Optimization of the partial oxidation of methane on ni mgo

OPTIMIZATION OF THE PARTIAL OXIDATION OF METHANE ON Ni-MgO/α-ALUMINA MONOLITH CATALYST IN A REVERSE FLOW REACTOR USING THE METHOD OF STEEPEST ASCENT A Thesis presented to the Faculty o

OPTIMIZATION OF THE PARTIAL OXIDATION OF METHANE

ON Ni-MgO/α-ALUMINA MONOLITH CATALYST IN A REVERSE FLOW

REACTOR USING THE METHOD OF STEEPEST ASCENT

A Thesis presented to the Faculty of the Graduate School of Chemical Engineering

ACKNOWLEDGEMENT

This thesis is dedicated to Almighty God who is the source of wisdom and knowledge and thank God for giving me the strength, guidance and patience to overcome so many problems to accomplish my thesis

¾ I would like to thank The ASEAN University Network Southeast Asia Engineering Education Development Network (AUN/SEED-Net) for its financial support and for giving me an opportunity to study in De La Salle University - Manila

¾ I am indebted to De La Salle University for furnishing very good facilities and the best conditions to finish the experiments I am very pleased to be a student

of De La Salle University

¾ I want to express my deepest gratitude to Dr Luis Razon, my thesis adviser, for inspiring and helping me to overcome many difficulties during my experiments This thesis would not have been possible without your support Thank you for patiently editing my thesis and giving me a lot of valuable comments and suggestions during my experiments and thesis-writing Your instructions and tolerance have always been appreciated

¾ I owe my deep gratitude to my thesis co-adviser, Dr Raymond Tan, whose guidance and support enabled me to develop a deeper understanding of this topic Thank you for spending time to correct my thesis

¾ I also want to thank my Japanese coadviser, Dr Hirofumi Hinode, for giving us instructions and support when they are needed and spending valuable time to visit and help us in De La Salle University

¾ I am heartily thankful to my thesis panel, Dr Joseph Auresenia (panel chair),

Dr Leonila Abella, Dr Susan Gallardo for offering me a lot of comments and suggestions to improve my thesis

¾ To Ms Gladys Cruz, thank you for taking care of me in Manila Your encouragements and prayers for me are also very much appreciated

¾ To Mr Dennis Yu, thank you for purchasing all equipment and tools which are necessary for my experiments

¾ To the technicians of the Chemical Engineering Department, Mr Benjamin Cardoza, Mr Peter Ascrate, Mr Manny Burgos, Mr Judito Valdez, Mr Ismael Serrano, thank you so much for your assistance during my experiments This thesis could not have beeen accomplished without you

¾ To the technicians of the Mechanical Engineering Department, Mr Ricky Aldanesa and Mr Fernando Barroz, thank you for cutting the monolith and your consideration regarding my thesis

¾ To Mr Phan Huy, thank you for guiding me how to use the set-up and the GC

¾ To Mr Anton Purmono and Mr Teddy Monroy, thank you for your instructions

¾ I also would express my gratitude to my parents, my brothers, my sister-in-law and my girlfriend who have always taken interest in my study and my life in Manila Thank you so much for your prayers and your encouragements

Finally, I want to offer my regards and blessings to all of those who supported me in any respect during my study in De La Salle University God bless you all!

ABSTRACT

Catalytic partial oxidation of methane (CPOM) has been recognized as a suitable method to produce synthesis gas for production of liquid fuel and hydrogen CPOM, which is a mildly exothermic reaction, can be conducted autothermally in a reverse flow reactor (RFR) wherein the direction of flow is reversed cyclically Implementation of real RFR is complicated Recent published studies have focused mainly on numerical simulation and control strategy, but there have been few published experimental studies

This study describes a systematic experimental optimization of a laboratory scale RFR for CPOM on Ni-MgO/α-Al2O3 monolith catalyst using the response surface methodology The effect of initial temperature (Tini), switching time (τ), total flowrate (F), molar feed ratio between methane and oxygen (M), and catalyst length were investigated Hydrogen yield and methane conversion are used as the experimental responses The steepest ascent path was established based on the first experimental design to determine the stationary point whose nature was confirmed

by the second experimental design The iteration of establishing the steepest ascent path and experimental design was done until the maximum point was specified

In this study, the optimum operating conditions were determined in the second experimental design The analysis of reactor operation proved to be challenging due

to the complex interplay of the different experimental factors The following interactions were found to be significant for methane conversion: M*τ, F*τ and M*F The interaction of F*τ also affected the hydrogen yield The third order interaction of F*τ*M was also found to be statistically significant The optimum methane conversion value of 56.38% could be obtained by setting switching time, total flowrate and molar ratio of 4.24 minutes, 543ml/min and 1.575, respectively The optimum value of hydrogen yield of 35.91% was reached by setting total flowrate, molar feed ratio and switching time of 540ml/min, 1.442 and 4.15 minutes, respectively

TABLE OF CONTENTS

TABLE OF CONTENTS i 

LIST OF FIGURES vi 

LIST OF TABLES viii 

NOMENCLATURE ix 

Chapter 1 INTRODUCTION 1 

1.1  Background of the study 1 

1.2  Statement of the problem 3 

1.3  Objectives of the study 4 

1.4  Significance of the study 5 

1.5  Scope and limitations 6 

Chapter 2 REVIEW OF RELATED LITERATURE 9 

2.1  Modification of reverse flow operation 9 

2.2  Review of recent studies in reverse flow reactor 10 

2.2.1  Control of reverse flow reactor 11 

2.2.2  Partial oxidation of methane in reverse flow reactor 12 

2.3  Optimization of cyclic processes 14 

2.4  Optimization of catalytic reactors 16 

2.4.1  Genetic algorithms in optimization catalytic reactor 17 

2.4.2  Response surface methods in optimization of catalytic reactors 19 

2.5  Optimization of reverse flow reactors 21 

2.6  The method of steepest ascent in optimization 23 

2.7  Related studies in De La Salle University - Manila 24 

Chapter 3 THEORETICAL CONSIDERATIONS 26 

3.1  Partial Oxidation of Methane (POM) 26 

3.1.1  Thermodynamics of POM 27 

3.1.1.1 Effects of temperature 28

3.1.1.2  Effects of molar feed ratio 29 

3.1.1.3  Effects of pressure 29 

3.1.2  Mechanism of Gas-Phase POM 30 

3.1.2.1  The Direct Mechanism 30 

3.1.2.2  The Pyrolysis Mechanism 31 

3.1.2.3  Two-step mechanism through complete oxidation 31 

3.1.2.4  Mechanism on the catalyst 32 

3.1.3  Catalysts for the POM 34 

3.1.3.1  Active Components 34 

3.1.3.2  Catalyst Supports 35 

3.1.3.3  Catalyst Promoters 35 

3.1.4  Monolith structure of the catalyst 36 

3.1.5  Characterization of Ni-MgO/αAl2O3 monolith catalyst 37 

3.1.6  Flammability Limits of Methane 37 

3.2  Factors affecting reverse flow reactor performance 38 

3.2.1  Initial conditions 39 

3.2.1.1  Initial Temperature Profile 39 

3.2.1.2  Initial Flowrate 40 

3.2.2  Operating Parameters 41 

3.2.2.1  Molar Feed Ratio 41 

3.2.2.2  Switching Time 41 

3.2.2.3  Flowrate of Feed Gas 42 

3.2.3  Design parameters 42 

3.2.4  Interaction between independent variables 43 

3.2.4.1  Switching Time and Feed Flowrate 43 

3.2.4.2  Switching Time and Catalytic Length 43 

3.3  Performances of reverse flow reactor 44 

3.3.1  Temperature profile at cyclic steady state 44 

3.3.2  The concentration of effluent gas 45 

3.4  Determination of cyclic steady state 46 

3.4.1  Definition based on the repeatability of the process behavior 46 

3.4.2  Thermodynamic definition 46 

3.4.3  Approach to cyclic steady state of reverse flow reator 47 

3.5  Theory of experimental optimization 50 

3.5.1  The steepest ascent method 50 

3.5.2  Ridge Analysis 51 

3.5.3  Canonical Analysis 54 

3.5.4  Multiple responses 55 

3.5.4.1  The weighted priorities strategy 55 

3.5.4.2  The desirability approach 56 

3.5.4.3  The mathematical programming approach 58 

Chapter 4 METHODOLOGY 60 

4.1  Preparation of NiO-MgO/α-Al2O3 catalyst 61 

4.2  Coating NiO-MgO/α-Al2O3 catalyst on monoliths 62 

4.2.1  Preparation of coating slurry 62 

4.2.2  The coating procedure 63 

4.3  Experimental set-up 64 

4.3.1  Description of the set-up 64 

4.3.2  Operation of the set-up 66 

4.3.2.1  Preparation before start-up 66 

4.3.2.2  Start-up procedure 67 

4.3.2.3  Reverse flow operation of the reactor 68 

4.3.2.4  Extinction of the reverse flow reactor 69 

4.3.2.5  The reverse flow reactor in cyclic steady state 70 

4.4  Activity Test 71 

4.5  Strategy of data analysis 71 

4.6  SAS/STAT® Software 72 

4.7  Factor space boundaries 72 

Chapter 5 RESULTS AND DISCUSSION 75 

5.1  Initial experimental design 75 

5.1.1  Interaction between initial temperature and catalyst length 77 

5.1.2  Interaction between molar feed ratio and total flowrate 78 

5.1.3  Interaction between molar feed ratio and switching time 80 

5.1.4  Interaction between total flowrate and switching time 81 

5.1.5  Summary from the initial experimental design 82 

5.2  Effect of initial temperature 83 

5.3  The steepest ascent path 84 

5.4  The second experimental design 85 

5.4.1  Regression results 87 

5.4.1.1  Regression results of methane conversion 87 

5.4.1.2  Regression results of hydrogen yield 88 

5.4.2  Meaning of quadratic and linear effects 90 

5.4.2.1  Quadratic and linear effects on methane conversion 90 

5.4.2.2  Quadratic and linear effects on hydrogen yield 92 

5.4.3  Meaning of interaction effects 93 

5.4.4  Meaning of third-order interactions 94 

5.4.5  Optimum Points 96 

5.5  Activity of catalyst 98 

5.5.1  Results of activity test 98 

5.5.2  Effects of in-use time 99 

5.5.3  Effects of the number of times the catalyst was reduced 100 

Chapter 6 CONCLUSIONS AND RECOMMENDATIONS 102 

6.1  Conclusions 102 

6.2  Recommendations 103 

Reference 105 

Appendix 1 Specifications of Materials 115 

Appendix 2 Activity Test 116 

Appendix 3 The face-centered experimental design 117 

Appendix 4 The Canonical Analysis 118 

Appendix 5 The comparisons of the experiments to the theoretical equilibrium data 119 

Appendix 6 The experimental data 120 

LIST OF FIGURES

Figure 2.1: Operation of a reverse flow reactor (Salomons et al., 2003) 9 

Figure 3.1: Concentration of species at equilibrium of POM with respect to temperature (oK) at molar feed ratio CH4/O2= 2 (Dang, 2005) 27 

Figure 3.2: A monolithic structure with square channels 36 

Figure 3.3: Flammability diagram of methane at an initial temperature and pressure of 25°C and 1atm (Mashuga & Crowl, 1998) 38 

Figure 3.4: Temperature profile with respect to time and reactor length (Botar-Jid et al., 2009) 40 

Figure 3.5: Central axis temperature profile after 20 cycles for different combinations of the specified velocity and switch time (Litto et al 2006) 44 

Figure 3.6: Development of the average temperature differences for methane combustion (0.4% CH4) in air (Gosiewski, 2004) 49 

Figure 3.7: Modification of the steepest accent method 51 

Figure 3.8: How the radius Rs depends on the choice of λ (Box & Draper 2007) 54 

Figure 4.1: Summary of methodology of the study 60 

Figure 4.2: Diagram of NiO-MgO/α-Al2O3 catalyst preparation 61 

Figure 4.3: Diagram of monolith catalyst preparation 63 

Figure 4.4: Schematic diagram of experimental set-up (Tran et al 2007) 64 

Figure 4.5: Schematic diagram the reactor (Tran et al 2007) 65 

Figure 4.6: Schematic diagram of reverse flow reactor in operation 66 

Figure 4.7: Initial temperature profile before operating the reverse-flow reactor (Tran et al., 2007) 67 

Figure 4.8: Reverse flow operation in the 1st half cycle (a) and 2nd half cycle (b) 69 

Figure 4.9: The temperature near the middle of the reactor during extinction (Tran

et al., 2007) 70 

Figure 4.10: An example of temperature record in cyclic steady state (Tran et al., 2007) 70 

Figure 5.1: Effect of initial temperature 84 

Figure 5.2: Results of experiments on steepest ascent path 85 

Figure 5.3: Contour plot of Methane Conversion 97 

Figure 5.4: Contour plot of Hydrogen Yield 97 

Figure 5.5: Activity test of monolithic catalyst 99 

Figure 5.6: Temperature trace of catalyst which is reduced twice 101 

Figure 5.7: Temperature trace of catalyst which is reduced three times 101 

LIST OF TABLES

Table 1.1 Information of the reverse flow reactor (Tran et al., 2007) 7 

Table 4.1 Summary of boundary conditions of independent factors 74 

Table 5.1 Experimental results from study of Tran et al (2007) 75 

Table 5.2 Multivariable regression of methane conversion 76 

Table 5.3 Multivariable regression of hydrogen yield 77 

Table 5.4 Effect of initial temperature 83 

Table 5.5 Experiments on steepest ascent path 84 

Table 5.6 The experimental results on the second design 86 

Table 5.7 The regression model of methane conversion on the second design 87 

Table 5.8 The first regression model of hydrogen yield on the second design 88 

Table 5.9 The second regression model of hydrogen yield on the second design 89 

Table 5.10 The second regression model of hydrogen yield on the second design 96  Table 5.11 Effect of in-use time on the catalyst 100 

Table 5.12 Effect of reduced times on the catalyst 100 

F Total flowrate (ml/min)

Fx readings of the flowrate of substance x

Lo Lower limit vector

px Partial pressure of substance x

R2 R-square value of least square regression

Rs Radius of hypersphere

t the state variable at the end of cycle

Tini Initial temperature (oC)

Up Upper limit vector

Δ(Fx) Error of flowmeter of substance x

ΔH Heat of reaction (kJ/mol)

ΔM resolution of molar feed ratio

δT Starting temperature deviation in consecutive half-cycles (K)

ΔTad Adiabatic temperature rise (K)

ΔT s Temperature difference due to heat transfer to surroundings

Chapter 1 INTRODUCTION

1.1 Background of the study

Synthesis gas, a mixture of hydrogen and carbon monoxide, is one of the six important feedstocks of petrochemical industries Synthesis gas can be used in the Fischer-Tropsch process to produce diesel, or could be converted into methanol and dimethyl ether in catalytic processes The purified carbon monoxide is a good feedstock for industrial power or some chemical processes, such as Monsanto process and Mond process The purified hydrogen is widely used in the petroleum and chemical industries Nowadays, applications of hydrogen can be found in the automotive, power generation, aerospace, and telecommunications industries Therefore, researchers are motivated to discover economical methods to produce synthesis gas

One of the raw materials for synthesis gas production is natural gas which consists mainly of methane There are two main methods to produce synthesis gas from natural gas: steam-reforming and partial oxidation Steam-reforming is an endothermic process in which an external heat source is required The combustion reaction of methane is used as the heat source of steam-reforming process Heat loss

in this process is quite high Moreover, steam-reforming produces a large amount of carbon dioxide which is less valuable than carbon monoxide (Bullis, 2007) The second method to produce synthesis gas is the partial oxidation of methane, a method which can be conducted with or without a catalyst The development of an economical catalyst with low cost, high activity and selectivity, high coking resistance, low temperature operation is important Doan (2005) developed a NiO-MgO/α-alumina catalyst for partial oxidation of methane to synthesis gas This catalyst is used in this study because it meets all requirements which have been

mentioned Partial oxidation is a mildly exothermic reaction If the reaction occurs

in a plug flow reactor, the outlet temperature is usually higher than the inlet temperature which causes heat loss Conducting partial oxidation of methane in a reverse flow reactor may be a solution to capture the heat In this reactor, the direction of flow is reversed cyclically Alteration of flow direction may capture the exothermic heat because there is heat exchange between the cool feed and the hot zone of the reactor

The first reverse flow reactor was defined in the patent of Cottrell (1938) as an apparatus in the gas purification process Frank-Kamenetski (1955) reused this term for the reactor in heterogeneous exothermic reaction According to Baljia et al (2007), this type of reactor has some advantages, such as autothermal operation, sustainability even under very poor feed conditions (for exothermic reactions), longer catalyst life and high performance Currently, many researchers study this reactor for many processes where energy trapping play an important factor The development of reverse flow reactor for partial oxidation of methane to synthesis gas is still at the initial stage because of some obstacles in catalyst preparation (Mitri et al., 2004), reactor design, reactor simulation and operation It may be difficult to develop an appropriate reactor with simple structure, low pressure drop and low cost operation The use of monolithic catalyst may be one solution to this problem In a flow reactor, the monolithic catalyst has an inherently low pressure drop because of its structure This structure can have a large surface area with lighter-weight materials Therefore, it is possible to increase the flowrate in the reactor or reduce the operating cost in energy for compression Partial oxidation of methane in a monolith reverse flow reactor may be an economical solution to produce synthesis gas

1.2 Statement of the problem

The implementation of reverse flow reactor in an industrial process still meets some obstacles Only a few industries employ this intricate concept in reactor operation (Baljia et al., 2007) The behavior of the reverse flow reactor is both continuous and discrete The flow in the reactor is continuous but its direction changes in discrete cycles Once the direction of flow changes, some properties of the reactants and the reactions in the reactor also change at the same time Researchers have developed many mathematical models for the processes in reverse flow reactor; recent studies focus on simulation and control strategy Computerized simulation of the reverse flow reactor has proven to be a valuable method to determine parameters which affect the reactor performance (Grigorios et al.,2001, Cittadini et al., 2002, Gosiewski and Warmuzinski, 2007) However, the simulation

of the reverse flow reactors requires many trials and much time in calculation Sometime, the results of simulation may not be a true reflection of reality; moreover, there are few published studies on real reverse flow reactors Determining the behavior and characteristic of the real reverse flow reactor may give more understanding regarding how to actually operate the reactor Therefore, the conduct

of studies about a real reverse flow reactor is necessary

The real reverse flow reactor which was optimized in this study was designed and built by Tran et al (2007) Some preliminary experiments were done to prove that the reactor could work The effect of varying the initial conditions on the final state and the transition to cyclic steady state was investigated by Phan (2008) Optimization has not been done in this reactor

It seems difficult to optimize the performance of a reverse flow reactor since its optimization inherits all of the complexity and difficulty of a cyclic process This may be the reason for the very few studies mentioned about optimization of this kind of reactor An appropriate methodology may solve this problem The response

significant method in optimization of the catalytic reactors (Silva et al., 2003; Hasan et al., 2005; Halim et al., 2007; Aziz et al., 2008; Liang, Zheng and Shen, 2008) The method of steepest ascent is chosen in this study because it is useful in the optimization of a cyclic system whose constraints and responses are determinate There are two possible responses of a reverse flow reactor that can be chosen

in optimization: temperature profile and functions of gas concentration (conversion and yields) The temperature profiles of reactors are usually chosen as the performance of reactors in simulation (Salomons et al., 2003; Kushsawa et al., 2004; Kushsawa et al., 2005 and Litto et al., 2006) The temperature profiles are very useful for engineers in the operation of a reverse flow reactor because the temperatures contain information about the conversion and stability of a reverse flow reactor (Litto et al., 2006) However, in a real reactor, it seems difficult to measure temperature at many points to obtain the temperature profile due to technical problems The yield of products and the conversion of reactants can be chosen as the responses in experimental optimization (Aziz et al., 2008; Halim et al., 2007; Liang, Zheng and Shen, 2008) The conversion of methane and yield of products which are chosen as the responses in this study are also meaningful parameters of partial oxidation of methane Hence, this study tries to answer the question:

How can the best value of hydrogen yield and methane conversion from partial oxidation of methane on NiO-MgO/α-alumina monolith catalyst in a reverse flow reactor be attained through the use of the method of steepest ascent?

1.3 Objectives of the study

This study intends to optimize initial conditions and operational parameters of the reverse flow reactor for partial oxidation of methane to synthesis gas over NiO-MgO/α-Al2O3 monolith catalyst using the method of steepest ascent This objective can be obtained through the following specific objectives:

1 To optimize the hydrogen yield and conversion of methane by changing five independent variables (factors): switching time, total flowrate, the molar feed ratio (CH4/O2); catalyst length and initial temperature

2 To investigate the effect of interactions among these five independent variables on the hydrogen yield and methane conversion

1.4 Significance of the study

Synthesis gas is a valuable feedstock of the petrochemical industries This gas can be used in the Fischer-Tropsch process to produce diesel, or it can be converted into methanol and dimethyl ether in catalytic processes Carbon monoxide can be used as energy for industrial power In the Monsanto process, carbon monoxide and methanol react to produce acetic acid in a homogeneous rhodium catalyst and hydrogen iodide This process is responsible for most of the industrial production of acetic acid Carbon monoxide is also used in industrial scale operations for purifying nickel and hydroformylation for production of high volume of aldehydes The hydrogen is widely used in the petroleum industry as an important reactant of hydrotreatment, such as hydrodealkylation, hydrodesulfurization, and hydrocracking Hydrogen in synthesis gas can be used in fuel cell and other green application The hydrogen economy is proposed to solve the ill effects of using hydrocarbon fuels and other end-use applications where the carbon is released to the atmosphere The investigation of partial oxidation of methane as a reaction which produces synthesis gas is, therefore, meaningful in industry

In this study, partial oxidation of methane is conducted in a reverse flow reactor This reactor has many advantages in saving energy, investment expenses and operating cost It is not necessary to supply heat to maintain high temperature, the heat from the exothermic reaction is used to maintain the reaction inside the reactor Moreover, NiO-MgO/α-Al2O3 is an economical catalyst and the monolithic

structure may decrease pressure drop and shorten the contact time The study may offer a comprehensive solution for partial oxidation of methane

Studies of partial oxidation of methane on structured catalyst, like monolith catalyst in a reverse flow reactor, is a challenging and promising research area Successful optimization of the reactor may offer information in improving the reverse flow reactor operation or its design on a larger scale Switching time, total flowrate and catalyst length are significant in design scale-up reactors (Dobrego et al., 2008a) The results of this study can also be used as a reference in experimental design of some studies such as: investigation of heat loss, alteration of catalyst Therefore, it is necessary to determine the optimum values of these variables in a real reactor

The behaviors of reverse flow reactors are complicated The optimum value of the responses cannot be obtained by simply changing the factor independently Therefore, studies on interactions of operational variables are useful in the operation of a real reverse flow reactor

The results of this study can offer information about the limitations of methane conversion and hydrogen yield in the operation of the current reactor Based on this information, the present reactor can be modified and improved Although, the optimum points have already been determined for this specific reactor, these values can still be reused in other studies using similitude analysis and dimensionless parameters

1.5 Scope and limitations

The reverse flow reactor which is mentioned in this study is a laboratory scale reactor whose information is represented in Table 1.1 Some operating parameters were limited such as: total flowrate, capacity and residence time The length and diameter of reactor cannot be changed during optimization

Table 1.1 Information of the reverse flow reactor (Tran et al., 2007)

Name

Dimensions

Materials Diameter

(m) Length (m) Thickness (mm)

Vacuum chamber 0.060 0.9 35 Stainless steel

Ceramic wool insulation 0.300 0.8 120 Ceramic wool

The length of the reactor and heating zone were fixed at values of 1m and

270mm respectively Therefore, increase of catalyst length was simultaneously

done with decrease of inert zone and vice-versa The catalyst length was limited by

the heating zone because the catalyst zone should be located inside the heating zone

The catalyst length was a discrete variable because of the limitation of cutting the

monolith The monoliths were prepared as small segments each of length 15mm

The catalyst length cannot be longer than the heating zone whose length was fixed

at 270mm

The thicknesses of insulator and vacuum jacket of reactor were fixed at values

of 120mm and 35mm, respectively The pressure in the vacuum jacket was

maintained as low as possible during experiments Therefore, effect of insulation

was excluded from the investigation The operation of the reactor was assumed to

be adiabatic; however, it could not be ensured that there was no heat loss during

reaction Therefore, eliminating the effect of insulation and the heat loss might be

limitation of this study

In this study, two positions along the central axis of the reactor were chosen to

monitor the temperature The first position was located in the middle of the central

axis; and the second one, on the edge of the catalytic zone Therefore, the central

axial and radial temperature profiles could not be determined However, these

temperature profiles are significant parameters They represent the two-dimensional

behaviors of the reactor Measurement of temperatures at only two positions is a

limitation of this study

The improvement and characterization of monolith catalyst were not included During optimization, activity test was done to confirm whether the catalyst deactivated during the course of the testing

The reactor was operated symmetrically The switching time of the two consecutive half cycles were equal Asymmetrical reverse flow operation was not included in this study All experiments were done under the pressure which was close to the atmospheric pressure

Methane with ultra-high purity and oxygen with high purity were used to conduct the experiments The specifications of other materials are presented in Appendix 1

Economic assessment is not included in optimization This study focuses on technical concerns

Chapter 2 REVIEW OF RELATED LITERATURE

2.1 Modification of reverse flow operation

A reverse flow reactor is a reactor in which the direction of flow is reversed cyclically In 1938, the idea of a reverse flow reactor was first defined in the patent

of Cottrell (Balaji et al., 2007) The reactor has many advantages in saving energy and expenses for investment and operation It is not necessary to supply heat to maintain a high temperature This temperature can be maintained by the exothermic heat of reaction

Figure 2.1: Operation of a reverse flow reactor (Salomons et al., 2003)

A unidirectional flow reactor has a temperature profile similar to the top forward flow profiles (a) and (b) The flow direction is reversed to accumulate energy as shown in (c) and (d) The temperature profile at cyclic steady state is shown in (e)

Figure 2.1 represents the operation of a reverse flow reactor In a plug flow reactor, the direction of flow is not changed with respect to time The flow enters the reactor at one end and leaves at the other end All properties of the reactor

change along the length Figure 2.1a and Figure 2.1b represent the temperature profiles of a plug flow reactor The peak of the profile moves from inlet to outlet with respect to time The inlet is always cool and the outlet is always hot because of the exothermic heat The high temperature in the outlet causes the loss in energy Therefore, recovery of the heat in this reactor is not possible One solution is the alteration of direction of flow to recover the heat Figure 2.1c and Figure 2.1d represent the temperature profiles when the flow is reversed The peak of the profile moves backward along the new direction with respect to time When the direction is altered cyclically, the peak of the profile also moves cyclically until the cyclic steady state is attained The temperature profile at cyclic steady state follows the shape represented in Figure 2.1e The peak of the profile in this state seems to oscillate around the middle of the reactor

2.2 Review of recent studies in reverse flow reactor

The difference between a reverse flow reactor and a counter-current reactor has been mentioned in some recent studies This topic clarifies the behavior of the reverse flow reactor by comparison with the classic plug flow reactor Botar-Jid et

al (2009) compared the performance of the two kinds of reactors using selective catalytic reduction of NOx with ammonia In the study of Botar-Jid et al (2009), investigation of the performance was done by a mathematical model based on heat and mass balances for the gas and solid phases The temperature profiles, the reactant conversion, as well as the response to disturbances in the feeding flow, were used as criteria for comparison Numerical simulations have shown that the counter-current reactor model may provide the same results as the reverse flow reactor model in terms of temperature profiles when certain values of heat transfer coefficient, switching time, flow conditions and reactor geometry are taken into consideration As a consequence of such similar thermal behavior, the counter-current reactor model could establish a limiting case of reverse flow reactor operation as regards the fast switching of the flow direction conditions

2.2.1 Control of reverse flow reactor

The reverse flow operation is both continuous and discrete in nature Control

of this system is challenging due to the unsteady state behavior of the process along with its mixed discrete and continuous behavior In the study of Edouard et al (2005), a linear-quadratic regulator control strategy is proposed and investigated to control a reverse flow reactor for the combustion of volatile organic compounds The new key issue of the control is to confine the temperature within two limits, instead of maintaining the temperature at a set point To achieve this, three phases

of operation were identified and two linear-quadratic regulator controllers were incorporated in a switching control structure With this strategy, the control objective is well defined and the control cost is minimized providing an advantage over the simple controller The reliability of the proposed control strategy is validated by simulation and experiments The hot spot temperature is well confined within the two limits, by dilution or internal heating, in the case of rich or lean feed, respectively (Edouard et al 2005)

Fuxman et al (2008) presented the formulation of a linear-quadratic feedback controller for a reverse flow reactor The controller was formulated and tested numerically for the catalytic combustion of lean methane The controller was developed on the basis of the catalytic reactor with unidirectional flow and was formulated to keep the temperature along the axis of the reactor at the stationary state values A spatially distributed input variable was considered to control the temperature distribution along the axis of the reactor and an upper bound was derived on the best achievable control The linear-quadratic controller was shown to lead to stable operation for inlet concentration disturbances which comprised the main source of process disturbance

The study of Balaji et al (2007) dealt with the control of a catalytic reverse flow reactor used for methane combustion using repetitive model predictive control strategy A one-dimensional pseudo-homogeneous nonlinear model extracted from

the detailed two-dimensional heterogeneous nonlinear model was used Dilution of the feed along with heat extraction from the mid section of the reactor under rich feed conditions and addition of reactants under poor feed conditions were done to maintain the maximum temperature of the reactor within the specified range According to Balaji et al (2007), the repetitive model predictive control strategy which was employed performed well The maximum temperature was controlled satisfactorily by means of the chosen manipulated variables One of the manipulated variables, the dilution rate became inadequate under abnormal feed conditions Therefore, the control strategy should be improved such as by withdrawing a part of the hot gas from the center of the reactor or adding cold gas

to the feed stream

2.2.2 Partial oxidation of methane in reverse flow reactor

In the 1990s the reverse flow reactor has been used to produce synthesis gas

by the partial oxidation of methane The catalyst in the partial oxidation of methane has an important role Mitri et al (2004) investigated the catalytic partial oxidation

of methane to synthesis gas at high temperature and short contact time conditions over three different noble metal catalysts (Pt, Rh, and Ir) The experimental results showed that reverse flow operation led to strong improvements in synthesis gas yields for all three catalysts, with particularly strong improvements for poorly performing catalysts Furthermore, as the catalyst temperature increased, resulting

in an accelerated deactivation of the unstable catalysts (Pt, Ir), the heat integration completely compensated for this acceleration Therefore, reverse flow operation has

an intrinsic “equalizing” and “self-regulating” effect on catalyst performance and offers a widely applicable reactor engineering approach to compensate for the poor

or degrading catalysts in high temperature partial oxidations with noble metal-based catalysts

Hevia et al (2007) also analyzed the role of the catalyst properties, such as the different activities and thermal stabilities of the studied catalysts, on the performance of reverse flow reactors for the combustion of lean methane-air mixtures The implications of these differences were studied using both a numerical heterogeneous one-dimensional model, and a bench-scale reverse flow reactor featuring a novel temperature control system Two different γ-Al2O3-supported industrial catalysts have been selected as representatives of the two types of catalysts used in these processes: metal oxides (mainly Mn oxide) and noble-metal-based (Pd) catalysts According to the results of Hevia et al (2007), noble-metal catalysts are more appropriate for leaner and stable mixture with closely constant composition; on the other hand, metal oxides are more appropriate for richer mixtures, allowing concentration variations to some extent The weaknesses of the noble-metal-based catalysts tend to disappear as their thermal resistance to deactivation is enhanced

In recent studies, the effect of steam on the partial oxidation of methane in a reverse flow reactor has been mentioned There are two approaches to demonstrate this influence In the study of Dobrego et al (2008b), steam was mentioned as a positive factor The influence of the addition of steam on partial oxidation methane

in a reverse flow porous media reactor is investigated numerically The model is validated via comparison to the experimental data obtained without steam addition According to the results of the study, hydrogen concentration in the product gas may be increased by 0.5–1% and the methane-to-hydrogen conversion ratio by 10–15% by the addition of steam to a working mixture Steam concentration which maximizes hydrogen yield is in the range of 5–10%; steam concentration which maximizes the conversion ratio is in the range of 20–50%

Bos et al (2007), however, mentions steam as a catalyst poison, moreover, the presence of steam may assist the steam-reforming process in the reactor Therefore, Bos et al (2007) suggest a novel reverse flow reactor to avoid feeding steam The

novel concept is obtained by adding two layers of a carefully selected adsorbent to both sides of the catalyst bed of a reverse flow reactor The steam is adsorbed at the low temperatures of the inlet section and thermally desorbed at the high temperature

of the reactor outlet Due to the periodic reverse flow operation, one adsorbent bed adsorbs water and the other works in desorption This novel reactor can be used to prevent undesired gases from entering the reactor

2.3 Optimization of cyclic processes

A cyclic process is a process that can reach a periodic state after a number of start-up cycles The periodic state is a limiting status in which the conditions at the end of each cycle are identical to those at the start Examples are pressure-swing adsorption processes, where the pressure changes periodically, temperature-swing adsorption processes, where the temperature changes periodically and the periodic reverse flow reactor, where the flow direction changes periodically Their control parameters and boundary conditions are also periodically changed Periodic separators and reactors are intrinsically dynamic processes, operated in a cyclic mode with a fixed cycle time Chemical processing today is increasingly reliant on dynamic processes for improved performance and efficiency To achieve process intensification, forced cyclic operations (which maximize energy efficiency or reduce capital costs) are attracting more attention (Chang et al., 2005; Adams and Seide, 2008)

The performance of periodic separators or reactors is critically affected by a large number of design and operating parameters These include, for example, the size of the beds, the physical characteristics of the adsorbent and the catalyst, the duration of the various steps in the cycle and the pressure levels in each step (van Noorden et al., 2003) These dynamic processes have many independent variables which cause complexity in control systems and difficulty in optimization According to van Noorden et al., (2003), there exists a distinction between two

different kinds of parameters in the optimization of cyclic processes: independent parameters and time-dependent parameters (also known as optimal control parameters) The time-dependent parameters are more significant than time-independent parameters because time-dependent parameter optimization can help to gain insight into the solution of a time-constant parameter optimization problem

time-Van Noorden et al (2003) optimized numerically the periodic adsorber and reactor behavior with respect to three time-constant parameters: the cycle duration, the feed pressure, and the ratio pressure between two steps of operating scheme which include the pressurization step and depressurization step The optimal controls of the feed pressure in both processes during the pressurization step were computed using a first-order gradient method in combination with the Newton–Picard method The computed optimal controls improved the performance of the processes considerably, as compared to the time-constant parameter optima The computed optimal controls indicated that the addition of two more steps in the operating scheme, a pre- and a post-pressurization step in which the feed end of the adsorber or reactor is closed, would also improve the time-constant parameter control performance of the processes To demonstrate this, the two processes were optimized with respect to five time-constant parameters: the individual duration of each the four steps in the cycle, and the feed pressure during the pressurization step The four-step cycle optima improved the performance of the optimal two-step cycles by approximately 25%

During optimization, the estimation of objective functions requires more time because the algorithms require many iterations Furthermore, it is very difficult or impossible to solve derivatives of the objective functions with respect to the

optimization variables Therefore, the objective functions are evaluated in a black

box, with inputs transformed into outputs in isolation (Adams and Seide, 2008)

There are two main types of important techniques in optimization of the cyclic

biological social networks where communications between members of the network help drive the optimizer toward the global optimum (Engelbrecht, 2005) These methods are compatible with unpredictable black-box objective functions and non-convex constraints In particle swarm optimization, the particles fly through the state space while evaluating the objective function at their current locations Each particle shares its best location with a network of “neighbors” and is used to influence their speed and direction (Engelbrecht, 2005)

Evolutionary algorithms, such as Genetic Algorithms use a fittest approach to create a “gene pool”, where each gene in the pool corresponds to one possible point in the search space Genes with poor objective functions are eliminated and replaced by the offspring of fitter genes (Wang et al 1998) Although this method is easy to implement and can be used for both continuous and discrete variables, particle swarm optimization is emerging as more effective for many systems, particularly in terms of efficiency (Adams and Seide, 2008)

survival-of-the-The two techniques mentioned above are useful for theoretical studies survival-of-the-There are few published studies in reverse flow reactor It seems difficult to optimize a real cyclic process because of the complexity of the system, the unpredictable objective and unknown constraints The solution can be obtained if there are many assumptions to simplify the system Therefore, optimum point may be the partial solution Moreover, simulation of cyclic process requires many trials and much time

in calculation Sometimes, the results of simulation may not be a true reflection of reality

2.4 Optimization of catalytic reactors

Optimization of reactors, especially catalytic reactors, is a non-trivial task because the performance of the reactor is related to a number of factors, including operation variables and catalyst performance, the physicochemical interactions among which are complicated and difficult to quantify (Zhou and Yuan, 2005) The

most complicated factor in optimizing this process is catalyst decay (Bartholomew, 2001) which is a consequence of physical and chemical changes on catalyst surface and leads to a continuous decreasing reactor performance According to Zhou and Yuan (2005), there are so many factors to be considered in optimization, a model which relates the performance of the reactor to the input variables required, on the basis of the extent to which the input variables can be optimized to maximize an economic index Several operating variables can be manipulated to maximize the profit, which include inlet temperature, feed concentration, feeding rate, operating pressure, and coolant temperature However, an economic index, especially the profit, is difficult to estimate and assess because there are many influencing factors which belong to social concerns

There are several aspects in the optimization of a reactor In recent studies, there are two common approaches of catalytic reactor optimization: stochastic methods (such as genetic algorithms) and response surface methods

2.4.1 Genetic algorithms in optimization catalytic reactor

Genetic algorithms are a class of non-traditional stochastic methods solving complex optimization problems of the real world They are optimization techniques that artificially simulate the gradual adaptation of natural chromosomes in the quest for better and more suitable individuals (Kordabadi and Jahanmiri, 2005) Genetic algorithms are used for optimization of the reactor and are used as powerful optimization techniques which give good solutions for this constrained nonlinear problem It is believed that genetic algorithms could be used as powerful techniques

to solve complex and real-world problems In the last two decades, genetic algorithms have been used on a large scale to solve engineering problems Some applications of genetic algorithms have been reported in chemical engineering such

as optimal design, operation and control (Nougués et al., 2002)

Most real-world problems involve the simultaneous optimization of multiple objectives Solution and results of these problems are conceptually different from single objective function problems In multiobjective optimization, there may not exist a solution that is the best with respect to all objectives Instead, there could exist an entire set of optimal solutions that are equally good, which are known as Pareto-optimal solutions A Pareto optimal set of solutions is such that when we go from any one point to another in the set, at least one objective function improves and at least one other worsens The combination of Pareto method and genetic algorithms offers comprehensive solution in theoretical studies in catalytic reactors (Yee et al., 2003)

In the study of Kordabadi and Jahanmiri (2005), the methanol synthesis reactor was optimized to maximize methanol production yield by genetic algorithms Methanol synthesis includes two stages In the first stage, natural gas is used to produce synthesis gas; in the second stage, methanol is produced from the synthesis gas Kordabadi and Jahanmiri (2005) tried to optimize the operation of a methanol synthesis reactor by using two different approaches In the first approach, optimal temperature profile along the reactor was studied for different activity level

In the second approach, a reactor with optimal two-stage cooling shell and optimal temperature trajectory during this time was realized This design yielded 2.9% additional methanol production during operating period A mathematical heterogeneous model was used in the optimization investigation

Rezende et al (2008) optimized a hydrogenation three-phase reactor The process considered in the study was the three-phase catalytic slurry reactor where the reaction of the hydrogenation of o-cresol on Ni/SO2 catalyst producing 2-methyl-cylcohexanol occurred The mathematical model used to describe this reactor is non-linear and of high dimensionality The genetic algorithm code was used, coupled with the non-linear mathematical model of the reactor The optimization employing genetic algorithm parameters optimized by trial and error

method showed that the genetic algorithm improved successfully the cyclohexanol productivity subject to the conversion environmental constraint In order to improve the optimization performance, the most significant genetic algorithm parameters on the genetic algorithm approach were determined by factorial design A central composite design was then used efficiently to find out the best values of these genetic algorithm parameters The fitted values of the genetic algorithm parameters led to the final optimization run, which found the best eight values of input process variables that gave the maximal steady state productivity of 2-methylcyclohexanol The results showed an improvement of 318% in the objective function when genetic algorithm parameters were optimized by factorial design approach rather than when non-optimized genetic algorithm parameters were employed

2-methyl-Genetic algorithms are theoretical methods for catalytic reactor optimization Besides theoretical understanding about catalytic reactor, the experimental knowledge is significant The combination of two approaches offers a comprehensive understanding about the behavior of the reactors

2.4.2 Response surface methods in optimization of catalytic

reactors

Response surface methodology is a collection of mathematical and statistical techniques widely used to determine the effects of several variables and to optimize different chemical and biotechnological processes (Aziz et al., 2008) Response surface methodology is considered the method of single objective optimization However, most real-world problems are combinations of multiple objectives Therefore, there are two different scalar approaches to handle the problems The first choice is optimization of one of the targets as a single objective function, treating additional targets as constraints The second solution is aggregation of all targets into a single objective function by using weighting factors Both approaches

require simple algorithms, but the solution depends on how the problem is structured According to Silva et al (2003), the drawback of the first approach is the choice of the function to be optimized and the levels of constraints to be set In the second approach, the assignment of the values to the weighting factors, which is often done quite arbitrarily, poses the deficiency of the method Moreover, the aggregation of all targets into a single objective function implies the homogenization of different quantities, such as costs, quality of the products and environmental effects, to a common unit of measure

Halim et al (2007) used the response surface methodology to optimize transesterification of waste cooking palm oil with methanol using tert-butanol as solvent in a continuously-packed-bed reactor The objectives were to better understand the relationships between the reaction variables (substrate flowrate and packed-bed height) and the response, fatty acid methyl esters yield and to achieve the optimal continuous transesterification condition in a packed-bed reactor system

by using statistical experimental design and response surface methodology A level-two-factor, centre composite rotatable design was employed The optimum conditions of packed bed height and substrate flowrate were 10.53 cm and 0.57ml.min-1, respectively and 79.1% fatty acid methyl esters yield was obtained The solution from the optimization contributes to the design and controls transesterification in the packed-bed reactor

five-In the study of Liang, Zheng and Shen (2008), three independent variables (cells loading, substrate concentration, air flowrate) were chosen to define the optimal conditions for β-alanine production by response surface methodology using

a 23 central composite design with seven central points and six axial points added Response surface methodology was employed to evaluate the effects of cell loadings, substrate concentration, and air flowrate on the productivity of β -alanine, which was produced in a bubble column reactor

In recent literatures, response surface methodology has been used as a meaningful method in experimental optimization (Halim et al., 2007; Liang, Zheng and Shen, 2008) However, response surface methodology has the disadvantage that the number of experiments increases with respect to the number of independent variables Therefore, the dimensions of optimization are limited Hence, it is necessary to submit the process to an initial screening design prior to optimization (Hasan et al., 2005) Plackett–Burman designs are very useful for picking the most important factors from a list of candidate factors, moreover, these designs require fewer runs than a comparable fractional design (Kalil et al., 2000; Hasan et al., 2005) However, the methodology presents contrasts that confound main effects with two-factor interactions, so it is assumed that the important main effects may be much larger than the two-factor interactions (Kalil et al., 2000) Furthermore, if the number of runs is higher than the number of variables, the resolution is better than with a saturated design This design is practical, especially when the investigator is faced with a large number of factors and is unsure which settings are likely to produce optimal or near optimal responses (Hasan et al., 2005)

2.5 Optimization of reverse flow reactors

Reverse flow reactor is a combination of cyclic process and catalytic reactor Therefore, the optimization of a reverse flow reactor is complex and difficult It may be the reason why very few studies mention the optimization of this kind of reactor especially in experimental optimization However, some studies tried to understand the behavior of a reverse flow reactor by modeling and simulation Litto

et al (2006) used simulation method to investigate the operation factors that affect a reverse flow reactor Thermal properties (including thermal mass and thermal conductivity), interaction between switching time and superficial gas velocity and geometric parameters (which include diameter of reactor and thickness of insulation) have strong effects on the behaviors of reverse flow reactor

Salomons et al (2003), based on the experiments performed from catalytic combustion of lean methane mixture in the reverse flow reactor, drew a number of conclusions The first is that it is possible to maintain auto-thermal operation of the reactor at methane concentrations as low as 0.22% with feed at ambient temperature This operation would not be possible in a direct flow system The overall performance of the system is dependent on methane concentration, cycle time and velocity In a system with relatively low inlet velocity and relatively high methane concentration, there is a chance of creating localized hot spots in the catalyst These hot spots form when the thermal energy generated by the reaction is not fully distributed through the catalyst Increasing the heat transfer between hot spots and the rest of the catalyst by increasing the effective thermal conductivity of the catalyst or by increasing convection heat transfer may help to delocalize the thermal energy A large disparity between the peak temperature and the extraction temperature may decrease the efficiency of energy extraction

The experimental results from the study of Salomons et al (2003) indicate the presence of radial gradients in the reactor These gradients are expected to affect reactor performance, and must be considered when evaluating the dynamics of the reactor A traditional centreline temperature profile is insufficient to capture the dynamics of the system adequately The gradients are dynamic and complex, and appear to be influenced by several competing factors Litto et al (2006) also confirm that the primary scaling parameter is the reactor diameter; special care must

be paid to this variable, especially in large units where the wall effects are expected

to be minimal However, the two-dimensional behavior of the reactor cannot be ignored in smaller units

Smit et al (2007) investigated the technical feasibility of the reverse flow catalytic membrane reactor concept with porous membranes for energy efficient synthesis gas production The study found that shorter switching times not only result in higher switching losses, but also in higher synthesis gas selectivity

Increasing the methane weight fraction in the air feed leads to higher temperatures outside the filter section, but remarkably to a lower carbon monoxide selectivity and

a lower methane conversion This is attributed to the fact that carbon dioxide, which

is generated during the combustion in the shell compartment, is converted very slowly to synthesis gas in the tube compartment This problem can be overcome by locating also some catalyst just outside the filter section With respect to the length

of the combustion section, it was observed that it should not be too long and not too short to prevent low temperatures at the end of the filter section just after switching the flow directions (Smit et al., 2007)

The study of Marin et al (2006) shows that the particle bed performs better in terms of reactor stability The difference between both configurations decreases as the surface velocity increases As regards the maximum temperature attained in the catalytic bed, the behavior of both types of beds is very similar, whereas the pressure drop is largely higher in the particle bed reactor In spite of its lower stability range, results from the study of Marin et al (2006) indicate that monolithic reverse flow reactors can perform adequately and are very significant alternatives for large-scale reactors This is mainly due to the lower pressure drop; but there are also other favorable characteristics, such as the higher intraparticle effectiveness factor, and higher solid density

2.6 The method of steepest ascent in optimization

The method of steepest ascent is a simple, economical and efficient procedure developed to move the experimental region of a response in the direction of the maximum change toward the optimum (Wang and Wan, 2008) If there are many factors in the system, the factors can be screened by the Plackett–Burman design to eliminate the insignificant factors before using this method (Wang and Wan, 2008) Wang and Wan (2008) briefly introduced design methods which are used in optimization In addition, the advantages and disadvantages of each design method

were mentioned Based on the discussed information, the combination of the method of steepest ascent and Plackett–Burman design is recommended

Anunziana and Cussa (2008) successfully optimized the activation of methane using ethane as co-reactant into higher hydrocarbons on Zn-containing zeolite catalyst using the method of steepest ascent There are four independent variables: time on stream, space velocity of ethane, molar fraction of methane and reaction temperature This methodology allows a better understanding of the influence of the independent variables on the methane conversion, reducing the operation costs, achieving efficiency and effectiveness of methane activation process Based on the results, Anunziana and Cussa (2008) indicated that the reaction time, the interactions of the time on stream and temperature significantly affect methane conversion

Reese et al (2009) used the steepest ascent method to maximize hydrogen production per mole of supplied oxygen in a laboratory-scale catalytic autothermal reformer Oxygen-to-carbon and water-to-carbon ratios were used as independent variables Surface response methodology was employed using a 22 factorial design The optimal experimental conditions occurred at the water-to-carbon ratio of 3.00–3.35 and the oxygen-to-carbon ratio of 0.44–0.48

The results from previous studies have confirmed the validity and capability

of the method of steepest ascent in autothermal reactors The steepest ascent method seems to be widely used in many fields However, there have been no published experimental studies about reverse flow reactor using this method Therefore, it is necessary to prove its validity in studies regarding reverse flow reactor

2.7 Related studies in De La Salle University - Manila

The preparation method of NiO-MgO/α-Al2O3 catalyst in powder form was investigated by Doan (2005) using partial oxidation of methane in a fixed-bed flow reactor Simultaneous dissolution of the nickel and magnesium salts may be a

preparation method which has better carbon deposition resistance (Doan, 2005) This method was also used in this study to prepare the powder catalyst and the detail of this method is presented in the section 4.1

Dang (2005) used simulation to determine the narrow ranges of some parameters of the reverse flow reactor such as: switching time, total flowrate, initial temperature Design and fabrication of the real reactor was done for the first time in

De La Salle University by Tran et al (2007) Coating catalyst powder on monolith was also proposed as the appropriate method in the preparation of ceramic monolithic catalyst (Tran et al., 2007) The preliminary experiments of Tran et al (2007) are used in this study as the first experiment design

Phan (2008) investigated the effect of initial temperature, operating parameters and start-up procedure on the behavior of the reverse flow reactor during start-up stage The initial temperature of 700oC was proposed Phan (2008) suggested the start-up procedure which is presented in section 4.3.2.2 In this procedure, the flowrate of methane and oxygen was increased gradually to the desired value during the start-up stage Based on the activity test, the old monolithic catalyst which was used in the reverse flow reactor for 30 hours had nearly the same activity as the new monolithic catalyst The effect of catalyst deactivation on experimental results can be eliminated when using a time duration less than 30 hours (Phan, 2008) The monolithic catalyst should be regenerated after using every ten hours