yields and ratios of product yields are set, they are

determined at the outlet of the adiabatic section, because in the adiabatic volume the reactions

still proceed and the product distribution still changes. The pressure based parameters, the COP

and the ethylene/ethane ratio are also determined at the outlet of the adiabatic section.

Figure 2.7: Sharp edge expansion of the tube diameter

2.7 Calculation of the physical and transport properties

2.7.1 Specific heat cp

The specific heat of the reaction components can be calculated from:

32

pT D + C.T + B.T +A Tc [2. 53]

with A, B, C and D obtained from Reid et al. (1979). The proposed polynomials are valid in a

temperature range between 300 and 1500 K.

2.7.2 Standard enthalpy of formation ΔHf

The heat of formation for pure components is given by:

A2

A1V1

V2


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T

T

p0ff

ref

dT TcTHTH [2. 54]

The reference temperature Tref is 298.15 K. When the cp is calculated from equation [2.53]

the integral in [2.54] becomes:

4

ref

43

ref

32

ref

2

ref

T

Tref

pTT

4

DTT

3

C+TT

2

BT-TAdTc [2. 55]

2.7.3 Viscosity µ

The viscosity of the reacting mixture can be calculated from the Sutherland formula (Reid et

al., 1979), derived from the kinetic gas theory:

c

c

n

1=jn

1=ij

i

ji

j

F

F+1

[2. 56]

The ji are estimated by the Wilke formulas (Reid et al., 1977)

2

1

i

j

2

4

1

j

i

2

1

i

j

ji

M

M1 8

M

M1

i > j [2. 57]

ji

i

j

j

i

ijM

M

i < j [2. 58]

The method of Stiel and Thodos (1962) leads to the following formulas for the viscosity:

- hydrocarbon gasses:


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6/1

3/21/24

j

NM10.60.4

c

c

T

p [2. 59]

With the value of N depending on the critical temperature:

1.5 Tfor 1.67) - (4.58T 0.0001778 N

1.5 Tfor T 0.0003400N

r

0.625

r

r

0.94

r

[2. 60]

- steam:

0.55 - T 01162.010 23.325 -8

j [2. 61]

with Tc the critical temperature, pc the critical pressure, Zc the critical compressibility factor and

Tr the gas temperature divided by the critical temperature. The values of the critical temperature,

pressure and the compressibility factor are tabulated in Reid et al. (1979).

2.7.4 Thermal conductivity λ

The thermal conductivity is calculated the same way as the viscosity:

c

c

n

1j=n

1=ij

i

ji

j

065.1F

F+1

[2. 62]

Again, different correlations were set up to calculate the thermal conductivity of a pure

compound. Generally these correlations have the form

i

i

2pi1iM

ccc

[2. 63]

with i the thermal conductivity, cpi the molar heat capacity, Mi the molecular weight and c1, c2

constants for each component.


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2.8 Calculation of the Coking Rate

Several models are developed at the Laboratorium voor Chemische Technologie to calculate the

coking rate. P. Plehiers (1989) set up an equation for the coking rate based on the interface

temperature:

2a1C 1 2 4 3 6

int

a22 2 4

int

a33 3 6

int

Er .exp - .C C H C C H .1000

R.T

E + .exp - .C C H .1000

R.T

E + .exp - .C C H .1000

R.T

A

A

A

[2. 64]

This model can be efficiently used with light feed stocks, such as ethane feeds.

Reyniers (1991) developed an equation for the coking rate, which can be used for the simulation

of naphthas:

a1C 1 2 2 1 3 4

a22 2 4 2 3 6

a33 4 8 3 4 8

a44 4 6 4

a55

Er .exp - . C C .C C

R.T

E + .exp - . C C H .C C

R.T

E + .exp - . C 1-C .C i-C

R.T

E + .exp - . C 1,3-C H .C 1,3

R.T

E + .exp - .C benzen

R.T

A H B H PD

A B H

A H B H

A B CPD

A

a66 5

a77

e

E + .exp - . C toluene .C xylene

R.T

E + .exp - .C styrene

R.T

A B

A

[2. 65]

In the above formulas, C stands for the concentration of the considered component [kmol·m-3].


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2.9 SIMCO

With the help of an artificial neural network, it is possible to reconstruct the molecular

composition of complex feedstocks with high accuracy, based on a number of commercial

indices. However, the development of a neural network requires an extensive amount of training

data. Such a library containing a large number of reference samples with widely varying

characteristics is not easily obtained or might not be available. Consequently, besides neural

networks, also a second method for the reconstruction of the molecular composition of petroleum

fractions has been developed. This method is based on Shannon’s information theory and does

not call for a huge set of reference samples. With this method, the mole fractions of the different

components are calculated based on a more general and theoretical approach. As a result, the

Shannon method is, in comparison with the other method, more commonly applicable. Instead of

only being able to interpolate, the Shannon method can be applied directly to all kinds of

mixtures, provided that a suitable molecular library is available, specifying which kind of

components should be taken into account.

The Shannon method adjusts the mole fractions of every component in the molecular library,

thus creating a mixture with approximately the same commercial indices compared to those of

the considered feedstock with unknown composition. Obviously, there is not a unique mixture

that meets all the specified commercial indices. According to the basic principle of the Shannon

criterion, the statistically favored composition is the one with maximum Shannon entropy. When

applying the Shannon method, a single composition with maximum Shannon entropy is selected

out of all the possible compositions that meet the boundary conditions. However, this does not

necessarily mean that the considered feedstock with unknown composition has exactly this

molecular composition.

The Shannon method and the neural network have a number of advantages and disadvantages.

For this reason a molecular reconstruction program, called SIMCO, is developed. This software

combines the two methods for molecular reconstruction. The central reconstruction method used

by the software is the Shannon entropy method. But, in case of the molecular reconstruction of

naphtha, the software is also able to use the neural network.


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2.9.1 General overview

Figure 2.8 provides a general and simplified overview of SIMCO. The starting point is the input

file containing the commercial indices of the feedstock with unknown composition. The data

from the input file is read into the program. First of all, this information is used to determine

what kind of feedstock is considered. The program can make a distinction between four types of

feedstock: naphtha, middle distillate, gas oil and natural gas condensate. The feedstock type

determines which molecular library will be used in the subsequent molecular reconstruction.

It is clear from Figure 2.8 that, in almost every situation, the Shannon entropy maximization

method will be used to reconstruct the molecular composition of the unknown feedstock.

However, if the feedstock is a naphtha fraction, the program will determine whether this naphtha

is within range of the neural network or not. If the naphtha is indeed within range and all of the

necessary commercial indices are available from the input file, the neural network will be used to

determine the molecular composition.


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Figure 2.8: General overview of SIMCO

SimCo

Read

input

Fraction

type?

Gas

condensateNaphtha

Kerosene or

DieselGas oil

Within

range?

Neural

Network

Shannon

Entropy

yes

no

Detailed

molecular

composition

Commercial

indices

Generate

output


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The neural network will produce acceptable results if the characteristics of the naphtha are

similar to thosee of the reference samples used to train the neural network. Based on the

commercial indices available from the input file, the software decides whether the naphtha is

comparable or not. To assess feedstock similarity, the principal component representation of the

feedstock is used. Principal component analysis (PCA) is a multivariate statistical technique

whereby the information carried by the original variables is projected onto a smaller number of

uncorrelated variables called principal components (PC), while preserving the most important

information. A three dimensional principal component representation of the training data allowed

graphical representation and also identification of the application range, represented by the blue

ellipsoid in Figure 2.9a. In Figure 2.9b two example naphthas are shown by their principal

component representation, derived from their commercial indices, indicating that naphtha A

(green) falls within the application range while naphtha B (red) falls outside the application

range.

(a) (b)

Figure 2.9: (a) Principal components representation of the training data; (b) Two example

naphthas: naphtha A (green) inside application range, naphtha B (red) outside application range.

After the molecular composition of the considered petroleum fraction is computed, the

commercial indices are calculated using the weight fractions of the different components and the


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properties of these components indicated in the molecular library. All the calculated parameters,

i.e. composition and commercial indices, are written out to the output files.

2.9.1.1 Neural network

Figure 2.10 gives a more detailed overview of the subroutine that uses the neural network to

calculate the detailed composition of the unknown feedstock. Besides the input file, several other

files are read into the program (weights.txt, max_min_input.txt, max_min_output.txt, bias.txt and

outputNN.txt). These files contain all the information about the network, i.e. the number of

hidden layers, the number of nodes in each layer, the number and type of output parameters and,

of course, the number of connections between each node along with the weight of the

connection. Using all this information, the input parameters can be converted to the desired

output, namely the detailed molecular composition of the feedstock.

Figure 2.10: Overview of the neural network subroutine

Read input

Detailed

molecular

composition

Commercial

indices

Read

molecular

library

Generate

output

Read

network

data

Execute

network


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After the weight fractions of the different components are calculated using the neural network,

the commercial indices are computed. To this end, the appropriate molecular library is also read

into the program.

It is important to mention that the neural network cannot be used to determine the detailed

composition if not all the necessary commercial indices are available. As mentioned previously,

the neural network is not as flexible as the Shannon method. Every commercial index used to

develop the network is required for the network to calculate the weight fractions of the different

components. These indispensable commercial indices are: the density, the PIONA analysis, the

initial boiling point, the 50 vol% boiling point and the final boiling point. If one or more of these

indices are not available in the input file, SIMCO will not be able to use the neural network, and

will be forced to use the Shannon entropy method.

2.9.1.2 Shannon entropy optimization

Using the Shannon entropy method, the mole fractions of the different components in the

petroleum fraction are calculated by maximizing an entropy function called the Shannon entropy.

This entropy function has to be maximized subject to a number of constraints that are determined

by the available commercial indices of the petroleum fraction with unknown composition.

Figure 2.11 gives a more detailed overview of the subroutines that are used when the Shannon

method is applied for molecular reconstruction.

After gathering the information from the input file and the appropriate molecular library, the

constraints are determined. Next, the optimization problem with constraints is converted into an

optimization problem without constraints using the Lagrange multiplier method, i.e. by

introducing a number of additional unknown variables. Mathematical deduction lead to the

following non linear objective function that comprises the entropy function and all of the J

constraints.

,1 11

ln exp with NJ J

j j j i jj ji

E Z f Z f

[2. 66]

By maximizing this objective function the values for the parameters i are obtained. With these

values the mole fractions of the N components in the molecular library can be calculated using

equation [2.67].


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,

1

exp

1,...,

J

j i jj

i

f

y i NZ

[2. 67]

Figure 2.11: Overview of the Shannon entropy optimization subroutine

Read input

Objective

function

Detailed

molecular

composition

Commercial

indices

Read

molecular

library

Calculate

error

Calculate

constraints fi,j

Rosenbrock

optimization

Initial

guess

Store

coposition with

lowest error

Generate

output

Repeat 1000 times


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After the detailed molecular composition is calculated, the commercial indices are determined.

Then, the calculated commercial indices are compared to the commercial indices mentioned in

the input file. The difference between them is translated into an error ε.

2

1

exp calc

i iCI CIJ

i

[2. 68]

As mentioned before, the Shannon criterion selects the composition with maximum Shannon

entropy out of all the compositions that meet the specified commercial indices. Since they

describe the unknown feedstock in greater detail, the boiling points are considered more

important than other commercial indices like the density or average molecular weight. Based on

the components from the molecular library, infinite amounts of compositions can be conceived

that have the same molecular weight, or amount of paraffins for example. The boiling points

however, significantly reduce the number of possible mixtures that meet those characteristics and

from which a unique composition is selected. The boiling point that can be determined most

accurately is the 50 vol% boiling point.

To locate the optimum of the objective function given in [2.66], the Rosenbrock method is used.

This optimization algorithm has been proven to always converge, i.e. global convergence to a

local optimum is assured. However, the global optimum is not necessarily reached. The

performance of the Rosenbrock algorithm is highly dependent on the initial guess for the

parameters i . For this reason the optimization is performed 1000 times, each time with another

initial guess for the parameters i . Finally, the molecular composition that gave rise to the

smallest error ε is stored and written out to the output files.

2.9.2 Molecular libraries

The basis for the Shannon entropy method is the molecular library that contains all necessary

information (e.g. boiling point, molecular weight, etc.) about all the components that could be

present in the considered petroleum fraction. A library containing components that are not

representative for the considered feedstock can never result in an accurate characterization.

If the neural network is used for reconstructing the molecular composition, this library is only

used to calculate the commercial indices.


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For each type of feedstock a separate molecular library was constructed. To determine which

components are included in each library, the experimental data available at the LCT and

information from literature was exploited. All of the properties given in Table 2.3 are included in

these molecular libraries.

Table 2.3: Available properties in the molecular libraries

Property Unit

Molecular weight g·mol-1

H/C ratio mol·mol-1

Density g·ml-1

PIONA group number -

Boiling point K

Carbon number -

COILSIM identification number -

2.9.2.1 Input files

The input file for SIMCO is feed.txt. In this file, either a detailed PIONA analysis can be entered

or an input based on several commercial indices. When a “0” is entered on the first line of the

file, it means that the file contains commercial indices. When a “1” is entered on the first line, the

file contains a detailed PIONA analysis.

A detailed PIONA analysis contains the weight percentage of n-paraffins, iso-paraffins, olefins,

naphthenes and aromatics for each carbon number, ranging from 1 to 33.

When the commercial indices are entered, SIMCO uses 27 input parameters. An example of such

an input file is shown in Figure 2.12. Twenty-one of the specified parameters are commercial

indices of the considered feedstock with unknown composition. The other 6 parameters are

necessary integers for the correct functioning of the software.


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Figure 2.12: Example of an input file for SIMCO

The first input parameter indicates the fraction type. This integer is required by the software

section that decides which molecular library is used. The following values are possible:

− 0, the software determines the fraction type based on the true initial boiling point and the

true final boiling point, if available. The decision tree shown in Figure 2.13 is considered.


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Figure 2.13: Decision tree for the determination of the fraction type

− 1, the considered feedstock is a natural gas condensate

− 2, the considered feedstock is a naphtha

− 3, the considered feedstock is a middle distillate (kerosene or diesel)

− 4, the considered feedstock is a gas oil

The second input parameter specifies which reconstruction method should be used by SIMCO.

− If this integer is set to 0, the software will decide which method is most likely to produce

the most accurate results. This means that, in almost every situation, the Shannon method

will be selected. Only if the considered feedstock is a naphtha fraction, the software will

determine whether the characteristics of the fraction are within range of the neural

network.

− If the integer equals 1, the software will be forced to use the Shannon method for

molecular reconstruction, also if a naphtha fraction within the range of the neural network

is considered.

− The integer can also be set to 2. In this case the neural network will be used to reconstruct

the molecular composition, but only if all the necessary commercial indices are available.

These include the density, the PIONA analysis and three boiling points (IBP, 50% BP

IBP > 100°C

Gas

condensate

no

yes

EBP < 270°C

EBP > 300°C

yes

no

Naphtha

Gas oilyes

noKerosene or

Diesel


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and FBP). The software cannot be forced to use the neural network if the considered

feedstock is not a naphtha.

The following three input parameters are the average molecular weight, the molar H/C ratio and

the specific density (60°F) of the considered feedstock with unknown composition. If either of

these indices is not available, their value should be set to zero. However, the neural network can

only be used when the density is available.

Next, an integer indicates whether the group type analysis, stated in the following 5 input

parameters, is available in wt% (integer equals 0) or vol% (integer equals 1). This integer also

determines whether the output, i.e. the molecular composition, is given in wt% or vol%.

The following integer specifies the type of analysis:

- 0, PIONA analysis

- 1, PONA analysis with P, the total amount of paraffinic components (normal+iso)

- 2, saturates – aromatics

The integer that follows the group type analysis specifies the unit of the available temperatures.

− If the integer equals 0, the temperatures are in °C.

− If the integer equals 1, the temperatures are in K.

− If the integer equals 2, the temperatures are in °F.

Next, another integer indicates the type of boiling point distillation curve, made up by the next

13 input parameters.

− If the integer equals 0, an ASTM D86 distillation point curve is available.

− If the integer equals 1, a true boiling point curve is available.

− If the integer equals 2, an ASTM D2887 distillation point curve is available.

If one or more temperatures are not available, their value can be set to zero, in which case they

will be estimated by non-linear interpolation. For the neural network to be used, the IBP, the

50% BP and the FBP have to be available.


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2.9.3 Boiling point conversion

If the Shannon method is used, a true boiling point distillation curve has to be available. The

neural network, on the other hand, needs an ASTM D86 distillation curve as input. As mentioned

before, the input file can contain true boiling points, ASTM D86 boiling points or ASTM D2887

boiling points. Depending on the information available from the input file, boiling points will

have to be converted to TBP data or ASTM D86 data. The following conversions can be

performed by SIMCO:

− Conversion of ASTM D86 to TBP distillation at atmospheric pressure

− Conversion of TBP to ASTM D86 distillation at atmospheric pressure

− Conversion of ASTM D2887 to TBP distillation at atmospheric pressure

− Conversion of ASTM D2887 to ASTMD86 distillation at atmospheric pressure

All the applied conversion procedures are included in API Technical Data Book and are proven

to produce acceptable results. However, every preformed conversion inevitably entails a certain

loss of accuracy. Furthermore, most conversion procedures can only convert a certain number of

boiling points. Consequently, some information will be lost entirely when this boiling point

conversion is performed. The unconverted boiling points will be determined by linear

interpolation, although this will lead to an additional loss of accuracy.

Boiling points that are not available from the input file will not be estimated using linear

interpolation, since this won’t improve the results.

2.9.3.1 Conversion of ASTM D86 to TBP distillation at atmospheric pressure

If an ASTM D86 boiling point curve is available and the Shannon method is used, the ASTM

D86 boiling points will be converted to true boiling points. Daubert (1994) developed a set of

equations to convert ASTM D86 to TBP. This is believed to be the most accurate currently

available method in literature and, therefore, has been included in the API Technical Data Book.

In this method, the first conversion should be made at the 50 vol% boiling point and then the

difference between two cut points is correlated.

Equation 2.69 is used to convert an ASTM D86 boiling point at 50 vol% to the corresponding

true boiling point.

1.0258

50% 50%0.8718 86 TBP ASTM D [2. 69]


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Where ASTM D8650% and TBP50% are temperatures at 50 vol% distilled in Fahrenheit. Equation

2.69 can also be used in a reverse form to estimate ASTM D86 from TBP. The following

equation is used to determine the difference between two cut points:

B

i iY A X [2. 70]

Where

Yi = calculated difference in TBP temperature between two cut points.

Xi = available difference in ASTM D86 temperature between two cut points.

A,B = constants varying for each cut point and are given in Table 2.4

Table 2.4: Constants used for determining TBP differences between two cut points

Cut Point Range

(vol%)

A B Maximum

allowable Xi

1 100 – 90 0.11798 1.6606 -

2 90 – 70 3.0419 0.7550 100

3 70 – 50 2.5282 0.8200 150

4 50 – 30 3.0305 0.8008 250

5 30 – 10 4.9004 0.7164 250

6 10 – 0 7.4012 0.6024 100

To determine the true boiling point temperature (°F) at any percent distilled, calculation should

begin with the calculation of the 50 vol% TBP temperature, followed by addition or subtraction

of the proper temperature differences Yi.

0% 50% 4 5 6

10% 50% 4 5

30% 50% 4

70% 50% 3

90% 50% 3 2

100% 50% 3 2 1

TBP TBP Y Y Y

TBP TBP Y Y

TBP TBP Y

TBP TBP Y

TBP TBP Y Y

TBP TBP Y Y Y

[2. 71]

This method was developed based on samples with ASTM D86 point temperature of less than

250 °C, but it is recommended for extrapolation up to fractions with ASTM 50% temperature of

315°C, as suggested by API Technical Data Book. Average absolute deviation for this method as


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reported by the API Technical Data Book is about 4.6 °C for some 70 petroleum cuts with

widely varying composition. Predicted TBP at 0 and 100% are the least accurate values followed

by values at 10% and 90% points.

This conversion method can also be used in reverse to convert a TBP curve to an ASTM D86

curve. This possibility is also used by SIMCO. Since the neural network requires ASTM D86

boiling points as input, an available true boiling point curve will be converted to ASTM D86

boiling points if the neural network is used.

2.9.3.2 Conversion of ASTM D2887 to TBP distillation at atmospheric pressure

This conversion is based on the same principle as the previously discussed procedure. Again, the

first conversion should be made at the 50 vol% boiling point, and then the difference between

two cut points is correlated:

50% 50%2887 TBP ASTM D [2. 72]

where ASTM D288750% and TBP50% are temperatures at 50 vol% distilled in Fahrenheit. The

following equation is used to determine the difference between two cut points:

B

i iY A X [2. 73]

where

Yi = calculated difference in TBP temperature between two cut points.


A,B = constants varying for each cut point. They are given in Table 2.5.


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Table 2.5: Constants used for determining TBP differences between two cut points

Cut Point Range

(vol%)

A B Maximum

allowable Xi

1 100 – 95 0.02172 1.9733 30

2 95 – 90 0.97476 0.8723 40

3 90 – 70 0.31531 1.2938 75

4 70 – 50 0.19861 1.3975 75

5 50 – 30 0.05342 1.6988 75

6 30 – 10 0.011903 2.0253 75

7 10 – 5 0.15779 1.4296 40

To determine the true boiling point temperature (°F) at any percent distilled, calculation should

begin with the calculation of the 50 vol% TBP temperature, followed by addition or subtraction


5% 50% 5 6 7

10% 50% 5 6

30% 50% 5

70% 50% 4

90% 50% 4 3

95% 50% 4 3 2

100% 50% 4 3 2 1

TBP TBP Y Y Y

TBP TBP Y Y

TBP TBP Y

TBP TBP Y

TBP TBP Y Y

TBP TBP Y Y Y

TBP TBP Y Y Y Y

[2. 74]

2.9.3.3 Conversion of ASTM D2887 to ASTMD86 distillation

Equation 2.75 is used to convert an ASTM D86 boiling point at 50 vol% to the corresponding

true boiling point.

1.0395

50% 50%86 0.77601 2887 ASTM D ASTM D [2. 75]

Where ASTM D8650% and ASTM D288750% are temperatures at 50 vol% distilled in Fahrenheit.

The following equation is used to determine the difference between two cut points.

B

i iY A X [2. 76]

Where

Yi = calculated difference in ASTM D86 temperature between two cut points.


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A,B = constants varying for each cut point and are given in Table 2.6.

Table 2.6: Constants used for determining ASTM D2887 differences between two cut points

Cut Point Range

(vol%)

A B Maximum

allowable Xi

1 100 – 90 2.6029 0.65962 100

2 90 – 70 0.30785 1.2341 100

3 70 – 50 0.14862 1.4287 100

4 50 – 30 0.07978 1.5386 100

5 30 – 10 0.06069 1.5176 150

6 10 – 0 0.30470 1.1259 150

To determine the ASTM D86 temperature (°F) at any percent distilled, calculation should begin

with the calculation of the 50 vol% ASTM D86 temperature, followed by addition or subtraction


0% 50% 4 5 6

10% 50% 4 5

30% 50% 4

70% 50% 3

90% 50% 3 2

100% 50% 3 2 1

86 86

86 86

86 86

86 86

86 86

86 86

ASTM D ASTM D Y Y Y

ASTM D ASTM D Y Y

ASTM D ASTM D Y

ASTM D ASTM D Y

ASTM D ASTM D Y Y

ASTM D ASTM D Y Y Y

[2. 77]

2.9.4 Calculation of the commercial indices

Once the detailed molecular composition is determined, the commercial indices are calculated

using the mole or weight fractions of the different components and the properties of these

components available from the molecular library.

2.9.4.1 Average molecular weight

The average molecular weight can be calculated using the following equation:

calc

i i

i

M y M [2. 78]


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2.9.4.2 H/C ratio

The H/C ratio is calculated using the following mixing rule:

i

ii

calcCHyCH // [2. 79]

2.9.4.3 Density

To calculate the density, the following mixing rule is applied:

1 i

calci i

x

d d

[2. 80]

With,

i ii calc

y Mx

M [2. 81]

The calculated density is used to determine the volume fractions, as follows:

calci

i

i

xv d

d [2. 82]

2.9.4.4 True boiling point distillation curve

To calculate, example.g. the 30 vol% boiling point, all of the components in the molecular

library are first sorted with increasing boiling point. Then the volume fractions of each

component are added up gradually, starting with the component with the lowest boiling point. As

soon as the cumulative volume fraction exceeds 30% the adding is stopped, and the

corresponding boiling point is calculated by linear interpolation.

2 1130% 0.30 1

2 1

BP BPBP BP

v vv

[2. 83]

With

1

2

0.30

0.30

v

v

[2. 84]

BP1 is the boiling point of the components last added to the cumulative volume fraction to reach

the value of v1. BP2 is the boiling point of the component that lead to volume fraction v2.


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The calculation is similar for all other boiling points. SIMCO determines the initial boiling point,

5 vol%, 10 vol%, 20 vol%, 30 vol%, 40 vol%, 50 vol%, 60 vol%, 70 vol%, 80 vol%, 90 vol%,

95 vol% boiling point and the final boiling point. Only these boiling points are used to calculate

the error ε.

2.9.4.5 PIONA analysis

To calculate the total amount of paraffins, isoparaffins, olefins, naphthenes and aromatics, all the

weight fractions of the components from a matching PIONA group are simply added together.

2.10 References

Amira R., Mohd L. A., Mustafa M. Broyden’s method for solving fuzzy non-linear equations,

Advances in fuzzy systems, 2010

Bolado R.G. Kinetic Modeling of Thermal Cracking of Heavy Hydrocarbons, Master thesis,

Ghent University, 2003.

Colannino, J. Mathematical Models for Characterizing and Predicting Heat Flux Profiles from

Ethylene Cracking Units. Ethylene Producer's Conference. Houston, TX, 2007.

De Buck J. Kinetische Studie van Cokesvorming bij het Thermisch Kraken van

Koolwaterstoffen, Master thesis, Ghent University, 1999.

Dente M., Ranzi E. Detailed Prediction of Olefin Yields from Hydrocarbon Pyrolysis through a

Fundamental Simulation Program SPYRO, Comp. Chem. Eng., 3, 61, 1979.

De Roo T. Modellering van Stroming, Modellering van Cokesvorming in de Warmtewisselaar

stroomafwaarts van een Thermische Kraker, Master thesis, Ghent University, 1998.

De Saegher J.J. Modellering van Stroming, Warmtetransport en Reactie in Reactoren voor

Thermisch Kraken van Koolwaterstoffen, Ph.D. thesis, Ghent University, 1994.

Elvers B., Hawkins S., Schulz G. Tubular reactors, Ullmann’s Encyclopedy of Industrial

Chemistry. B4, 181-198, 1992.

Habibi A., Merci B., Heynderickx G.J., Impact of radiation in CFD simulations of steam

cracking furnaces, Computers & Chemical Engineering, 2007

Hottel H.C., Sarofim A.F. Radiative Transfer, McGraw-Hill, New York, 1967.

Jossi, Stiel, and Thodos, AIChE J., 8, 59 (1962).


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Kelley C.T. Solving non-linear equations with Newton’s method, Siam, 29, 2003

Li S., Petzold L.R. Design of New DASPK for Sensitivity Analysis, UCSB Technical report,

1999.

McNaught A.D., Wilkinson A. Compendium of Chemical Terminology. The Gold Book, 2nd

Edition, Blackwell Science, 1997.

Meade D.B., Haran B.S. White R.E. The shooting Technique for the Solution of Two-Point

Boundary Value Problems, 1996

Oprins A. J. M., Heynderickx G. J., Calculation of three-dimensional flow and pressure fields in

cracking furnaces, Chemical Engineering Science, Volume 58, Issue 21, 2003, 4883-4893

Plehiers P.M. Rigoureuze Modellen voor de Simulatie van Fornuizen voor de Thermische

Kraking van Lichte Koolwaterstoffen, Ph.D. thesis, Ghent University, 1989.

Qing A. Differential Evolution: Fundamentals and applications in electrical engineering, Wiley,

2009

Rao M.V.R., Plehiers P.M., Froment G.F. The Coupled Simulation of Heat Transfer and

Reaction in a Pyrolysis Furnace, Chem. Eng. Sci., 43, 1222, 1988.

Reid R.C., Prausnitz J.M., Poling B.R. Properties of gases and Liquids, McGraw-Hill, 1979.

Reyniers M.F., Froment G.F. Influence of Metal Surface and Sulfur Addition on Coke

Deposition in the Thermal Cracking of Hydrocarbons, Ind. Eng. Chem. Res., 34, 773-785,

1995.

Reyniers G. Ph.D. thesis, Cokesvorming bij het Thermisch Kraken van Koolwaterstoffen, Ghent

University, 1991.

Smith J. M. Chemical Engineering Kinetics, McGraw-Hill Book Company, New York, 1981.

Stefanidis G.D, Merci B., Heynderickx G.J., Marin G.B., CFD simulations of steam cracking

furnaces using detailed combustion mechanisms, Computers & Chemical Engineering,

Volume 30, Issue 4, 2006, 1779-1789

Van Damme P.S., Willems P.A., Froment G.F. Temperature, not Time, Controls Steam Cracking

Yields, Oil & Gas Journal., 68-73, 1984.

Van Goethem M.W.M., Kleinendorst F.I., Van Leeuwen C., Van Velzen N. Equation-Based

SPYRO® Model and Solver for the Simulation of the Steam Cracking Process, Comp.

Chem. Eng., 25, 905-911, 2001.

Van Geem K.M., Reyniers M.F., Marin G.B., Song J., Mattheu D.M., Green W.H. Automatic

Network generation using RMG for Steam Cracking of n-Hexane, AIChE Journal, 52, 718-

730, 2006.


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Van Keer R., Slodicka M., Numerieke Wiskunde, Coarse intended for students of BSM 1,

UGent, 2004

Vercauteren C. Rigoureuze Kinetische Schema’s voor de Thermische Kraking van

Koolwaterstoffen, PhD dissertation, UGent, 1991.

Wauters S, Marin G.B. Kinetic Modeling of Coke Formation during Steam Cracking, Ind. Eng.

Chem. Res., 41, 2379, 2002.

Chapter 3: Program and Data File Description

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Chapter 3:

Program and Data File Description

3.1 Introduction

COILSIM1D is a computer program developed at the Laboratory for Chemical Technology to

simulate the cracking behavior of hydrocarbon feedstocks in steam cracking coils. The program is

written for the most part in FORTRAN. A graphical user interface is developed in Visual

Studio.Net that allows creating the necessary input files for process conditions, reactor geometry

and feedstock composition.

3.2 Installing COILSIM1D

COILSIM1D comes with a deployment package and can be easily installed on any PC running on

Windows XP or Windows 7. The program might work with Windows Vista but this has not been

verified by the developers. To start the installation procedure, double click on COILSIM1D.msi in

explorer.

The following screen will pop-up:


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Click “Next”:

Again click “Next”:


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Click “Install”:

COILSIM1D is now installed on your PC. Note that you need the Microsoft .NET Framework

Version 4.0 Redistributable Package installed on your PC. This package can be found using the

following link:


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http://www.microsoft.com/downloads/en/details.aspx?FamilyID=9cfb2d51-5ff4-4491-b0e5-

b386f32c0992

3.3 Installing the CodeMeter security key

COILSIM1D comes with an USB dongle to protect the software. Before inserting this dongle the

drivers need to be installed. To do this, launch CodeMeterSDK32.exe or CodeMeterSDK64.exe,

depending on your operating system.

For further information concerning the installation of CodeMeter, the user is referred to

http://support.codemeter.de/en/setup/index.html.

3.4 Important data files

3.4.1 thermochemistry.i

thermochemistry.i is an unformatted file. It contains all the physical information of 700 molecules

and 250 radicals.

NM : number of molecules

NRA : number of radicals

AHF0R : standard enthalpy of formation for a radical (kcal·kmol-1

)

AMRS : molecular weight of a radical (kg·kmol-1

)

AS0R : standard entropy of a radical (kcal·kmol-1

/K-1

)

AS0 : standard entropy of a molecule (kcal·kmol-1

/K-1

)

ANMRS : name of the molecule or radical

AMOLMASSM: molecular weight of a molecule (kg·kmol-1

)

AHF0 : standard enthalpy of formation for a molecule (kcal·kmol-1

)

NRH : number of the molecule that is formed through

addition of H. to a radical

AVA, AVB : coefficients used for the calculation of the viscosity

http://www.microsoft.com/downloads/en/details.aspx?FamilyID=9cfb2d51-5ff4-4491-b0e5-b386f32c0992%20

http://www.microsoft.com/downloads/en/details.aspx?FamilyID=9cfb2d51-5ff4-4491-b0e5-b386f32c0992%20

http://support.codemeter.de/en/setup/index.html


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of a pure component

ACA, ACB, ACC, ACD : Cp-coefficients of a molecule

ACAR, ACBR, ACCR, ACDR : Cp-coefficients of a radical

3.5 Input files

In the following paragraph, the important input files related to user input will be described. These

files are located in %appdata%\coilsim1d\Projects\Projname. Where Projname is the name of the

project defined in simulation.txt which will be described further on.

3.5.1 Units.txt

Units.txt is automatically created with the GUI, but can also be created using Wordpad or Notepad.

It contains data about the units used in the following input files:

Dunit : Standard units for distance (Input)

1 = m

2 = cm

3 = ft

4 = inch

Aunit : Standard units for angles (Input)

1 = rad

2 = °

Qunit : Standard units for heat flux (Input)

1 = kcal·m-²·s-1

2 = kJ/m²/s

3 = BTU/ft²/h

4 = BTU/ft²/s

MFunit : Standard units for mass flow rate (Input)

1 = kg·h-1

2 = g·s-1

3 = g·hr-1

4 = lb·s-1


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Tunit : Standard units for temperature (Input)

1 = °C

2 = K

3 = °F

Punit : Standard units for pressure (Input)

1 = atm

2 = bara

3 = barg

4 = Pa

5 = psi

feedUnit : Standard units for feed composition (Input)

1 = wt/wt

2 = wt%

3 = mole·mole-1

4 = mole%

DensUnit: Standard units for density (Input)

1 = kg·m-³

2 = lb·ft-³

CondUnit: Standard units for conductivity (Input)

1 = kcal·K-1·m-1·s-1

2 = kW·K-1·m-1

3 = W·K-1·/m-1

ConvUnit: Standard units for convection (Input)

1=kcal·K-1·m-²·s-1

2 = kW·K-1·m-²

3 = W·K·m-²

ViscUnit : Standard units for viscosity (Input)

1 = Pa·s

2 = Poise

3 = cPoise


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4 = lb·ft-1·s-1

All this variables are repeated once more but this time for the output units.

3.5.2 reactor.txt

reactor.txt is automatically created with the GUI, but can also be created using Wordpad or

Notepad. The file contains all the information about the reactor configuration. As the used

variables are declared, it will be clear which input is necessary for a simulation.

normal : switch for implementation of shooting algorithm

= 1 no shooting

= 2 implementation of shooting algorithm

ncoil : switch for how reactor geometry will be specified

= 1 non standard coil

= 2 Millisecond

= 3 U-coil

= 4 W-coil

= 5 SRT I

= 6 SRT II, SRT III

= 7 SRT IV

= 8 Technip GK I

= 9 Technip GK VI

= 10 Linde Pyrocrack 1-1, 1-2, 2-4

= 11 SRT IV

= 12 SRT VI

= 13 SL-2

= 14 M-coil

If a non standard coil is used, the following input should be provided, see Figure 3.1

NJT : Total number of junctions in the coil

QADTW : Wall thickness

QADI : The wetted perimeter in each section

QAOM : Tube cross section area in each section

QAZI : Axial coordinates of the junctions

QANA : Angle of the bend in each junction

QARB : Radius of the bend in each junction

QAGI : Mass flow factor in each section

REACT : Number of the junction where the adiabatic volume starts


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In the file, a line follows with the following text:

0 1 0 0

The first two numbers are necessary to tell the program that the feedstock composition is placed in

nafta.i. The last two zeros correspond to iflag and ilamda.

IFLAG : = 0 smooth tube

= 1 other correlation used for the calculation of the friction factor

and/or the number of Nusselt (format = I3)

ILAMDA: = 0 linear correlation conduction coefficient

= 1 other correlation conduction coefficient (format = I3)

Figure 3.1: Example of reactor.txt file

If IFLAG = 1, the following variables must be defined for each junction of the reactor.

QIFRIC : = 0 smooth circular tube

= 1 spiral fin tube (Lummus)

= 2 straight fin tube (Lummus)

= 3 rifled fin tube


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= 4 straight fin tube

= 5 Nu = 2.98

QFFRIC : Perimeter ratio to account for the change in inside surface area

If IFLAG = 0 : QFFRIC = 1

QINUS : Same as QIFRIC

If ILAMDA = 1, one of three different wall materials has to be selected. The material should be

specified for each junction of the reactor.

QALAMDA : = 0 800 / 800H

= 1 silicon carbide

= 2 aluminum

At the end, if ITA = 0, the gas temperature and the pressure profile must be defined.

ATI : Gas temperature (°C)

API : Pressure (atm)

The last lines in reactor.txt define the parameters of the profile used in the shooting method:

AUTOSHOOT: = 1 Use of built-in parameters

= 0 Use of manually specify profile parameters

If AUTOSHOOT equals 0, profile parameters have to be given. The number of parameters

depends on the chosen shooting profile. If uniform shooting or custom shooting are chosen, no

additional parameters are necessary. If linear shooting or long flame shooting are chosen, one

additional parameter, namely DECREASE needs to be specified. The following shape is used:

with:

QAZI : Axial position in the reactor

QAQFA : Heat flux on specified position in the reactor

STOT : Total length of the reactor (including adiabatic volume)

DECREASE : Parameter specified by the user in reactor.txt


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When linear shooting is chosen, a is a constant. When using a long flame profile, a is dependent on

the position inside the furnace and is calculated as mentioned in Chapter 2.

If sinusoidal shooting is chosen, two additional parameters need to be specified, namely

DECREASE and AMPLITUDE. The following shape is used:

( (

)) (

)

with:

QAZI : Axial position in the reactor

QAQFA : Heat flux on specified position in the reactor

STOT : Total length of the reactor (including adiabatic volume)

POSB(n) : Position of the nearest bend after the current axial position

POSB(n-1) : Position of the nearest bend before the current axial position

DECREASE : Parameter specified by the user in reactor1.txt

AMPLITUDE : Parameter specified by the user in reactor1.txt

+ : Used when the gas is moving downwards in the oven

- : Used when the gas is moving upwards in the oven

If a standard coil is used, the reactor.txt file is completely different, as shown in Figure 3.2. This

input file is different for every standard reactor coil and it is recommended to use the GUI to create

these files. Schematic diagrams of various standard reactors were presented in Figure 2.6 of

Chapter 2.


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Figure 3.2: Example of reactor.txt for Millisecond reactor

The last integer indicates if an adiabatic volume is present or not. This is the part of the reactor

between the firebox and the transfer line exchanger, where no heat transfer occurs. Due to the high

gas temperatures, the reactions still proceed in this area, influencing the product distribution. It is

important to implement this possibility for all reactors in the future, because the presence of this

adiabatic volume has an influence on the product distribution. If the adiabatic volume flag is equal

to 1, then the following data need to be additionally added:

Advol : adiabatic volume (10-3

m³) (format = 9F8.0)

Addia : diameter of the adiabatic section (m) (format = 9F8.0)

Adiwand : wall thickness of the adiabatic section (m) (format = 9F8.0)

Numberadiabatic : reactors connected to adiabatic V (format = I3)

If the adiabatic volume flag is equal to zero, these lines should be omitted from the input file.

The hydrocarbon flow in the file is always the flow in the first tube entrance for split coils. The

program calculates the hydrocarbon flow in the following tubes.


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Figure 3.3: Example of reactor.txt for U coil

If ncoil equals 4, a W coil is chosen, see Figure 3.4. For each leg of the W coil the length (m),

diameter (m) , wall thickness (m) and whether or not the leg is adiabatic needs to be specified.

After each leg, the length of the bend (m) and whether or not the bend is adiabatic needs to be

specified. Similarly, the U coil (ncoil = 3, see Figure 3.5) can be defined, but only two legs and

one bend are necessary in this case.


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Figure 3.4: Example of reactor.txt for W coil

For an SRT I coil, the reactor.txt file looks as follows, see Figure 3.5. Note that examples for each

of the standard coils are included in with COILSIM1D. This helps to implement each standard coil

for simulations.


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Figure 3.5: Example of reacor.txt for SRT I

3.5.3 nafta.i

nafta.i is a file containing the composition of the feedstock. An example is given in Figure 3.6.

NNAF : Number of naphtha components (format = I3)

NPA : total number of products (format = I3)

NLA : number of these products in THERMOCHEMISTRY.I (format = 25I3)

For each naphtha composition, the following data should be provided as declared below:

NNFA : number of naphtha components (max. 500 are allowed) (format = I3)

AAAN : weight fraction of the naphtha component (format = F8.0)

LLNA : number naphtha component in THERMOCHEMISTRY.I (format = I3)

IINSC : = 1 component is included in conversion

= 0 component is not included in conversion (format = I2)


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Figure 3.6: Example of a nafta.i file


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3.5.4 cokes.da

This file contains all information to simulate the formation of coke.

NPREC : number of precursors (format = I3)

NBPR : number in THERMOCHEMISTRY.I of precursor (format = 15I3)

ISW : choice between the different coking models (1 or 2)

= 1 : model of Plehiers (1989)

= 2 : model of Reyniers (1991) (format = I3)

RLAMBDAC : conduction coefficient coke (kcal·m-1·K-1·s-1) (format = F13.6)

RHOC : density of the coke (kg·m-³) (format = F13.6)

3.5.5 coke.i

There is also an option to perform a simulation in time. To do so, the following variables should be

provided:

TIME : start time (h) (format = F8.0)

DTIME : time step (h) (format = F8.0)

If TIME is not equal to 0, then the following data should be given :

NSTEP : number of steps (format = I3)

RC : coking rate (g·h-1·m-²) (format = F13.8)

DCOKE : coke thickness (m) (format = F13.8)

3.5.6 exp.txt

The exp.txt file can have different formats, depending on how the process conditions are specified.

On the first line, COILSIM1D reads whether outlet conditions (2) or a heat flux or temperature

profile (1) are used.

normal : Switch for conditions (format = I1)

= 1 profile

= 2 outlet conditions


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If a profile is used for the process conditions, the exp.txt can look as follows:

Figure 3.7: Example of a exp.txt file using a heat flux profile as input

ITA : Switch for the input variables (format = I1)

= 0 gas temperature and pressure profile

= 1 heat flux profile

= 2 external wall temperature profile

QAQFA : Heat flux profile, if ITA = 1 (kcal·/mint-2·s-1

) (format = 9F8.0)


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Wall temperature profile, if ITA = 2 (°C)

QAGI : HC flow in each junction (kgHC·h-1) (format = 9F8.0)

ADELTA: Steam dilution (kgsteam·kgHC-1

) (format = 9F8.0)

ACIT : Coil inlet temperature (°C) (format = 9F8.0)

ACIP : Coil inlet pressure (atm) (format = 9F8.0)

The input for the shooting method is provided in the same file, but the format is completely

different. Figure 3.8 shows an example of a typical input file:

Figure 3.8: Example of a exp.txt file when outlet conditions are specified

The second value in the exp.txt is, in this case, the shooting flag. Depending on this value,

different outlet conditions can be specified.

shooting flag : temperature related severity (format = I3)

= 1 coil outlet temperature (COT)

= 2 propylene/ethylene ratio (P/E)


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= 3 methane/propylene ratio (M/P)

= 4 ethane conversion

= 5 propane conversion

= 6 n-butane conversion

= 7 n-pentane conversion

= 8 n-hexane conversion

= 9 yield maximization

= 10 ethylene production

= 11 methane production

= 12 conversion of a custom component

shooting value : value for selected shooting flag (format = 9F8.0)

estimate 1 : estimates for initial heat flux (format = 9F8.0)

estimate 2 : estimates for initial heat flux (format = 9F8.0)

pressure flag : pressure related severity (format = I3)

= 1 coil outlet pressure (COP)

= 2 ethylene/ethane ratio

pressure value : value for selected pressure flag (format = 9F8.0)

profile : linear or sinusoidal (format = I3)

= 1 linear

= 2 sinusoidal

= 3 uniform

= 4 custom

= 5 long flame

flow rate : flow in kg/h to one inlet tube (format = 9F8.0)

dilution : kg steam per kg hydrocarbons (format = 9F8.0)

CIT : Coil inlet temperature (°C) (format = 9F8.0)

CIP : Coil inlet pressure (°C) (format = 9F8.0)

If shooting flag equals twelve, the component which is used to calculate the conversion also needs

to be specified:

mc : Number of component in thermochemistry.i

Note that the value for the flow rate is the flow rate to one inlet tube. Therefore, if a split coil

design is used where two inlet tubes merge into one outlet tube, half of the total reactor flow rate

has be given as input. Estimate 1 and 2 are estimates for the heat flux at the first section of the


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reactor. However the GUI can automatically select proper values for each type of coil. The CIT

and CIP are separated by a space.

3.5.7 profileshape.i

If the custom profile option is chosen, a file ‘profileshape.i’ is needed, specifying the heat flux

profile to all junctions:

FLUX(i) : the heat flux to junction i (kcal·m-²·s-1

) (format = F8.0)

3.5.1 burnerflux.da

If the long flame profile option is chosen, a file ‘burnerflux.da’ is needed, specifying the relative

heat flux at three points, as mentioned in chapter two:

FLUX1,H1: height, normalized heat flux for the lower point (m, kcal·m-²·s-1

) (format = 2F8.0)

FLUX2,H2: height, normalized heat flux for the middle point (m, kcal·m-²·s-1

) (format = 2F8.0)

FLUX3,H3: height, normalized heat flux for the upper point (m, kcal·m-²·s-1

) (format = 2F8.0)

HREACTOR: height where reactor enters the furnace (m) (format = F8.0)

DIRECTION: first pass is upwards or downwards in the furnace (-1 or 1)

The lower and upper points specify, respectively, where the parabolic heat flux starts and where it

ends. The middle point defines the shape of the parabola. Below and above this parabolic part, the

heat flux is kept constant, equal to the heat flux of the lower and upper point, respectively.

3.5.2 pitch.da

When iflag equals 1, the subroutine uses pitch.da, which contains the following variables:

B : the distance between two fins (m)

PITCH : the pitch is only valid for the helicoidally finned tube, and is the distance

between two successive turns (m)


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For custom coils, both B and PITCH have to be specified at each junction. For standard coils, the

same value is used throughout the reactor. If the variable is not applicable to the chosen tube type,

e.g. smooth tubes, an arbitrary value should still be provided.

3.5.3 test.da

The user can select the correlations used for the thermal conductivity in this data file.

ICON : switch for the thermal conductivity (format = I1)

ICON = 1 : the correlation of Prandtl

ICON = 2 : the correlation of Eucken

ICON = 3 : the correlation of Stiel and Thodos

ICON = 4 : the modified correlation of Eucken

3.5.4 runlength.txt

This file contains all the information for execution of a run length simulation. It contains the

following variables:

RLSWITCH : Switch for run length simulations

0 : No run length simulation

1 : Run length simulation

if RLSWITCH equals 1, the following variables also need to be defined:

MAXTEMP : Maximal wall temperature of the tube (format = 9F8.0)

MAXPRESS : Maximal pressure drop over the reactor (format = 9F8.0)

LINRED : Linear reduction coefficient for the formation of cokes (%)

(format = 9F8.0)

if LINRED equals -1, the following function is applied to LINRED:


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(

(

) )

where Afactor, Bfactor and T need to be defined in runlength.txt

AFACTOR : parameter

BFACTOR : parameter

T : Estimate of the run length

A value of 100 % should be used for the linear reduction coefficient for the formation of cokes if

willing to use the coke mechanism with the parameters obtained by the LCT. It is important to note

that LINRED is multiplied with the coking rate. Therefore if, e.g. a value of LINRED = 90% is

used as input, the coking rate will be 90% of the originally calculated one.

3.5.1 simulation.txt

This file contains the number of simulations to be carried out and the name of each simulation.

It is the only input file that needs to be located in the “%appdata%\coilsim1d” folder. It contains

the variables

SIMU : Number of simulations (format = I1)

SENS : Switch for sensitivity analysis

0: No sensitivity analysis

1: Sensitivity analysis: estimates for estimate1, estimate2 and pin are

taken from the previous simulation.

NAME(S): Name of each simulation (no spaces)

For each simulation to be carried out, a name has to be entered. The input files for this simulation

need to be located in “%appdata%/Projects/NAME”. Otherwise an error will occur.


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3.6 Output files

3.6.1 simulation_overview.txt

Simulation_overview.txt contains an overview of all the simulations that were performed, and

indicates if they were successful or not. If the error is known, the file will contain details about

what went wrong.

Figure 3.9: Example of a error.txt file when outlet conditions are specified

3.6.2 results.txt, general_info.csv, yields.csv, yieldprofiles.csv

The different output files are stored in the directory ”%appdata%\coilsim1d\Projects\Name\”. If a

run length simulation is carried out, different output files will be located in subdirectories

(“StepX”). According to the output switches NOL, NOK, NET and NOF, different results can be

written down. The network and the reaction rate coefficients can first be mentioned if NET equals

1. Next, a detailed description of the coil geometry and the flow in each junction is written down.

Then, for each junction, a number of results is written out, see Figure 3.10:

- axial distance ZP (m) - gas temperature TA (K) -

- pressure PP (atm) - residence time VBT (s)

- conversion (mol%) - expansion EXPA (mole·mole-1

)

- internal wall temperature TWI (K) - interface temperature TINTC (K)

- external wall temperature TWE (K) - heat flux QF (kJ·m-2·s-1)

- Reynolds number RE - Prandtl number PRNDL

- Nu-number ANU - convection coefficient (kJ·m-2·K-1)

- coke layer thickness DCOKES (m) - coking rate (g·h·m-²)

- coke yield COKEYIELD (wt%) - CO yield (wt%)


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Figure 3.10: First part a reactor.txt file

At the end of the file, the product yields at the reactor outlet are given, as shown in Figure 3.11.


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Figure 3.11: Second part a reactor.txt file

Next to the results.txt file, 3 other output files are generated: yields.csv, containing the product

yields at the reactor outlet; yieldprofiles.csv, containing the profiles of the main products as a

function of the axial position; and general_info.csv, containing pressure, temperature and heat flux

profiles, as a function of the axial position.


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Figure 3.12: yields.csv


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Figure 3.13: yield_profiles.csv


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Figure 3.14: general_info.csv


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3.6.3 SensitivityOverview.csv

If multiple simulations are carried out (in batch or a sensitivity analysis), the file

sensitivityoverview.csv is created. This file is located in “%appdata%\coilsim1d\Projects” for

batch simulations and “%appdata%\coilsim1d\Projects\name” for a sensitivity analysis.

This file contains an overview of all the important conditions, as well as all the important products

for each simulation. A warning will be generated if COILSIM1D was unable to create this file.

3.6.4 RunlengthOverview.csv

If a run length simulation is carried out, another file called runlenghtoverview.csv is created. This

file is located in “%appdata%\Projects\name”. It contains an overview of all important conditions

as well as all the important products for each time step in the run length simulation. A warning will

be generated if COILSIM1D was unable to create this file.

3.7 Running COILSIM1D

When using COILSIM1D for the first time, or running an updated version for the first time, you

need to start the GUI first, which can be done by pressing the shortcut on the desktop or in the

Start menu. When the GUI is launched for the first time it creates a directory

“%appdata%\coilsilm1D” where the input files for manual simulations can be found, as well as the

projects created with the GUI.


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3.8 COILSIM1D GUI

The first pop-up screen of COILSIM1D looks like this. Pressing the ‘start COILSIM1D’ button

allows you to continue to the main application window.


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The main application window gives an indication of the basic build-up of COILSIM1D:

information about the reactor, the feedstock and the process conditions needs to be specified to

obtain simulation results. Typical input files for each part are alsi included with COILSIM1D.

First, you have to start clicking on the ‘New’ button. The latter can also be found in the Project

menu.

By clicking on “new”, the following pop-up screen appears in the application:

Here, a name for the project has to be entered. The name will also be the name that all the input

and output files will be saved to. After pressing “Ok” the following window pops up:


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There are three options: importing an existing input file; creating a detailed input file using

detailed input; or using the predefined coil option. The last option allows to specify the necessary

coil information in a straightforward way. In the next example, a detailed coil geometry is

imported.

The detailed geometry screen looks as follows:


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If the predefined coil option is selected, then the user can choose between the following coil

options: millisecond coil, U coil, W coil, SRT- SRT VI coils, GK I and GK VI coils, and a set of

pyrocrack coils.

If the millisecond coil is chosen, the following screen appears:


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Figure 3.15: detailed geometry of SRT V coil


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The pop-up screen is different for each predefined coil geometry because the necessary input for

all these coils varies accordingly. The specified coil characteristics can be saved to a text file, to

use later in a next simulation without having to provide all the input values again. For an SRT V

coil with a geometry as the one specified in Figure 3.15, the input screen looks as follows:

After clicking on “Continue”, some more information about the reactor is required, as well as the

calculation method for the conductivity coefficient of the gas and the correlation used to calculate

the friction coefficient. In case of a custom coil reactor, this information is already entered in the

previous step and this step will be skipped.


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In this window it is also possible to add new materials to the Coilsim1D material database. When

right clicking on the material drop down box the following menu appears:

If you then click on “Add new material”, the following window appears:


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Here, the coefficients used in the equations to calculate the conductivity coefficient of the material

have to be entered, as well as the expansion coefficient of the material.

If in the preceding screen the “Continue” button is clicked, a new pop-up screen appears. In this

screen, the necessary input for the feedstock should be provided. Three options exist: using a set of

commercial indices, using the detailed naphtha composition, or using the detailed PIONA matrix.

Again, there is always an open option which allows you to import a specific file. Note that when

opening a specific feed file, you have to be on the corresponding tab-page. For example, if willing

to use a set of commercial indices previously saved to a text file, then you have to be on the

commercial indices tab-page, presented below. The same holds for the detailed composition tab

page and the PIONA weight fractions tab page.


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If the commercial index tab page is used, then the necessary input for SimCO should be provided.

SimCO works with any set of commercial indices, and as can be expected, more data will increase

the accuracy of the results. By clicking the composition button SimCO is automatically started.

As mentioned earlier, a detailed composition can also be used as input for COILSIM1D. The list of

components can be found in Appendix A of this manual. Additionally, in the GUI, all the

components which can be used are present in the drop-down boxes.


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The third and final option for specifying the feedstock composition is using a detailed PIONA

matrix as input. In this case, the weight fractions following from a detailed PIONA GC analysis

can be given as input for SimCO. The latter creates a proper nafta.i file for COILSIM1D.

Clicking on the “Composition” button takes the user to the conditions input screen, which presents

four options: working with a predefined process gas temperature and pressure profile, working

with a heat flux or external tube wall temperature profile, or using a set of outlet conditions. By

switching between profile and outlet conditions, one of the 4 possibilities can be selected.


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If the outlet conditions option is selected, the following screen is displayed:


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When “Output conditions” is selected, it is possible to execute a sensitivity analysis of the

following variables: HC mass flow, coil inlet temperature, steam dilution, temperature related

severity and pressure related severity. Only one sensitivity can be executed in a single run. When

clicking on “Continue”, the final input screen, i.e. the run length simulation, screen pops up.

Here the user can decide whether or not to execute a run length simulation. If the checkbox “Yes”

is selected, the GUI will look as follows:


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Clicking on “Continue” will start the calculations of COILSIM1D. During this calculations, the

screen will look like this:


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If COILSIM1D fails to converge, an error message will pop-up. The detailed results can be

checked in the ‘Results’ menu. Here the results can be visualized using Microsoft Excel, or they

can simply be read by opening the results.txt file.

Note that to save the results of a specific simulation, the output files have to be renamed or copied

into a new directory. The GUI allows also to quickly browse the simulation results. The “Results”

form consists of four tab pages. The first tab option ‘yield profiles’ allows to visualize the main

product yields as a function of the axial reactor position.


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On the second tab page ‘General info’, information about the process gas temperature profile and

the external and internal wall temperature profiles are given. Also the pressure profile and coking

rate profile, as well as the coke thickness can be seen here.


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The third ‘Yields’ tab page shows a summary of the main product yields, divided in 5 different

groups: Permanent gases, light alkenes, light alkanes, pyrolysis gasoline, and Fuel oil.

On the fourth tab, an overview of the most important parameters and simulation results are

summarized:


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If a sensitivity analysis is carried out, the Results window contains another tab called Sensitivity.

Here, all variables can be plotted as a function of the chosen variable.

Note that if you encounter difficulties in running a specific simulation and you have verified the

input you provided, please contact the developer of COILSIM1D on the following e-mail address:

[email protected]. Also when there are specific options you would like to see introduced

in COILSIM1D please feel free to provide any suggestions to the developer team.

mailto:[email protected]

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Chapter 4:

Feedstock Definition

Introduction 4.1

COILSIM1D works with a detailed feedstock composition. Since a large number of

molecular components are considered in the reaction network of COILSIM1D, the user has a

certain level of flexibility in defining the molecular composition. Therefore, in this chapter,

several guidelines are given to properly select an adequate molecular composition for a given

feedstock.

Molecular components 4.2

In Chapter 1, an overview of the different molecular components considered in the reaction

network is given. The current reaction network considers more than 700 different molecules.

Many components are so-called pseudo components or lumped components and they represent

several molecules. Which components are lumped, and which not, is explained extensively in

section 1.3.1. In Appendices A and B the numbers of the different components are given.

When a feedstock composition is given it has to be 'transformed' to the components

available in the reaction network. This is most readily done by means of Table 4.1. For each

carbon number the available components are classified as n-paraffins, isoparaffins (mono-, di-,

tri- and tetra- substituted), olefins (1- and 2- olefins, subdivided in normal and iso components),

naphthenes (5- and 6-rings, subdivided in non-, mono- and di-olefinic components) and aromatic

components. Shaded entries in Table 1 indicate lumped components. The following section deals

with the problems that might be encountered when transforming a given feedstock.

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Table 4.1: Components available for feedstock definition in the reaction network for steam cracking. Shaded entries indicate lumped components.

C0 C1 C2 C3 C4 C5 C6 C7 C8 C9 n-paraffins 1* H2 2 CH4 5 C2H6 9 C3H8 15 nC4H10 29 n C5 243 C6 npar 244 C7 npar 245 C8 npar 246 C9 npar isoparaffins 286** C9 ipar mono 14 iC4H10 28 iso C5 74 C6 2mip 271 C7 2mip 272 C8 2mip 273 C9 2mip 27 Neo C5 275 C6 3mip 276 C7 3mip 277 C8 3mip 278 C9 3mip

325 C7 3etp 280 C8 4mip 281 C9 4mip 326 C8 3etp 327 C9 3etp di 311 C6 23dm 312 C7 23dm 313 C8 23dm 314 C9 23dm 608 C6 22dm 316 C7 24dm 317 C8 24dm 318 C9 24dm 609 C7 22dm 320 C8 25dm 321 C9 25dm

613 C7 33dm 610 C8 22dm 323 C9 26dm 614 C8 33dm 611 C9 22dm 621 C8 34dm 615 C9 33dm 627 C8 2m3e 622 C9 34dm 628 C9 2m3e tri 617 C7 223t 618 C8 223t 619 C9 223t 624 C8 234t 625 C9 234t tetra

olefins mono n 3* C2H2 6* C3H4(MA) 11 1C4H8 22 1C5H10 32 C6ol 36 C7ol 104 1 C8 ol 105 1 C9 ol 4 C2H4 8 C3H6 12 2C4H8 23 2C5H10 129 2 C6 ol 130 2 C7 ol 131 2 C8 ol 132 2 C9 ol iso 13 iC4H8 24 2m1C4H8 33 iC6ol 37 iC7ol 661 iC8ol 662 iC9ol 25 3m1C4H8 26 2m2C4H8 di n 7 C3H4(PD) 10 1,3 C4H6 19 13C5di 30 C6di 34 C7di 38 C8di 81 C9di 632 C4H4 20 14C5di iso 21 Isoprene 31 iC6di-1 35 iC7di 39 iC8di 639 iC9di 75 iC6di-2 naphthenes 5-ring 40 cyC5 43 mcyC5 329 C7 ncy5 330 C8 ncy5 331 C9 ncy5 630 dm cyC5 381 C8 icy5 382 C9 icy5

631 tm cyC5 1 41 cyC5ol 44 mcyC5ol 2 42 CPD 45 mCPD

6-ring 46 cyC6 49 mcyC6 52 t13dmcy6 356 C9 ncy6 55 etcyC6 407 C9 icy6 633 tm cyC6 1 47 cyC6ol 50 mcyC6ol 53 dmcyC6ol 156 C9 cyol

58 vicyC6ol 56 etcyC6ol 2 48 cyC6di 51 mcyC6di 54 dmcyC6di 59 vicyC6di 57 etcyC6di aromatics 60 Benzene 61 Toluene 62 Xylene 489 C9 1aro 63 etBenz 69 Indene 64 Styrene 65 iP-C9aro 66 C9arool

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C10 C11 C12 C13 C14 C15 C16 C17 C18 C19 n-paraffins 247 C10 npar 248 C11 npar 249 C12 npar 250 C13 npar 251 C14 npar 252 C15 npar 253 C16 npar 254 C17 npar 255 C18 npar 256 C19 npar isoparaffins 287** C10 ipar 288 C11 ipar 289 C12 ipar 290 C13 ipar 291 C14 ipar 292 C15 ipar 293 C16 ipar 294 C17 ipar 295 C18 ipar 296 C19 ipar mono 274 C10 2mip 279 C10 3mip

282 C10 4mip 328 C10 3etp di 315 C10 23dm 319 C10 24dm 322 C10 25dm

324 C10 26dm 612 C10 22dm 616 C10 33dm 623 C10 34dm 629 C10 2m3e tri 620 C10 223t 626 C10 234t tetra 635 Pristaan

olefins mono n 106 1 C10 ol 107 1 C11 ol 108 1 C12 ol 109 1 C13 ol 110 1 C14 ol 111 1 C15 ol 112 1 C16 ol 113 1 C17 ol 114 1 C18 ol 115 1 C19 ol 133 2 C10 ol 134 2 C11 ol 135 2 C12 ol 136 2 C13 ol 137 2 C14 ol 138 2 C15 ol 139 2 C16 ol 140 2 C17 ol 141 2 C18 ol 142 2 C19 ol iso 663 iC10ol 664 iC11ol 665 iC12ol 666 iC13ol 667 iC14ol 668 iC15ol 669 iC16ol 670 iC17ol 671 iC18ol 672 iC19ol di n 82 C10di 83 C11di 84 C12di 85 C13di 86 C14di 87 C15di 88 C16di 89 C17di 90 C18di 91 C19di iso 639 iC10di 640 iC11di 641 iC12di 85 iIC13di 642 iC14di 643 iC15di 644 iC16di 645 iC17di 646 iC18di 647 iC19di naphthenes 5-ring 0 332 C10 ncy5 333 C11 ncy5 334 C12 ncy5 335 C13 ncy5 336 C14 ncy5 337 C15 ncy5 338 C16 ncy5 339 C17 ncy5 340 C18 ncy5 341 C19 ncy5 383 C10 icy5 384 C11 icy5 385 C12 icy5 387 C13 icy5 388 C14 icy5 389 C15 icy5 390 C16 icy5 392 C17 icy5 393 C18 icy5 394 C19 icy5

6-ring 0 357 C10 ncy6 358 C11 ncy6 359 C12 ncy6 360 C13 ncy6 361 C14 ncy6 362 C15 ncy6 363 C16 ncy6 364 C17 ncy6 365 C18 ncy6 366 C19 ncy6 408 C10 icy6 409 C11 icy6 410 C12 icy6 411 C13 icy6 412 C14 icy6 413 C15 icy6 414 C16 icy6 415 C17 icy6 416 C18 icy6 417 C19 icy6 1 157 C10 cyol 158 C11 cyol 159 C12 cyol 160 C13 cyol 161 C14 cyol 162 C15 cyol 163 C16 cyol 164 C17 cyol 165 C18 cyol 166 C19 cyol

2 aromatics 490 C10 1aro 491 C11 1aro 492 C12 1aro 493 C13 1aro 494 C14 1aro 495 C15 1aro 496 C16 1aro 497 C17 1aro 498 C18 1aro 499 C19 1aro 514 C10 iaro 515 C11 iaro 516 C12 iaro 517 C13 iaro 518 C14 iaro 519 C15 iaro 520 C16 iaro 521 C17 iaro 522 C18 iaro 523 C19 iaro 70 mIndene 73*** Biphenyl 686 anthracen 688 methylant 690 pyrene 687 phenan 689 methylph 71 Naphth 72 mNaphth 538 C12 2aro 539 C13 2aro 540 C14 2aro 541 C15 2aro 542 C16 2aro 543 C17 2aro 544 C18 2aro 545 C19 2aro 560 C15 3aro 561 C16 3aro 562 C17 3aro 563 C18 3aro 564 C19 3aro 691 C17 4aro 692 C18 4aro 693 C19 4aro 68*** C10arool 179 C11arool 180 C12arool 181 C13arool 182 C14arool 183 C15arool 184 C16arool 185 C17arool 186 C18arool 187 C19arool

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C20 C21 C22 C23 C24 C25 C26 C27 C28 C29 n-paraffins 257 C20 npar 258 C21 npar 259 C22 npar 260 C23 npar 261 C24 npar 262 C25 npar 263 C26 npar 264 C27 npar 265 C28 npar 266 C29 npar isoparaffins 297** C20 ipar 298 C21 ipar 299 C22 ipar 300 C23 ipar 301 C24 ipar 302 C25 ipar 303 C26 ipar 304 C27 ipar 305 C28 ipar 306 C30 ipar mono

di

tri tetra 635 Pristaan

olefins mono n 116 1 C20 ol 117 1 C21 ol 118 1 C22 ol 119 1 C23 ol 120 1 C24 ol 121 1 C25 ol 122 1 C26 ol 123 1 C27 ol 124 1 C28 ol 125 1 C29 ol 143 2 C20 ol 144 2 C21 ol 145 2 C22 ol 146 2 C23 ol 147 2 C24 ol 148 2 C25 ol 149 2 C26 ol 150 2 C27 ol 151 2 C28 ol 152 2 C29 ol iso 663 iC10ol 664 iC11ol 665 iC12ol 666 iC13ol 667 iC14ol 668 iC15ol 669 iC16ol 670 iC17ol 671 iC18ol 672 iC19ol di n 92 C20di 93 C21di 94 C22di 95 C23di 96 C24di 97 C25di 98 C26di 99 C27di 100 C28di 101 C29di iso 639 iC10di 640 iC11di 641 iC12di 85 iIC13di 642 iC14di 643 iC15di 644 iC16di 645 iC17di 646 iC18di 647 iC19di naphthenes 5-ring 0 342 C20 ncy5 393 C20 icy5

6-ring 0 367 C20 ncy6 418 C20 icy6 1 167 C20 cyol

2 aromatics 500 C20 1aro 524 C20 iaro 546 C20 2aro 565 C20 3aro 694 C20 4aro 695 C21 4aro 696 C22 4aro 697 C23 4aro 698 C24 4aro 188** C20arool 189 211arool 190 C22arool 191 213arool

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C30 C31 C32 C33 n-paraffins 267 C30 npar 268 C31 npar 269 C32 npar 270 C33 npar isoparaffins 307** C30 ipar 308 C31 ipar 309 C32 ipar 310 C33 ipar mono

di

tri tetra

olefins mono n 126 1 C30 ol 127 1 C31 ol 128 1 C32 ol 153 2 C30 ol 154 2 C31 ol 155 2 C32 ol iso di n 102 C30di 103 C31di 104 C32di iso naphthenes 5-ring 0

6-ring 0 1

2 aromatics

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Feedstock transformation 4.3

When transforming a given feedstock composition to the components available in the

reaction network, one of the following four situations can occur:

A. A component or a lump in the given feedstock composition also exists in the reaction

network

B. A lump in the given feedstock composition needs to be represented by specific

suitable components in the reaction network

C. One or several components in the given feedstock can or need to be represented by a

suitable lump in the reaction network

D. A specific component or lump in the given feedstock does not exist in the reaction

network, neither as a specific component nor as a suitable lump

For situations A and C, the approach is straightforward and leads to a unique definition of the

feedstock in the reaction network. When situation B is encountered, a distribution key has to be

chosen to divide the given lump over the suitable specific components in the reaction network.

This can be done in (at least) four different ways:

1. Equal (linear) distribution of the mass fraction of the lump over the available, specific

components in the reaction network [B1]

2. Assigning the mass fraction of the lump to one specific component in the reaction

network [B2]

3. Distribution of the mass fraction of the lump over the available, specific components

in the reaction network according to an experimentally pre-determined distribution

key (Vercauteren, 1991) [B3]

4. Distribution of the mass fraction of the lump over the available, specific components

in the reaction network according to a distribution key based on thermodynamic

considerations [B4]

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Hillewaert (1986) determined an experimental distribution key for lumps of isoparaffinic

components, based on a number of naphtha and kerosene analyses (Vercauteren, 1991), see

Table 1.2. When a number of isomers given in Table 1.2 cannot exist in a specific lump (i.e. C7

isoparaffin cannot contain a 5-methyl component) the remaining distribution factors can be used

after re-scaling. In case situation D is encountered, there are again four ways to treat the given

feedstock component or lump:

1. The mass fraction of the given component or lump can be assigned to a similar

component or lump in the reaction network [D1]

2. The given component or lump can be eliminated from the feedstock by assigning its

mass fraction to the most abundant component in the feedstock [D2]

3. The given component or lump can be eliminated from the feedstock by re-scaling the

mass fraction of all remaining feedstock components and keeping the total mass flow

constant [D3]

4. The given component or lump can be eliminated from the feedstock by re-scaling the

mass fraction of all remaining feedstock components and decreasing the total mass

flow according to the eliminated component [D4]

The first option comes down to replacing heavier feedstock components that are not present in

the network by a similar component with a lower carbon number. It is for example possible to

replace the C20+ branched 6 ring naphthenes by an existing branched 6 ring naphthene with the

highest carbon number (i.e. C20 n-paraffin). In the same way, one can consider replacing non-

existing di-olefins by mono-olefins with the same carbon number. When dealing with small

amounts of 'insignificant' components or when no similar components can be found, the last

three options might become more appropriate. In this context, 'insignificant' means that such

components are not expected to have a large influence on the obtained product distribution.

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Influence of feedstock definition on product distribution 4.4

In this section, an example of transformation of a given feedstock to the components

available in the reaction network is given. A number of COILSIM1D simulations are carried out

to illustrate the effect of different transformation strategies. On the left-hand side of Table 4.2,

the original feedstock composition is given. The first three columns indicate the provided name,

its shorthand notation and its number. The fourth column contains the mass fraction (wt%) of

each of these components in the feedstock. On the right-hand side, the names and numbers of the

components that can be used to describe the original feedstock are indicated. The last column

specifies the type of transformation that can be used (A, Bx, C, Dx). In this specific case, about

68 wt% of the feedstock composition can be directly transformed to components in the reaction

network (transformation type A). About 30 wt% consists of lumped components that need to be

specified in the reaction network and for which a distribution key has to be chosen

(transformation type Bx). The remaining 2 wt% of the original feedstock had to be transformed

using transformation type Dx. Several distribution keys were tested for the following lumps:

• C6, C7 and C8 isoparaffins

• C7 naphthenes

• C9 aromatics

In other cases, a linear distribution key was chosen. In Table 4.3 the resulting feed

definitions used for these simulations are summarised. Simulations S1, S2, S3 and S4 differ in

the distribution key for the C6, C7 and C8 isoparaffins, simulations S5, S6, S7, S8 and S9

illustrate the effect of the C7 naphthene specification and simulations S10, S11, S12 and S13 the

effect of the C9 aromatics transformation. The shaded areas indicate the differences in the

transformation used. For simulations S1 to S4 the transformations are B1, B2, B2 and B3

respectively. For simulations S5 to S13 transformation type B2 is used for the lumped

component under consideration, using a different key component in each simulation. The

simulations provide information about the effect of the choice of several specific feed

components on the product distribution.

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Table 4.2: Example of the transformation of a given feedstock

Specified Composition COILSIM1D Specified Composition COILSIM1D n-butane NBUTA 14 0.80 → n-C4H10 15 A C8 isoparaffin C8ISO 58 5.10 → Bx isobutane IBUTA 15 1.30 → i-C4H10 14 A C8 4mip 280 cyclopentane CPTAN 21 0.60 → cyC5 40 A C8 3etp 326 n-pentane NC5 25 7.80 → n C5 29 A C8 23dm 313 isopentane IC5 26 6.50 → iso C5 28 A C8 24dm 317 benzene BENZ 27 2.30 → benzene 60 A C8 25dm 320 cyclohexane CESAN 36 0.80 → cyC6 46 A C8 22dm 610 methylcyclopentane MCPTA 37 1.20 → mcyC5 43 A C8 33dm 614 C6 n-paraffin NC6 39 6.90 → C6 npar 243 A C8 34dm 621 C6 isoparaffin C6ISO 40 6.60 → Bx C8 2m3e 627

C6 2mip 74 C8 223t 618 C6 3mip 275 C8 234t 624 C6 23dm 311 C9 aromatic C9ARO 61 1.75 → Bx C6 22dm 608 C9 1aro 489

toluene TOLUO 41 1.10 → toluene 61 A Indene 69 C7 naphthen C7NAF 47 3.60 → Bx iP-C9aro 65

C7 ncy5 329 C9arool 66 dmcyC5 630 C9 naphthene C9NAF 62 3.95 → Bx mcyC6 49 C9 ncy5 331 mcyC6ol 50 C9 icy5 382 mcyC6di 51 C9 ncy6 356

C7 n-paraffin NC7 48 5.80 → C7 npar 244 A C9 icy6 407 C7 isoparaffin C7ISO 49 5.40 → Bx tm cyc6 633

C7 2mip 271 C7 3mip 276 C9 n-paraffin NC9 63 3.00 → C9 npar 246 A C7 3etp 325 C9 isoparaffin C9ISO 64 4.10 → C9 ipar 286 A C7 23dm 312 → Bx C7 24dm 316 C9 2mip 273 C7 22dm 609 C9 3mip 278 C7 33dm 613 C9 4mip 281 C7 223t 617 C9 3etp 327

xylene XILO 51 0.96 → xylene 62 A C9 23dm 314 ethylbenzene EBENZ 52 0.24 → etBenzene 63 A C9 24dm 318 C8 naphthene C8NAF 56 3.00 → Bx C9 25dm 321

t1,3dmcyC6 52 C9 26dm 323 etcyC6 55 C9 22dm 611 C8 ncy5 330 C9 33dm 615 C8 icy5 381 C9 34dm 622

C8 n-paraffin NC8 57 4.10 → C8 npar 245 A C9 2m3e 628 C8 isoparaffin C8ISO 58 5.10 → Bx C9 223t 619

C8 2mip 272 C9 234t 625 C8 3mip 277 C10 n-paraffin NC10 67 4.16 → C10 npar 247 A

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Specified Composition COILSIM1D Specified Composition COILSIM1D

C10 isoparaffin C10IS 68 6.22 → C10 ipar 287 A C21 naphthene NAF21 95 0.16 → D1 → Bx C20 ncy5 342 C10 2mip 274 C20 ncy6 367 C10 3mip 279 C20 icy5 393 C10 4mip 282 C20 icy6 418 C10 3etp 328 C20 n-paraffin NC20 96 0.14 → C20 npar 255 A

C10 23dm 315 C20 isoparaffin ISO20 97 0.25 → C20 ipar 294 A C10 24dm 319 C10 25dm 322 C10 26dm 324

C10 22dm 612 C10 33dm 616 C10 34dm 623 C10 2m3e 629

C10 223t 620 C10 234t 626 C11 di-olefine DNA11 70 0.71 → C11di 83 A C12 mono aromatic C12AR 74 0.97 → Bx

C12 1aro 492 C12 iaro 516

C12 naphthene NAF12 75 3.57 → Bx C12 ncy5 334 C12 icy5 385 C12 ncy6 359 C12 icy6 410

C14 di-olefine DIA14 76 0.26 → C14di 86 A C15 mono aromatic C15AR 78 0.06 → Bx

C15 1aro 492 C15 iaro 516

C15 di-naphtene DNA15 79 0.33 → D1 + Bx

C12 ncy5 334 C12 ncy6 359 C12 icy5 385 C12 icy6 410

C15 naphthene NAF15 80 1.50 → D1 + Bx

C15 ncy5 337 C15 ncy6 362 C15 icy5 388

C15 icy6 413 C15 n-paraffin NC15 81 1.91 → C15 npar 252 A C15 isoparaffin ISO15 82 2.82 → C15 ipar 292 A polycondensate FUEL2 84 0.02 → n C5 29 D2

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Table 4.3: Feed compositions (mass fractions). The shaded areas indicate where the relevant differences in the distribution key occur.

Number S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13

n-C4H10 15 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 i-C4H10 14 0.013 0.013 0.013 0.013 0.013 0.013 0.013 0.013 0.013 0.013 0.013 0.013 0.013 cyC5 40 0.006 0.006 0.006 0.006 0.006 0.006 0.006 0.006 0.006 0.006 0.006 0.006 0.006 n C5 29 0.078943 0.078942 0.078942 0.078942 0.078943 0.078943 0.078943 0.078943 0.078943 0.078943 0.078943 0.078943 0.078943 iso C5 28 0.065 0.065 0.065 0.065 0.065 0.065 0.065 0.065 0.065 0.065 0.065 0.065 0.065 benzene 60 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 0.023 cyC6 46 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 0.008 mcyC5 43 0.012 0.012 0.012 0.012 0.012 0.012 0.012 0.012 0.012 0.012 0.012 0.012 0.012 C6 npar 243 0.069 0.069 0.069 0.069 0.069 0.069 0.069 0.069 0.069 0.069 0.069 0.069 0.069 C6 2mip 74 0.0165 0.066 0.027434 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 C6 3mip 275 0.0165 0.066 0.030614 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 C6 23dm 311 0.0165 0.007952 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 C6 22dm 608 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 0.0165 toluene 61 0.011 0.011 0.011 0.011 0.011 0.011 0.011 0.011 0.011 0.011 0.011 0.011 0.011 C7 ncy5 329 0.0072 0.0072 0.0072 0.0072 0.036 0.0072 0.0072 0.0072 0.0072 dmcyC5 630 0.0072 0.0072 0.0072 0.0072 0.036 0.0072 0.0072 0.0072 0.0072 mcyC6 49 0.0072 0.0072 0.0072 0.0072 0.036 0.0072 0.0072 0.0072 0.0072 mcyC6ol 50 0.0072 0.0072 0.0072 0.0072 0.036 0.0072 0.0072 0.0072 0.0072 mcyC6di 51 0.0072 0.0072 0.0072 0.0072 0.036 0.0072 0.0072 0.0072 0.0072 C7 npar 244 0.058 0.058 0.058 0.058 0.058 0.058 0.058 0.058 0.058 0.058 0.058 0.058 0.058 C7 2mip 271 0.00675 0.054 0.015634 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 C7 3mip 276 0.00675 0.054 0.017446 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 C7 3etp 325 0.00675 0.014425 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 C7 23dm 312 0.00675 0.004531 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 C7 24dm 316 0.00675 0.001964 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 C7 22dm 609 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 C7 33dm 613 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 C7 223t 617 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 0.00675 xylene 62 0.0096 0.0096 0.0096 0.0096 0.0096 0.0096 0.0096 0.0096 0.0096 0.0096 0.0096 0.0096 0.0096 etBenzene 63 0.0024 0.0024 0.0024 0.0024 0.0024 0.0024 0.0024 0.0024 0.0024 0.0024 0.0024 0.0024 0.0024 t1,3dmcyC6 52 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 etcyC6 55 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 C8 ncy5 330 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 C8 icy5 381 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 0.0075 C8 npar 245 0.041 0.041 0.041 0.041 0.041 0.041 0.041 0.041 0.041 0.041 0.041 0.041 0.041 C8 2mip 272 0.003923 0.051 0.012523 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 C8 3mip 277 0.003923 0.051 0.013975 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 C8 4mip 280 0.003923 0.007744 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923

Confidential

Number S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13

C8 3etp 326 0.003923 0.011555 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 C8 23dm 313 0.003923 0.00363 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 C8 24dm 317 0.003923 0.001573 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 C8 25dm 320 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 C8 22dm 610 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 C8 33dm 614 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 C8 34dm 621 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 C8 2m3e 627 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 C8 223t 618 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 C8 234t 624 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 0.003923 C9 1aro 489 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.0175 Indene 69 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.0175 iP-C9aro 65 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.0175 C9arool 66 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.004375 0.0175 C9 ncy5 331 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 C9 icy5 382 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 C9 ncy6 356 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 C9 icy6 407 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 tm cyC6 633 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 0.006583 C9 npar 246 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 C9 ipar 286 0.041 0.041 0.041 0.041 0.041 0.041 0.041 0.041 0.041 0.041 0.041 0.041 0.041 C10 npar 247 0.0416 0.0416 0.0416 0.0416 0.0416 0.0416 0.0416 0.0416 0.0416 0.0416 0.0416 0.0416 0.0416 C10 ipar 287 0.0622 0.0622 0.0622 0.0622 0.0622 0.0622 0.0622 0.0622 0.0622 0.0622 0.0622 0.0622 0.0622 C11di 83 0.0071 0.0071 0.0071 0.0071 0.0071 0.0071 0.0071 0.0071 0.0071 0.0071 0.0071 0.0071 0.0071 C12 1aro 492 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 C12 iaro 516 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 0.00488 C12 ncy5 334 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 C12 icy5 385 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 C12 ncy6 359 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 C12 icy6 410 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 0.0139 C14di 86 0.0026 0.0026 0.0026 0.0026 0.0026 0.0026 0.0026 0.0026 0.0026 0.0026 0.0026 0.0026 0.0026 C15 npar 252 0.0191 0.0191 0.0191 0.0191 0.0191 0.0191 0.0191 0.0191 0.0191 0.0191 0.0191 0.0191 0.0191 C15 ipar 292 0.0282 0.0282 0.0282 0.0282 0.0282 0.0282 0.0282 0.0282 0.0282 0.0282 0.0282 0.0282 0.0282 C18 npar 255 0.0014 0.0014 0.0014 0.0014 0.0014 0.0014 0.0014 0.0014 0.0014 0.0014 0.0014 0.0014 0.0014 C17 ipar 294 0.0025 0.0025 0.0025 0.0025 0.0025 0.0025 0.0025 0.0025 0.0025 0.0025 0.0025 0.0025 0.0025

143

Confidential

Figure 4.1: Heat flux profile used for the COILSIM1D simulations presented in this work.

In Table 4.4, the simulation conditions are summarized. Figures 4.2 to 4.10 show the results

of the different simulations for the concentration profiles of the six most important products

(ethylene, propylene, benzene, 1,3-butadieen, methane and hydrogen) and the propylene to

ethylene ratio (PER) as a measure for the severity. The process gas temperature and the coking

rate as a function of the axial distance in the reactor are also indicated. Figures 4.2, 4.3 and 4.4

show the results for simulations S1 to S4; Figures 4.5, 4.6 and 4.7 for simulations S5 to S9 and

Figures 4.8, 4.9 and 4.10 the results for simulations S10 to S13. In the next section, the most

important results will be discussed.

axial distance [m]

0 10 20 30 40 50 60

heat

flux

[kca

l·min

w-2

·s-1

]

0

10

20

30

40

50

144

Confidential

Table 4.4: Reactor conditions for the COILSIM1D simulations with feedstock definitions S1 to

S13 as summarized in Table 4.3

Heat flux profile Figure 4.1

Inlet temperature 873 K

Hydrocarbon flow 2625 kg/h

Steam dilution 0.40 kgH2O/kgHC

Inlet pressure 2.532 atm

Reactor length (8 passes) 56.6684 m

Reactor (internal) diameter 0.1143 m

Coil Outlet Pressure 1.9 atm

Coil Outlet Temperature 1113 K

4.4.1 C6, C7 and C8 isoparaffins

For simulations S1 to S4, the isoparaffins under consideration amount to 17.1 wt% of the

total feedstock. When comparing the concentration profiles for simulations S2 (3-methyl) and S3

(2-methyl), it is obvious that in simulation S3 the production of propylene is more pronounced.

This can be easily explained since bond breakage in a 2-methyl compound can immediately give

rise to a propylene precursor (a propyl radical). In the same way, bond breakage in a 3-methyl

compound can lead to a precursor for 1,3-butadieen (a butyl radical), which explains the slightly

higher production of this component in simulation S2. The ethylene production seems to be

mostly determined by the fraction of the 2- and 3-methyl components in the lump. Substitution

of these components by the remaining isoparaffins in the lump will therefore lead to a reduction

in the ethylene production. The propylene production, on the other hand, seems to be mostly

dependent on the 2-methyl concentration. Substitution with other isoparaffins than 2-methyl

appears to decrease the propylene production. These effects are also reflected in the propylene to

ethylene ratio (PER). The influence of the isoparaffin distribution on the process gas temperature

and the coking rate is rather small in these cases.

Confidential

Figure 4.2: Ethylene, propylene, benzene and 1,3-butadiene mass fraction profiles, from COILSIM1D simulation results for feedstock definitions S1 to

S4 in Table 4.3, using the heat flux profile indicated in Figure 4.1

axial distance [m]

0 10 20 30 40 50 60

C2H

4 m

ass

frac

tion

[-]

0.00

0.05

0.10

0.15

0.20

0.25

0.30

axial distance [m]

0 10 20 30 40 50 60

C3H

6 m

ass

frac

tion

[-]

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

axial distance [-]

0 10 20 30 40 50 60

benz

ene

mas

s fr

actio

n [-

]

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

axial distance [m]

0 10 20 30 40 50 60

1,3-

C4H

6 m

ass

frac

tion

[-]

0.00

0.01

0.02

0.03

0.04

0.05

0.06

S3

S2

S4

S1

S3

S1

S4

S2

S1

S2

S4

S3

S2

S4

S3

S1

S3

S4

S1

S2

Confidential

Figure 4.3: Methane and hydrogen mass fraction profiles and Propylene to Ethylene Ratio (PER) profile, from COILSIM1D simulation results for

feedstock definitions S1 to S4 in Table 4.3, using the heat flux profile indicated in Figure 4.1

axial distance [m]

0 10 20 30 40 50 60

CH

4 m

ass

frac

tion

[-]

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

axial distance [m]

0 10 20 30 40 50 60

H2

mas

s fr

actio

n [-

]

0.0000

0.0010

0.0020

0.0030

0.0040

0.0050

0.0060

0.0070

0.0080

axial distance [m]

0 10 20 30 40 50 60

PE

R [-

]

0.5

0.6

0.7

0.8

0.9

1.0

1.1

S3

S1

S4

S2

S1

S2

S4

S3 S1

S4

S3

S2

Confidential

Figure 4.4: Process gas temperature and coking rate profiles, from COILSIM1D simulation results for feedstock definitions S1 to S4 in Table 4.3, using

the heat flux profile indicated in Figure 4.1

axial distance [m]

0 10 20 30 40 50 60

proc

ess

gas

tem

pera

ture

[o C]

550

600

650

700

750

800

850

900

axial distance [m]

0 10 20 30 40 50 60

coki

ng r

ate

[g·h

-1·m

-2]

0

1

2

3

4

5

6S1

S4

S2

S3

S1

S3

S4

S2

Confidential

Figure 4.5: Ethylene, propylene, benzene and 1,3-butadiene mass fraction profiles, from COILSIM1D simulation results for feedstock definitions S5 to

S9 in Table 4.3, using the heat flux profile indicated in Figure 4.1

axial distance [m]

0 10 20 30 40 50 60

C2H

4 m

ass

frac

tion

[-]

0.00

0.05

0.10

0.15

0.20

0.25

0.30

axial distance [m]

0 10 20 30 40 50 60

C3H

6 m

ass

frac

tion

[-]

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

axial distance [-]

0 10 20 30 40 50 60

benz

ene

mas

s fr

actio

n [-

]

0.00

0.02

0.04

0.06

0.08

0.10

0.12

axial distance [m]

0 10 20 30 40 50 60

1,3-

C4H

6 m

ass

frac

tion

[-]

0.00

0.01

0.02

0.03

0.04

0.05

0.06

S9

S5, S7, S8

S6

S6

S7

S5

S8

S9

S8

S9

S5, S6, S7

S7

S6, S5, S9

S8

Confidential

Figure 4.6: Methane, and hydrogen mass fraction profiles and Propylene to Ethylene Ratio (PER) profile, from COILSIM1D simulation results for

feedstock definitions S5 to S9 in Table 4.3, using the heat flux profile indicated in Figure 4.1

axial distance [m]

0 10 20 30 40 50 60

CH

4 m

ass

frac

tion

[-]

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

axial distance [m]

0 10 20 30 40 50 60

H2

mas

s fr

actio

n [-

]

0.0000

0.0010

0.0020

0.0030

0.0040

0.0050

0.0060

0.0070

0.0080

axial distance [m]

0 10 20 30 40 50 60

PE

R [-

]

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

S8, S9

S5, S6

S7

S8

S9

S5, S6, S7

S6

S7

S5

S8

S9

Confidential

Figure 4.7: Process gas temperature and coking rate profiles, from COILSIM1D simulation results for feedstock definitions S5 to S9 in Table 4.3, using

the heat flux profile indicated in Figure 4.1

axial distance [m]

0 10 20 30 40 50 60

proc

ess

gas

tem

pera

ture

[o C]

550

600

650

700

750

800

850

900

axial distance [m]

0 10 20 30 40 50 60

coki

ng r

ate

[g·h

-1·m

-2]

0

1

2

3

4

5

6

7S9

S8

S6

S5

S7

S9

S8

S6

S5

S7

Confidential

Figure 4.8: Ethylene, propylene, benzene and 1,3-butadiene mass fraction profiles, from COILSIM1D simulation results for feedstock definitions S10

to S13 in Table 4.3, using the heat flux profile indicated in Figure 4.1

axial distance [m]

0 10 20 30 40 50 60

C2H

4 m

ass

frac

tion

[-]

0.00

0.05

0.10

0.15

0.20

0.25

0.30

axial distance [m]

0 10 20 30 40 50 60

C3H

6 m

ass

frac

tion

[-]

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

axial distance [-]

0 10 20 30 40 50 60

benz

ene

mas

s fr

actio

n [-

]

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

axial distance [m]

0 10 20 30 40 50 60

1,3-

C4H

6 m

ass

frac

tion

[-]

0.00

0.01

0.02

0.03

0.04

0.05

0.06

S11

S10, S13

S12

S10, S11, S12, S13

S10, S11, S12, S13

S11

S13

S10

S12

Confidential

Figure 4.9: Methane and hydrogen mass fraction profiles, and Propylene to Ethylene Ratio (PER) profiles, from COILSIM1D simulation results for

feedstock definitions S10 to S13 in Table 4.3, usingthe heat flux profile indicated in Figure 4.1

axial distance [m]

0 10 20 30 40 50 60

CH

4 m

ass

frac

tion

[-]

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

axial distance [m]

0 10 20 30 40 50 60

H2

mas

s fr

actio

n [-

]

0.0000

0.0010

0.0020

0.0030

0.0040

0.0050

0.0060

0.0070

0.0080

axial distance [m]

0 10 20 30 40 50 60

PE

R [-

]

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

S13, S12

S10, S11

S10, S11, S12, S13

S10, S11, S12, S13

Confidential

Figure 4.10: Process gas temperature and coking rate profiles, from COILSIM1D simulation results for feedstock definitions S10 to S13 in Table 4.3,

using the heat flux profile indicated in Figure 4.1

axial distance [m]

0 10 20 30 40 50 60

proc

ess

gas

tem

pera

ture

[o C]

550

600

650

700

750

800

850

900

axial distance [m]

0 10 20 30 40 50 60

coki

ng r

ate

[g·h

-1·m

-2]

0

1

2

3

4

5

6

S10, S11, S12, S13

S10, S11, S12, S13

154

Confidential

4.4.2 C7 naphthenes

The influence of the C7 naphthenes (3.6 wt% of the total feedstock) distribution is shown in

Figures 4.5, 4.6 and 4.7. The concentration profiles indicate that there is little or no difference

between the results for simulations S5, S6 and S7, except that methyl cyclo-hexane (simulation

S7) seems to favour the production of 1,3-butadiene. However, large differences occur between

simulations S5, S6 and S7 and simulations S8 and S9. In these last two simulations, a large

increase in benzene, methane and hydrogen production is observed near the inlet of the reactor.

Near the outlet, a decrease in the propylene production is observed. The increase in benzene,

methane and hydrogen production can be explained by the fact that in simulations S8 and S9, the

specific components chosen to represent the C7 naphthenes contain an unsaturated C6 ring with

a methyl substituent. Because of the unsaturated C6 ring, fast dehydrogenation and splitting of

the methyl group will occur, producing hydrogen, methane and benzene. These effects also have

a large influence on the process gas temperature profile, and simulations S8 and S9 have higher

outlet temperatures compared to simulations S5, S6 and S7 (about 10 to 20 K). The small

temperature drop at the inlet of the reactor for simulation S8 is remarkable. The increase in

coking rate for simulations S8 and S9 is the result of the increase in process gas temperature, but

may also be influenced by the higher benzene concentration.

4.4.3 C9 aromatics

The influence of the C9 aromatics distribution is negligible on the concentration, process

gas temperature and coking rate profiles as can be seen in Figures 4.8, 4.9 and 4.10. This can be

the result of the relatively small fraction of the C9 aromatics in the feedstock (1.75 wt%) or these

components may also participate in a similar way in the reaction network (and might therefore be

lumped).

155

Confidential

Conclusions 4.5

• There are more than 700 components included in the reaction network for steam cracking

of hydrocarbons.

• In general, a provided feedstock definition will have to be transformed to a definition that

uses the available components in the reaction network

• The concentration of and the ratio between 2-methyl and 3-methyl isoparaffinic

compounds in the feedstock both have a relatively large influence on the product

distribution, in particular on the ethylene and propylene production. When this ratio is not

known for a given feedstock, assumptions have to be made concerning the distribution

key for these components. The choice of a pre-determined distribution key (e.g.

Vercauteren, 1991) seems to be most adequate in this case.

• Including naphthenic compounds with an unsaturated C6 ring in the feedstock definition

has a large influence on the production of benzene, hydrogen and, in case of methyl

substituents, on the production of methane. This is also reflected in the process gas

temperature and the coking rate. Consequently, these components should be chosen

carefully and used only when they are known to be present in the given feedstock.

• The choice of specific C9 aromatic components has a negligible influence on the product

distribution, process gas temperature and coking rate.

References 4.6

Vercauteren C. Rigoureuze Kinetische Schema’s voor de Thermische Kraking van Koolwaterstoffen, PhD dissertation, UGent, 1991.

Van Geem K.M. Single Event Microkinetic Model for Steam Cracking of Hydrocarbons, PhD dissertation, UGent, 2006.

Appendix A: List of Molecules in the Reaction Network

I

Appendix A:

List of Molecules in the Reaction Network

1 H2 2 CH4 3 C2H2 4 C2H4

5 C2H6 6 C3H4 (MA) 7 C3H4 (PD) 8 C3H6 9 C3H8 10 1,3 C4H6 11 1-C4H8 12 2-C4H8 13 i-C4H8 14 i-C4H10 15 n-C4H10 16 H2O 17 CO 18 CO2 19 1,3-C5di 20 1,4-C5di 21 isoprene 22 1-C5H10 23 2-C5H10 24 2m-1-C4H8 25 3m-1-C4H8 26 2m-2-C4H8 27 neo C5 28 iso C5 29 n C5 30 C6di 31 iC6di-1 32 C6ol 33 iC6ol 34 C7di 35 iC7di 36 C7ol 37 iC7ol 38 C8di 39 iC8di 40 cyC5 41 cyC5ol 42 CPD 43 mcyC5 44 mcyC5ol 45 mCPD 46 cyC6 47 cyC6ol 48 cyC6di 49 mcyC6 50 mcyC6ol 51 mcyC6di 52 t1,3dmcyC6 53 dmcyC6ol 54 dmcyC6di 55 etcyC6 56 etcyC6ol 57 etcyC6di 58 vicyC6ol 59 vicyC6di 60 benzene 61 toluene 62 xylene 63 etBenzene 64 styrene 65 iP-C9aro 66 vinyltoluene 67 Dm,etbenzene 68 Dm,vinyl benz. 69 indene 70 mIndene 71 Naphthalene 72 mNaphthalene 73 biphenyl 74 C6 2mip 75 iC6di-2 76 dmNaphthale 77 M,et-benzene 78 acenaphthylen 79 N2 80 m-vi-naphthal 81 C9di 82 C10di 83 C11di 84 C12di 85 C13di 86 C14di 87 C15di 88 C16di 89 C17di 90 C18di 91 C19di 92 C20di 93 C21di 94 C22di 95 C23di 96 C24di 97 C25di 98 C26di 99 C27di 100 C28di 101 C29di 102 C30di 103 C31di 104 1 C8 ol 105 1 C9 ol 106 1 C10 ol 107 1 C11 ol 108 1 C12 ol 109 1 C13 ol 110 1 C14 ol 111 1 C15 ol 112 1 C16 ol 113 1 C17 ol 114 1 C18 ol 115 1 C19 ol 116 1 C20 ol 117 1 C21 ol 118 1 C22 ol 119 1 C23 ol 120 1 C24 ol 121 1 C25 ol 122 1 C26 ol 123 1 C27 ol 124 1 C28 ol 125 1 C29 ol 126 1 C30 ol 127 1 C31 ol 128 1 C32 ol 129 2 C6 ol 130 2 C7 ol 131 2 C8 ol 132 2 C9 ol 133 2 C10 ol 134 2 C11 ol 135 2 C12 ol 136 2 C13 ol


II

137 2 C14 ol 138 2 C15 ol 139 2 C16 ol 140 2 C17 ol

141 2 C18 ol 142 2 C19 ol 143 2 C20 ol 144 2 C21 ol 145 2 C22 ol 146 2 C23 ol 147 2 C24 ol 148 2 C25 ol 149 2 C26 ol 150 2 C27 ol 151 2 C28 ol 152 2 C29 ol 153 2 30 ol 154 2 C31 ol 155 2 C32 ol 156 C9 cyol 157 C10 cydiol 158 C11 cydiol 159 C12 cydiol 160 C13 cydiol 161 C14 cydiol 162 C15 cydiol 163 C16 cydiol 164 C17 cydiol 165 C18 cydiol 166 C19 cydiol 167 C20 cydiol 168 C21 cydiol 169 C22 cydiol 170 C23 cydiol 171 C24 cydiol 172 C25 cydiol 173 C26 cydiol 174 C27 cydiol 175 C28 cydiol 176 C29 cydiol 177 C30 cydiol 178 C31 cydiol 179 C11 arol 180 C12 arol 181 C13 arol 182 C14 arol 183 C15 arol 184 C16 arol 185 C17 arol 186 C18 arol 187 C82 arol 188 C20 arol 189 C21 arol 190 C22 arol 191 C23 arol 192 C24 arol 193 C25 arol 194 C26 arol 195 C27 arol 196 C28 arol 197 C29 arol 198 C30 arol 199 C31 arol 200 C32 arol 201 C11 naol 202 C12 naol 203 C13 naol 204 C14 naol 205 C15 naol 206 C16 naol 207 C17 naol 208 C18 naol 209 C19 naol 210 C20 naol 211 C21 naol 212 C22 naol 213 C23 naol 214 C24 naol 215 C25 naol 216 C26 naol 217 C27 naol 218 C28 naol 219 C29 naol 220 C30 naol 221 C31 naol 222 C32 naol 223 C12 nadi 224 C13 nadi 225 C14 nadi 226 C15 nadi 227 C16 nadi 228 C17 nadi 229 C18 nadi 230 C19 nadi 231 C20 nadi 232 C21 nadi 233 C22 nadi 234 C23 nadi 235 C24 nadi 236 C25 nadi 237 C26 nadi 238 C27 nadi 239 C28 nadi 240 C29 nadi 241 C30 nadi 242 C31 nadi 243 C6 npar 244 C7 npar 245 C8 npar 246 C9 npar 247 C10 npar 248 C11 npar 249 C12 npar 250 C13 npar 251 C14 npar 252 C15 npar 253 C16 npar 254 C17 npar 255 C18 npar 256 C19 npar 257 C20 npar 258 C21 npar 259 C22 npar 260 C23 npar 261 C24 npar 262 C25 npar 263 C26 npar 264 C27 npar 265 C28 npar 266 C29 npar 267 C30 npar 268 C31 npar 269 C32 npar 270 C33 npar 271 C7 2mip 272 C8 2mip 273 C9 2mip 274 C10 2mip 275 C6 3mip 276 C7 3mip 277 C8 3mip 278 C9 3mip 279 C10 3mip 280 C8 4mip 281 C9 4mip 282 C10 4mip 283 C6 ipar 284 C7 ipar 285 C8 ipar 286 C9 ipar 287 C10 ipar 288 C11 ipar 289 C12 ipar 290 C13 ipar 291 C14 ipar 292 C15 ipar 293 C16 ipar 294 C17 ipar 295 C18 ipar 296 C19 ipar 297 C20 ipar 298 C21 ipar 299 C22 ipar 300 C23 ipar 301 C24 ipar 302 C25 ipar 303 C26 ipar 304 C27 ipar 305 C28 ipar 306 C29 ipar 307 C30 ipar 308 C31 ipar 309 C32 ipar 310 C33 ipar 311 C6 23dm 312 C7 23dm 313 C8 23dm 314 C9 23dm 315 C10 23dm 316 C7 24dm


III

317 C8 24dm 318 C9 24dm 319 C10 24dm 320 C8 25dm 321 C9 25dm 322 C10 25dm 323 C9 26dm 324 C10 26dm 325 C7 3etp 326 C8 3etp 327 C9 3etp 328 C10 3etp 329 C7 ncy5 330 C8 ncy5 331 C9 ncy5 332 C10 ncy5 333 C11 ncy5 334 C12 ncy5 335 C13 ncy5 336 C14 ncy5 337 C15 ncy5 338 C16 ncy5 339 C17 ncy5 340 C18 ncy5 341 C19 ncy5 342 C20 ncy5 343 C21 ncy5 344 C22 ncy5 345 C23 ncy5 346 C24 ncy5 347 C25 ncy5 348 C26 ncy5 349 C27 ncy5 350 C28 ncy5 351 C29 ncy5 352 C30 ncy5 353 C31 ncy5 354 C32 ncy5 355 C33 ncy5 356 C9 ncy6 357 C10 ncy6 358 C11 ncy6 359 C12 ncy6 360 C13 ncy6 361 C14 ncy6 362 C15 ncy6 363 C16 ncy6 364 C17 ncy6 365 C18 ncy6 366 C19 ncy6 367 C20 ncy6 368 C21 ncy6 369 C22 ncy6 370 C23 ncy6 371 C24 ncy6 372 C25 ncy6 373 C26 ncy6 374 C27 ncy6 375 C28 ncy6 376 C29 ncy6 377 C30 ncy6 378 C31 ncy6 379 C32 ncy6 380 C33 ncy6 381 C8 icy5 382 C9 icy5 383 C10 icy5 384 C11 icy5 385 C12 icy5 386 C13 icy5 387 C14 icy5 388 C15 icy5 389 C16 icy5 390 C17 icy5 391 C18 icy5 392 C19 icy5 393 C20 icy5 394 C21 icy5 395 C22 icy5 396 C23 icy5 397 C24 icy5 398 C25 icy5 399 C26 icy5 400 C27 icy5 401 C28 icy5 402 C29 icy5 403 C30 icy5 404 C31 icy5 405 C32 icy5 406 C33 icy5 407 C9 icy6 408 C10 icy6 409 C11 icy6 410 C12 icy6 411 C13 icy6 412 C14 icy6 413 C15 icy6 414 C16 icy6 415 C17 icy6 416 C18 icy6 417 C19 icy6 418 C20 icy6 419 C21 icy6 420 C22 icy6 421 C23 icy6 422 C24 icy6 423 C25 icy6 424 C26 icy6 425 C27 icy6 426 C28 icy6 427 C29 icy6 428 C30 icy6 429 C31 icy6 430 C32 icy6 431 C33 icy6 432 C11 2naf 433 C12 2naf 434 C13 2naf 435 C14 2naf 436 C15 2naf 437 C16 2naf 438 C17 2naf 439 C18 2naf 440 C19 2naf 441 C20 2naf 442 C21 2naf 443 C22 2naf 444 C23 2naf 445 C24 2naf 446 C25 2naf 447 C26 2naf 448 C27 2naf 449 C28 2naf 450 C29 2naf 451 C30 2naf 452 C31 2naf 453 C32 2naf 454 C33 2naf 455 C15 3naf 456 C16 3naf 457 C17 3naf 458 C18 3naf 459 C19 3naf 460 C20 3naf 461 C21 3naf 462 C22 3naf 463 C23 3naf 464 C24 3naf 465 C25 3naf 466 C26 3naf 467 C27 3naf 468 C28 3naf 469 C29 3naf 470 C30 3naf 471 C31 3naf 472 C32 2naf 473 C33 3naf 474 C19 4naf 475 C20 4naf 476 C21 4naf 497 C22 4naf 498 C23 4naf 499 C24 4naf 480 C25 4naf 481 C26 4naf 482 C27 4naf 483 C28 4naf 484 C29 4naf 485 C30 4naf 486 C31 4naf 487 C32 4naf 488 C33 4naf 489 C9 1aro 490 C10 1aro 491 C11 1aro 492 C12 1aro 493 C13 1aro 494 C14 1aro 495 C15 1aro 496 C16 1aro


IV

497 C17 1aro 498 C18 1aro 499 C19 1aro 500 C20 1aro 501 C21 1aro 502 C22 1aro 503 C23 1aro 504 C24 1aro 505 C25 1aro 506 C26 1aro 507 C27 1aro 508 C28 1aro 509 C29 1aro 510 C30 1aro 511 C31 1aro 512 C32 1aro 513 C33 1aro 514 C10 iaro 515 C11 iaro 516 C12 iaro 517 C13 iaro 518 C14 iaro 519 C15 iaro 520 C16 iaro 521 C17 iaro 522 C18 iaro 523 C19 iaro 524 C20 iaro 525 C21 iaro 526 C22 iaro 527 C23 iaro 528 C24 iaro 529 C25 iaro 530 C26 iaro 531 C27 iaro 532 C28 iaro 533 C29 iaro 534 C30 iaro 535 C31 iaro 536 C32 iaro 537 C33 iaro 538 C12 2aro 539 C13 2aro 540 C14 2aro 541 C15 2aro 542 C16 2aro 543 C17 2aro 544 C18 2aro 545 C19 2aro 546 C20 2aro 547 C21 2aro 548 C22 2aro 549 C23 2aro 550 C24 2aro 551 C25 2aro 552 C26 2aro 553 C27 2aro 554 C28 2aro 555 C29 2aro 556 C30 2aro 557 C31 2aro 558 C32 2aro 559 C33 2aro 560 C15 3aro 561 C16 3aro 562 C17 3aro 563 C18 3aro 564 C19 3aro 565 C20 3aro 566 C21 3aro 567 C22 3aro 568 C23 3aro 569 C24 3aro 570 C25 3aro 571 C26 3aro 572 C27 3aro 573 C28 3aro 576 C29 3aro 575 C30 3aro 576 C31 3aro 577 C32 3aro 578 C33 3aro 579 C11 naro 580 C12 naro 581 C13 naro 582 C14 naro 583 C15 naro 584 C16 naro 585 C17 naro 586 C18 naro 587 C19 naro 588 C20 naro 589 C21 naro 590 C22 naro 591 C23 naro 592 C24 naro 593 C25 naro 596 C26 naro 595 C27 naro 596 C28 naro 597 C29 naro 598 C30 naro 599 C31 naro 600 C32 naro 601 C33 naro 602 C10 naol 603 C10 2naf 604 C14 3naf 605 C18 4naf 606 C14 3aro 607 C10 naro 608 C6 22dm 609 C7 22dm 610 C8 22dm 611 C9 22dm 612 C10 22dm 613 C7 33dm 614 C8 33dm 615 C9 33dm 616 C10 33dm 617 C7 223t 618 C8 223t 619 C9 223t 620 C10 223t 621 C8 34dm 622 C9 34dm 623 C10 34dm 624 C8 234t 625 C9 234t 626 C10 234t 627 C8 2m3e 628 C9 2m3e 629 C10 2m3e 630 dm cyC5 631 tm cyC5 632 C4H4 633 tm cyC6 634 tm Benz 635 Pristaan 636 Phytaan 637 Squalaan 638 iC9di 639 iC10di 640 iC11di 641 iC12di 642 iC13di 643 iC14di 644 iC15di 645 iC16di 646 iC17di 647 iC18di 648 iC19di 649 iC20di 650 iC21di 651 iC22di 652 iC23di 653 iC24di 654 iC25di 655 iC26di 656 iC27di 657 iC28di 658 iC29di 659 iC30di 660 iC31di 661 iC8ol 662 iC9ol 663 iC10ol 664 iC11ol 665 iC12ol 666 iC13ol 667 iC14ol 668 iC15ol 669 iC16ol 670 iC17ol 671 iC18ol 672 iC19ol 673 iC20ol 674 iC21ol 675 iC22ol 676 iC23ol


V

677 iC24ol 678 iC25ol 679 iC26ol 680 iC27ol 681 iC28ol 682 iC29ol 683 iC30ol 684 iC31ol 685 iC32ol 686 anthracene 687 phenantrene 688 methylanthrace 689 methylphenan 690 pyrene 691 C17 4aro 692 C18 4aro 693 C19 4aro 694 C20 4aro 695 C21 4aro 696 C22 4aro 697 C23 4aro 698 C24 4aro 699 Fluorene 700 mFluorene

The names of the COILSIM1D compounds contain the following abbreviations:

aro, ar = aromatic compound

naro = naphtheno-aromatic compound

cy = cyclic compound

di = a diolefin

dm = two methyl substituents

et = ethyl substituent

i = iso compound

m = methyl substituent on carbon atom 2

meth = methyl

n = normal compound

na = naphthenic compound

naf = naphthene

ol = olefin

par, p = paraffinic compound

vi = vinyl substituent

In the table below, some examples of the used nomenclature are given. The first column is the

COILSIM number, second is the COILSIM name, third a description of the compound. In the

last column the structure of the compound is shown. For lumped compounds, several isomers are

lumped into one COILSIM compound, and an example of one possible isomer is depicted.

Number Name Description Structure


VI

44 mcyC5ol cyclopentane ring with

double bond and methyl

substituent

45 mCPD methyl cyclopentadiene

48 cyC6di cyclohexadiene

53 dmcyC6ol dimethyl cyclohexene

57 etcyC6di ethyl cyclohexadiene

58 vicyC6ol vinyl cyclohexene

68 Dm,vinyl

benz. dimethyl vinyl benzene


VII

74 C6 2mip 2-methyl pentane

105 1 C9 ol 1-nonene

129 2 C6 ol lump compound of C6

olefins except 1-hexene

179 C11 arol mono-aromatic compound

with 11 carbon atoms

having one double bond

204 C14 naol naphthenic compound with

14 carbon atoms having

one double bond. The

double bond can be in- or

outside of the ring.

245 C8 npar octane

271 C7 2mip 2-methyl hexane

283 C6 ipar lump of C6 isoparaffins


VIII

312 C7 23dm 2,3 dimethyl pentane

326 C8 3etp 3-ethyl hexane

329 C7 ncy5 compound of 7 carbon

atoms, having one C5 ring

and the alkyl group is

straight, i.e. ethyl pentane

381 C8 icy5 compound of 8 carbon

atoms, having one C5 ring

and the alkyl group is

branched, i.e. isopropyl

pentane

432 C11 2naf compound of 11 carbon

atoms having two

naphthenic rings

455 C15 3naf compound of 15 carbon

atoms having three

naphthenic rings

489 C9 1aro compound of 9 carbon

atoms having one aromatic

ring, with the alkyl group

being straight, i.e. propyl


IX

benzene

514 C10 iaro compound of 10 carbon

atoms having one aromatic

ring, with the alkyl group

being branched

538 C12 2aro compound of 12 carbon

atoms having two aromatic

ring

579 C11 naro compound of 11 carbon

atoms having a naphthenic

and an aromatic ring

617 C7 223t 2,2,3 trimethyl butane

634 tm Benz tri-methyl benzene

639 iC10di iso-di-olefin of 10 carbon

atoms


X

661 iC8ol iso-olefin of 8 carbon

atoms

Appendix B: List of Radicals in the Reaction Network

XI

Appendix B:

List of Radicals in the Reaction Network

701 H. 702 CH3. 703 C2H3. 704 C2H5.

705 C3H5. 706 vC3H5-1. 707 vC3H5-2. 708 1C3H7.

709 2C3H7. 710 1C4-3. 711 1C4-4. 712 2C4-1.

713 iC4H7. 714 1 C4H9. 715 2 C4H9. 716 iC4H9.

717 t C4H9. 718 neo C5. 719 iC5-1. 720 iC5-2.

721 iC5-3. 722 iC5-4. 723 nC5-1. 724 nC5-2.

725 nC5-3. 726 1C5ol-5. 727 1C5ol-4. 728 1C5ol-3.

729 2C5ol-5. 730 2C5ol-5. 731 3m1C4-4. 732 3m1C4-3.

733 2m1C4-4. 734 2m1C4-3. 735 cyC5. 736 cC5ol-4.

737 cC5ol-3. 738 isopryl 739 C5di-3. 740 2m1C4-5.

741 23dmC4-1. 742 2mC5-3. 743 22dmC4-1. 744 3mC5-3.

745 2mC5-1. 746 3mC5-2. 747 nC6-3. 748 1C6ol-5.

749 4m1C5ol5. 750 4m1C5ol4. 751 33m1C4ol. 752 3m1C5ol5.

753 3et1C4ol. 754 1C6ol4. 755 C6di-as. 756 24mC5ol5.

757 2mC6ol6. 758 5mC6ol6. 759 34mC5ol5. 760 44mC5ol5.

761 4mC6ol5. 762 1C7ol5. 763 4etC5ol5. 764 C7di-as.

765 5m1C6-5. 766 6m2C7-6. 767 55m2C6-6. 768 35m1C6-5.

769 344mC5-5. 770 25m1C6-5. 771 244mC5-5. 772 C5di-5.

773 benzyl 774 2-phenyleth-1-yl 775 1-phenyleth-1-yl 776 1-phenantryl meth

777 1-naphthyl meth 778 1-peryl meth 779 1-anthracyl meth 780 dummy

781 dummy 782 dummy 783 dummy 784 dummy





In the above list, the following abbreviations are used :

aro, ar = aromatic compound

cy = cyclic compound di = diolefin

dm = dimethyl, i.e. two methyl substituents

et = ethyl substituent

Appendix B: List of Radicals in the Reaction Network

XII

i = iso compound

m = methyl substituent on carbon atom 2

meth = methyl

n = normal compound

na = naphthenic compound

naf = naphthene ol = olefin

par, p = paraffinic compound

vi = vinyl substituent

The numbers that are used in the symbolic names indicate the position(s) of the substituent(s) on

the molecule.

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