Modeling and Simulation
Hajar seyfi; Sirous shafiei; Reza Dehghanzadeh; Parya Amirabedi
Abstract
Removal of Acrylonitrile (AN) from waste gas streams using biological methods has recently gained more attraction due to their better performance. The purpose of this research is modeling of the AN removal by a bio-filter. The model validation is done using the experimental data of a bench-scale bio-filter ...
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Removal of Acrylonitrile (AN) from waste gas streams using biological methods has recently gained more attraction due to their better performance. The purpose of this research is modeling of the AN removal by a bio-filter. The model validation is done using the experimental data of a bench-scale bio-filter bed column including yard waste compost and shredded hard plastics and thickened municipal activated sludge. In this work the kinetics of the biodegradation of Acrylonitrile is first investigated. Then equations of the biofilm and air are obtained at steady state and constant temperature. The unknown parameters of the model are determined by the least square optimization method along with solving the model equations using MATLAB. For inlet concentrations less than 1 g/m3 the model results show reasonable similarity to the experimental data. The effect of various parameters on bio-filter performance is evaluated. Peclet number, biofilm thickness and biomass concentration are the most important parameters respectively. The proposed model can be useful for design aims.
Modeling and Simulation
M. Hosseini; A.H Oudi; Y. Davoodbeygi
Abstract
The fully mixed continuous stirred tank reactor is an important type of industrial reactors mainly used to produce high volume products such as petrochemicals, detergents, sanitary products and products that are in demand in the market. Knowing the dynamic behavior of chemical reactors is of great importance ...
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The fully mixed continuous stirred tank reactor is an important type of industrial reactors mainly used to produce high volume products such as petrochemicals, detergents, sanitary products and products that are in demand in the market. Knowing the dynamic behavior of chemical reactors is of great importance in setting up, designing, controlling and stopping reactors. In this paper, the effect of non-dimensional numbers Damkohler and Stanton on the stability of a continuous stirred tank reactor in which a first-order exothermic reaction takes place is investigated. First, a mathematical model of the system's dynamic behavior was presented. Then, by simultaneous solving of the equations of mass and energy around the fixed point in MATLAB software, the effect of the mentioned numbers was investigated. The results show that the continuous stirred tank reactor shows different behaviors in different ranges of Damkohler and Stanton numbers. This reactor behaves unstable in small and large ranges of Damkohler and Stanton numbers due to the presence of mixed or positive and negative eigenvalues. The best range for Damkohler and Stanton numbers is close to 1, because in this range the reactor shows stable behavior due to having two negative eigenvalues. In this range, in addition to the stability, the conversion is also 100%. Finaly the ratio of Stanton to DamKohler was investigated as St / Da˃1 and St / Da = 1. If St / Da = 1, the system is in steady state, but in St / Da˃1, the system moves away from steady state.
Modeling and Simulation
M. Etebarian; k. movagharnejad
Volume 16, Issue 2 , Spring 2019, , Pages 14-40
Abstract
Two main objectives have been considered in this paper: providing a good model to predict the critical temperature and pressure of binary hydrocarbon mixtures, and comparing the efficiency of the artificial neural network algorithms and the support vector regression as two commonly used soft computing ...
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Two main objectives have been considered in this paper: providing a good model to predict the critical temperature and pressure of binary hydrocarbon mixtures, and comparing the efficiency of the artificial neural network algorithms and the support vector regression as two commonly used soft computing methods. In order to have a fair comparison and to achieve the highest efficiency, a comprehensive search method is used in neural network modeling, and a particle swram optimization algorithm for SVM modeling. To compare the accuracy of the models, various criteria such as ARD, MAE, MSE, RAE and R2 are used. The simulation results show that the ARD for the prediction of the true critical temperature and pressure of the binary hydrocarbon mixtures for the final optimized ANN-based model is equal to 0.0161 and 0.0387, respectively. The corressponding ARD value for the SVM-based model is equal to 0.0086 and 0.0091 for critical temperature and pressure, respectively. Simulation results show that although both models have a very high predictive accuracy, the SVM has higher learning speed and accuracy than ANN.
Modeling and Simulation
M. rasteh
Volume 16, Issue 2 , Spring 2019, , Pages 41-56
Abstract
In this study, an Eulerian-Eulerian multi-fluid model (MFM) was used to simulate the segregation pattern of a conical fluidized bed containing ternary mixtures of equidensity TiO2 particles. Experimental 'freeze–sieving' method was employed to determine the axial mass fraction profiles of the ...
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In this study, an Eulerian-Eulerian multi-fluid model (MFM) was used to simulate the segregation pattern of a conical fluidized bed containing ternary mixtures of equidensity TiO2 particles. Experimental 'freeze–sieving' method was employed to determine the axial mass fraction profiles of the different-sized particles, and validate the simulation results. The profiles of mass fraction for large, medium and small sized particles along the bed height during the simulation time indicated that the particles’ segregation can be predicted by CFD model. Effect of superficial gas velocity on segregation pattern was also investigated. It was shown that for U0=1.2Umf, partial segregation of large particles occurred, while for U0=1.6Umf, small and medium size particles also segregated and full segregation was achieved. By increasing U0 to 2Umf, mixing of different sized particles was increased and particles segregation was reduced. Therefore, it can be concluded that there was a critical velocity below which particles would segregate while above which their mixing increased.
Transport Phenomena,
R. Beigzadeh
Volume 16, Issue 2 , Spring 2019, , Pages 57-69
Abstract
In the present study, Adaptive Neuro–Fuzzy Inference System (ANFIS) approach was applied for predicting the heat transfer and air flow pressure drop on flat and discontinuous fins. The heat transfer and friction characteristics were experimentally investigated in four flat and discontinuous fins ...
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In the present study, Adaptive Neuro–Fuzzy Inference System (ANFIS) approach was applied for predicting the heat transfer and air flow pressure drop on flat and discontinuous fins. The heat transfer and friction characteristics were experimentally investigated in four flat and discontinuous fins with different geometric parameters including; fin length (r), fin interruption (s), fin pitch (p), and fin thickness (t). Two ANFIS models were developed using the Computational Fluid Dynamic (CFD) results which validated by the experimental data. The ANFIS models were applied for prediction of Nusselt number (Nu) and friction factor (f) as functions of Reynolds number (Re), and fin geometric parameters including, spanwise spacing ratio (p/t), and streamwise spacing ratio (s/r). The low error values for testing data set, which were not employed in the training of the ANFIS, proved the precise and validity of the model. The root mean square error (RMSE) of 0.7343 and mean relative error (MRE) of 1.33% were resulted for prediction Nu. In addition, these values for estimation of the f were resulted 0.0158, 3.32%, respectively.
Modeling and Simulation
A. Sinkakarimi; A. Ghadi
Volume 16, Issue 2 , Spring 2019, , Pages 103-118
Abstract
Computational fluid dynamics (CFD) is a powerful numerical tool that is becoming widely used to simulate many processes in the industry. In this work study of the stirred tank with 7 types of concave blade with CFD was presented. In the modeling of the impeller rotation, sliding mesh (SM) technique was ...
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Computational fluid dynamics (CFD) is a powerful numerical tool that is becoming widely used to simulate many processes in the industry. In this work study of the stirred tank with 7 types of concave blade with CFD was presented. In the modeling of the impeller rotation, sliding mesh (SM) technique was used and RNG-k-ε model was selected for turbulence. Power consumption in various speeds in the single phase, mean tangential, radial and axial velocities in various points, effects of disc diameter and thickness and mixing time were investigated. The optimum concave impeller was selected and the effect of tracer feed position and probe location was investigated on it. Results suggested that power consumption is exactly depending on impellers scale and geometry, was in a good agreement with the experimental data and in turbulent flow is relatively independent of Reynolds number. Power number increases with increasing disc diameter for both concave and Rushton and concave´s power is relatively independent on disc thickness but increasing it decreases Rushton´s power. The data revealed that the power number was 2.3±0.3 for blade angle 40° whereas for blade 25°, 50° and 55° respectively 43% lower and 57% and 43% higher.
Modeling and Simulation
M. Khajeh Amiri; A. Ghaemi; H. Arjomandi
Volume 16, Issue 1 , Winter 2019, , Pages 54-64
Abstract
In this work, zeolite 13X with porosity structure has been used as an adsorbent for adsorption of CO2 flue gas. The effect of operating conditions including pressure and time on adsorption capacity were investigated. The experiments conditions are constant temperature, the range of pressure 1 - 9 bar ...
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In this work, zeolite 13X with porosity structure has been used as an adsorbent for adsorption of CO2 flue gas. The effect of operating conditions including pressure and time on adsorption capacity were investigated. The experiments conditions are constant temperature, the range of pressure 1 - 9 bar and the registration of adsorption capacity with passing of time. Experimental data were adjusted with adsorption isotherm models including two and three parameters isotherm. Also the process was studied in terms of kinetic models and after the implementation of the experimental data with kinetic models, the speed of this process equations were obtained. The best kinetic model for this process was selected first order equation. The results showed that adsorption capacity of 13X is 71.5 mg/g at pressure of 8 bars. Also the result indicate that 13x has high capacity at low pressures. With regard to achieved results for adsorption isotherm modeling, the adsorption isotherm followed of the three-parameter and among three-parameter models, Toth isotherm can be interpreted the process. Also the results of the fixed bed indicate a very high adsorbent selectivity to carbon dioxide adsorption and there was little oxygen and nitrogen adsorption.
Modeling and Simulation
A. Yousefi; k. movagharnejad
Volume 16, Issue 1 , Winter 2019, , Pages 83-100
Abstract
Solubility data of solid in aqueous and different organic solvents are very important physicochemical properties considered in the design of the industrial processes and the theoretical studies. In this study, experimental solubility data of 666 pharmaceutical compounds in water and 712 pharmaceutical ...
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Solubility data of solid in aqueous and different organic solvents are very important physicochemical properties considered in the design of the industrial processes and the theoretical studies. In this study, experimental solubility data of 666 pharmaceutical compounds in water and 712 pharmaceutical compounds in organic solvents were collected from different sources. Three different artificial neural networks including multilayer perceptron, radial basis function and support vector machine were constructed to predict the solubility of these different pharmaceutical compounds in water and different solvents. Molecular weight, melting point, temperature and the number of each functional group in the pharmaceutical compound and organic solvents were selected as the input variables of these three different neural network models. The neural network predictions were compared with the experimental data and the SVR-PSO model with the Average Absolute Relative Deviation equal to 0.0166 for the solubility in water and 0.0707 for solubility in organic compounds was selected as the most accurate model.
Modeling and Simulation
M. Bahoosh; E. Kashi; S. Shokrollahzadeh; Kh. Rostami
Volume 16, Issue 1 , Winter 2019, , Pages 101-116
Abstract
Reverse osmosis is a commonly used process in water desalination. Due to the scarcity of freshwater resources and wastewater problems, a lot of theory and experimental studies have been conducted to optimize this process. In the present study, the performance of reverse osmosis membrane module of salt–water ...
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Reverse osmosis is a commonly used process in water desalination. Due to the scarcity of freshwater resources and wastewater problems, a lot of theory and experimental studies have been conducted to optimize this process. In the present study, the performance of reverse osmosis membrane module of salt–water separation was simulated based on computational fluid dynamics technique and solution-diffusion theory. Eight geometries of membrane modules four flat sheets, and four tubular membranes were investigated. It was found that if the membrane surface area and inlet flow rate were kept constant for the eight modules, the pressure drop and permeated flow rate would be approximately similar for some geometries (such as the performance of primary flat sheet channel is same as 3 tubular membranes with R=1/3 Rref). The results also showed that because of the phenomenon of concentration polarization, if it is possible to use more membranes with a smaller length, it can reduce the pressure drop and increase the permeation flux of water. Furthermore, the results showed that in similar conditions between the tubular and the plate membranes; the tubular one is more suitable for the water permeation due to its ease of construction and its ability to withstand ECP.
Modeling and Simulation
M. rasteh; F. Farhadi
Volume 15, Issue 3 , Summer 2018, , Pages 53-71
Abstract
Abstract The effect of the solid–wall boundary condition on the segregation behavior of a sand ternary mixture differing in size but having the same proportion has been investigated in a gas–solid bubbling fluidized bed. A multi-fluid computational fluid dynamics model incorporating the kinetic ...
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Abstract The effect of the solid–wall boundary condition on the segregation behavior of a sand ternary mixture differing in size but having the same proportion has been investigated in a gas–solid bubbling fluidized bed. A multi-fluid computational fluid dynamics model incorporating the kinetic theory of granular flow has been used. The mass fraction profiles of the different-sized particles along the bed height have been experimentally measured by 'freeze–sieving' method. The simulation results of mass fraction distribution and segregation index have been compared against our experimental data in order to evaluate solid–wall boundary conditions in terms of specularity and particle-wall restitution coefficients. The analysis indicates that, the specularity coefficients in range 0.5 to 0.9 lead to the satisfactory results and the best agreement is obtained for =0.9 which corresponds to partial–slip wall boundary condition while the particle–wall restitution coefficient has only a negligible effect on the results. Also maximum segregation index occurs at specularity coefficient of 0.9 at which the segregation pattern may be affected by simultaneous mechanisms of particles circulation and bubbles rising. The effects of superficial gas velocity on the segregation behavior in bubbling regime have also been studied and a significant reduction in segregation index has been observed with increasing gas velocity from 1.1Umf to 1.3Umf.
Modeling and Simulation
A. Abdi; M.Sh Izadkhah; A. Karimi; M. Razzaghi; H. Moradkhani
Volume 15, Issue 3 , Summer 2018, , Pages 82-93
Abstract
A three-layer artificial neural network (ANN) model was developed to predict the remained DO (deoxygenation) in water after DO removal with an enzymatic granular biocatalyst (GB), based on the experimental data obtained in a laboratory stirring batch study. The effects of operational parameters such ...
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A three-layer artificial neural network (ANN) model was developed to predict the remained DO (deoxygenation) in water after DO removal with an enzymatic granular biocatalyst (GB), based on the experimental data obtained in a laboratory stirring batch study. The effects of operational parameters such as initial pH, initial glucose concentration and temperature on DO removal were investigated. On the basis of batch reactor test results, the optimum value of operating temperature, glucose concentration and pH were found to be 30oC, 80 mM and 7, respectively. After back-propagation training, the ANN model was able to predict the remained DO with a tangent sigmoid function (tansig) at hidden layer with 7 neurons and a linear transfer function (purelin) at the output layer. The linear regression between the network outputs and the corresponding targets were proven to be satisfactory with a correlation coefficient of 0.995 for three model variables used in this study.
Modeling and Simulation
N. Hadi; A. Niaei; r. alizadeh
Volume 15, Issue 2 , Spring 2018, , Pages 22-37
Abstract
The high silica Mn-substituted MFI metallosilicate catalyst with Si/Al molar ratio of 220 and Si/Mn molar ratio of 50 was successfully synthesized by hydrothermal method. The catalyst sample was appropriately characterized by XRD, FE-SEM, EDX and BET techniques. The Mn-substituted MFI metallosilicate ...
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The high silica Mn-substituted MFI metallosilicate catalyst with Si/Al molar ratio of 220 and Si/Mn molar ratio of 50 was successfully synthesized by hydrothermal method. The catalyst sample was appropriately characterized by XRD, FE-SEM, EDX and BET techniques. The Mn-substituted MFI metallosilicate has not been reported as the potential catalyst for the methanol to propylene (MTP) reaction. The prepared catalyst was examined in the MTP reaction at the optimal operating conditions. Furthermore, for elucidating the flow field of the MTP fixed bed reactor, a three-dimensional (3D) reactor model was developed. A detailed reaction mechanism which was proposed for the MTP reaction over the Mn-impregnated MFI zeolite (Mn/H-ZSM-5) was properly employed. The reaction mechanism was integrated to a computational fluid dynamics (CFD) for simulating the kinetic, the energy equation and the hydrodynamics of the MTP process, simultaneously. The component distribution during proceeding of the MTP reaction was also simulated as a function of time on stream. The CFD modeling results were validated by the actual data which were obtained over the Mn-substituted MFI metallosilicate catalyst. With regard to the findings, the experimental data were in good agreement with the predicted values of the CFD modeling.
Modeling and Simulation
k. movagharnejad; F. Saffar
Volume 15, Issue 2 , Spring 2018, , Pages 78-90
Abstract
In the present research, three different architectures were investigated to predict the coefficients of the Daubert and Danner equation for calculation of saturated liquid density. The first architecture with 4 network input parameters including critical temperature, critical pressure, critical volume ...
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In the present research, three different architectures were investigated to predict the coefficients of the Daubert and Danner equation for calculation of saturated liquid density. The first architecture with 4 network input parameters including critical temperature, critical pressure, critical volume and molecular weight, the second architecture with 6 network input parameters including the ones in the first architecture with acentric factor and compressibility factor. The third architecture contains 12 network input parameters including 6 input parameters of the second architecture and 6 structural functional groups of different hydrocarbons. The three different architectures were trained and tested with the 160 sets of Daubert and Danner coefficients gathered from the literature. The trained neural networks were also applied to 15 un-known hydrocarbons and the outputs (Daubert and Danner coefficients) were used to predict the saturated liquid densities. The calculated liquid densities were compared with the experimental values. The Results indicated that the coefficients obtained from the second architecture produced more precise values for the liquid densities of the 15 selected hydrocarbons.
Modeling and Simulation
H. Salimi; Sh. shahhosseini
Volume 15, Issue 1 , Winter 2018, , Pages 1-17
Abstract
Abstract Gas to liquid (GTL) process involves heterogeneous catalytic chemical reactions that convert synthesis gas to hydrocarbons and water vapor. A three phase reactor, called Low temperature Fischer-Tropsch (LTFT) is commonly applied for GTL process. In this reactor the gaseous phase includes the ...
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Abstract Gas to liquid (GTL) process involves heterogeneous catalytic chemical reactions that convert synthesis gas to hydrocarbons and water vapor. A three phase reactor, called Low temperature Fischer-Tropsch (LTFT) is commonly applied for GTL process. In this reactor the gaseous phase includes the synthesis gas, light hydrocarbons and water vapor, the liquid phase is a mixture of the heavy hydrocarbons, and the solid phase is composed of the catalyst and the waxy products. The presence of the liquid phase in LTFT reactor causes mass transfer restriction, affecting the reaction conversion. In this work a numerical simulation of the LTFT fixed bed reactor in trickle flow regime has been accomplished to understand the impact of the liquid phase on the reactor performance. For this purpose, we have developed an axisymmetric two-dimensional multiphase heterogeneous model, where contain carbon monoxide and hydrogen, are transferred into the liquid phase. The reactor consisted of a shell and a tube that was filled with the spherical cobalt catalyst. The reaction conditions were as follows: the wall temperature was 473 K, pressure was 20 bars and a gas hour space velocity (GHSV) was 111 Nml.g_cat^(-1).h^(-1). The numerical simulation results proved the negative impact of the liquid phase on the reaction conversion. The model predictions were evaluated against the reported experimental data and also compared with the result of a numerical pseudo-homogeneous model. It was found that applying the heterogeneous model instead of the pseudo-homogeneous model clearly decreases the deviation of the numerical results.
Modeling and Simulation
M. Varmazyar; R. Mohamady; M. Bazargan
Volume 15, Issue 1 , Winter 2018, , Pages 35-48
Abstract
The Lattice Boltzmann Method is used to simulate the dynamics of droplet deformation in a channel flow under various conditions. The droplet behavior has been investigated under transient conditions. For cases where the droplet remains attached to the surface, the shape deformation of the droplet during ...
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The Lattice Boltzmann Method is used to simulate the dynamics of droplet deformation in a channel flow under various conditions. The droplet behavior has been investigated under transient conditions. For cases where the droplet remains attached to the surface, the shape deformation of the droplet during crawling is captured. It has been shown that there is a limiting value for the droplet volume beyond which the critical shear rate remains almost constant and does not demonstrate much correlation with the size of the droplet. The predicted shapes of the droplet at various stages of deformation in the course of the flow by the current LBM code demonstrates more resemblance to the reported experiments than those obtained by a traditional CFD code. The effect of the droplet's initial volume and Reynolds number on the detachment and crawling processes are also investigated. The results are presented at various time steps to better demonstrate the droplet separation. Under the flow conditions investigated, wherever the Aniline droplet detaches, the entire droplet separates from the surface. For an Isoquinoline droplet however, once the main body is detached, a small part of the droplet remains attached to the surface in flows with low Reynolds numbers.
Modeling and Simulation
A. Ahmadpour; A. Haghighiasl; N. Fallah
Volume 15, Issue 1 , Winter 2018, , Pages 46-72
Abstract
In this research, photocatalytic degradation method has been introduced to clean up Spent Caustic of Olefin units of petrochemical industries (neutralized Spent Caustic by means of sulfuric acid) in the next step, adaptable method and effective parameters in the process performance have been investigated. ...
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In this research, photocatalytic degradation method has been introduced to clean up Spent Caustic of Olefin units of petrochemical industries (neutralized Spent Caustic by means of sulfuric acid) in the next step, adaptable method and effective parameters in the process performance have been investigated. Chemical oxygen demand (COD) was measured by the commercial zinc oxide that synthesized with precipitation synthesis method in a two-shell photoreactor. The percent of reduction of COD in the photocatalytic process was modeled using Box–Behnken design and artificial neural network techniques. It was concluded that the ANN was a more accurate method than the design of experiment. The effect of important parameters including oxidant dosage, aeration rate, pH, and catalyst loading was investigated. The results showed that all of the parameters, except pH, had positive effects on increasing COD removal. According to the obtained results, adsorption and photolysis phenomena had a negligible effect on COD removal.
Modeling and Simulation
L. Mahmoodi; B. Vaferi; M. Kayani
Volume 14, Issue 4 , Autumn 2017, , Pages 48-58
Abstract
Temperature distribution is a key function for analyzing and optimizing the thermal behavior of various process equipments. Moving bed reactor (MBR) is one of the high-tech process equipment which tries to improve the process performance and its energy consumption by fluidizing solid particles in a base ...
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Temperature distribution is a key function for analyzing and optimizing the thermal behavior of various process equipments. Moving bed reactor (MBR) is one of the high-tech process equipment which tries to improve the process performance and its energy consumption by fluidizing solid particles in a base fluid. In the present study, thermal behavior of MBR has been analyzed through mathematical simulation. Good agreement between the obtained results and both experimental data and analytical solution by self-adjoint method is observed. Mathematical results confirm that the average particle temperature linearly increases across the reactor length. Fluid temperature changes in a parabolic manner, and then it changes linearly. Increasing the Biot number ( ) results in increasing the temperature gradient inside the particle to a maximum value, and thereafter a decreasing pattern is observed. The numerical results confirmed that the finite difference method can be used for thermal analysis of the moving bed reactor.
Transport Phenomena,
A. Saberimoghaddam; M. M Bahri Rasht Abadi
Volume 14, Issue 3 , Summer 2017, , Pages 3-18
Abstract
Joule-Thomson cooling systems are used in refrigeration and liquefaction processes. There are extensive studies on Joule-Thomson cryogenic systems, but most of them coverage steady state conditions or lack from experimental data. In the present work, transient thermal behavior of Joule-Thomson cooling ...
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Joule-Thomson cooling systems are used in refrigeration and liquefaction processes. There are extensive studies on Joule-Thomson cryogenic systems, but most of them coverage steady state conditions or lack from experimental data. In the present work, transient thermal behavior of Joule-Thomson cooling system including counter current helically coiled tube in tube heat exchanger, expansion valve, and collector was studied by experimental tests and simulations. The experiments were carried out by small gas liquefier and nitrogen gas as working fluid. The recuperative heat exchanger was thermally analyzed by experimental data obtained from gas liquefier. In addition, the simulations were performed by an innovative method using experimental data as variable boundary conditions. A comparison was done between presented and conventional methods. The effect of collector mass and convection heat transfer coefficient was also studied using temperature profiles along the heat exchanger. The higher convection heat transfer coefficient in low-pressure gas leads to increase in exchanging energy between two streams and faster cooling of heat exchanger materials, but the higher convection heat transfer coefficient in high-pressure gas does not influence on cool-down process.
Modeling and Simulation
A. Parvareh; . Parvizi
Volume 14, Issue 3 , Summer 2017, , Pages 55-64
Abstract
Abstract In this work, the role of appropriate mixing for mercaptan removal from Kerosene using caustic soda has been investigated in the pilot scale. Static mixer at different condition has been used as a passive mixing tool to achieve proper mixing and consequently high performance of mercaptan removal. ...
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Abstract In this work, the role of appropriate mixing for mercaptan removal from Kerosene using caustic soda has been investigated in the pilot scale. Static mixer at different condition has been used as a passive mixing tool to achieve proper mixing and consequently high performance of mercaptan removal. Two lengths of static mixer including 20 and 40 cm as well as two pitches 1 and 3 mm were considered in a straight line. NaOH was injected to the Kerosene line to remove ( convert it to disulfide) the mercaptan. The effect of mixer length, mixer element pitch at different flow rates of Kerosene, including 2, 18 and 30 mL/s was investigated on the mercaptan removal. The experimental results showed that the concentration of mercaptan in the pilot line outlet will decrease as the flow rates of Kerosene decreases. Also, at a fixed flow rate of Kerosene, increasing the length of the static mixer and decreasing its element pitch caused the mercaptan to decrease due to proper mixing. Computational Fluid Dynamics (CFD) modeling technique was employed to describe the experimental results, fluid flow pattern, and mixing performance. Qualitative predicted results of CFD modeling show a good agreement with the experimental data.
Modeling and Simulation
M.R zeynali; M. Nazari; S. Karimi; S. M. Seyedmohaghegh; S. Soltani
Volume 14, Issue 2 , 2017, , Pages 3-16
Abstract
In this research samples of PVOH were synthesized at various reaction conditions (temperature, time, and amount of catalyst). First at 25˚C and 45˚C and constant catalyst weight samples of PVOH were prepared with different degree of hydrolysis at various times. For investigation of the effects of temperature, ...
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In this research samples of PVOH were synthesized at various reaction conditions (temperature, time, and amount of catalyst). First at 25˚C and 45˚C and constant catalyst weight samples of PVOH were prepared with different degree of hydrolysis at various times. For investigation of the effects of temperature, at times 20 and 40 min and constant weight of catalyst PVOH was prepared at various temperatures. Increasing the time and temperature of the hydrolysis reaction caused increasing degree of hydrolysis and reducing the molecular weight of the samples. Considering the variation of reaction condition, the effects of each parameter on molecular weight, degree of hydrolysis and conversion were investigated individually and also collective. Also, by an artificial neural network method, using experimental results (temperature, time and catalyst amount as input and conversion, degree of hydrolysis and molecular weight as output) a network by Levenberg-Marquardt (LM) back propagation with tan-sigmoid transfer function was established. Finally, the established model presented a good prediction capability and enabled us to predict the output in terms of arbitrary in puts. PVOH is an important polymer and prediction its properties during production significantly improves the quality of the products. Neural network technique is used to model the chemical processes to predict the behavior of the process. In this research we investigated the effects of various processing parameters on the properties of PVOH.
Modeling and Simulation
I. Omidi; M. Kalbasi
Volume 14, Issue 2 , 2017, , Pages 17-32
Abstract
The performance of the solid acid fuel cell by CsH2PO4 electrolyte was analyzed using the present model of the electrochemical reaction and transport phenomena, which are fully coupled with the governing equations. Development of such a model requires creating the three-dimensional geometry and its mesh ...
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The performance of the solid acid fuel cell by CsH2PO4 electrolyte was analyzed using the present model of the electrochemical reaction and transport phenomena, which are fully coupled with the governing equations. Development of such a model requires creating the three-dimensional geometry and its mesh grid, discretization of momentum, mass and electric charge balance equation and solving the equations based on the information of electrical and electrochemical models in different areas of the cell consisting of porous electrodes, gas channels, and the solid parts like the current collector. The model equations were solved employing a finite elements technique solver of cell potential. Different parameters including current density (i), cell potential (V), cell power and concentration distribution of hydrogen, oxygen and water vapor have been investigated in this study. Also, the effect of different voltages on the concentration distribution of all the mentioned species through the cell length are taken into account. Comparing the polarization curve values with the experimental results shows a good agreement between the computed and experimental values (Maximum error is less than 4%). The results showed that there is a noticeable difference between H2, O2 and H2O concentration through the cell length subjected to various voltages. This difference was more apparent at lower voltages due to higher current density and higher consumption of species. The polarization curve is well consistent with the model and experimental data which verify the present simulation results.
Modeling and Simulation
E. Pashai; M. R. Dehghani; F. Feyzi
Volume 14, Issue 2 , 2017, , Pages 33-47
Abstract
Varnish and sludge formation are considered as one of the most common problems in lubrication and hydraulic systems. In order to simulate the condition of sludge formation, base stock lubricant (Group 1 API) has been selected and exposed to heat in a laboratory setup. Sludge formation process accelerated ...
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Varnish and sludge formation are considered as one of the most common problems in lubrication and hydraulic systems. In order to simulate the condition of sludge formation, base stock lubricant (Group 1 API) has been selected and exposed to heat in a laboratory setup. Sludge formation process accelerated in the laboratory scale and solid liquid equilibrium data were extracted. Then solid-liquid equilibrium has been modeled using SAFT equation of state through sludge formation. The results for prediction of sludge formation showed that the absolute average deviations between experimental and theoretical results were less than 1.4%. The calculated results for solubility coefficient of the oxidation byproducts from SN100 (solvent neutral Group I) base stock in fresh (un-oxidized) oil were in good agreement with the experimental data, and average deviation between calculated and experimental data was less than 6.5%. The amount obtained for binary interaction parameter K_ij was – 0.0447. It is shown that SAFT equation of state has the capability of solid liquid equilibrium.
Modeling and Simulation
A. Saberimoghaddam; M. M Bahri Rasht Abadi
Volume 14, Issue 1 , Winter 2017, , Pages 15-25
Abstract
Longitudinal heat conduction is an important parameter in the cryogenic field, especially in cryogenic heat exchangers. In the present work, the parasitic effect of tube wall longitudinal heat conduction on temperature measurement has been studied in cryogenic laminar hydrogen flow. The effects of various ...
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Longitudinal heat conduction is an important parameter in the cryogenic field, especially in cryogenic heat exchangers. In the present work, the parasitic effect of tube wall longitudinal heat conduction on temperature measurement has been studied in cryogenic laminar hydrogen flow. The effects of various parameters such as wall cold end temperature, wall thermal conductivity, gas volumetric flow, and tube wall thickness have been investigated by finite element method. The model was also validated versus the data obtained from experiments. The simulations showed that the temperature decrease in gas flow occurs in the end section of tube length. This section is independent of tube cold end temperature and causes for large temperature measurement error in laminar flows. Results showed that a few millimeters change in temperature sensor position results in measurement errors up to 80 %. The higher tube wall thermal conductivity and tube wall thickness result in higher parasitic effects of longitudinal heat conduction.
Transport Phenomena,
T. Zarei; J. Khorshidi
Volume 14, Issue 1 , Winter 2017, , Pages 40-51
Abstract
This paper addresses an experimental investigation in the hydrodynamic behavior of a modified slotted sieve tray. Slotted sieve tray (Push valve sieve tray) is a sieve tray that the push valves have been utilized on the tray deck to eliminate liquid gradients and non-uniformity of liquid distribution ...
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This paper addresses an experimental investigation in the hydrodynamic behavior of a modified slotted sieve tray. Slotted sieve tray (Push valve sieve tray) is a sieve tray that the push valves have been utilized on the tray deck to eliminate liquid gradients and non-uniformity of liquid distribution on the tray. The air-water system was used in an industrial scale experimental rig with an internal diameter of 1.2 m. The dry pressure drop, total pressure drop, weeping and entrainment of the modified slotted sieve tray were measured and compared with the conventional sieve tray. Weeping and pressure drop data for the tray was correlated. Results show the better hydrodynamic behavior of the modified push valve sieve tray than a conventional sieve tray. This modification can be an effective and inexpensive way to debottleneck sieve tray columns, because it has good characteristic of sieve tray and eliminate the disadvantage of sieve tray by increasing the operating window of the tray.
Modeling and Simulation
mohsen pirdashti; kamyar movagharnejad; silvia Curteanu; Florin Leon; Farshad Rahimpour
Volume 13, Issue 4 , Autumn 2016, , Pages 14-32
Abstract
Guanidine hydrochloride has been widely used in the initial recovery steps of active protein from the inclusion bodies in aqueous two-phase system (ATPS). The knowledge of the guanidine hydrochloride effects on the liquid-liquid equilibrium (LLE) phase diagram behavior is still inadequate and no comprehensive ...
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Guanidine hydrochloride has been widely used in the initial recovery steps of active protein from the inclusion bodies in aqueous two-phase system (ATPS). The knowledge of the guanidine hydrochloride effects on the liquid-liquid equilibrium (LLE) phase diagram behavior is still inadequate and no comprehensive theory exists for the prediction of the experimental trends. Therefore the effect the guanidine hydrochloride on the phase behavior of PEG4000+ potassium phosphate+ water system at different guanidine hydrochloride concentrations and pH was investigated in this study. To fill the theoretical gaps, the typical of support vector machines was applied to the k-nearest neighbor method in order to develop a regression model to predict the LLE equilibrium of guanidine hydrochloride in the above mentioned system. Its advantage is its simplicity and good performance, with the disadvantage of an increase the execution time. The results of our method are quite promising: they were clearly better than those obtained by well-established methods such as Support Vector Machines, k-Nearest Neighbour and Random Forest. It is shown that the obtained results are more adequate than those provided by other common machine learning algorithms.