SIMULATION AND STATIC BIFURCATION BEHAVIOR OF INDUSTRIAL FCC UNITS

A relatively simple model of optimum degree of sophistication for riser-reactor industrial fluid catalytic cracking (FCC) units is developed. An efficient iterative computer code is developed for the solution of the nonlinear two-point boundary value model equations. Sets of data for three industrial units are used to adjust the parameters of the model. Independent sets of data for each unit are used to verify the reliability of the model without any adjustable parameters. The model is used to investigate the static bifurcation behavior and its implications for design, operation, and control.     

Modelling coke formation in an industrial ethane-cracking furnace for ethylene production

The development of a model for predicting coke formation in an industrial ethylene cracking furnace is described. Expressions for predicting the rates of catalytic and pyrolytic coke formation are developed and a differential equation is derived to predict changes in coke thickness with time and position. An expression is developed to account for a decline in the rate of catalytic coke formation with increasing thickness of the coke layer. The proposed coke model equations are used to extend a previously developed ethane pyrolysis furnace model that ignored coke. Three model parameters related to coke formation are estimated using industrial data to obtain reliable model predictions. Two of these parameters are coefficients that appear in the catalytic and pyrolytic coke formation rate expressions. The third is a characteristic-length parameter used to reduce the rate of catalytic coke formation as the coke layer grows. The resulting dynamic model matches the industrial data well and can be used to simulate furnace operation and predict coke thickness profiles over a variety of the operating conditions, thereby helping process engineers who plan the decoking process.     

Chemical reactor network application to predict the emission of nitrogen oxides in an industrial combustion chamber

A new chemical reactor network model is developed to predict the emission of nitrogen oxides in an industrial combustion chamber operating on liquefied petroleum gas. The boundary conditions and operating parameters used for this model are typical operating conditions of an industrial combustion chamber. The global mechanism is developed by GRI-MECH 3.0 in the UW code. The model predictions are compared with experimental data. The chemical reactor network model provides an accurate estimation of nitrogen oxide emission.     

Translation of MAT Kinetic Data to Model Industrial Catalytic Cracking Units

Bench‐ and laboratory‐scale reactors are required to infer kinetic data for catalytic cracking units. One of the most common methods is the microactivity test (MAT, ASTM D‐3902–92), that emulates the catalyst‐to‐oil ratio using a fixed‐bed reactor and a semibatch accumulator of liquids. Translation of data obtained from MAT tests in order to infer kinetic parameters to model continuous industrial units is, consequently, difficult and uncertain. In this work, the extraction of kinetic data obtained in a MAT reactor is analyzed. Estimation of a kinetic rate equation to evaluate instantaneous conversion in MAT reactors is performed. The activation energy obtained is kinetic and can be used during the modeling of riser reactors. It was possible, also, to infer values of the remaining catalytic activity after each experiment; these values were used to adjust a hyperbolic deactivation function, useful to model industrial riser reactors.     

Linking yield stress measurements: Spread test versus Viskomat

Two rheological tools widely used in the cement industry are compared: the Viskomat rheometer and the spread test. It is shown that proper calibration of the first, and selection of an adequate physical model for the second yield to a quantitative agreement of yield stress values. Such results are important for industrial labs that may translate existing data in arbitrary units into rheologically relevant parameters.     

Modelling of heat transfer and pyrolysis reactions in an industrial ethylene cracking furnace

The development of a relatively simple mechanistic model for an industrial ethylene cracking furnace is described, including the estimation of selected model parameters to improve model predictions. Energy balance equations are developed to account for radiative, conductive, and convective heat transfer in the radiant section, and for convection and conduction in the ultra‐selective heat exchanger (USX) and in the transfer line exchanger (TLE). Kinetic schemes by Ranjan et al. and Sundaram and Froment are used to model the cracking reactions. 1 , 2 The heat transfer model is combined with mass and momentum balances to model gas composition, pressure, and temperature changes as a function of position along the reactor tubes. Initial values and uncertainty ranges are assigned to 44 model parameters based on information in the literature and our industrial sponsor. A sensitivity‐based technique and a mean‐squared‐error (MSE) criterion are used to select the appropriate subset of 22 parameters for tuning. Parameters are estimated and model predictions are validated using industrial data. Model predictions provide a good match to data that were not used for estimation.     

Optimal hybrid modeling approach for polymerization reactors using parameter estimation techniques

The dynamics of polymerization catalytic reactors have been investigated by many researchers during the past five decades; however, the emphasis of these studies was directed towards correlating process model parameters using empirical investigation based on small scale experimental setup and not on real process conditions. The resulting correlations are of limited practical use for industrial scale operations. A statistical study for the relative correlation of each of the effective process parameters revealed the best combination of parameters that could be used for optimizing the process model performance. Parameter estimation techniques are then utilized to find the values of these parameters that minimize a predefined objective function. Published real industrial scale data for the process was used as a basis for validating the process model. To generalize the model, an artificial neural network approach is used to capture the functional relationship of the selected parameters with the process operating conditions. The developed ANN-based correlation was used in a conventional fluidized catalytic bed reactor (FCR) model and simulated under industrial operating conditions. The new hybrid model predictions of the melt-flow index and the emulsion temperature were compared to industrial measurements as well as published models. The predictive quality of the hybrid model was superior to other models. The suggested parameter estimation and modeling approach can be used for process analysis and possible control system design and optimization investigations.     

Expert System for the Design of an Industrial Fermentation Plant for the Production of Alcohol

A user-friendly expert system was developed for the design of large scale continuous fermentation units for alcohol production. This expert system utilized an intensive rule-based program, with a knowledge base structured using both expert knowledge data and industrial practices, as well as computer simulations. The simulation algorithm was developed from mass and energy conservation of continuous multi-staged plants and kinetic equations representing the fermentation process by Saccharomyces cerevisiae. The kinetic parameters were adapted from industrial data, leading to a reliable mathematical model that represented the industrial process reasonably well. Since the system was designed for continuous processes with several stirred tanks connected in series, the optimal volume profile and number of stages were previously optimized. The system developed could be utilized either for the design of industrial plants or for the improvement and modernization of existing plants. This system was shown to be reliable since the difference between theoretical calculations and practical results was minimal. © 1997 SCI.     

Mathematical modeling of an industrial steam-methane reformer for on-line deployment

A mathematical model of an industrial steam-methane reformer (SMR) is developed for use in monitoring tube-wall temperatures. The model calculates temperature profiles for the outer-tube wall, inner-tube wall, furnace gas and process gas. Inputs are the reformer inlet-stream conditions, the furnace geometry and material properties of the furnace and catalyst-bed. The model divides the reformer into zones of uniform temperature and composition. Radiative-heat transfer on the furnace side is modeled using the Hottel Zone method. Energy and material balances are solved numerically. The effect of important model parameters on reformer temperature profiles is assessed and the parameters are fit to data from an industrial SMR. At plant rates greater than 85% the model accurately predicts the process-gas outlet temperature, composition, pressure, flow rate and tube-wall temperatures. The adjustable parameters may need to be re-estimated using additional low plant rate data. The model has the capacity to be developed into a more complex model that accounts for classes of tubes associated with different radiative environments.     

北方裂解炉的动态仿真

建立了北方裂解炉的动态模型。将裂解炉分为原料油预热段、过热段、锅炉水预热段、辐射段等几个部分 ,结合各部分的结构与传热特点 ,分别建立机理仿真模型。另外 ,在建模过程中 ,结合现场数据 ,引入了部分经验参数 ,使模型得到合理简化。应用结果表明本模型适用范围广、逼真度高 ,满足动态仿真适时性和精度要求     

A new generic approach for the modeling of fluid catalytic cracking (FCC) riser reactor

A new kinetic model for the fluid catalytic cracking (FCC) riser is developed. An elementary reaction scheme, for the FCC, based on cracking of a large number of lumps in the form of narrow boiling pseudocomponents is proposed. The kinetic parameters are estimated using a semi-empirical approach based on normal probability distribution. The correlation proposed for the kinetic parameters’ estimation contains four parameters that depend on the feed characteristics, catalyst activity, and coke forming tendency of the feed. This approach eliminates the need of determining a large number of rate constants required for conventional lumped models. The model seems to be more versatile than existing models and opens up a new dimension for making generic models suitable for the analysis and control studies of FCC units. The model also incorporates catalyst deactivation and two-phase flow in the riser reactor. Predictions of the model compare well with the yield pattern of industrial scale plant data reported in literature.     

Modeling of an industrial fixed bed reactor based on lumped kinetic models for hydrogenation of pyrolysis gasoline

In this work, a mathematical model of an industrial fixed bed reactor for the catalytic hydrogenation of pyrolysis gasoline produced from olefin production plant is developed based on a lumped kinetic model. A pseudo-homogeneous system for liquid and solid phases and three pseudo-components: diolefins, olefins, and parraffins, are taken into account in the development of the reactor model. Temperature profile and product distribution from real plant data on a gasoline hydrogenation reactor are used to estimate reaction kinetic parameters. The developed model is validated by comparing the results of simulation with those collected from the plant data. From simulation results, it is found that the prediction of significant state variables agrees well with the actual plant data for a wide range of operating conditions; the developed model adequately represents the fixed-bed reactor.     

A Learning Process Simulator for Fluidized Bed Dryers Application to Bentonite Drying

A fluid bed dryer simulator was developed under Excel 5 wlth Visual Basic for Applications environment The simulator iS based on a mathematical model describing heat and mass transfer in the dryer. The total model incorporates empirical models for the Drying Constant and the Residence Time. These empirical models are crucial in the total model efficiency. Thus a procedure for updating the parameters of the empirical models is provided. This procedure constitutes the 'learnhg' property of the simulator. Two databases are Supplied. The first contains laboratory drying data and it is used for tuning the Drying Constant empirical model. The second contains industrial drying data from the real operation of the dryer, and it is used for tuning the Residence Time empirical model. The experience from the industrial application of the simulator proved that the simulator is a powerful tool for flexible operation of an industrial dryer. This paper is presents the total mathematical model of the dryer, the learning concept, and the databases, including useful information concerning the drying kinetics of bentonite. A simulator outline is presented and typical capabilities and uses are briefly described. A case study for flexible operation of an industrial dryer is discussed.     

Influence of Water and Supercooling on Permeability and Compressibility of Acrylic Acid Crystal Beds

The performance of a solid‐liquid separation process is often limited by size distribution and morphology of the crystals. To predict the filtration behavior, a robust and applicable model based only on crystallization process parameters is necessary. Therefore, a model has been successfully developed for the industrial system of aqueous acrylic acid melt to predict compressibility and permeability of a crystal bed. For this purpose, common equations are transferred successfully to nonspherical particles. Chord length distributions (CLDs) obtained from an inline focused beam reflectance measurement (FBRM) probe and crystal aspect ratios have been used in combination to determine the major input parameters for the model. Integration of a complex mathematical restoration of crystal size distribution (CSD) from CLD data by the use of existing models is avoided. Considering acceptable fault tolerances of the model, a simple approach used as a robust industrial application is employed. The adjustment of all required constants used in the permeability model was based on simple filtration tests.     

Modeling and optimization of an industrial hydrocracking unit to improve the yield of diesel or kerosene

Hydrocracking is used in the petroleum industry to convert low-quality feedstocks into highly-valued transportation fuels. This process is the best source of low-sulfur and low-aromatics diesel fuel as well as high-smoke point jet fuel. Many approaches have been proposed for solving optimization of hydrocracking units in the last decades, but they usually neglect the reaction in hydrotreater where hydrocarbon cracking often occurs, thus leading to suboptimal solutions in industrial problems. Unlike existing literature, this paper considers the hydrocarbon cracking reactions in hydrotreater and hydrocracker simultaneously. The models are based on energy balance, mass balance and a discrete lumped model approaches for kinetic modeling. Before optimization, the properties of feedstock are predicted with ASPEN PLUS by using laboratory data from the refinery, and then the model parameters are estimated with genetic algorithm (GA) based on industrial data and validated by comparing the simulating results with industrial data. To improve the yield of the lighter products, the operation conditions are optimized by GA and Sequential Quadratic Programming (SQP). The yields of the diesel or kerosene increase with the proposed approach.     

A Learning Process Simulator for Fluidized Bed Dryers Application to Bentonite Drying

ABSTRACT

A fluid bed dryer simulator was developed under Excel 5 wlth Visual Basic for Applications environment The simulator iS based on a mathematical model describing heat and mass transfer in the dryer. The total model incorporates empirical models for the Drying Constant and the Residence Time. These empirical models are crucial in the total model efficiency. Thus a procedure for updating the parameters of the empirical models is provided. This procedure constitutes the ‘learnhg’ property of the simulator. Two databases are Supplied. The first contains laboratory drying data and it is used for tuning the Drying Constant empirical model. The second contains industrial drying data from the real operation of the dryer, and it is used for tuning the Residence Time empirical model. The experience from the industrial application of the simulator proved that the simulator is a powerful tool for flexible operation of an industrial dryer. This paper is presents the total mathematical model of the dryer, the learning concept, and the databases, including useful information concerning the drying kinetics of bentonite. A simulator outline is presented and typical capabilities and uses are briefly described. A case study for flexible operation of an industrial dryer is discussed.     

乙烯氧氯化流化床反应器的模型化及操作条件优化

对工业乙烯氧氯化挡板流化床反应器建立了以两相理论为基础的多釜串联反应器模型,利用大量工业数据求解模型参数并检验模型,计算结果表明模拟值与工业值基本吻合.在此基础上,对反应器操作条件进行优化,得到不同生产负荷下的最优操作条件.     

Simulation of the ammonia oxidation process over an oxide monolith catalyst

A mathematical model of ammonia oxidation over an oxide monolith honeycomb catalyst has been developed. Experimental data from a pilot unit operating under process conditions equal to those in a type UKL-7 commercial nitric acid plant were used to refine the parameters of the mathematical model. The results from calculating the NO yield are in satisfactory agreement with the pilot unit data. There is now computer program that allows us to calculate the conditions of an industrial reactor functioning.     

Simultaneous robust data reconciliation and gross error detection through particle swarm optimization for an industrial polypropylene reactor

In a previous study, a nonlinear dynamic data reconciliation procedure (NDDR) based on the particle swarm optimization (PSO) method was developed and validated in line and in real time with actual industrial data obtained for an industrial polypropylene reactor (Prata et al., 2009, Prata et al., 2008b). The procedure is modified to allow for robust implementation of the NDDR problem with simultaneous detection of gross errors and estimation of model parameters. The negative effects of the less frequent gross errors are eliminated with the implementation of the Welsch robust estimator, avoiding the computation of biased estimates and implementation of iterative procedures for detection and removal of gross errors. The performance of the proposed procedure was tested in line and in real time in an industrial bulk propylene polymerization process. A phenomenological model of the real process, based on the detailed mass and energy balances and constituted by a set of algebraic-differential equations, was implemented and used for interpretation of the actual plant behavior. The resulting nonlinear dynamic optimization problem was solved iteratively on a moving time window, in order to capture the current process behavior and allow for dynamic adaptation of model parameters. Results indicate that the proposed procedure, based on the combination of the PSO method and the robust Welsch estimator, can be implemented in real time in real industrial environments, allowing for the simultaneous detection of gross errors and estimation of process states and model parameters, leading to more robust and reproducible numerical performance.     

由邻硝基甲苯生产三硝基甲苯过程模拟

引　言目前 ,国内外生产三硝基甲苯大都采用甲苯三段硝化工艺 .混合硝基甲苯生产线是由甲苯硝化成一硝基甲苯 ,然后再将一硝基甲苯根据其异构体性质的不同分离成对位 (36 .1% )、邻位 (5 9.2 % )、间位硝基甲苯 (4.7% ) [1] 3种产品 .市场上对硝基甲苯的需求量远远大于邻、间硝基甲苯 ,在生产中占较大比例的邻硝基甲苯不能得到充分利用 ,如用其代替甲苯生产三硝基甲苯 ,可将三段硝化工艺减为二段 ,且邻硝基甲苯得到合理利用 .本文根据硝化与氧化反应动力学理论[2 ] 建立了用邻硝基甲苯生产三硝基甲苯的末段硝化过程的稳态模型 ,根据生产数据…