Plug Flow Tubular Reactor Research Articles

Modeling an Industrial Hydrochlorination of Glycerol – A Systematic Study of Basic Reactor Types

AbstractModeling and optimization of real chemical reactors is challenging. A program to systematically compare the performance of an existing reactor with basic reactor models was built. The program was tested on the hydrochlorination of bio‐based glycerol in a bubble column. The model‐based approach provided insights into the reactor's concentration profiles, mass transfer, and mixing. In this case study, a plug‐flow tubular reactor (PFTR) is sufficient as a model for process intensification. Based on the results, a novel reactor design that significantly improves yields was proposed and simulated.

Chromatography assisted in-vitro refolding and purification of recombinant peptibody: Recombinant Romiplostim a case study

In-vitro protein refolding is one of the key rate-limiting unit operations in manufacturing of fusion proteins such as peptibodies expressed using E. coli. Dilution-assisted refolding is the most commonly used industrial practice to achieve the soluble, native functional form of the recombinant protein from the inclusion bodies. This study is focused on developing a chromatography-assisted in-vitro refolding platform to produce the biologically active, native form of recombinant peptibody. Recombinant Romiplostim was selected as a model protein for the study. A plug flow tubular reactor was connected in series with capture step affinity chromatography to achieve simultaneous in-vitro refolding and capture step purification of recombinant Romiplostim. Effect of various critical process parameters like fold dilution, temperature, residence time, and Cysteine: DTT ratio was studied using a central composite based design of experiment strategy to achieve a maximum refolding yield of selected peptibody. Under optimum refolding conditions, the maximum refolding yield of 57.0 ± 1.5 % and a purity of over 79.73 ± 3.4 % were achieved at 25-fold dilution, 15 °C temperature, 6 h residence time with 6 mM and 10 mM of cysteine and DTT, respectively. The formation of native peptibody structure was examined using various orthogonal analytical tools to study the protein's primary, secondary, and tertiary structure. The amino acid sequence for the disulfide-linked peptide was mapped using collision-induced dissociation (CID) to confirm the formation of interchain disulfide bonds between Cys7-Cys7 and Cys10-Cys10 similarly for intra-chain disulfide bonds between Cys42-Cys102, and Cys148-Cys206. The developed protocol here is a valuable tool to identify high-yield scalable refolding conditions for multi-domain proteins involving inter-domain disulfide bonds.

Funnel control for a class of nonlinear infinite-dimensional systems

An adaptive funnel control method is considered for the regulation of the output for a class of nonlinear infinite-dimensional systems on real Hilbert spaces. After a decomposition of the state space and some change of variables related to the Byrnes–Isidori form, it is shown that the funnel controller presented in Berger et al. (2020) achieves the control objective under some assumptions on the nonlinear system dynamics, like well-posedness and Bounded-Input-State Bounded-Output (BISBO) stability. The theory is applied to the regulation of the temperature in a chemical plug-flow tubular reactor whose reaction kinetics are modeled by the Arrhenius nonlinearity. Furthermore a damped sine–Gordon model is shown to fit the required assumptions as well. The theoretical results are illustrated by means of numerical simulations.

Simulation and design of a heat-integrated double-effect reactive distillation process for propylene glycol methyl ether production

A double-effect reactive distillation (DERD) process was proposed for the production of propylene glycol methyl ether from propylene oxide and methanol to overcome the shortcoming of low selectivity and high-energy consumption in the tubular plug-flow reactor. A single-column reactive distillation (RD) process was conducted under optimized operating conditions based on sensitivity analysis as a reference. The results demonstrated that the proposed DERD process is able to achieve more than 95% selectivity of the desired product. After that, a design approach of the DERD process with an objective of the minimum operating cost was proposed to achieve further energy savings in the RD process. The proposed DERD configuration can provide a large energy-savings by totally utilization of the overhead vapor steam in the high-pressure RD column. A comparison of the single-column RD process revealed that the proposed DERD process can reduce the operating cost and the total annual cost of 25.3% and 30.7%, respectively, even though the total capital cost of DERD process is larger than that of the RD process.

Positive observers for semilinear positive systems

Abstract The problem of designing a positive Luenberger observer for a class of infinite-dimensional semilinear positive systems is addressed. The proposed observer is positive. That is, it ensures that the state estimates are non-negative at any time. The positive observer is designed based on positive bounded perturbation results. In particular it is shown that, under suitable conditions the state estimation error converges exponentially to zero. The results are illustrated by numerical simulations based on an exothermic Plug-Flow Tubular reactor model and show the effectiveness of the proposed positive observer.

Identifying Key Descriptors for the Single-Atom Catalyzed CO Oxidation

Identifying Key Descriptors for the Single-Atom Catalyzed CO Oxidation

A Forward Feedback Control Scheme for a Solar Thermochemical Moving Bed Counter-Current Flow Reactor

Abstract Pelletized thermochemical energy storage media has a potential for long-duration energy storage. Production of solid-state energy storage media can be done within a cavity chemical reactor that captures concentrated solar radiation from a solar thermal field. The temperature stability of a solar reactor is directly influenced by the solar flux intercepted. This paper presents a low-order physical model to simulate the dynamic response of temperature inside a tubular plug-flow reactor prototype. Solid granular particles are fed to the reactor from the top whereas a counter-current flowing gas enters the reactor from the bottom. An in-house code was developed to model transient heat transfer of the reactor wall, gas, and moving particles. The model was preliminarily validated with packed beds for different temperature ranges and two gas flowrates. Dynamic response of the reactor temperature is simulated for different input power and gas/particle flowrates. The results show that the system response can be controlled efficiently by utilizing input power (solar flux) as a control parameter. A conventional proportional integral (PI) controller is designed to control the temperature inside the reactor and to maintain it during the solar flux intermittency. The controller parameters are tuned using the Ziegler–Nichols method to ensure optimal system response. The results show that the feedback control model is successful in tracking different reference reactor temperatures within a reasonable settling time of 30 min and eliminated overshoot. This study can be extended to include a hybrid reactor with a multi-input, multi-output variable system.

A Simplified Numerical Approach to Characterize the Thermal Response of a Moving Bed Solar Reactor

Abstract Concentrated solar thermochemical storage in the form of a zero-emission fuel is a promising option to produce long-duration energy storage. Solar fuel is produced using a cavity reactor that captures concentrated solar radiation from a solar field of heliostats. In this paper, heat transfer model of a tubular plug-flow reactor designed and manufactured for a solar fuel production is presented. Experimental data collected from a fixed bed tubular reactor testing are used for model comparison. The system consists of an externally heated tube with counter-current flowing gas and moving solid particles as the heated media. The proposed model simulates the dynamic behavior of temperature profiles of the tube wall, gas, and particles under various gas flowrates and residence times. The heat transfer between gas–wall, solid particle–wall, and gas–solid particle is numerically studied. The model results are compared with the results of experiments done using a 4 kW furnace with a 150 mm heating zone surrounding a horizontal alumina tube (reactor) with 50.8 mm outer diameter and thickness of 3.175 mm. Solid fixed particles of magnesium manganese oxide (MgMn2O4) with the size of 1 mm are packed within the length of 250 mm at the center of the tube length. Simulation results are assessed with respect to fixed bed experimental data for four different gas flowrates, namely, 5, 10, 15, and 20 standard liters per minute of air, and furnace temperatures in the range of 200–1200 °C. The simulation results showed good agreement with maximum steady state error that is less than 6% of those obtained from the experiments for all runs. The proposed model can be implemented as a low-order physical model for the control of temperature inside plug-flow reactors for thermochemical energy storage applications.

In-depth characterization through dimensional analysis of the performance of a membrane-integrated fuel processor for high purity hydrogen generation

Efficient production of high purity hydrogen from reforming of natural or synthetic hydrocarbons is an enabling technology for the competitiveness of hydrogen-based systems. Specifically, fuel processors based on membrane-integrated reformers are one of the most promising technologies being potentially more efficient than state-of-the-art fuel processors. The effects of the operating parameters on the performance of the complete membrane-integrated fuel processor are relevant and have not been properly investigated, especially in terms of mutual interactions. Therefore, we analyze the effects of the pressure and temperature of the steam reforming reactor as well as of the steam to fuel and air to fuel ratios, on the system efficiency. To this aim, we use a steady state model developed in Aspen Plus® that implements a hybrid lumped-distributed parameter approach. To generalize our results to diverse system sizes and fuel compositions we conduct a dimensional analysis to express all the parameters in non-dimensional form.The results show that the fuel processor efficiency based on lower heating value varies between 75% and 84% as a function of the operating parameters. Notably, it always exceeds 75% that is the reference value for a state-of-the-art fuel processor based on pressure swing adsorption purification. We also note that the retentate composition has a relevant impact on the fuel processor operation. Specifically, when the retentate is rich in fuel content the fuel processor can turn in exothermic regime or can suffer oxygen starvation in the catalytic oxidation reaction. However, when the fuel processor operates in regular conditions the only relevant mutual interaction is between the steam to fuel and air to fuel ratios. Also, the fuel processor efficiency is mostly sensitive to the operating temperature and to the steam to fuel ratio. The 770 °C optimal temperature implies that only dense ceramic membranes can be used to build a fuel processor that operates at the maximum possible efficiency. Finally, leveraging on such results we evaluate the preliminary design of an innovative tubular plug flow reactor with layer catalysts.

Optimal equilibrium stabilization for a nonlinear infinite-dimensional plug-flow reactor model

This paper studies the stabilization of optimal equilibrium profiles in nonisothermal plug-flow tubular reactors actuated by a heat exchanger that acts as a distributed control input. As a first result, we show that the heat exchanger temperature that achieves the minimal value of the steady-state reactant concentration at the outlet is the maximal allowed one. Then, a control strategy is proposed to reach these optimal equilibrium profiles. As main results, we prove that the control law stabilizes exponentially the nonlinear dynamics around the optimal equilibrium while it converges to the optimal heat exchanger temperature. In addition we show that the control law is optimal for some cost criterion of infinite-horizon integral type. Finally, the main results are illustrated with some numerical simulations.

Laboratory-Scale Research of Non-Catalyzed Supercritical Alcohol Process for Continuous Biodiesel Production

This work investigates the non-catalyzed supercritical methanol (SCM) process for continuous biodiesel production. The lab-scale setup was designed and used for biodiesel production in the temperature range of 520–650 K and 83–380 bar with an oil-to-methanol molar ratio ranging from 1:5 to 1:45. The experiments were performed in the coiled plug flow tubular reactor. The volumetric flow rate of the methanol/oil ranged from 0.1–10 mL/min. This work examines a new reactor technology involving preheating and pre-mixing of the methanol/oil mixture to reduce setup cost and increase biodiesel yield under the same reaction conditions. Work performed showed that FAME’s yield increased rapidly with temperature and pressure above the methanol critical points (i.e., 513 K and 79.5 bar). The best methyl-ester yield using this reaction technology was 91% at 590 K temperature and 351 bars with an oil-to-methanol ratio of 39 and a 15-min residence time. Furthermore, the kinetics of the free catalyst transesterification process was studied in supercritical methanol under different reaction conditions.

Adaptive λ-tracking controller for an exothermic chemical plug flow tubular reactor

ABSTRACT This paper deals with the tracking of a prespecified profile temperature for exothermic chemical tubular reactor whose dynamics is described by a set of nonlinear partial differential equations where the state variables are the reactor temperature and the reactant concentration. The coolant temperature, the inlet temperature and the inlet concentration are considered as control actions. For practical reasons, it is preferable to consider a non distributed control law to achieve the control objective. In contrast to our previous work that considers fully distributed control actions where the three control inputs are assumed to be distributed along the reactor, here the last two control inputs are applied at the reactor inlet and only the coolant temperature is distributed along the reactor. We show that the temperature of the reactor tends asymptotically to a ball of arbitrary prescribed radius , centred at the given temperature profile.

Minimum Entropy Generation Rate and Maximum Yield Optimization of Sulfuric Acid Decomposition Process Using NSGA-II.

Based on the theory of finite-time thermodynamics (FTT), the effects of three design parameters, that is, inlet temperature, inlet pressure, and inlet total mole flow rate, of a tubular plug-flow sulfuric acid decomposition reactor on the total entropy generation rate (EGR) and SO2 yield are analyzed firstly. One can find that when the three design parameters are taken as optimization variables, the minimum total EGR and the maximum SO2 yield of the reference reactor restrict each other, i.e., the two different performance objectives cannot achieve the corresponding extremum values at the same time. Then, the second-generation non-dominated solution sequencing genetic algorithm (NSGA-II) is further used to pursue the minimum total EGR and the maximum SO2 yield of the reference reactor by taking the three parameters as optimization design variables. After the multi-objective optimization, the reference reactor can be Pareto improved, and the total EGR can be reduced by 9% and the SO2 yield can be increased by 14% compared to those of the reference reactor. The obtained results could provide certain theoretical guidance for the optimal design of actual sulfuric acid decomposition reactors.

A Modelling Approach of the Catalytic Oxidation of Volatile Organic Compounds in the SCR-DeNOx Monolithic Reactor

Monolithic reactors play an important role in the integrated approach to environmental protection, especially in air pollution abatement. Mathematical modelling of catalytic reactors has become a key procedure in the design, development and optimisation of many industrial processes. The objective of this study was the modelling and simulation of the catalytic oxidation of volatile organic compounds by a commercial V2O5-WO3/TiO2 honeycomb catalyst, specific for the SCR-DeNOx process in high-dust flue gases from stationary incineration. The mathematical model is developed for the numerical simulation of a tubular plug flow reactor, using mass balance equation to predict results for benzene conversion under isothermal conditions.

Deactivation Kinetics of the Catalytic Alkylation Reaction

A kinetics theory of catalyst deactivation is presented of the solid acid-catalyzed alkylation reaction of isobutane with propylene or butene that gives alkylate, a high octane fuel, as product. The intimate relation between the kinetics network of the reaction, catalyst deactivation kinetics, and residence time distribution is analyzed. The question is addressed why the deactivation of the alkylation reaction in a continuously stirred tank reactor (CSTR) is slow compared to that in a tubular plug flow reactor (PFR). Conditions are derived where such differences will be minimum and maximum. In the reaction regime of high alkylate selectivity, linear and quadratic power law kinetics equations in propylene concentration can be deduced from microkinetics. They are used to derive analytical expressions of deactivation times for CSTR and PFR. The theoretical power law kinetics equations can be related to previously established empirical rate equations of catalyst deactivation. We show that, in the CSTR, the self-alkylation reaction path contributes substantially to the deactivation time. In the self-alkylation reaction, alkylate is formed by reaction of the isobutene reaction intermediate and isobutane. Catalysts of high proton strength can benefit catalyst deactivation times by suppressing the carbenium ion deprotonation reaction that produces alkenes as isobutene. In the PFR, selective alkylate formation occurs only when the reaction occurs in a reaction zone of the catalyst bed. Deactivation is faster than in CSTR because of the reactant profile in the reaction zone. This reaction zone has restricted mobility due to the fast deactivation of reactive protons located behind the reaction zone by alkenes formed by nonselective reactions in the reaction zone. In PFR, as long as the reaction is limited to an immobile reaction zone, deactivation time is independent of reaction site density and contact time. Contact time dependence arises when the reaction zone is mobile. Overall deactivation time then depends strongly on the degree of deactivation of the protons behind the reaction zone.

Mathematical Modeling of the Catalytic Pyrolysis of High-Density Polyethylene in a Plug-Flow Tubular Reactor

A detailed mathematical model for the catalytic pyrolysis of high-density polyethylene is presented. The model is based on the known kinetic mechanism of the catalytic cracking of hydrocarbons, whi...

Effects of different vehiculization strategies for the allium derivative propyl propane thiosulfonate during dynamic simulation of the pig gastrointestinal tract

This paper evaluates the bioavailability of allium derivative propyl propane thiosulfonate (PTSO) in the pig gastrointestinal tract by means of an in vitro dynamic gastrointestinal tract simulator system (GITSS). The GITSS is based on a membrane bioreactor comprising a continuous stirred-tank reactor connected in series to a continuous plug-flow tubular reactor. Bioavailability values have been evaluated for different vehiculization strategies, including mere carriers such as polyethylene glycol sorbitan monooleate (a nonionic surfactant also known as Tween 80) and encapsulation matrices (β-cyclodextrin vs. mono- and di-glycerides of edible fatty acids mixed with hydrogenated sunflower oil) and compared with the absorption of free PTSO. The net absorbed amount of PTSO in the GITSS when Tween 80 was used as a carrier was over 3.5 times higher than the one for free PTSO. Neither the encapsulated PTSO in β-cyclodextrin nor by means of mono- and di-glycerides of fatty acids plus a vegetable oil succeeded to improve absorption values for free PTSO. These promising results indicate that Tween 80 provides an interesting and high resistance to the PTSO molecule against the simulated digestive conditions in the stomach, and thus it enables favorably the subsequent absorption process of PTSO along the intestine.

Adaptive neuro-fuzzy inference system (ANFIS) – based model predictive control (MPC) for carbon dioxide reforming of methane (CDRM) in a plug flow tubular reactor for hydrogen production

The current sources of our energy supply are plagued with many problems and the impact on the climate is of grave concern. Hydrogen (H2), when extracted from one of its many sources with carbon dioxide (CO2) capture, is considered a non-polluting, efficient and environmentally sustainable energy source. In this study, the control of a pilot-scale reformer for the production of H2 was studied. H2 was produced through the CO2 reforming of methane (CH4). An ANFIS approach was used to model the process. Type-2 fuzzy sets and systems was implemented as the fuzzy inference engine, which renders a piece-wise linearization of the nonlinear model. The generalized bell-shape membership functions were used and optimized based on empirical training data. This model was further used within an MPC framework to devise optimal control strategies. An unconstrained optimization method on the piece-wise quasi-linear model was carried out by adopting appropriate weights on the control inputs in the objective function. These weights were tuned to avoid actuator saturation via simulation. Experimental results showed that the ANFIS model was able to accurately replicate the response of the process to changes in temperature. Based on the ANFIS model, an MPC strategy was formulated for the process.

Acceleration of CO2 mineralisation of alkaline brines with nickel nanoparticles catalysts in continuous tubular reactor

CO2 mineralisation is an effective process to sequester this greenhouse gas into solid carbonates permanently. A source of alkaline earth metals for CO2 mineralisation that has significant sequestration capacity based on worldwide availability, but seldom studied, are desalination brines. In this work, we investigate the brine carbonation process with a continuous plug-flow tubular reactor. This reaction system is particularly suitable for industrial applications as it can be easily scaled-up, and enables better process control, optimization and integration. Catalytically active nickel nanoparticles (NiNPs) are applied to improve the mineralisation process, by accelerating the rate-limiting step of carbonic acid formation. To counter CO2 acidification effect, the brine was contacted with blast furnace (BF) slags to transfer alkalinity, with sodium hydroxide being used as an additional alkali to achieve the required pH. The effects of reaction temperature, composition of alkaline brine solution and residence time in the tubular reactor, on the calcium conversion efficiency (CCE) and the mineral composition of the precipitates were investigated. The extent of brine carbonation, and hence carbonate precipitation in the outlet solution was measured by ICP-OES, and by imaging of the void fraction in the outlet stream. The mineralogy and morphology of precipitates were analysed by XRD, FTIR and SEM. It was found that CCE is increased by about 10% at 50 °C with 30-ppm NiNPs addition, which also favoured the formation of calcite polymorph. Under other process conditions, such as in the presence of other salts (Mg2+, Na+), aragonite and vaterite polymorphs were also obtained.

An efficient polynomial chaos expansion strategy for active fault identification of chemical processes

This paper is concerned with a highly efficient active fault detection and isolation (FDI) framework. An auxiliary, fault-revealing input is derived by solving an optimization problem. As we implement a model-based approach, the active FDI framework is robustified against model parameter uncertainties, including parameter correlations which are common for experimentally derived parameters. Moreover, critical safety limits are considered, and an optimal process performance is fulfilled in parallel. In this work, which is an extension to our ESCAPE-2017 contribution, a novel highly effective polynomial chaos expansion (PCE) approach is used to address parameter uncertainties and to include process design parameters directly. To reduce the computational load, we combined the PCE with a least angle regression (LAR) strategy. The overall effectiveness of the novel one-shot sparse polynomial chaos expansion (OS2-PCE) concept is demonstrated by analyzing a tubular plug flow reactor illustrating the need for uncertainty and parameter correlation analysis in FDI while ensuring an optimal and safe process operation, respectively.