Iranian Journal of Chemical Engineering (IJChE)

Abstract An industrial ethane thermal cracking reactor was modeled assuming a molecular mechanism for the reaction kinetics coupled with material, energy, and momentum balances of the reactant-product flow along the reactor. To carry out the multi-objective optimization for two objectives such as conversion and ethylene selectivity, the elitist non-dominated sorting genetic algorithm was used. The Pareto optimum set was obtained successfully and finally the effect of the decision variable was discussed.
 
 

Abstract Prediction of the dynamic crossflow ultrafiltration rate of a protein solution such as milk poses a complex non-linear problem as the filtration rate has a strong dependence on both the solution physicochemical conditions and the operating conditions. As a result, the development of general physics-based models has proved extremely challenging. In this study an alternative dynamic neuro-fuzzy model for milk ultrafiltration that describes the variation in dynamic permeate flux decline with temperature, transmembrane pressure (TMP), fat percentage, pH and molecular weight cut off (MWCO) has been developed with the experimental data of the pilot spiral wound membrane test rig. By increasing the temperature, TMP, and pH the permeate flux is increased, and by increasing fat concentration the permeate flux is decreased. The MWCO variation indicates a paradoxical permeate flux. Additionally, a hybrid physical model for dynamic prediction of total resistance in the milk ultrafiltration by combination of two neuro-fuzzy (ANFIS) models and a physical model (BLA model) is developed. By increasing the TMP and fat concentration, the total resistance is increased. But by increasing the pH and temperature, the total resistance is decreased. Also, MWCO variation indicates a paradoxical total resistance value.

Abstract Common methods to design heat exchanger networks (HENs) by pinch technology usually need an evolutionary step to reduce the number of heat transfer units. This step is called loop breaking and is based on the removal of exchangers that impose minimum increase on utility consumption. Loops identification and breaking is a tedious task and becomes more complicated in large networks. This paper presents a rapid nonlinear programming (NLP) formulation for the evolution of HENs in which loop identification is not required. The objective of the NLP is the minimization of HENs annual cost, which is not considered in current methods. In this method a search is done to find the best units elimination of which improves HENs annual cost. The search continues until the minimum number of units (MNU) is achieved and the exchangers that must be removed from the network are specified. The method was applied to some networks reported in the literature and better results were obtained. Also, the convergence of the presented method is very fast and it can be applied to different networks designed by pinch technology.

Abstract Synthesis of heat exchanger networks (HENs) is inherently a mixed integer and nonlinear programming (MINLP) problem. Solving such problems leads to difficulties in the optimization of continuous and binary variables. This paper presents a new efficient and robust method in which structural parameters are optimized by genetic algorithm (G.A.) and continuous variables are handled due to a modified objective function for maximum energy recovery (MER). Node representation is used for addressing the exchangers and networks are considered as a sequence of genes. Each gene consists of nodes for generating different structures within a network. Results show that this method may find new or near optimal solutions with a less than 2% increase in Hen annual costs.

Abstract "> In the present study the reaction kinetic and dynamic modeling of the reactor for syngas transformation into dimethyl ether using a mixture of a metallic oxides (CuO, ZnO, Al2O3), and an acidic component (γ-Al2O3) as the catalyst has been investigated. A combination of the Graff kinetic model for methanol synthesis and the Bercic model for methanol dehydration was correlated with the experimental results obtained in this study. Activity and kinetic measurements were carried out using a catalytic fixed bed micro reactor. The operating temperature range was 230-300 °C and the pressure was 8 barg. The experimental runs were performed applying a wide range of catalyst to feed ratios. A simple dynamic model for the reactor performance was developed and tested with the experimental data. The mean absolute deviation, concerning the data for the steady state conditions, was less than 8%.

Abstract "> Accurate prediction of the minimum miscibility pressure (MMP) in a gas injection process is crucial to optimizing the management of gas injection projects. Because the experimental determination of MMP is very expensive and time-consuming, searching for a fast and robust mathematical determination of CO2-oil MMP is usually requested. This paper presents a new model based on a hybrid neural-genetic algorithm for predicting pure and impure CO2-oil MMP. The CO2-oil MMP of a reservoir fluid was correlated with the reservoir temperature, the composition of the oil, and that of the solution gas. The developed model is able to reflect the impacts on the CO2–oil MMP of the molecular weight of the C5+ fraction, reservoir temperature, and solution gas in the oil. The validity of this new model was successfully approved by comparing the model results to the calculated results for the common pure and impure CO2-oil MMP correlations. The new model yielded the accurate prediction of the experimental slim-tube CO2-oil MMP with the lowest mean absolute percentage error (MAPE), the standard deviation of error (SD), the root mean square error (RMSE), and the highest correlation coefficient among tested impure and pure CO2-oil MMP correlations. The results demonstrate that the hybrid neural-genetic model can be applied successfully and provide high accuracy and reliability for MMP forecasting.

Abstract The spreading of a tracer in a bubbly two-phase grid-generated turbulent flow system is studied. In this work both particle image velocimetry (PIV) and planer laser-induced fluorescence (PLIF) are used to study the effect of the dispersed phase flow rate on the mixing characteristics of the tracer. The turbulent intensity of the continuous phase in the bubbly two-phase grid-generated turbulent flow is close to isotropic, and increasing the gas void fraction reduces the degree of non-isotropicity. The self-similarity of mean and RMS values of the cross-stream concentration distribution is observed. A new mathematical model is suggested to describe the self-similarity of the cross-stream profiles of the mean concentration based on two separate Gaussian curves into the central and outer region of the flow. The turbulent diffusivity is calculated using the Taylor hypothesis, which is based on the growth of the variance of the cross-stream profiles of the mean concentration, with a position along the direction of the flow. An increase in the void fraction does not affect the diffusivity of the superimposed distribution of the plume in the central region, however it did increase in the outer region.

Abstract Analytical gas-permeation models for predicting the separation process across  membranes (exit compositions and area requirement) constitutes an important and necessary step in understanding the overall performance of  membrane modules. But, the exact (numerical) solution methods suffer from the complexity of the solution. Therefore, solutions of nonlinear ordinary differential equations that govern the performance of the membrane modules for gas separations by approximate and asymptotic methods are useful in the design and comparison of processes. In this work, the asymptotic methods were applied for predicting the performance of nanometric tubular ceramic membranes in the separation of binary gas mixtures with cocurrent and countercurrent flow patterns. Also, the exact (numerical) solutions of the governing equations using the fourth order Rung-Kutta technique were proposed. The comparison of the results showed a good agreement between the exact solution and asymptotic analysis methods over the whole range of selectivities (). Because, the asymptotic curves into the former () and latter () boundaries had a suitable overlap with each other to cover the whole range of selectivities. The accuracy of this method was verified by a comparison of the predicted results with different literature experimental data and mathematical models. This result suggests the use of the asymptotic analysis method to provide excellent shortcut, preliminary design information.
 
 
 

Abstract In this paper a two impinging streams cyclone contacting system suitable for handling of solid-liquid systems has been studied. Certain pertinent parameters such as: solid holdup, mean residence time and Residence Time Distribution (RTD) of solid particles have been investigated. A stochastic model based on Markov chains processes has been applied which describe the behavior of solid particles in the contacting system. From this model the RTD data were estimated and compared with the experimental results. The RTD data were obtained at different Dt and compared with those estimated from the model. At Dt = 0.362 s a good correlation has been observed between the predicted and experimental data. The RTD data may be used to determine certain pertinent characteristic parameters of physical and chemical apparatuses such as conversion in chemical reactors.
 
 

Abstract In this research, Fischer Tropsch synthesis (FTS) has been modeled in the fixed bed chromatographic reactor for the first time by applying a rather complex dispersed plug flow model for fluid phase and linear driving force (LDF) model for adsorbent. Model equations are dynamic, multi-component, non-linear and heterogeneous including reaction and adsorption simultaneously Complex kinetics for FTS and water-gas shift (WGS) reaction and the multicomponent Langmuir adsorption isotherm is used in the model. A set of partial differential and ordinary differential equations with algebraic equations have been converted into a set of ordinary differential equations by using the orthogonal collocation technique. Then this set of equations has been solved by multi-step methods of Numerical Differentiation Formulae (NDF) or Backward Dif-ferentiation Formulae (BDF) Known as the Gear’s method. Consequently, results for dynamic model and effects of modeling parameters have been analyzed. Through this fixed bed chromatographic reactor model, one may develop a suitable configuration of simulated moving bed chromatographic reactors.
 
 
 

Abstract The aim of this study was to investigate the particulate dispersion from Kerman Cement Plant. The upwind – downwind method was used to measure particle concentration and a cascade impactor was applied to determine particle size distribution. An Eulerian model, Gaussian plume model and an artificial neural network have been used to compute and predict concentration of PM₁₀ from Kerman Cement Plant. Eulerian model incorporates source related factors, meteorological factors, surface roughness and particle settling to estimate pollutant concentration from continuous sources. The measured data have been used to create an artificial neural network for predicting suspended particle concentration from Kerman Cement Plant. The data includes particle concentration, distance from source, mixing height, lateral and vertical dispersion parameters and 10 meters wind speed. The performance of these models has been compared with the measured data. The AAPD (Average Absolute Percent Deviation) parameter for the results of the Eulerian model, Gaussian model and ANNs was 25.53%, 15.38% and 5.91% respectively.
 
 
 
 
 

Abstract Due to increasing application of multi effect falling film evaporators in food industry, the exact modeling of these processes is important. The aim of this paper is use ability of nonlinear modeling in determining falling film evaporator state variables. Because of large time delays and process disturbances, the tight exact control of product concentration is difficult. By using the nonlinear modeling, the control of three effect falling film evaporator with the use of cascade control algorithm is analyzed. This paper discusses the application and design of a cascade algorithm to control the product concentration in a milk powder three effect falling-film evaporator. It has been shown that the disturbance rejection properties can be significantly improved with cascade control while still maintaining the tracking properties.

Abstract Deposition of colloidal particles onto surfaces is usually assumed to follow the Derjaguin-Landau-Verwey-Overbeek (D.L.V.O.) theory for colloidal stability. In the work presented here the D.L.V.O theory is extended to include the case where the surface is electronically conducting. The effect of application of an electric field to the surfaces on the rate of deposition of 5.4 µm colloidal particles is simulated.

Abstract Prediction of particle removal efficiency in all kinds of dust collectors includes mathematical modeling of particle-laden flow. One of the main problems for such modeling is to find particle velocity distribution which can he predicted using a particle momentum balance equation. A common simple alternative is to use equilibrium or settling velocities. In this work, a comprehensive mathematical model for particle removal in double-stage electrostatic precipitators was developed. Analysing the results of this model shows that the equilibrium assumption can be considered as a reliable method for a Stokes number less than 0.001. Atm for a higher Stokes number, an explicit Eulerian method was developed for the evaluation of particle velocities explicitly. This method eliminates solving particle momentum balance equations which is a relatively time-consuming step in mathematical modeling of dust collectors. 

Abstract In this paper, a simplified formulation for a compositional reservoir simulator is presented. These type of simulators are used when interphase mass transfer depends on phase composition as well as pressure. The procedure for solving compositional model equations is completely described. The Peng Robinson equation of state is used for preparing a compositional thermodynamic program for equilibrium calculation, property estimation and pseudo component determination. Another purpose of this paper is to prepare an experimental apparatus for the displacement of oil by gas injection. In each test, oil recovery as a function of injected pore volume was measured. The application of the developed simulator to simulate the results of the oil recovery from slim tube experiments is also presented. Finally, the model was run for a 2-D reservoir. Acceptable trends were obtained from the model predictions.

Abstract ge-newline"> One method for conversion of methane to more valuable products is by non-catalytic gas-phase oxidative coupling of methane (OCM), through which methane is converted into ethylene. The product of this process is ethylene, accompanied by acetylene, ethane, a small quantity of three carbon compounds as coupling products, and carbon oxides due to complete oxidation of hydrocarbons. The kinetic model proposed for the OCM process consists of 75 elementary reactions and 23 chemical species. In previous studies, the reactor-kinetic modeling of this process, was implemented in a laboratory micro-reactor at constant temperature and pressure. Considering that this process proceeds with severe variation in the enthalpy, in the present study, in addition to isothermal, the operation of the system has also been modeled for the adiabatic state. The modeling has been carried out in a tubular reactor system. Comparison of the qualitative and quantitative results of the model with experimental data at constant temperature shows that the proposed kinetic model predicts the experimental results properly. Furthermore, in the present study, the effect of various parameters on the operation of the system has also been examined. These studies have been performed in the following ranges of pressure, temperature and CH4/O2 ratio respectively: 1≤ P ≤ 10 (bar), 950≤ T≤ 1100 (K), 4 ≤ CH4/O2 ≤ 10. It has been shown that, by increasing the temperature, the reaction rate increases. Raising the total pressure of the system causes an increase in methane conversion and selectivities of desired products as well as the reaction rate. On the other hand, increasing the residence time in the reactor will result in conversion of desired products to undesirable ones. Finally, it is shown that by decreasing the ratio of methane to inlet oxygen, conversion of methane increases, selectivities of the desired products decrease and the heat released during the reaction rises.

Abstract n this work, computational fluid dynamics of the flow behavior in a cold flow of fluidized bed is studied. An improved finite volume based finite element method has been introduced to solve the two-phase gas/solid flow hydrodynamic equations. This method uses a collocated grid, where all variables are located at the nodal points. The fluid dynamic model for gas/solid two-phase flow is based on the two fluid model where both phases are continues and fully interpenetrating. For the gas and solid phases the Navier-Stokes equation based on the concept of local average is obtained. Results are verified against experimental data reported in the literature.

Abstract The presence of wall strengtheners in double-stage electrostatic precipitators affects gas velocity, electrical field and particle movement over the ESP. In this work we have used our previous mathematical model for double-stage ESP {Talaie et. al (2001) [10]] to study the effect of wall strengtheners on the performance of double-stage ESP. One of the important findings was that, due to the fact that wall strengtheners increase the degree of turbulence, the effect of gas turbulence on particle movement can not be ignored. The results of the calculations show that the simple Lagrangian model in which this effect is neglected is not suitable, whereas using an Eulerian approach provides much better results. The results of this model also revealed that the collection efficiency for small particles increases while that for large particles decreases when a baffle is used as wall strengthener.

Abstract KATAPAK-S is a type of structured catalytic packing, which is used in reactive distillation processes. The dry pressure drop characteristic (the pressure drop in the absence of liquid flow) is of significant importance for the investigation of process hydrodynamics. In this paper, the dry pressure drop within the catalyst packed channels of KATAPAK-S has been investigated using Computational Fluid Dynamics (CFD). Results of the CFD simulations were validated using experimental pressure drop data and empirical correlations. The CFD results showed an excellent agreement with theoretical and experimental data. Keywords: KATAPAK-S structures, Pressure drop, Structured packing, CFD

Abstract A new model to calculate heat eddy diffusivity in separating and reattaching flows based on modification of constant Prt is proposed. This modification is made using an empirical correlation between maximum Nusselt number and entrance Reynolds number. The model includes both the simplicity of Prt=0.9 assumption and the accuracy of two-equation heat-transfer models. Furthermore, an appropriate low Reynolds number k — e model is adopted for calculation of eddy viscosity. The model is used for prediction of Nusselt number distribution at various ranges of Reynolds number and expansion ratio. The numerical results are compared with available experimental data in the literature and have shown good agreement. The CPU time for the present model is about 33% less than that of two-equation heat-transfer model.

Abstract General modeling and optimization of syngas production via noncatalytic autothermal partial oxidation of methane are carried out using our developed scientific software which was based on the minimization of total Gibbs energy. In this work, a novel application of the direct search and Newton-Raphson methods was introduced to apply to optimization of a complex chemical reaction. Sensitivity analysis was done to investigate the effect of several parameters on the quality of syngas and the production yield. The acceptable concentrations of CO2 and H2O injected into the methane feed are optimized in the specified temperature and pressure range, while H2/CO ratio in the product stream is set to remain at 1.5 or 2, methane slip in the syngas is less than 1.5% and the non-endothermic conversion area of reaction prevail, simultaneously. This facilitates monetizing CO2 in the petrochemical and steel industries. The output from this software is comparable both with the experimental results, cited in Ref [1] , and with that from ASPEN PLUS in simulating the experiments mentioned in Ref [2]

Abstract n this paper, a mathematical model has been derived to predict the granulation time of anaerobic sludge in UASB reactors. In the proposed model, some physical, chemical and biological parameters affecting the granulation phenomena have been considered. To validate the model, 12 pilot-scale experiments in 4 UASB reactors are carried out and the results are discussed here. The reactors are started up at different environmental conditions and the granulation time in each experiment is determined. The results show that the model is able to explain different mechanisms involved in the granulation process.

Abstract The present study attempted deriving and solving the falling- cylinder governing equations for power law model non-Newtonian fluids. Based on this theoretical study, a novel falling- cylinder rheometer (FCR) was designed and constructed to measure the Theological properties of non-Newtonian fluids. Different falling cylinders with predesigned densities were used to determine the apparent viscosity of polyvinyl alcohol (PVA) solutions in water with various concentrations. The results indicate that all PVA solutions obey the power law model with the power law index as well as the consistency index changing linearly with concentration. Increasing concentration of the solution decreases power law index, while enhances consistency index and apparent viscosity.

Abstract Arterial stenosis, for example Atherosclerosis, is one of the most serious forms of arterial disease in the formation of which hemodynamic factors play a significant role. In the present study, a 3-D rigid carotid artery with axisymmetric stenosis with 75% reduction in cross-sectional area is considered. Laminar blood flow is assumed to have both Newtonian and non-Newtonian behavior (generalized Newtonian fluid), while steady state and pulsatile cases are imposed separately. Governing equations are momentum and continuity. Employing the finite volume technique, flow features such as velocity profiles, flow separation zone and wall shear stress distribution in post stenotic region are calculated. Based on the results of the steady state situation, reverse and circulating flows exist until far from stenosis in Newtonian case. But, in non-Newtonian condition, these regions are limited to smaller areas near the stenosis. As blood flow becomes unsteady, in Newtonian case reverse flows become larger and stronger even far from stenosis while circulating flows weaken. Considering the same assumptions with non-Newtonian behavior, circulating flows become stronger than those of Newtonian model, while reverse flows weaken. Obtained results agree with the analytical results available for Newtonian fluid..

Abstract SHAHAB is a PC- based simulator developed by Olefin Research Group (ORG), with the simultaneous simulation of the reactor, the firebox, the convection section and the transfer line exchanger in steam Cracking units. The reaction mechanism of thermal cracking of hydrocarbons is generally accepted as free-radical chain reactions. Using a rigorous kinetic model, a complete reaction network for representing the decomposition of hydrocarbon feedstocks has been developed and used for simulation of thermal hydrocarbon crackers. Taking into account the kinetics of coke formation, SHAHAB provides a detailed understanding of product, temperature and pressure distribution, coke thickness profile, reactor run length, fuel consumption and the amount of steam generated.