A comparison of auto-thermal and conventional methanol synthesis reactor in the presence of catalyst deactivation

This study proposed a one-dimensional dynamic plug flow model to analyze and compare the performance of an auto-thermal and a conversional methanol synthesis reactor in the presence of catalyst deactivation. An auto-thermal two-stage industrial methanol reactor type is a system with two catalyst beds instead of one single catalyst bed. In the first catalyst bed, the synthesis gas is partly converted to methanol in a water-cooled reactor. In the second bed which is a gas-cooled reactor, the reaction heat is used to preheat the feed gas to the first bed. To analyze the effect of important control variables on the rector performance, steady state and dynamic simulations are utilized to investigate effect of operating parameters on the performance of reactors. The simulation results show that there is a favorable profile of temperature along the two-stage auto-thermal reactor type in comparison with conventional single stage reactor type. In this way the catalysts are exposed to less extreme temperatures and, catalyst deactivation via sintering is reduced. Overall, this study resulted in beneficial information about the performance of the reactor over catalyst life-time.     

Dynamic mathematical modeling of a novel dual-type industrial ethylene oxide (EO) reactor

In this paper, the dynamic behavior of a novel dual-type industrial ethylene oxide reactor has been proposed with taking catalyst deactivation into account. The configuration of two catalyst beds instead of one single catalyst bed is developed for conversion of ethylene to ethylene oxide. In the first reactor which is an industrial fixed-bed water-cooled reactor, the feed gas is partly converted to ethylene oxide. This reactor functions at very high yield and at a higher than normal operating temperature. In the second converter, the reaction heat is used to preheat the feed gas to the first reactor and a milder temperature profile is observed. The potential possibilities of a two-stage catalyst bed system are analyzed using a 1D heterogeneous dynamic model to obtain necessary comparative estimates. A differential evolution (DE) algorithm is applied as an effective and robust method to optimize the reactors length ratio. The results obtained from the simulation demonstrate that there is a desirable catalyst temperature profile along the dual-type reactor (DR) compared with the conventional single-type reactor (SR). In this way, the catalysts are exposed to less extreme temperatures and thus, diminishing the catalyst deactivation via sintering. Results from this study provided beneficial information about the effects of reactors configuration on catalyst lifetime and ethylene oxide production rate simultaneously.     

Dynamic modeling and operability analysis of a dual-membrane fixed bed reactor to produce methanol considering catalyst deactivation

The goal of this research is dynamic operability analysis of dual-membrane reactor considering catalyst deactivation to produce methanol. A dynamic heterogeneous one-dimensional model is developed to predict the performance of this configuration. In this configuration, a conventional reactor has been supported by a Pd/Ag membrane tube for hydrogen permeation and alumina–silica composite membrane tube to remove water vapor from the reaction zone. To verify the accuracy of the considered model, the results of conventional reactor are compared with the plant data. The main advantages of the dual-membrane reactor are: higher catalyst activity and lifetime, higher CO₂ conversion and methanol production.     

Application of hydrogen-permselective Pd-based membrane in an industrial single-type methanol reactor in the presence of catalyst deactivation

This work presents application of palladium-based membranes in a conventional single-type methanol reactor. A novel reactor configuration with hydrogen-permselective Pd and Pd–Ag membrane are proposed. In this configuration the reacting synthesis gas is fed to the shell side of reactor while the high pressure product is routed from recycle stream through tubes of the reactor in a co-current mode with reacting gas. The reacting gas is cooled simultaneously with recycle gas in tube and saturated water in outer shell. The permselective palladium layer on inner tube allows hydrogen to penetrate from the tube side to the reaction side. In this work, the results of two types of novel membrane reactors are compared with a conventional methanol synthesis reactor at identical process conditions. Also the effect of key parameters such as membrane thickness, reaction and tube side pressure, ratio of tube side flow rate to reaction side flow rate on performance of reactor are investigated. The steady-state and quasi-steady-state simulations results show that there are favorable profiles of temperature and methanol mole fraction along the reactor in proposed reactor relative to conventional reactor system. Therefore using this novel configuration in industrial single-type methanol reactor improves methanol production rate.     

Methanol synthesis in a novel axial-flow, spherical packed bed reactor in the presence of catalyst deactivation

Since in the foreseeable future liquid hydrocarbon fuels will play a significant role in the transportation sector, methanol might be used potentially as a cleaner and more reliable fuel than the petrochemical-based fuels in the future. Consequently, enhancement of methanol production technology attracts increasing attention and, therefore, several studies for developing new methanol synthesis reactors have been conducted worldwide. The purpose of this research is to reduce the pressure drop and recompression costs through the conventional single-stage methanol reactor. To reach this goal, a novel axial-flow spherical packed bed reactor (AF-SPBR) for methanol synthesis in the presence of catalyst deactivation is developed. In this configuration, the reactor is loaded with the same amount of catalyst in the conventional single-stage methanol reactor. The reactants are flowing axially through the reactor. The dynamic simulation of the spherical reactors has been studied in the presence of long-term catalyst deactivation for four reactor configurations and the results are compared with the achieved results of the conventional tubular packed bed reactor (CR). The results show that the three and four stages reactor setups can improve the methanol production rate by 4.4% and 7.7% for steady state condition. By utilizing the spherical reactors, some drawbacks of the conventional methanol synthesis reactors such as high pressure drop, would be solved. This research shows how this new configuration can be useful and beneficial in the methanol synthesis process.     

Study of the catalyst deactivation in an industrial gasoil HDS reactor using a mini-scale laboratory reactor

The activity of a hydrodesulphurization catalyst loaded in an industrial hydrotreater is studied at start up and end of run. Catalyst initial and final activity was determined by performing HDS experiments at industrial conditions in a laboratory mini-scale hydrotreater. The results show that the deactivation of the catalyst samples collected from three different places of the industrial reactor do not vary significantly, the maximum difference among the catalyst samples, being less than ±4%. The experimentally determined deactivation level of the catalyst samples is compared with the deactivation estimated for the same industrial reactor and the same load using a hybrid neural network model trained with operational data of the industrial and the results are in close agreement. Catalyst deactivation appears to be faster for hydrogen consumption reactions than for hydrodesulphurization reactions indicating a decreasing hydrogen consumption trend with time in operation for specific sulphur content in the product.     

The effect of a membrane reactor upon catalyst deactivation during hydrodechlorination of dichloroethane

The hydrodechlorination of 1,2-dichloroethane was studied over a Rh/SiO₂ catalyst. The catalyst deactivated with use; only part of the deactivation was reversible. The reversible deactivation could be quantitatively accounted for by assuming quasi-equilibrium between surface chlorine and gas phase HCl. An empirical power-law rate expression was found that adequately described the kinetics when used in combination with this assumption of quasi-equilibrium. Experimental results as well as simulation showed that a membrane reactor can reduce the degree of catalyst deactivation by selective removal of HCl. The membrane reactor can also lessen deactivation through dilution of the reaction zone. In this study, using a porous membrane, the predominant effect is one of dilution, not selective HCl removal.     

Dynamic operation of butadiene dimerization reactor undergoing catalyst deactivation

Operation of fixed-bed catalytic reactors undergoing catalyst deactivation has been investigated as an optimal control problem to yield optimal temperature policies. An efficient numerical scheme using a control vector iteration method based on gradients in functional space is developed. The procedure is applied to develop optimal temperature profiles for a butadiene dimerization process. The temperature-time trajectories and dynamic activity profiles are strongly influenced by kinetics. A sensitivity analysis is done to study the effect of flow rates, conversion level and parameters that influence kinetic and deactivation processes. These results have been validated with experimentation on a lab scale reactor and a 9.14 m pilot-plant reactor.     

On the dynamical instability of packed-bed reactors in the presence of catalyst deactivation

Due to the thermal instability of the packed-bed reactor running an exothermic reaction, unsteady-state operation (for example a fluctuating inflow temperature) can result in a variety of thermal responses. These include the amplification of input temperature perturbations and high-temperature pre-extinction waves. Catalyst deactivation adds further dynamical features to these scenarios. We explore them numerically, using a first-order exothermic reaction and a pseudo-homogeneous (single phase) model of the PBR together with a first-order deactivation model of the catalyst. At low deactivation rate, moving hot spots are found, as well as a non-uniform activity profile of the catalyst. At high deactivation rate, however, high-temperature waves (so-called pre-extinction waves) are followed by the complete extinction of the reactor. The amplification of input temperature perturbations is generally enhanced by the presence of catalyst deactivation. Finally, a power-law model is derived numerically that predicts the resonance frequency for amplification as a function of operating parameters.     

Dynamic modelling of catalytic liquid-phase reactions in fixed beds—Kinetics and catalyst deactivation in the recovery of anthraquinones

Dynamic modelling of catalytic fixed-bed reactors with liquid-phase feed is of crucial importance, since catalyst deactivation often plays a central role in reaction engineering. General dynamic modelling of liquid-phase fixed beds was considered, including complex reaction kinetics and catalyst deactivation. The modelling concept was applied on a catalytic liquid-phase conversion reaction. The model was tested with pilot-plant data and showed a good predictivibility. The model can be used to optimize the production life cycles of fixed beds with catalyst deactivation.     

A pseudo-dynamic optimization of a dual-stage methanol synthesis reactor in the face of catalyst deactivation

This paper presents an optimization investigation on methanol synthesis reactor in the face of catalyst deactivation using multi-objective genetic algorithms. Catalyst deactivation is a challenging problem in the operation of methanol synthesis reactor and has an important role on productivity of the reactor. Therefore, determination of the optimal temperature profile along the reactor could be a very important effort in order to cope with catalyst deactivation. Our previous studies clarify the benefits of a two-stage reactor over a single stage reactor. In this study, an optimal temperature trajectory is obtained for each stage of the corresponding two-stage reactor. Here, steady state optimization is performed in six different activity levels by maximizing the yield and minimizing the temperature of the first stage of the reactor. Multi-objective genetic algorithms are used to solve this two-objective optimization. The set of optimal solutions obtained for six activity levels represents an optimal temperature trajectory for each stage, which has been extended and proposed as a dynamic optimization. This optimization resulted in an additional 3.6% yield, during the course of 4-year process.     

Fuzzy modeling and hybrid genetic algorithm optimization of virus removal from water using microfiltration membrane

Membranes are finding increasing applications in disinfection processes including virus removal from water for municipal effluent reuse. The capability of virus removal from water by microfiltration membranes has previously been demonstrated. In this study, the capability of fuzzy logic for modeling and simulation of dead-end microfiltration process for removal of IBR and FMD viruses from water was elucidated. The main parameters indicating membrane performance i.e. flux and rejection were experimentally obtained under different conditions and compared with theoretically calculated flux and rejection using fuzzy inference system. The genetic algorithm which is an efficient and systematic method was employed in the design of fuzzy model for optimization of the poorly understood, irregular and complex membership function with improved performance. Hybrid genetic algorithm was used for optimizing the parameters that are located at the Gaussian membership functions in the premise and consequent of each rule.The results indicated that fuzzy inference system predicts the key parameters i.e. flux and rejection for different operating conditions with an acceptable error. In other words FIS is able to apply for modeling the microfiltration membrane which is mathematically difficult or in many cases an unpredictable process.     

Dynamic simulation of a cascade fluidized-bed membrane reactor in the presence of long-term catalyst deactivation for methanol synthesis

In this work, a dynamic model for a cascade fluidized-bed hydrogen permselective membrane methanol reactor (CFBMMR) has been developed in the presence of long-term catalyst deactivation. In the first catalyst bed, the synthesis gas is partly converted to methanol in a water-cooled reactor, which is a fluidized-bed. In the second bed, which is a membrane assisted fluidized-bed reactor, the reaction heat is used to preheat the feed gas to the first bed. This reactor configuration solves some observed drawbacks of new conventional dual type methanol reactor (CDMR) and even fluidized-bed membrane dual type methanol reactor (FBMDMR) such as pressure drop, internal mass transfer limitations, radial gradient of concentration and temperature in both reactors. A dynamic two-phase theory in bubbling regime of fluidization is used to model and simulate the proposed reactor. The proposed model has been used to compare the performance of a cascade fluidized-bed membrane methanol reactor with fluidized-bed membrane dual-type methanol reactor and conventional dual-type methanol reactor. The simulation results show a considerable enhancement in the methanol production due to the favorable profile of temperature and activity along the CFBMMR relative to FBMDMR and CDMR systems.     

Multiobjective dynamic optimization of an industrial nylon 6 semibatch reactor using genetic algorithm

The nondominated sorting genetic algorithm (NSGA) is adapted and used to obtain multiobjective Pareto optimal solutions for three grades of nylon 6 being produced in an industrial semibatch reactor. The total reaction time and the concentration of an undesirable cyclic dimer in the product are taken as two individual objectives for minimization, while simultaneously requiring the attainment of design values of the final monomer conversion and for the number-average chain length. Substantial improvements in the operation of the nylon 6 reactor are indicated by this study. The technique used is very general in nature and can be used for multiobjective optimization of other reactors. Good mathematical models accounting for all the physicochemical aspects operative in a reactor (and which have been preferably tested on industrial data) are a prerequisite for such optimization studies. © 1998 John Wiley & Sons, Inc. J Appl Polym Sci 69: 69–87, 1998     

A dense Pd/Ag membrane reactor for methanol steam reforming: Experimental study

This paper focuses on an experimental study of the methanol steam reforming (MSR) reaction. A dense Pd/Ag membrane reactor (MR) has been used, and its behaviour has been compared to the performance of a traditional reactor (TR) packed with the same catalyst type and amount. The parameters investigated are reaction time, temperature, feed ratio and sweep gas flow rate. The few papers dealing with MR applications for the MSR reaction mainly analyse the effect of temperature and pressure on the reaction system. The investigation of new parameters permitted to better understand how the fluid-dynamics of the MR influences the hydrogen separation effect on methanol conversion and product selectivity. The comparison between MR and TR in terms of methanol conversion shows that the MR gives a higher performance than the TR at each operating condition investigated. Concerning hydrogen production, the experiments have shown that the overall selectivity towards hydrogen is identical for both MR and TR. However, the MR produces a free-CO hydrogen stream, which could be useful for direct application in proton exchange membrane fuel cells. A comparison, in terms of methanol conversion versus temperature, with literature data is also included.     

Multiobjective optimization of an industrial grinding operation using elitist nondominated sorting genetic algorithm

The elitist version of nondominated sorting genetic algorithm (NSGA II) has been adapted to optimize the industrial grinding operation of a lead-zinc ore beneficiation plant. Two objective functions have been identified in this study: (i) throughput of the grinding operation is maximized to maximize productivity and (ii) percent passing of one of the most important size fractions is maximized to ensure smooth flotation operation following the grinding circuit. Simultaneously, it is also ensured that the grinding product meets all other quality requirements, to ensure least possible disturbance in the following flotation circuit, by keeping two other size classes and percent solid of the grinding product and recirculation load of the grinding circuit within the user specified bounds (constraints). Three decision variables used in this study are the solid ore flowrate and two water flowrates at two sumps, primary and secondary, each of them present in each of the two stage classification units. Nondominating (equally competitive) optimal solutions (Pareto sets) have been found out due to conflicting requirements between the two objectives without violating any of the constraints considered for this problem. Constraints are handled using a technique based on tournament selection operator of genetic algorithm which makes the process get rid of arbitrary tuning requirement of penalty parameters appearing in the popular penalty function based approaches for handling constraints. One of the Pareto points, along with some more higher level information, can be used as set points for the previously mentioned two objectives for optimal control of the grinding circuit. Implementation of the proposed technology shows huge industrial benefits.     

Membrane/sorption-enhanced methanol synthesis process: Dynamic simulation and optimization

In this study, a dynamic mathematical model of a Membrane-Gas-Flowing Solids-Fixed Bed Reactor (Membrane-GFSFBR) with in-situ water adsorption in the presence of catalyst deactivation is proposed for methanol synthesis. The novel reactor consists of water adsorbent and hydrogen-permselective Pd-Ag membrane. In this configuration feed gas and flowing adsorbents are both fed into the outer tube of the reactor. Contact of gas and fine solids particles inside packed bed results in selective adsorption of water from methanol synthesis which leads to higher methanol production rate. Afterwards, the high pressure product is recycled to the inner tube of the reactor and hydrogen permeates to the outer tube which shifts the reaction towards more methanol production. Dynamic simulation result reveals that simultaneous application of water adsorbent and hydrogen permeation in methanol synthesis process contributes to a significant enhancement in methanol production. The notable advantage of Membrane-GFSFBR is the continuous adsorbent regeneration during the process. Moreover, a theoretical investigation has been performed to evaluate the optimal operating conditions and to maximize the methanol production in Membrane-GFSFBR using differential evolution (DE) algorithm as a robust method. The obtained optimization result shows there are optimum values of inlet temperatures of gas phase, flowing solids phase, and shell side under which the highest methanol production can be achieved.     

Multiobjective optimization of an industrial nylon-6 semibatch reactor system using genetic algorithm

Multiobjective Pareto optimal solutions for three different grades of nylon-6 produced in an industrial semibatch reactor are obtained by using the adapted Nondominated Sorting Genetic Algorithm (adapted NSGA). The two objective functions minimized are the total reaction time and the concentration of undesirable cyclic dimer in the product, while simultaneously attaining desired values of the monomer conversion and the number average chain length. The control variables used are the fractional valve opening f(t) and the jacket fluid temperature T_J. The study shows a marked improvement over current industrial operation. It is found that the optimal values of the cyclic dimer concentration in the product are worse (higher) when the reactor-control valve system is studied than when the reactor is considered alone. This is because the control valve leads to additional constraints. The technique used is quite general and can be used to study other reactor systems as well. © 1999 John Wiley & Sons, Inc. J Appl Polym Sci 73: 729–739, 1999     

A two-stage catalyst bed concept for conversion of carbon dioxide into methanol

Conversion of CO₂ into methanol by catalytic hydrogenation has been recognized as one of the most promising processes for stabilizing the atmospheric CO₂ level, and furthermore the methanol produced could be used as fuel or basic chemical for satisfying the large demand world-wide. The present work investigates a two-stage catalyst bed concept for conversion of CO₂ to methanol. A system with two catalyst beds instead of one single catalyst bed is developed for conversion of CO₂ to methanol. In the first catalyst bed, the synthesis gas is partly converted to methanol in a conventional water-cooled reactor. This bed operates at higher than normal operating temperature and at high yield. In the second bed, the reaction heat is used to pre-heat the feed gas to the first bed. The continuously reduced temperature in this bed provides increasing thermodynamic equilibrium potential. In this bed, the reaction rate is much lower and, consequently, so is the amount of the reaction heat. This feature results in milder temperature profiles in the second bed because less heat is liberated compared to the first bed. In this way the catalysts are exposed to less extreme temperatures and, catalyst deactivation via sintering is circumvented. In this work, a one-dimensional dynamic plug flow dynamic is used to analyze and compare the performance of two-stage bed and conventional single bed reactors. The results of this work show that the two-stage catalyst bed system can be operated with higher conversion and longer catalyst life time.