Modeling of industrial multiphase reactors

The upgradation of the bottom of the barrel has gained much interest across the refineries due to severe environmental rules, limitations of conventional oil reserves, and its flexibility to produce light end products which benefit end users. Slurry phase hydrocracking is one of the growing technologies to fulfil the increasing demand for light cut. Modelling of an industrial slurry phase reactor (SPR) for vacuum residue hydrocracking using different kinetic models is proposed. The axial dispersion model (ADM) is used for modelling an industrial SPR. The mathematical model of the reactors is incorporated for the three different lump kinetic models. This study deals with the continuous stirred tank reactor (CSTR) and SPR modelling, followed by industrial SPR modelling. The small lab‐scale reactor models are validated with the experimental data reported in the literature. The study's objective was to investigate the one‐dimensional and two‐dimensional concentration dynamics of each lump along the axial and radial positions of industrial SPR. The vacuum residue conversion into the light fractions was obtained by more than 73% in industrial SPR. Also, the yield of vacuum gas oil and resins were evaluated as 49% and 63%, respectively. The sensitivity analysis was performed to explain the effect of process variables. The optimum range was found as a length of 15 m, liquid hourly space velocity (LHSV) of 0.2 h −1 , 1% catalyst concentration, and 420°C reaction temperature to enhance the throughput of the reactor.

The achievement of new economically viable chemical processes often involves the translation of observed lab-scale phenomena into performance in an industrial reactor. In this work, the in silico design and optimization of an industrial ethanol dehydration reactor were performed, employing a multiscale model ranging from nano-, over micro-, to macroscale. The intrinsic kinetics of the elementary steps was quantified through ab initio obtained rate and equilibrium coefficients. Heat and mass transfer limitations for the industrial design case were assessed via literature correlations. The industrial reactor model developed indicated that it is not beneficial to utilize feeds with high ethanol content, as they result in lower ethanol conversion and ethene yield. Furthermore, a more pronounced temperature drop over the reactor was simulated. It is preferred to use a more H2O-diluted feed for the operation of an industrial ethanol dehydration reactor.

Catalytic reforming of naphtha occupies an important issue in refineries for obtaining high octane gasoline and aromatic compounds, which are the basic materials of petrochemical industries. In this study, a novel of design parameters for industrial continuous catalytic reforming reactors of naphtha is proposed to increase the aromatics and hydrogen productions. Improving a rigorous mathematical model for industrial catalytic reactors of naphtha is studied here based on industrial data applying a new kinetic and deactivation model. The optimal design variables are obtained utilizing the optimization process in order to build the model with high accuracy and such design parameters are then applied to get the best configuration of this process by new design variables. New results related to aromatic and hydrogen production have been obtained (the highest hydrogen and aromatic) in comparison with those reported in the literature and with the conventional method.

Influence of parameter uncertainty on modeling of industrial ammonia reactor for safety and operability analysis

Simulation of an industrial adiabatic multi-bed catalytic reactor for sulfur dioxide oxidation using the Maxwell–Stefan model

A modeling approach is presented that is able to handle the most important aspects of industrial fluidized-bed reactors. A particular focus is to describe the relationship between catalyst attrition, solids recovery in the reactor system, and chemical performance of the fluidized-bed reactor. The competing influences of attrition of the catalyst particles and efficiency of the solids recovery lead to the etablishment of a catalyst particle size distribution in the bed inventory, which, in turn, influences via the hydrodynamic characteristics of the fluidized bed and, thereby, the performance of the chemical reactor. The usefulness of this approach is illustrated with model calculations for a fictituous first-order reaction in which the fluidized bed is equipped with different solids recovery systems including one single-stage cyclone, several cyclones in parallel, and two- and three-stage cyclone systems. Model calculations illustrate the importance of a high efficiency of solids recovery to keep the fines in the system which is decisive for a high performance of the reactor. The calculations reveal that it might take months until a quasi-steady state of the bed particle size distribution is obtained.

A NARX(Nonlinear Autoregressive Exogenous Input) neural network model of an industrial UASB reactor was developed in this research work. A total of 111 days' data were used for the modeling process, specifically, 100 for training and 11 for comparison of predictions. Several designs were generated for the neural network to check the behavior of the predictive model during the training phase. The final design was optimized by observing performance characteristics and regression analysis by using a customized MATLAB script. The model was capable of realizing the dynamics of the system. A 5-6-2 architecture was capable of suitably modeling the UASB reactor and predicting values of biogas production rate and outlet COD concentration. Almost all predictions lied within ±10% deviations. Such a model may be utilized to predict the output of UASB reactor satisfactorily for its supervision, monitoring and control.

This paper describes the development of a dynamic simulation model for stirred tank batch or semi‐batch chemical reactors fitted with an alternative heating‐cooling system. Heat and mass balances are established for the reactor and its jacket. Since the general purpose of our research is the thermal control of these reactors, special attention is devoted to the behaviour of the heating‐cooling system. In this article, we are particularly concerned with an alternative system, i.e. different fluids at a constant temperature can be alternatively delivered to the jacket. The computer simulation programme is flexible, enabling simulation of a batch or semi‐batch reaction vessel, ranging from a laboratory pilot plant to a full‐scale production plant. A control algorithm is included which allows reactor operation with open or closed‐loop temperature control. To demonstrate the good performance of the simulation model, experimental results are presented for both a pilot plant and an industrial reactor.

Via coupling the mass balance, energy balance, and power law kinetic equations, a tanks‐in‐series reactor model is established to describe the performance of the industrial in‐series stirred‐tank oxidation reactors for adipic acid (AA) synthesis. Industrial‐scale experiments are carried out for model verification, and the satisfactory agreement between the experimental results and calculated data indicates the validity of model for the investigation of the reactor behaviors. First, single tank research is taken, and the results illustrate that the most sensitive parameter in the single reactor is the coolant temperature. Second, the five in‐series stirred‐tank reactors are selected according to the calculated intermediates conversion over the total tank number from 1 to 5. The optimal ketone–alcohol (K/A) oil feed distribution is found to be 1.7, 1.4, 1.1, 0.6, and 0.4 t/h. The corresponding reaction temperature distribution is 343.15, 346.15, 349.15, 351.15, and 353.15 K. The average residence time distribution is found to be 7.02, 6.61, 6.37, 5.80, and 5.63 min. The total yield of AA could reach up to 97.30% under the optimal conditions.

An ever-increasing complexity of the models of catalytic cracking (which is rarely justified by available monitoring data) makes "practical" modeling for industrial units challenging. In this work, we develop a simple numerical model for an industrial catalytic riser, the model with phenomenological parameters that are determined from available monitoring data. The model is based on a four-lump reaction scheme (with coke being one of the lumps), with the kinetic parameters determined for an industrial reactor with a zeolite-containing catalyst that is used for the production of wet gases. The expression for the reaction rate reflects that reactions in the gaseous phase occur in the presence of the solid (catalyst) phase. Hydrodynamics of nonisothermal reactive gas–solid mixtures is captured by a two-fluid model. The strong turbulence nature of the reactor flow makes it possible to disregard the kinetic theory-based values for viscous, diffusion, and thermal conductivity coefficients (additionally reducing the number of needed empirical coefficients). The resultant model is applied for an in-depth analysis of the flow fields in the reactor, demonstrating good agreement of the results with more sophisticated approaches. The model is also applied for the calculation of optimal intakes of water vapor and catalyst.

A comparison of homogeneous and heterogeneous dynamic models for industrial methanol reactors in the presence of catalyst deactivation

Heterogeneous non-catalytic gas-solid reactors are commonly used in the production of chemicals, metals and metal oxides, for example, rotary drum reactor for producing quick lime; blast furnace, a moving bed reactor for producing iron, etc. Industrial processes involve multicomponent mixtures of solids as most of the naturally occurring materials such as minerals are multicomponent in nature. Generally the raw materials are heterogeneous and their physical and chemical characteristics vary from one source to another. The solid particles are also usually moist, the moisture content varying from season to season. The physico-chemical phenomena that take place in these reactors include flow of gases through porous media, heat transfer between the gases, solids, equipment and the environment, evaporation and condensation of moisture, reactions between gases and solids and within a single phase, melting and solidification depending on the temperatures inside the reactor, etc. The flow of particles is also of great importance especially in rotary drum and moving bed reactors. General features of the mathematical models for non-catalytic reactors are described along with models for the phenomena mentioned above. Case studies from the iron and steel industry on model-based optimization of production of direct reduced iron in a rotary kiln and induration of wet iron ore pellets on a moving packed bed reactor are discussed here.

State and Parameter Estimation with Augmented Kalman Filter Applied to an Industrial Polymer Reactor

174 The dynamic modeling and optimization of an industrial batch reactor

Modeling of an industrial naphtha isomerization reactor and development and assessment of a new isomerization process