Kinetic Modeling of the Partial Oxidation of Propylene to Acrolein: A

Jan 8, 2019 - Tan, H. S.; Bacon, D. W.; Downie, J. The reaction network for the oxidation of propylene over a bismuth molybdate catalyst. Can. J. Chem...
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Kinetics, Catalysis, and Reaction Engineering

Kinetic Modeling of the Partial Oxidation of Propylene to Acrolein: A Systematic Procedure for Parameter Estimation Based on Non-isothermal Data Gunnar Ganzer, and Hannsjörg Freund Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.8b05583 • Publication Date (Web): 08 Jan 2019 Downloaded from http://pubs.acs.org on January 12, 2019

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Kinetic Modeling of the Partial Oxidation of Propylene to Acrolein: A Systematic Procedure for Parameter Estimation Based on Non-isothermal Data Gunnar Ganzer and Hannsjörg Freund∗ Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Lehrstuhl für Chemische Reaktionstechnik, Egerlandstr. 3, 91058 Erlangen, Germany E-mail: [email protected] Phone: +49 (0)9131 85-27424

Abstract Based on non-isothermal experiments in an integral pilot scale reactor, the heterogeneously catalyzed gas phase oxidation of propylene to acrolein was investigated at industrial relevant process conditions. From an extensive experimental data set both reaction scheme and reaction rates were derived. Beside the main components propylene, oxygen, acrolein and water, the proposed reaction network includes a variety of side products. The reaction rates were modeled by a semi-mechanistical approach given by Mars and van Krevelen. Based on a two-dimensional, pseudohomogeneous reactor model, the kinetic parameters were estimated successfully by introducing a systematic procedure for a stepwise determination using different regions with different characteristics to estimate the pre-exponential factors and activation energies individually, i. e.

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separated from each other. The model is able to predict the data included in the parameter estimation and independent data measured at different process conditions as well. Furthermore, it provides reliable results for an industrial plant.

Keywords: Kinetic modeling, parameter estimation, propylene oxidation, acrolein, reactor modeling

Dedicated to Professor Gerhard Emig on the occasion of his 80th birthday.

1

Introduction

Acrolein has a large economic importance as intermediate for producing a variety of products such as acrylic acid or methionine. This aspect motivates the continuous development and improvement of the catalyst system and the optimization of the reactor design to increase propylene conversion as well as acrolein selectivity. Since bismuth molybdate catalysts were introduced in 1957 by Sohio (today BP) the catalyst systems were further developed towards multicomponent metal oxide catalysts so that the today’s selectivity to acrolein is at a high level within 83 to 90 % 1 . However, the oxidation of propylene over bismuth molybdate catalysts comprises of a variety of parallel and consecutive reactions resulting in a complex reaction network 2–9 which cannot be prevented by a further refinement of catalyst composition and structure. The observed byproducts include carbon oxides 2,3,10–16 , acetaldehyde 5,9,17–20 , formaldehyde 19,21 , acrylic acid 2,3,5,6,9 , acetic acid 2,3,5,9,18 , ethylene 9,17 and acetone 9,21 . To improve the selectivity to acrolein in spite of these byproducts, the design of optimal reactors and the development of advanced process control strategies become more and more important for the complex reaction system which leads in the same way to the requirement of a detailed and reliable kinetic model applicable for typical process conditions (coolant temperature, pressure, space velocity) in industrial practice. The catalytic propylene oxidation has already been investigated since about the last 50 2

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years, whereby detailed studies regarding the mechanism of the main reaction were carried out several times 22–33 . As a result of this extensive research the single elementary steps of the partial oxidation are very well-known, including a first hydrogen abstraction from the propylene molecule to form an intermediate complex at the catalyst surface followed by an incorporation of lattice oxygen and the second hydrogen abstraction 29–33 . The first hydrogen abstraction is widely accepted as the rate-determing step of the macroscopic reaction step. Regarding the state of oxidation the sequence of these partial steps leads to a so-called reduced catalyst which is then reoxidized by gas phase oxygen. This two step mechanism (reduction & reoxidation) is well-known as redox mechanism and can be modeled by the reaction rate approach proposed by Mars and van Krevelen 34 (MvK). Even though the mechanism of oxidation reactions on metal oxide catalysts is understood quite well, only few kinetic models for the catalytic propylene oxidation are based on the MvK approach 35–38 . Many kinetic models consist of simple power law rate expressions with dependencies on the partial pressure of propylene 2,4,13,20,39,40 , oxygen 2,4 , or both 41 . Especially for the main reaction of propylene to acrolein, other studies suggest two power law rate expessions to describe the reduction step and reoxidation step separately from each other 2,4,42 . Neither one simple power law nor two expressions to describe reduction and reoxidation reflect the real substeps according to the well-known redox mechanism correctly. Beside these theoretical aspects, many proposed kinetic models either describe only a narrow range of reaction conditions, were only evaluated in ideal laboratory reactors or consider the complex network of this reaction system insufficiently. Furthermore, the distinct role of water vapour in the gas mixture as it was described by Novakova et al. 43 and Saleh-Alhamed et al. 44,45 is commonly neglected, except for the rate expressions proposed by Redlingshoefer et al. 2,4 . Despite many detailed investigations it is shown that modeling the propylene oxidation with respect to industrial relevant process conditions is still a challenge those days, and most of the proposed models are very limited in their applicability. The huge amount of heat produced by the reactions, the complex network of many parallel and consecutive reactions 3

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and a highly dynamic catalyst system makes modeling of this system very difficult. Due to the limitations of existing models, the aim of the present work is to study the partial oxidation of propylene on an industrial bismuth molybdate catalyst under industrial relevant process conditions. In contrast to the conventional procedure of model development using an ideal laboratory reactor to derive a kinetic model and a subsequent analysis of experimental data from a pilot plant to adjust the model to industrial conditions, we use directly non-isothermal experiments from a pilot scale reactor. Apart from the reactor length (shorter than for an industrial plant), the reactor reflects the same characteristic process conditions compared to an industrial scale reactor. This approach offers two main advantages. By applying this kind of reactor it is possible to consider effects such as radial heat transport through the catalyst bed already at an early stage of process development. Furthermore, the one-step approach proposed in this work offers many advantages over the conventional two-step methodology. In particular, with this one-step procedure the costs for process development as well as the time-to-market can be significantly reduced. This, in turn, leads to higher profitability. However, using the one-step methodology the parameter estimation itself is very challenging due to the necessity to use a more complex reactor model and due to the existence of large temperature and concentration gradients in axial and radial direction. We therefore introduce an efficient systematic approach for determining kinetic parameters based on non-isothermal experimental runs which is generally applicable. Our approach includes a stepwise determination of the pre-exponential factors and the activation energies which enables a very reliable estimation also from the statistical perspective. The following sections are structured according to the methodology proposed. First of all, the experimental set-up and representative results are provided in section 2 as basis for the model development. Afterwards, the reactor as well as kinetic model are introduced in section 3. Furthermore, this section gives a detailed description of the systematic procedure of the parameter estimation applied. In section 4, the results of the parameter estimation are presented and discussed in detail followed by a validation of the developed model. 4

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2

Experimental

2.1

Set-up and process conditions

The experimental investigations were carried out in a continuously operated, polytropic pilot scale reactor. The reactor was a cooled single tube with a total length of 1 m consisting of a preheated inert zone with a length of 0.212 m and a catalytic bed length of 0.788 m. The reactor tube was cooled from the outside by a circulating thermofluid (Marlotherm). Due to the highly exothermic reaction system of propylene to acrolein an additional measure was required to control the large amount of heat produced by the reactions and guarantee the thermal stability of the reactor accordingly. The catalyst bed was therefore diluted with inert material whereby the catalyst support of the used egg-shell catalyst was applied as inert material to prevent any segregation effects in this way. Furthermore, the catalyst support was used as diluent to ensure that the heat transfer characteristics between the different particle types within the fixed bed are very similar. In this work, the catalyst bed was diluted with 50 % inert material along the whole reactor tube. The spherical catalyst used is a commercial multicomponent bismuth molybdate with alumina as catalyst support featuring an averaged diameter of 0.0052 m. The feeds of propylene, air, nitrogen (inert gas) and water were controlled by several mass flow controllers (MFC) and preheated to coolant temperature in the first section of the reactor tube. By using a catalytic afterburning the reaction products and unreacted propylene were oxidized to carbon dioxide and water before sending it to the exhaust. The air supply required for the afterburning was controlled analogously by a rotameter. An overall presentation of the plant is given in Figure 1. As it is shown in Figure 1, the measurement of reaction temperature and concentration profiles were carried out with in total seven taps along the reactor length where the first two taps are located in the inert section. The reaction temperature was monitored with side-entry thermocouples located in the center of the tube. It can be expected that the kinetic parameters are strongly temperature dependent. Thus, monitoring the temperature 5

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Figure 1: Schematic representation of the plant used in this investigation including the tubular fixed bed reactor with external cooling system, analytics (thermocouples & GC), educt feeding via MFCs and catalytic afterburning. as precise as possible is in principle desirable. However, each side-entry thermocouple will introduce some disturbance to the arrangement of the particles in the randomly packed bed. Therefore, a reasonable trade-off between sufficient information on the temperature profile in the bed and acceptable disturbance of the bed by the thermocouples has to be found. In our work, we decided to use five thermocouples along the catalytic bed. The gas composition along the reactor axis was analyzed via online gaschromatography (online-GC). Propylene, acrolein, oxygen as main components and acrylic acid, carbon dioxide, carbon monoxide, acetaldehyde, acetic acid and allyl alcohol as side products were detected via GC to identify the gas composition. The analysis of the gas composition shows also smaller amounts of propionic acid, benzene and other components which are neglected in this investigation due to the very low selectivity. The error in the C balance is less than 1 %. The organic and inorganic components were analyzed separately by using FID (flame ionization detector) for 6

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organic compounds and TCD (thermal conductivity detector) for inorganic compounds. To quantify the organic compounds a free fatty acid phase column (FFAP) is used. The inorganic components were analyzed via a PoraPlotQ column to characterize carbon oxides and ˚ to determine the concentrations of oxygen and a column of a molecular sieve (zeolite 5 A) nitrogen. Due to the complexity of multicomponent mixed metal oxides a variety of process parameters are relevant for a detailed characterization of the catalytic oxidation of propylene to acrolein 2,5 . Beside typical operating conditions such as coolant temperature Tc and total pressure pin , the composition of the reaction mixture at the reactor inlet plays a very important role for this gas phase reaction. Due to a direct participation of the catalyst in reactions taking place as well as the continuous exchange between lattice and gas phase oxygen at the surface, these catalysts show a highly dynamic behavior. Therefore, the propylene content in the feed composition yP P,in can have a strong influence on the reactor behavior. The same applies to the oxygen-to-propylene and the water-to-propylene ratio 2,5 , which are abbreviated by O2 /P P and H2 O/P P . The parameters studied in the non-isothermal fixed bed experiments are listed in the following. The ranges investigated include process conditions typical for industrial practice 1 . The given values are related to the settings of the central point, respectively, and thus describe dimensionless parameters. The central point was measured in each of the experimental blocks to control catalyst activity and performance over the whole time of measurements. • Coolant temperature: Tc∗ = 0.995; 0.997; 1; 1.004; 1.007; 1.009 • Pressure at reactor inlet: p∗in = 0.93; 1; 1.13 • Inlet propylene concentration: yP∗ P,in = 0.94; 1; 1.06; 1.12 • Inlet molar oxygen-to-propylene ratio: (O2 /P P )∗ = 0.84; 0.9; 0.95; 1; 1.01 • Inlet molar water-to-propylene ratio: (H2 O/P P )∗ = 0.48; 0.67; 0.86; 1; 1.19 7

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Before the kinetic measurements were started, the catalyst was activated for a timeframe of two weeks. At the end of this activation time, the results of temperature and conversion profiles were stable and reproducible for the operating conditions of the central point. The analysis of temperature and concentration profiles within the kinetic measurements were carried out at steady state conditions. That means, each of the experimental runs was started and operated without any measurement for a timeframe of 6 h. Afterwards, steady state conditions were proven and then five GC measurements per tap were performed which lead to a total measuring time of about 9 h. This procedure was used in all experimental runs in the same way.

2.2

Results

In Figure 2 typical results of measured temperature profiles along the reactor length are shown exemplarily for different coolant temperatures. The black line and the green line represent a typical temperature profile as it results from a highly exothermic gas phase reaction 1.16 Tc∗ Tc∗ Tc∗ Tc∗

1.12 T /Tin / −

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= 0.995 = 0.997 =1 = 1.009

1.08

1.04

1 0

0.2

0.4

0.6

0.8

1

z/L / −

Figure 2: Measured temperature profiles along the reactor length for different coolant temperatures. 8

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carried out in a wall cooled fixed bed reactor. Apart from these typical temperature profiles the broad range of investigated experimental conditions can lead to different temperature profiles along the reactor length which is given exemplarily for a lower coolant temperature in Figure 2. As it is shown, decreasing the coolant temperature compared to the central point of the experimental investigations results in a strong inhibition of the reactions and thus a damped temperature profile. The same behavior was observed for lower inlet molar ratios of O2 /P P and H2 O/P P . In Figure 3a, the normalized concentration profiles of the main reaction components (propylene, oxygen, acrolein, water) are shown exemplarily for a typical temperature profile. It can be seen that the partial oxidation of propylene to acrolein on a bismuth molybdate catalyst is a highly selective process. As it is shown in Figure 3b, the influence of reaction temperature, system pressure and different feed compositions on the molar fraction of acrolein are negligible over a wide range of conversions of propylene. However, the final yield of acrolein at the reactor outlet increases with an increasing coolant temperature. A decreasing molar ratio of H2 O/P P in the feed composition results in a strong inhibition of the formation rate of acrolein. The variation of the molar ratio of O2 /P P shows the same behavior as it was found in the variation of H2 O/P P . Especially at conversion levels higher than 80 % the dependence of the acrolein molar fraction from the conversion of propylene changes, and it can be observed that the slope of the curve flattens significantly. Hence, it seems to reach an optimum as it was also observed in the experimental studies of Redlingshöfer et al. 2,3 . Despite the high selectivity to acrolein this behavior indicates that a variety of side reactions, parallel as well as consecutive reactions, takes place on bismuth molybdate catalysts. A typical range of byproducts as it was found in the experimental runs includes carbon dioxide, carbon monoxide, acrylic acid, acetaldehyde, acetic acid and allyl alcohol. Typical normalized profiles of molar fractions along the reactor axis are shown in Figure 4 which gives a lot of information about the reaction network. First of all, during all experiments 9

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3.5 3

yi /yP P,in / −

2.5 PP O2 AC H2 O

2 1.5 1 0.5 0 0

0.2

0.4

0.6

0.8

1

80

100

z/L / − (a)

1 Tc∗ p∗in (H2 O/P P )∗

0.8 yAC /yP P,in / −

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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0.6

0.4

0.2

0 0

20

40

60

XP P / % (b)

Figure 3: (a) Typical experimental results for normalized profiles of molar fractions of propylene, oxygen, acrolein and water along the reactor length. (b) Normalized molar fraction of acrolein vs. conversion of propylene for different measured coolant temperatures, system pressures and molar water-to-propylene ratios.

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0.16 CO2 AA CO ACET ACET A ALL

0.14 0.12 yi /yP P,in / −

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0.1 0.08 0.06 0.04 0.02 0 0

0.2

0.4

0.6

0.8

1

z/L / −

Figure 4: Typical experimental results for normalized profiles of molar fractions of carbon oxides, acrylic acid, acetaldehyde, acetic acid and allyl alcohol. allyl alcohol could be clearly identified as an intermediate in the reaction system, whereby the consecutive reaction from allyl alcohol should be faster than its production rate. In detailed experimental studies using molecular probes Burrington and Grasselli 46 have shown that allyl alcohol reacts further to acrolein very selectively. Yet, it is not proven that allyl alcohol is formed in a parallel reaction step from propylene, however, this pathway seems to be very likely 6 . All the other profiles of the components show a systematic increase along the reactor length. The curves for carbon monoxide, acetaldehyde and acetic acid seem to be flattening with increasing reaction progress. In contrast, the increase of the yields of carbon dioxide and acrylic acid do not seem to slow down at higher reaction progress. This indicates the formation via consecutive reaction pathways, whereby parallel steps cannot be excluded directly. The influence of the coolant temperature on the formation of byproducts is shown in Figure 5. In these graphs, the normalized molar fraction of the component considered is given as a function of the conversion of propylene. As it was already shown, the most im-

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portant byproducts of the partial oxidation of propylene are acrylic acid, carbon dioxide and carbon monoxide which are shown in Figure 5a - c. The curves of acrylic acid represent a typical behavior of a product formed in a consecutive reaction. On the one hand, each profile features a sharp increase at conversions of propylene higher than 80 %. On the other hand, at lower coolant temperatures the formation of acrolein is strongly inhibited, which leads to a strongly reduced temperature level within the catalyst bed (see Figure 2) due to the high selectivity of bismuth molybdate catalysts to acrolein. In that case, a significant reduction of the formation of acrylic acid can be observed which, in turn, allows for the conclusion that acrylic acid is formed in a consecutive reaction step. Furthermore, the results indicate that the temperature dependence of this pathway is very high. The systematic rise during the stepwise increase of the coolant temperature supports this argumentation. The experimental data describing the formation of carbon oxides show some very interesting and important results. It seems that the formation steps to carbon oxides feature a very low temperature dependency, because the yield of carbon oxides at the reactor outlet is very similar for all investigated coolant temperatures. Depending on the reaction conditions the molar ratio between carbon dioxide and carbon monoxide varied between 1.5 and 2.5, which was also found in a similar range elsewhere 2,3 . As it is shown in Figure 5b and c, at low coolant temperature the formation of carbon oxides is even enhanced. Since the product formation is strongly inhibited otherwise, this behavior can only be traced to parallel reaction steps from propylene. Different molar ratios of H2 /P P and O2 /P P showed the same tendencies in the corresponding experimental runs. Accordingly, it is reasonable to conclude that most of carbon oxides are formed via parallel reaction steps. Nevertheless, looking at high conversions of propylene, the sharp increase of the formation rate indicates that carbon oxides are formed in consecutive reaction steps as well. Figure 5d shows the interaction between the coolant temperature and the formation of acetaldehyde as a function of the conversion of propylene. As it can be seen, the formation rate of acetaldehyde is almost independent from the coolant temperature. There is a 12

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Tc∗ Tc∗ Tc∗ Tc∗ Tc∗ Tc∗

0.08 0.06

0.14 = 0.995 = 0.997 =1 = 1.004 = 1.007 = 1.009

yCO2 /yP P,in / −

yAA /yP P,in / −

0.1

0.04 0.02 0

0

20

40 60 XP P / %

80

Tc∗ Tc∗ Tc∗ Tc∗ Tc∗ Tc∗

0.12 0.1 0.08

= 0.995 = 0.997 =1 = 1.004 = 1.007 = 1.009

0.06 0.04 0.02 0

100

0

20

40 60 XP P / %

(a) Tc∗ Tc∗ Tc∗ Tc∗ Tc∗ Tc∗

0.04 0.03

0.02 = 0.995 = 0.997 =1 = 1.004 = 1.007 = 1.009

0.02 0.01 0

0

20

80

100

80

100

(b)

yACET /yP P,in / −

0.05 yCO /yP P,in / −

40 60 XP P / %

80

Tc∗ Tc∗ Tc∗ Tc∗ Tc∗ Tc∗

0.015 0.01

= 0.995 = 0.997 =1 = 1.004 = 1.007 = 1.009

0.005 0

100

0

20

(c)

40 60 XP P / % (d)

0.01 yACET A /yP P,in / −

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Tc∗ Tc∗ Tc∗ Tc∗ Tc∗ Tc∗

0.008 0.006

= 0.995 = 0.997 =1 = 1.004 = 1.007 = 1.009

0.004 0.002 0

0

20

40 60 XP P / %

80

100

(e)

Figure 5: Normalized profiles of molar fractions for different coolant temperatures: (a) acrylic acid, (b) carbon dioxide, (c) carbon monoxide, (d) acetaldehyde, (e) acetic acid.

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slight tendency to an enhanced formation at lower temperatures similar to the formation of carbon oxides. At conversions smaller than 60 % the yield is at least the same compared to higher coolant temperatures. This behavior indicates that acetaldehyde is formed by a parallel reaction from propylene which is in very good agreement to studies reported in literature 2–4,7,8,35,36,47 . The strong increase of the formation at conversion levels higher than 80 % further provides evidence for a consecutive reaction. The results from the variation of the feed composition (molar ratios) further substantiate the conclusion that acetaldehyde is formed in a parallel as well as consecutive reaction. As it is shown in Figure 5e, the dependencies of acetic acid are the same to those of acetaldehyde, however, showing a stronger increase at high conversion levels which is in good agreement to a formation route via a consecutive reaction step (equally to acrylic acid).

3

Modeling

3.1

Reactor model

With the experimental data in our work it is shown that many side reactions occur and large temperature gradients in axial as well as radial direction exist. This combination inherently leads to the necessity of a complex reactor model, so that the focus of the derivation in this work is to keep the model as simple as possible to get reliable results from the parameter estimation. Hence, a two-dimensional pseudohomogeneous continuum model according to the αw model approach 48,49 is used. The derivation of this simplified model is carried out based on the following assumptions: • Steady-state experiments • No external and internal diffusion limitations • Axial symmetry is assumed, temperature and concentration gradients in circumferential direction are neglected 14

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• Axial dispersion and axial heat conduction are neglected • Plug-flow is assumed • According to experimental results pressure drop along the reactor axis is neglected • Constant coolant temperature along the reactor length is assumed according to experimental results Possible external and internal diffusion limitations were checked on the basis of the criterion of Weisz-Prater (internal) as well as the criterion of Mears (external) which are given in the supporting information to this work. The reaction rate required for the estimations is calculated based on the experimental data and the assumption that only the main reaction from propylene to acrolein takes place. According to the criteria the estimations show that internal as well as external diffusion limitations can be excluded in our case 50,51 . The corresponding component material balance in form of weight fraction and the energy balance in temperature form for steady state are given in Equation (1) and Equation (2). Dr 1 ∂wi = · u0 · ρf · ∂z r ∂r

u0 · ρf · cp,f

  NR X ∂ (wi · ρf ) νi,j · rj r· + (1 − ) · ρcat · a · Mi · ∂r j=1

∂T λr ∂ · = · ∂z r ∂r

  NR X ∂T r· + (1 − ) · ρcat · a · (−∆r h)j · rj ∂r j=1

(1)

(2)

By introducing parameter a the catalyst bed dilution is considered in the balance equations. Due to the assumption of an ideal mixture of active and inert particles in the packing, the parameter is defined to be constant along the reactor length as well as reactor radius at a level of 0.5 according to the experimental setup. To solve the balance equations, the initial

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and boundary conditions summarized in Equation (3) and (4) are used. For

0≤r≤R:

For

0