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In the present contribution, the historical development of dimensionless numbers describing axial mixing effects in chemical reactors is analyzed. While the Bodenstein number has become established in Europe, the American literature often uses the Péclet number for this purpose. A journey through the historical reaction engineering literature shows that the development was complex and that Langmuir's decisive role in particular has hardly been acknowledged to date. Unfortunately, despite decades of using dimensionless numbers for mass and heat transport in chemical reactors, no consensus has yet been reached on a uniformly accepted nomenclature. To remedy this shortcoming, a proposal for consistently defined numbers at the molecular and the reactor level is made. [ABSTRACT FROM AUTHOR]

The use of ternary molten carbonate mixtures Li2CO3—K2CO3—Na2CO3 as heat transfer systems for the CSP technology as well as for heat storage for the chemical industry is widely under consideration. Experiments were carried out on austenitic steels DMV310N compared to nickel alloys in order to evaluate the corrosion properties in a molten 33 wt.% Li2CO3—33 wt.% K2CO3—34 wt.% Na2CO3 mixture at 700 and 750 °C for 1000 h in closed crucibles. The austenitic steel DMV 310N passivates by the formation of an outer LiFeO2 scale due to its iron content. If the iron content is low (< 5 wt.%), as in Alloy 625 the alloy forms NiO, which obviously does not passivate the material and leads to a strong internal corrosive attack. It has been shown by short-term experiments (3, 30, 300 and 1000 h) that a quick formation of LiFeO2 is necessary to avoid chromium dissolution and NiO formation. If LiFeO2 is formed quickly, the growth of the internal corrosion front by chromium dissolution is retarded. [ABSTRACT FROM AUTHOR]

Searching an optimal value of the neural emulator adaptive rate presents a great problem. Indeed, a new scheme of neural emulators based on the Particle Swarm Optimization (PSO) algorithm for nonlinear systems is adopted in this paper. The main goal of this approach consists in adjusting effectively the neural emulator adaptive rate in order to accelerate the convergence speed and to improve the precision degree. The obtained results are compared with those reached with an intelligent tuning strategy. An experimental validation of the new emulator adaptation is carried on chemical reactor. Efficiency of the proposed method is proved according to the obtained performances. [ABSTRACT FROM AUTHOR]

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It is known that physics‐informed learning become a new learning philosophy that has been applied in many scientific domains. However, this approach often struggles to achieve optimal performance in addressing the issue of multiphysics coupling. Here, for the first time, we extend this approach to modeling chemical reactor systems. We design a new decoupling–coupling training framework, which consists of decoupling pre‐training and multiphysics coupling training steps. With decoupling pre‐training, the complex physical domain is decomposed into subdomains of fluid flow, heat transfer, and mass transfer combined with reaction kinetics. Each subdomain is represented by a specialized neural network that can provide a coarse but reasonable distribution of network parameters for initializing the sub‐networks for the subsequent multiphysics coupling training. The capabilities of this approach, in comparison with the traditional CFD simulation, are demonstrated through an example of a plate reactor system with a heating cylinder. [ABSTRACT FROM AUTHOR]

The main aim of the manuscript was to investigate the impact of modifying the parameters of the gas nitriding process of samples made from AISI 1085 steel on the course and results of the process carried out in a chemical reactor allowing for thermogravimetric measurements. The tested steel was subjected in a chemical reactor to the process of gas nitriding in the temperature range of 490–580 °C, using different sample heating rates (in the range of 1–25 °C/min) and various mixtures of nitriding gases (pure NH3, or NH3 with the addition of H2 or N2). To assess the impact of the tested process parameters on its efficiency, the thickness of the nitrided layers produced, the change in sample mass, the structure of the phases produced, the phase composition and the microhardness were examined. For the research methodology used, it was found that reducing the amount of NH3 and/or using H2 or N2 admixtures adversely affects the thickness of the nitride layers produced. At the same time, the use of a lower maximum process temperature with the same gas mixture resulted in a significant difference in the thickness of the layers. It was also found that the use of pure NH3 or a gas mixture (NH3 + H2) with higher NH3 contents resulted in higher surface microhardnesses of the samples and that for these samples, the hardness increased to a greater depth. [ABSTRACT FROM AUTHOR]

Cutting-edge research introduces a chemical reactor for liquid radioactive waste treatment, utilizing a four-stage radiochemical separation. Biomass conversion yielded activated carbons with impressive adsorption capacities up to 1 × 104 Bq/g and proved effective for Cs removal. Standout coagulants, AlCl3·6H2O and FeSO4·7H2O, achieved an 80% decontamination factor for six radionuclides. Sulphonated DVB ion-exchange resins showed high efficiency, achieving 100% Cs decontamination at pH 4 ± 2. Integrated processes successfully decontaminated twelve radionuclides up to 99 ± 1% with substantial demineralization of waste, up to 95%, was achieved. Current reactor system is invaluable for routine and emergency scenarios for treating liquid radioactive waste with varying radionuclide compositions. [ABSTRACT FROM AUTHOR]

The problem of the shape optimization of tubular-type plug-flow chemical reactors equipped with a fluid flow-based cooling system is considered in this work. The hydraulic radius Rh(z) = 2A(z)/P(z) and an equivalent surface area-based radius Rs = P(z)/(2π) were computed from the cross-sectional area A(z) and perimeter P(z) measured along the nasal duct of Northern reindeer and used for shape optimization as nature-inspired design. The laminar flow in the cooling system was modeled using the Navier–Stokes equations for an incompressible liquid. In the central tube, a set of chemical reactions with temperature-dependent rates was considered. The temperature and flow velocity fields, pumping pressure, mass flow rate, and total heat flux Jth were obtained by numerical methods. Comparative analyses of the efficiency of different geometries were conducted on Pareto frontiers for hydraulic resistivity Zh, thermal resistivity Zth, thermal inlet length Lth, and entropy production Sirr as a sum of contributions from chemical reactions, thermal, and viscous dissipation. It was shown that the tube with Rs(z) as an interface between the reactor and cooler has the best Pareto efficiency using the (Zh,Zth,Lth) objective functions. Surprisingly, this design also exhibits the lowest Sirr and a more uniform distribution Sirr(z) (i.e., equipartition) among other designs. This geometry is suggested for densely packed tubular reactors. [ABSTRACT FROM AUTHOR]

Halohydrin dehalogenase HheG is an industrially interesting biocatalyst for the preparation of different β‐substituted alcohols starting from bulky internal epoxides. We previously demonstrated that the immobilization of different HheG variants in the form of cross‐linked enzyme crystals (CLECs) yielded stable and reusable enzyme immobilizes with increased resistance regarding temperature, pH, and the presence of organic solvents. Now, to further establish their preparative applicability, HheG D114C CLECs cross‐linked with bis‐maleimidoethane have been successfully produced on a larger scale using a stirred crystallization approach, and their application in different chemical reactor types (stirred tank reactor, fluidized bed reactor, and packed bed reactor) was systematically studied and compared for the ring opening of cyclohexene oxide with azide. This revealed the highest obtained space‐time yield of 23.9 kgproduct gCLEC−1 h−1 Lreactor volume−1 along with the highest achieved product enantiomeric excess [64%] for application in a packed‐bed reactor. Additionally, lyophilization of those CLECs yielded a storage‐stable HheG preparation that still retained 67% of initial activity (after lyophilization) after 6 months of storage at room temperature. [ABSTRACT FROM AUTHOR]

Constructions with vibratory mixing devices designed for processing liquids, suspensions, and gas–liquid dispersions are reviewed analytically. Various design schemes of such devices are discussed, the design features of the working bodies are described, and various design options for vibration drives and equipment operating modes are examined. More than 170 relevant patent documents published within the last 70 years are identified to determine the development trend of the technology. Analysis of the global development trends suggests that inventors are interested in works performed to improve the current types of equipment and to develop new ones. [ABSTRACT FROM AUTHOR]

The main aim of the manuscript was to investigate the impact of modifying the parameters of the gas nitriding process of samples made from AISI 1085 steel on the course and results of the process carried out in a chemical reactor allowing for thermogravimetric measurements. The tested steel was subjected in a chemical reactor to the process of gas nitriding in the temperature range of 490–580 °C, using different sample heating rates (in the range of 1–25 °C/min) and various mixtures of nitriding gases (pure NH3, or NH3 with the addition of H2 or N2). To assess the impact of the tested process parameters on its efficiency, the thickness of the nitrided layers produced, the change in sample mass, the structure of the phases produced, the phase composition and the microhardness were examined. For the research methodology used, it was found that reducing the amount of NH3 and/or using H2 or N2 admixtures adversely affects the thickness of the nitride layers produced. At the same time, the use of a lower maximum process temperature with the same gas mixture resulted in a significant difference in the thickness of the layers. It was also found that the use of pure NH3 or a gas mixture (NH3 + H2) with higher NH3 contents resulted in higher surface microhardnesses of the samples and that for these samples, the hardness increased to a greater depth.

An arbitrary choice of the neural controller adaptive rate can have a negative effect on the performance of the closed-loop system. In this study, we propose a novel methodology for neural controller adaptive rate using Particle Swarm Optimization algorithm. The developed control scheme is composed of a recurrent neural networks emulator and controller with decoupled adaptive rates. Constraints on the adaptive rate are derived from the Lyapunov stability method. Particle Swarm Optimization is proposed as a mechanism to optimize the adaptive rate of the NC to improve the closed-loop performances. The advantages of the proposed new control algorithm are as follows: (1) online optimal choice of adaptive rate, which reduces the effort for searching an adequate neural controller adaptive rate when considering the conventional methods and (2) ensuring stability, faster convergence, disturbance rejection, and good tracking. The efficiency of the proposed PSO adaptive rate is demonstrated with numerical control of SISO nonlinear system. The obtained results prove the efficiency of the proposed NC compared to those obtained with existing methods. An application of the developed approach on a semi-batch reactor is presented to validate simulations results. [ABSTRACT FROM AUTHOR]

The problem of the shape optimization of tubular-type plug-flow chemical reactors equipped with a fluid flow-based cooling system is considered in this work. The hydraulic radius Rh(z) = 2A(z)/P(z) and an equivalent surface area-based radius Rs = P(z)/(2π) were computed from the cross-sectional area A(z) and perimeter P(z) measured along the nasal duct of Northern reindeer and used for shape optimization as nature-inspired design. The laminar flow in the cooling system was modeled using the Navier–Stokes equations for an incompressible liquid. In the central tube, a set of chemical reactions with temperature-dependent rates was considered. The temperature and flow velocity fields, pumping pressure, mass flow rate, and total heat flux Jth were obtained by numerical methods. Comparative analyses of the efficiency of different geometries were conducted on Pareto frontiers for hydraulic resistivity Zh, thermal resistivity Zth, thermal inlet length Lth, and entropy production Sirr as a sum of contributions from chemical reactions, thermal, and viscous dissipation. It was shown that the tube with Rs(z) as an interface between the reactor and cooler has the best Pareto efficiency using the (Zh,Zth,Lth) objective functions. Surprisingly, this design also exhibits the lowest Sirr and a more uniform distribution Sirr(z) (i.e., equipartition) among other designs. This geometry is suggested for densely packed tubular reactors.

This work presents the experimental study conducted on a newly developed ammonium bicarbonate reactor for the purposes of carbon capturing and utilization. This reactor produces ammonium bicarbonate with the assistance of an industrial catalyst (such as steel) and an electromagnetic induction heater for enhancing the production of ammonium bicarbonate. The experimental setup is prepared to have three cases which are the baseline case, catalyst case, and induction heating case. These three cases are compared in terms of ammonium bicarbonate production by mass and the ratio of actual mass produced over their theoretical limits. The results of our present experiments show that the steel catalyst is proven to be an effective catalyst as it helps improve the production of ammonium bicarbonate by a factor of 1.56 when the inlet exhaust gases have 30% mol of carbon dioxide compared to the baseline case. In addition, the ammonium bicarbonate production improves by a factor of 2.56 when a steel catalyst and an induction heater are used together compared to the baseline case where the carbon dioxide composition entering the reactor is 80%mol. These results present the promising potential for implementing a cheap catalyst and an electromagnetic induction heater for the enhancement of carbon capture and utilization reactors. • A new reactor with an electromagnetic induction heater is proposed and compared. • Adding a steel catalyst improves carbon utilization by 80%. • The induction heater enhances ammonium bicarbonate production by a factor of 2.56. • Energy consumption and ammonium bicarbonate production are studied parametrically. [ABSTRACT FROM AUTHOR]

A novel type of neural network with an architecture based on physics is proposed. The network structure builds on a body of analytical modifications of classical numerical methods. A feature of the constructed neural networks is defining parameters of the governing equations as trainable parameters. Constructing the network is carried out in three stages. In the first step, a neural network solution to an equation corresponding to a numerical scheme is constructed. It allows for forming an initial low-fidelity neural network solution to the original problem. At the second stage, the network with physics-based architecture (PBA) is further trained to solve the differential equation by minimising the loss function, as is typical in works devoted to physics-informed neural networks (PINNs). In the third stage, the physics-informed neural network with architecture based on physics (PBA-PINN) is trained on high-fidelity sensor data, parameters are identified, or another task of interest is solved. This approach makes it possible to solve insufficiently studied PINN problems: selecting neural network architecture and successfully initialising network weights corresponding to the problem being solved that ensure rapid convergence to the loss function minimum. It is advisable to use the devised PBA-PINNs in the problems of surrogate modelling and modelling real objects with multi-fidelity data. The effectiveness of the approach proposed is demonstrated using the problem of modelling processes in a chemical reactor. Experiments show that subsequent retraining of the initial low-fidelity PBA model based on a few high-accuracy data leads to the achievement of relatively high accuracy. [ABSTRACT FROM AUTHOR]

In this paper, the Discrete Element Method of simulation was used to study the catalytic granule size effect on the efficiency of a bed reactor for the ethylbenzene dehydrogenation reaction. The model constructed for the laboratory experiment was made of catalyst granules of lengths 3, 6 and 9 mm, and diameters 2.8, 3, and 3.2 mm. A detailed evaluation of the catalyst total surface area and porosity effect was conducted owing to the analysis of particles size effect on the packing. Different results were observed for a wide feed gas mixture rate. Calculations performed allowed to deduce dependences of the reaction product concentration, the pressure drops, and the reactor productivity for all the particle sizes investigated. [ABSTRACT FROM AUTHOR]

Because of its high adsorption capacity, activated carbon is frequently employed as an effective adsorbent. Activated carbon is a main element for treatment of wastewater, groundwater and water purification. The activating agents greatly affects the porosity and surface area of the produced activated carbon. In this study, the use of agricultural leftovers for the production of activated carbon is discussed in detail. The pyrolysis stage is investigated in relation to a number of process variables. The effects of physical and chemical activation circumstances on the properties of activated carbon are discussed. Under controlled process conditions, many active carbons with Brunauer–Emmett–Teller surface areas ranging from 250 to 2,410 m2/g and pore volumes ranging from 0.022 to 91.4 cm3/g were produced. A review of reaction kinetic modelling applied to pyrolysis of agricultural wastes is also carried out. In this study, effort has been given to show the preparation of activated carbon from various agricultural residues. Also the comparisons of different activated carbon prepared from various agricultural residues have been shown. In the present review, the preparation of activated carbon by treating with different chemicals has also been incorporated. [ABSTRACT FROM AUTHOR]

Due to their high toxicity, propensity for cancer, teratogenicity, mutagenicity, and genotoxicity, hazardous water-soluble phenolic compounds must be controlled immediately. In this study, a model was created to simulate the degradation of harmful recalcitrant organic compounds in a combined chemical and biological treatment system. The parameter estimations with inhibition coefficient (Haldane model) and without inhibition coefficient (Michaelis-Menten model) were assessed over a wide range of initial concentrations using the Monod-like model. The kinetic parameters were optimized using AQUASIM 2.0 software. At a 50 mg·L−1 feed concentration of 4-chlorophenol, removal efficiencies of more than 98% were attained under these circumstances. The primary kinetic parameters were identified and their values models were validated using the fitted parameter values that reached a good degree of agreement (R2 = 0.998). We may better comprehend and make use of the complex phenolic compounds' biodegradation processes, such as progress optimization and scale-up, by understanding the mechanisms of substrate interaction and the new kinetic models that have been provided in this work. [ABSTRACT FROM AUTHOR]

The present work focuses on the design of an interval multiobserver for nonlinear systems with internal and external disturbances. The structure of the developed interval multiobserver is based on a discrete uncoupled multimodel. The used multimodel is known for its flexibility in the modeling step, since the state variables of the partial models can evolve in state spaces with different dimensions. Sufficient stability conditions are formulated in terms of linear matrix inequalities (LMIs), and nonnegativity constraints are imposed to ensure the cooperativity dynamic of the observation errors. A numerical example and an experimental validation on an esterification reactor are given to prove the significance of the proposed interval multiobserver. • This paper deal with the design of an interval multiobserver for nonlinear systems with internal and external disturbances. • The structure of the developed interval multiobserver is based on a discrete uncoupled multimodel. • Sufficient stability conditions are formulated in terms of linear matrix inequalities (LMIs), and nonnegativity constraints are imposed in order to ensure the cooperativity dynamic of the observation errors. [ABSTRACT FROM AUTHOR]

The quest for real-time dynamic optimization solutions in the process industry represents a formidable computational challenge, particularly within the realm of applications like model-predictive control, where rapid and reliable computations are critical. Conventional methods can struggle to surmount the complexities of such tasks. Quantum computing and quantum annealing emerge as avant-garde contenders to transcend conventional computational constraints. We convert a dynamic optimization problem, characterized by an optimization problem with a system of differential–algebraic equations embedded, into a Quadratic Unconstrained Binary Optimization problem, enabling quantum computational approaches. The empirical findings synthesized from classical methods, simulated annealing, quantum annealing via D-Wave's quantum annealer, and hybrid solver methodologies, illuminate the intricate landscape of computational prowess essential for tackling complex and high-dimensional dynamic optimization problems. Our findings suggest that while quantum annealing is a maturing technology that currently does not outperform state-of-the-art classical solvers, continuous improvements could eventually aid in increasing efficiency within the chemical process industry. • Maps dynamic optimization problem for a CSTR model onto a QUBO framework for quantum annealing. • Compares the performance of quantum annealers with classical optimization solvers. • Reports on the application of D-Wave's hybrid solver to manage problem embedding. • Illuminates the limitations of current quantum hardware for complex optimization tasks. • Suggests future directions for algorithm development compatible with quantum systems. [ABSTRACT FROM AUTHOR]

Computational fluid dynamics (CFD) is an essential tool for solving engineering problems that involve fluid dynamics. Especially in chemical engineering, fluid motion usually has extensive effects on system states, such as temperature and component concentration. However, due to the critical issue of long computational times for simulating CFD, application of CFD is limited for many real-time problems, such as real-time optimization and process control. In this study, we developed a surrogate model of a continuous stirred tank reactor (CSTR) with van de Vusse reaction using physics-informed neural network (PINN), which can train the governing equations of the system. We propose a PINN architecture that can train every governing equation which a chemical reactor system follows and can train a multi-reference frame system. Also, we investigated that PINN can resolve the problem of neural network that needs a large number of training data, is easily overfitted and cannot contain physical meaning. Furthermore, we modified the original PINN suggested by Raissi to solve the memory error and divergence problem with two methods: Mini-batch training and weighted loss function. We also suggest a similarity-based sampling strategy where the accuracy can be improved up to five times over random sampling. This work can provide a guideline for developing a high performance surrogate model of the chemical process. [ABSTRACT FROM AUTHOR]

Currently, one of the main important tasks at oil refineries is to increase their productivity and product quality. Hydrotreating of diesel fuel is important in the oil refining process. The main purpose of hydrotreating is to improve the quality of fuel and remove sulfur, nitrogen and oxygen compounds from it. The diesel fuel hydrotreating process has a significant impact on product quality. As an object of study, a chemical reactor has a nonlinear characteristic and has the property of a reverse chemical reaction during the hydrotreating of diesel fuel. Also, the diesel fuel hydrotreating process is considered a nonlinear and multidimensional control object, and all its parameters cannot be measured online. Therefore, a mathematical model was developed that takes into account the features of the technological process that arises when creating a highly efficient control system. The article deals with the synthesis of effective algorithms for controlling a chemical reactor and developed a synergistic controller for a class of indefinite nonlinear dynamic systems. The synthesis of control laws is performed by the method of analytical design of aggregated controllers (ADAR).

A novel type of neural network with an architecture based on physics is proposed. The network structure builds on a body of analytical modifications of classical numerical methods. A feature of the constructed neural networks is defining parameters of the governing equations as trainable parameters. Constructing the network is carried out in three stages. In the first step, a neural network solution to an equation corresponding to a numerical scheme is constructed. It allows for forming an initial low-fidelity neural network solution to the original problem. At the second stage, the network with physics-based architecture (PBA) is further trained to solve the differential equation by minimising the loss function, as is typical in works devoted to physics-informed neural networks (PINNs). In the third stage, the physics-informed neural network with architecture based on physics (PBA-PINN) is trained on high-fidelity sensor data, parameters are identified, or another task of interest is solved. This approach makes it possible to solve insufficiently studied PINN problems: selecting neural network architecture and successfully initialising network weights corresponding to the problem being solved that ensure rapid convergence to the loss function minimum. It is advisable to use the devised PBA-PINNs in the problems of surrogate modelling and modelling real objects with multi-fidelity data. The effectiveness of the approach proposed is demonstrated using the problem of modelling processes in a chemical reactor. Experiments show that subsequent retraining of the initial low-fidelity PBA model based on a few high-accuracy data leads to the achievement of relatively high accuracy.

The conditions for the hydrothermal synthesis of industrially significant zeolite with the Beta structure are optimized by reducing the amount of toxic reagents used (tetraethylammonium hydroxide), acting as structure directing agents, reducing the temperature, and shortening the synthesis time relative to the known method. The use of stirring the reaction medium during the synthesis using the Premex Avalon reactor system, the addition of Zeolite Beta seeds, and the aging of the initial gel are considered as factors allowing the optimization of the synthesis conditions. The results of X-ray phase analysis and the study of the morphology of the samples show the possibility of synthesizing zeolite Beta with the average particle diameter of 200 to 300 nm at 130°C for 20 h with a significant decrease (by 75%) in the amount of tetraethylammonium hydroxide in the initial gel relative to the known methods. [ABSTRACT FROM AUTHOR]

The development of mathematical models plays a fundamental role in the design, optimization, and control of processes. Regarding heat transfer in moving bed reactors, the chemical reaction implies the inclusion of a nonhomogeneous and nonlinear term in model equations, making the analytical integration a very difficult task. Up to date, there is not an analytic and/or a semi-analytic solution to a heat transfer model of a moving bed reactor (MBR) with isothermal walls to the distributed parameters in the solid phase. Therefore, starting from analytical solutions of the associated homogeneous (linear) problems and through the spectral expansion of the nonhomogeneous vector, this work presents strategies for determining semi-analytical solutions of nonhomogeneous and nonlinear problems. An MBR with a first-order chemical reaction in the solid phase--kaolinite dehydroxylation in the kaolinite flash calcination process--is selected as the case study; however, the strategies can easily be applied to other nonlinear models. Results for conversion, and fluid and particle temperatures, are given for different parameter values. The solutions perform stable, fast, and accurate. When compared with a hybrid finite difference and finite analytic (FD&FA) numerical method, the solution showed a very good agreement. [ABSTRACT FROM AUTHOR]

In this paper, we describe one of the solutions of a nonlinear optimal control problem for a chemical reactor. A solution on finding a chemical reactor’s optimal temperature regime for having a maximum concentration of final product is presented. The optimal control has been found by immersion method for boundary value problem with a phase and control restrictions. This method is reducing the original boundary value problem to a special optimal control problem, using the general solution of the Fredholm integral equation of the first kind. With this method's solution had been created a software for the problem calculations. Analysis of the method is presented. [ABSTRACT FROM AUTHOR]

In the process of CO2 capture by chemical absorption, regeneration energy consumption accounts for 70%-80% of the total energy consumption. Currently, the most critical issue is how to reduce the energy consumption of regeneration. Equipment such as micro-reaction calorimeter (Thermal Hazard Technology provides), differential reaction calorimeter and Setaram C80 thermal differential calorimeter is used to compare the reference and sample solutions, which are simultaneously heated to compensate for heat loss of the sample solution during the measurement, but the heat of reaction cannot be directly measured. In this study, the reaction heats of MEA (ethanolamine) and MDEA (N-methyldiethanolamine) with CO2 at 10%, 20%, 30%, 40%, and 50% mass fraction were measured by synchronous thermal tracing technique. By synchronously controlling the temperature of the shell of the container and the internal solution, the temperature gradient was reduced to form a "thermal barrier"to prevent the solution from exchanging heat with the external environment in the form of conduction, convection, or radiation. A dynamic adiabatic environment was obtained without thermal compensation. The accuracy of direct measurement of the trace gas-liquid reaction heat was improved to save the sample amount. The experimental results show that the simultaneous thermal tracking method is more accurate. With the increase of solution concentration, the reaction heat of MEA first decreases and then increases, and the reaction heat of MDEA decreases gradually. When the mass concentration of MEA and MDEA is between 20% and 40%, the mass concentration has no significant effect on the reaction heat. The curve of temperature rise formed by exothermic reaction appears to be concave.

Due to their high toxicity, propensity for cancer, teratogenicity, mutagenicity, and genotoxicity, hazardous water-soluble phenolic compounds must be controlled immediately. In this study, a model was created to simulate the degradation of harmful recalcitrant organic compounds in a combined chemical and biological treatment system. The parameter estimations with inhibition coefficient (Haldane model) and without inhibition coefficient (Michaelis-Menten model) were assessed over a wide range of initial concentrations using the Monod-like model. The kinetic parameters were optimized using AQUASIM 2.0 software. At a 50 mg·L−1 feed concentration of 4-chlorophenol, removal efficiencies of more than 98% were attained under these circumstances. The primary kinetic parameters were identified and their values models were validated using the fitted parameter values that reached a good degree of agreement (R2 = 0.998). We may better comprehend and make use of the complex phenolic compounds’ biodegradation processes, such as progress optimization and scale-up, by understanding the mechanisms of substrate interaction and the new kinetic models that have been provided in this work.

This undertaking delves into the designing of a based nonlinear discrete-time control scheme. The control input exploits the feedback linearization technique, the gain scheduling control approach, and genetic algorithms to develop an optimization method, for achieving trajectory tracking objectives. In order to demonstrate the effectiveness of the proposed scheme, the results from this investigation was compared with those attained using the fuzzy control method. The simulation results from the application of the designed approach to a continuous stirred tank reactor (CSTR) temperature control problem, revealed the efficiency of this scheme, and its satisfactory overall performance. [ABSTRACT FROM AUTHOR]

This paper tackles the control problem of nonlinear disturbed polynomial systems using the formalism of output feedback linearization and a subsequent sliding mode control design. This aims to ensure the asymptotic stability of an unstable equilibrium point. The class of systems under investigation has an equivalent Byrnes–Isidori normal form, which reveals stable zero dynamics. For the case of modeling uncertainties and/or process dynamic disturbances, conventional feedback linearizing control strategies may fail to be efficient. To design a robust control strategy, meta-heuristic techniques are synthesized with feedback linearization and sliding mode control. The resulting control design guarantees the decoupling of the system output from disturbances and achieves the desired output trajectory tracking with asymptotically stable dynamic behavior. The effectiveness and efficiency of the designed technique were assessed based on a benchmark model of a continuous stirred tank reactor (CSTR) through numerical simulation analysis. [ABSTRACT FROM AUTHOR]

The main goal of this work is the construction of a class of controller, which employs directly a Lagrangian formulation to resolve the classical brachistochrone problem, this allows to obtain an optimal controller which reaches in a minimum time the stabilization of an isothermal continuous stirred tank reactor, whose chemical kinetic model is based on the power law. The proposed methodology is compared with an input/output linearizing which achieve asymptotic and exponential closed-loop convergence, sliding-mode controller with a finite time convergence and an exact gradient optimal control to compare the time convergence performance. Numerical experiments show the satisfactory performance of the proposed controller, despite sustained disturbances in the concentration input feed. [ABSTRACT FROM AUTHOR]

We consider an optimal control problem for some mathematical problem of a chemical reactor. We prove the existence of a solution to the system in variations which arises in deriving a necessary optimality condition in the form of the Pontryagin Maximum Principle. [ABSTRACT FROM AUTHOR]

We studied the reaction of phenyl radicals (C6H5) with propylene (C3H6) exploiting a high temperature chemical reactor under combustion-like conditions (300 Torr, 1,200-1,500 K). The reaction products were probed in a supersonic beam by utilizing tunable vacuum ultraviolet (VUV) radiation from the Advanced Light Source and recording the photoionization efficiency (PIE) curves at mass-to-charge ratios of m/z = 118 (C9H10+) and m/z = 104 (C8H8+). Our results suggest that the methyl and atomic hydrogen losses are the two major reaction pathways with branching ratios of 86 10 percent and 14 10 percent. The isomer distributions were probed by fitting the recorded PIE curves with a linear combination of the PIE curves of the individual C9H10 and C8H8 isomers. Styrene (C6H5C2H3) was found to be the exclusive product contributing to m/z = 104 (C8H8+), whereas 3-phenylpropene, cis-1-phenylpropene, and 2-phenylpropene with branching ratios of 96 4 percent, 3 3 percent, and 1 1 percent could account for signal at m/z = 118 (C9H10+). Although searched for carefully, no evidence of the bicyclic indane molecule could be provided. The reaction mechanisms and branching ratios are explained in terms of electronic structure calculations nicely agreeing with a recent crossed molecular beam study on this system.

In the present work, based on numerical simulation, a comparative analysis of the flow of a chemically reacting gas flow through a catalyst is performed using the example of selective hydrogenation of acetylene in a wide range of flow temperatures variation. Catalyst models are based on open-cell foam material. A comparison is also made with calculations and experimental data for a granular catalyst. The porosity and cell diameter were chosen as variable parameters for the porous catalyst. The results of numerical studies were obtained in the form of component concentration fields of the gas mixture, vector fields of gas movement, values of conversion, and selectivity of the reaction under study. The parameters of the porous material of the catalyst are determined for the maximum efficiency of the process under study.

The paper considers the calculation of the combustion chamber of a chemical reactor in the software complex Ansys CFX, which allows to determine the thermal characteristics, as well as the concentration of CO, CO2 at the output with different air flow coefficients. The paper presents the computational model, the initial conditions, and describes the calculation algorithm and the formation of the diffusion scheme. Verification of the methodology for adequacy when comparing the numerical model in ANSYS CFX with the literature data, which showed a maximum discrepancy of 6,92 %. Calculations shows that the operating mode of the reactor will be observed for 1.

A one-dimensional model and numerical solution of the non-stationary modes of the adiabatic gas-droplet chemical plug-flow reactor are considered. The developed approach permits to investigate processes of heat and mass transfer in the laminar flow of the reacting gas mixture with hydrocarbon fuels droplets. It may be useful for hazard operability.

Oscillations, including chaotic ones, can spontaneously appear in chemical reactors or lean premixed combustors. Such behavior of the system is undesirable and should be identified at the stage of its modeling. This article analyzes the behavior of reverse-flow tubular chemical reactor with longitudinal dispersion in terms of chaotic oscillations. The purpose of using reverse flow is to increase the conversion degree. For the analysis of the reactor, among others, spectral analysis, entropy, and bifurcation analysis were used. The obtained results show the chaotic behavior of the reactor in a wide range of changes in the parameter’s values.

This paper displays an efficient numerical technique of realizing mathematical models for an adiabatic tubular chemical reactor which forms an irreversible exothermic chemical reaction. At a steady-state solution for an adiabatic rounded reactor, the model can be diminished to a conventional nonlinear differential equation which converts into a system of the nonlinear equation that can proceed numerically utilizing Newton's iterative method. An operational matrix of coordination is derived and is utilized to decrease the model for an adiabatic tubular chemical reactor to an arrangement of algebraic equations. Simple execution, basic activities, and precise arrangements are the fundamental highlights of the proposed wavelet technique. The numerical solutions attained by the present technique have been contrasted and compared with other techniques. [ABSTRACT FROM AUTHOR]

In this paper fractional differential transform method is implemented for modelling and solving system of the time fractional chemical engineering equations. In this method the solution of the chemical reaction, reactor, and concentration equations are considered as convergent series with easily computable components. Also, the obtained solutions have simplicity procedure, high accuracy and efficient. [ABSTRACT FROM AUTHOR]