Enhanced model predictive control of a catalytic flow reversal reactor

The combustion of lean methane air mixtures in a catalytic flow reversal reactor (CFRR) is studied using a two dimensional heterogeneous continuum model, based on mole and energy balance equations for the solid (the inert and catalytic sections of the reactor) and the fluid phases. Following a design of experiments (DOE), many simulations were carried out to investigate the reactor performance. The results show the impact on the methane conversion and the maximum temperature in the reactor of key process parameters such as the methane inlet concentration, the superficial gas velocity, the switching time, and the mass extraction rate. A simple empirical model is deduced to predict the maximum temperature and conversion of methane in the reactor at stationary state. This model is combined with a model predictive control (MPC) strategy in the form of a terminal constraint to improve the controller performance. Results show that the control of the reactor is improved.     

A logic-based controller for the mitigation of ventilation air methane in a catalytic flow reversal reactor

The control system of a catalytic flow reversal reactor (CFRR) for the mitigation of ventilation air methane was investigated. A one-dimensional heterogeneous model with a logic-based controller was applied to simulate the CFRR. The simulation results indicated that the controller developed in this work performs well under normal conditions. Air dilution and auxiliary methane injection are effective to avoid the catalyst overheating and reaction extinction caused by prolonged rich and lean feed conditions, respectively. In contrast, the reactor is prone to lose control by adjusting the switching time solely. Air dilution exhibits the effects of two contradictory aspects on the operation of CFRR, i.e., cooling the bed and accumulating heat, though the former is in general more prominent. Lowering the reference temperature for flow reversal can decrease the bed temperature and benefit stable operation under rich methane feed condition.     

Demonstration of a control system for combustion of lean hydrocarbon emissions in a reverse flow reactor

In this work, the performance of a simple logic-based controller for a reverse flow reactor (RFR) has been tested experimentally. The controller is a hybrid system using the inside reactor temperature as the controlled variable, and the switch of the flow direction as the manipulated variable. Three different control logic rules (depending on the point selected to measure the inside reactor temperature) have been compared for the catalytic combustion of methane in a bench-scale RFR unit. A procedure for tuning the controllers was established. The controller that measures the temperature in the middle of the reactor showed the best performance, as it provided complete methane conversion with high capacity to overcome both low and high feed concentration disturbances.     

Catalytic Combustion Kinetics: Using a Direct Search Algorithm to Evaluate Kinetic Parameters from Light‐Off Curves

This paper describes a method for evaluating the kinetic constants in a rate expression for catalytic combustion applications using experimental light‐off curves. The method uses a transient one‐dimensional single channel monolith finite element reactor model to simulate reactor performance. The heat and mass transfer models used account for developing flow in the entrance region. A parameter global optimization routine based on a generalized pattern Search algorithm is used to determine the best fit parameters in the rate expression for the oxidation of CO and mixtures of CO and CH4. The algorithm is compared to a more classical gradient method, the Fletcher‐Reeves method.     

CATALYTIC COMBUSTION OF NATURAL GAS IN A FIXED BED REACTOR WITH FLOW REVERSAL

A new application of the fixed bed catalytic reactor with flow reversal for combustion of natural gas is investigated by mathematical modeling and computer simulation. Comparison between the results obtained for this new reactor and those for a classic catalytic fixed bed is made. Inexpensive perovskite type catalysts containing no noble metals were used. It is shown that an appropriate choice of operating parameters (concentration and temperature of input gas mixture, superficial gas velocity, size and shape of catalyst and inert material, volumetric ratio between catalyst and inert material in the bed) allows for a methane combustion at must lower temperatures in the reactor with flow reversal than in a classic catalytic reactor. Under such a low temperature combustion, no nitrogen oxides are produced.     

Distributional uncertainty analysis and robust optimization in spatially heterogeneous multiscale process systems

Multiscale models have been developed to simulate the behavior of spatially‐heterogeneous porous catalytic flow reactors, i.e., multiscale reactors whose concentrations are spatially‐dependent. While such a model provides an adequate representation of the catalytic reactor, model‐plant mismatch can significantly affect the reactor's performance in control and optimization applications. In this work, power series expansion (PSE) is applied to efficiently propagate parametric uncertainty throughout the spatial domain of a heterogeneous multiscale catalytic reactor model. The PSE‐based uncertainty analysis is used to evaluate and compare the effects of uncertainty in kinetic parameters on the chemical species concentrations throughout the length of the reactor. These analyses reveal that uncertainty in the kinetic parameters and in the catalyst pore radius have a substantial effect on the reactor performance. The application of the uncertainty quantification methodology is illustrated through a robust optimization formulation that aims to maximize productivity in the presence of uncertainty in the parameters. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2374–2390, 2016     

Identification and control of a riser‐type FCC unit

This paper addresses the use of feedforward neural networks for the steady‐state and dynamic identification and control of a riser type fluid catalytic cracking unit (FCCU). The results are compared with a conventional PI controller and a model predictive control (MPC) using a state space subspace identification algorithm. A back propagation algorithm with momentum term and adaptive learning rate is used for training the identification networks. The back propagation algorithm is also used for the neuro‐control of the process. It is shown that for a noise‐free system the adaptive neuro‐controller and the MPC are capable of maintaining the riser temperature, the pressure difference between the reactor vessel and the regenerator, and the catalyst bed level in the reactor vessel, in the presence of set‐point and disturbance changes. The MPC performs better than the neuro controller that in turn is superior to the conventional multi‐loop diagonal PI controller.     

Dynamic Matrix Control of a Bubble‐Column Reactor for Microbial Synthesis Gas Fermentation

A spatiotemporal metabolic model of a representative syngas bubble‐column reactor was applied to design and evaluate dynamic matrix control (DMC) schemes for regulation of the desired by‐product ethanol and the undesired by‐product acetate. This model was used to develop linear step response models for controller design and also served as the process in closed‐loop simulations. A 2 × 2 DMC scheme with manipulation of the liquid and gas feed flows to the column provided a superior performance to proportional integral (PI) control due to slow process dynamics combining the multivariable and constrained nature of the control problem. Ethanol concentration control for large disturbances was further improved by adding the flow of a pure hydrogen stream as a third manipulated variable. The advantages of DMC for syngas bubble‐column reactor control are demonstrated and a design strategy for future industrial applications is provided.     

Integrating data‐based modeling and nonlinear control tools for batch process control

A data‐based multimodel approach is developed in this work for modeling batch systems in which multiple local linear models are identified using latent variable regression and combined using an appropriate weighting function that arises from fuzzy c‐means clustering. The resulting model is used to generate empirical reverse‐time reachability regions (RTRRs) (defined as the set of states from where the data‐based model can be driven inside a desired end‐point neighborhood of the system), which are subsequently incorporated in a predictive control design. Simulation results of a fed‐batch reactor system under proportional‐integral (PI) control and the proposed RTRR‐based design demonstrate the superior performance of the RTRR‐based design in both a fault‐free and faulty environment. The data‐based modeling methodology is then applied on a nylon‐6,6 batch polymerization process to design a trajectory tracking predictive controller. Closed‐loop simulation results illustrate the superior tracking performance of the proposed predictive controller over PI control. © 2011 American Institute of Chemical Engineers AIChE J, 2012     

Study of unsteady-state catalytic oxidation of sulfur dioxide by periodic flow reversal

A systematic study of catalytic oxidation of sulfur dioxide in a fixed bed reactor operated in flow reversal mode was made. A heterogeneous transient model of the reactor was developed. The global rate equations and the heat transfer parameter correlation were obtained, based on a series of previous experiments. The experiments of unsteady-state oxidation of low concentration SO₂ were conducted in a bench-scale fixed bed reactor, packed with a domestic commercial catalyst. The model can successfully predict the transient concentration and temperature profiles when a correction factor is introduced to the global rate equations.     

Heterogeneous Catalytic Reactor Design with Non‐Uniform Catalyst Considering Shell‐Progressive Poisoning Behavior

A novel methodology has been developed to design an optimum heterogeneous catalytic reactor, by considering non‐uniform catalyst pellet under shell‐progressive catalyst deactivation. Various types of non‐uniform catalyst pellets are modelled in combination with reactor design. For example, typical non‐uniform catalyst pellets such as egg‐yolk, egg‐shell and middle‐peak distribution are developed as well as step‐type distribution. A progressive poisoning behavior is included to the model to produce correct effectiveness factor from non‐uniform catalyst pellet. As opposed to numerical experiment with limited type of kinetic application to the model in the past, this paper shows a new methodology to include any types of kinetic reactions for the modeling of the reactor with non‐uniform catalyst pellet and shell‐progressive poisoning. For an optimum reactor design, reactor and catalyst variables are considered at the same time. For example, active layer thickness and location inside pellet are optimised together with reactor temperature for the maximisation of the reactor performance. Furthermore, the temperature control strategy over the reactor operation period is added to the optimization, which extends the model to three dimensions. A computational burden has been a major concern for the optimization, and innovative methodology is adopted. Application of profile based synthesis with the combination of SA (Simulated Annealing) and SQP (Successive Quadratic Programming) allows more efficient computation not only at steady state but also in dynamic status over the catalyst lifetime. A Benzene hydrogenation reaction in an industry scale fixed‐bed reactor is used as a case study for illustration.     

Catalytic membrane reactor for Suzuki‐Miyaura C−C cross‐coupling: Explanation for its high efficiency via modeling

A polymeric catalytic membrane was previously prepared that showed remarkable efficiency for Suzuki‐Miyaura C‐C cross‐coupling in a flow‐through configuration. A mathematic model was developed and fitted to the experimental data to understand the significant apparent reaction rate increase exhibited by the catalytic membrane reactor compared to the catalytic system under batch reaction conditions. It appears that the high palladium nanoparticles concentration inside the membrane is mainly responsible for the high apparent reaction rate achieved. In addition, the best performance of the catalytic membrane could be achieved only in the forced flow‐through configuration, that, conditions permitting to the reactants be brought to the catalytic membrane by convection. © 2016 American Institute of Chemical Engineers AIChE J, 63: 698–704, 2017     

A computational study of the effects of multiphase dynamics in catalytic upgrading of biomass pyrolysis vapor

A recurring challenge among the variety of existing biomass‐to‐biofuel conversion technologies is the need to ensure optimal and homogeneous contact between the various phases involved. The formulation of robust design rules from an empirical standpoint alone remains difficult due to the wide range of granular flow regimes coexisting within a given reactor. In this work, a volume‐filtered Eulerian‐Lagrangian framework is employed that solves chemically reacting flows in the presence of catalytic particles. The simulation strategy is used to quantify the role of the particle clustering on catalytic upgrading of biomass pyrolysis vapor in risers. It is shown that particle clustering can reduce the catalytic conversion rate of biomass pyrolysis vapors by up to about 50%. The simulation results are also compared with an engineering model based on continuously stirred tank reactor (CSTR). A one‐dimensional Reynolds‐averaged transport equation is derived, and the unclosed terms that account for the heterogeneity caused by clusters are evaluated. © 2018 American Institute of Chemical Engineers AIChE J, 64: 3341–3353, 2018     

A porous carbon membrane reactor for the homogeneous catalytic hydration of propene

A porous carbon membrane contactor was studied to determine whether such a reactor could be used for homogeneous catalytic reactions. The hydration of propene, catalysed by an aqueous solution of phosphoric acid, was selected as a suitable model reaction. Experiments at high pressure and temperature were conducted in a laboratory-scale gas phase continuous reactor equipped with a flat carbon membrane contactor. It was shown that reasonably stable operation of the reactor could be achieved at high operating pressures by tailoring the porous structure of the carbon membrane and coupling the reactor with an on-line feedback pressure controller. The reactor operated in a mass transfer limited regime due to mass transfer resistance in the liquid filled membrane pores. Periodic oscillation of transmembrane pressure was shown to reduce mass transfer resistance and considerably improve the overall reactor performance.A dynamic model of the reactor was developed and the results of simulations compared favourably with experiments and the performance of a commercially operated conventional reactor employing a supported liquid phase (SLP) catalyst.     

Comparison of two-phase upflow and downflow fixed bed reactors performance: Catalytic SO2 oxidation

A time- and space-dependent model based on the piston-dispersion-exchange model for liquid flow was developed to analyze the performance of two-phase upflow and downflow fixed bed reactors and was applied to the catalytic SO₂ oxidation. The hydrodynamic parameters were determined from residence time distribution measurements, using an imperfect pulse method for time-domain analysis of nonideal pulse tracer response. A transient diffusion model of the tracer in the porous particle coupled with the PDE model was used to interpret the obtained RTD curves. Gas-liquid mass transfer parameters were determined by a stationary method based on the least square fit of the calculated concentration profiles in gas phase to the experimental values. It is shown that two-phase downflow fixed bed reactor performs better at low liquid flow rates, while two-phase downflow fixed bed reactor performs better at low liquid flow rates, while two-phase upflow performs better at high liquid flow rates.     

Reactor Modeling of Gas‐Phase Polymerization of Ethylene

A model is developed for evaluating the performance of industrial‐scale gas‐phase polyethylene production reactors. This model is able to predict the properties of the produced polymer for both linear low‐density and high‐density polyethylene grades. A pseudo‐homogeneous state was assumed in the fluidized bed reactor based on negligible heat and mass transfer resistances between the bubble and emulsion phases. The nonideal flow pattern in the fluidized bed reactor was described by the tanks‐in‐series model based on the information obtained in the literature. The kinetic model used in this work allows to predict the properties of the produced polymer. The presented model was compared with the actual data in terms of melt index and density and it was shown that there is a good agreement between the actual and calculated properties of the polymer. New correlations were developed to predict the melt index and density of polyethylene based on the operating conditions of the reactor and composition of the reactants in feed.     

Synthesis gas production from natural gas in a fixed bed reactor with reversed flow

The feasibility of producing synthesis gas by partial oxidation of natural gas on a Ni-catalyst in a fixed bed reactor with reversed flow was investigated by means of simulation. A one dimensional reactor model of the non-steady state heterogeneous type, accounting for internal diffusional limitations, was applied. A double temperature peak is observed just after flow reversal, influencing the selectivities at the exit through enhanced steam reforming reactions. The second peak gradually decreases in importance with time during the semi-cycle. The influence of several operating conditions on the reactor performance was studied. Most of the coke deposited in a semi-cycle can be removed after flow reversal. This observation opens new perspectives for the reversed flow operation.     

Mathematical modeling of a moving bed reactor for post‐combustion CO2 capture

A mathematical model for a moving bed reactor with embedded heat exchanger has been developed for application to solid sorbent‐based capture of carbon dioxide from flue gas emitted by coal‐fired power plants. The reactor model is one‐dimensional, non‐isothermal, and pressure‐driven. The two‐phase (gas and solids) model includes rigorous kinetics and heat and mass transfer between the two phases. Flow characteristics of the gas and solids in the moving bed are obtained by analogy with correlations for fixed and fluidized bed systems. From the steady‐state perspective, this work presents the impact of key design variables that can be used for optimization. From the dynamic perspective, the article shows transient profiles of key outputs that should be taken into account while designing an effective control system. In addition, the article also presents performance of a model predictive controller for the moving bed regenerator under process constraints. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3899–3914, 2016     

Robust control of a reverse-flow reactor

This paper is focused on the design of a robust controller for a catalytic fixed-bed reactor with periodical inversion of the flow direction (reverse-flow reactor, RFR). The analogy between the RFR operated at infinite switching frequency and the countercurrent reactor is the basis of the simplified mathematical model of the reactor.The control system uses dilution and internal electric heating to ensure complete conversion of the reactants and to prevent overheating of the catalyst. As the state of the system is not fully available, apart from some temperature measurements, an observer is designed and used in the control algorithm. This is a typical case of nonlinear system with uncertainties. Following the procedure described in detail by Fissore [2008. Robust control in presence of parametric uncertainties: observer-based feedback controller design. Chemical Engineering Science, in press, doi:10.1016/j.ces.2007.12.019.], the extended model for the process is setup, thus taking into account all the simplifications of the model and linking performance and robustness to the control law, which is a simple state feedback. Simulations with randomly varying feeding concentration have been carried out in order to demonstrate the effectiveness of the proposed control system.