Iranian Journal of Chemical Engineering (IJChE)

Abstract Drilling muds are the most applicable fluids in drilling. Two basic types of drilling fluids are used, water based muds (WBM) and oil based muds (OBM). Water based muds are more applicable than oil based muds. One of the most important applications of this fluid is cooling a bit. Chemical engineers try to change drilling mud‘s rheological property in order to increase heat transfer to the bit. Rheological properties of drilling muds are well described by the Herschel Bulkley model. Adding polyacrylic acid to water changes its rheological property to Herschel Bulkley fluid. Standard
equations like Shah and London and Hausen correlations were not able to predict local Nusselt number of non-Newtonian fluids.This study concerns estimating parameters of a local Nusselt number of Herschel Bulkley fluids with CuO nanoparticles in four concentrations of 0.1, 0.3, 0.6 and 0.05% in constant heat flux and laminar region. A
nonlinear optimization algorithm (CMA-ES) was used to estimate local Nusselt number. There is good agreement between experimental data and those predicted by proposed correlations withܴ  ଶ greater than 0.99.

Abstract Secondary breakup of Newtonian droplet into continuous air jet was numerically studied. A coupled Large Eddy Simulation (LES)/ Volume of Fluid (VOF) technique was used in this investigation. Dynamic adaptive mesh was also employed. To this end, the open source CFD package, OpenFOAM, was used to perform the numerical study and was modified to meet the needs of the problem. In order to reduce the error, resulting from the spurious currents, Laplacian smoothing filter was used, which transforms the volume fraction into a smoother volume fraction. This filtering process also helped to obtain a sharp fluid interface. The smoothing has qualitatively and quantitatively improved the simulation results in bag breakup regime. Comparing the results of the RNG k-ε turbulence model and LES model showed the great influence of LES model to improve results. The detailed physics of two different breakup regimes, i.e. bag and multimode (streamer) were investigated. The numerical drop breakup regimes showed appropriate agreement with experimental observation. According to the analogy between the secondary and primary atomization, the outcomes can be used for development of the atomization models.

Abstract By using response surface methodology, Batch shaking biosorption of cobalt (II) experiments were conducted in order to examine the combined effects of operating parameters. The results indicate that magnesium nitrate performed as an effective biosorbent surface modifier, which increases the rate of adsorption capacity. At optimal conditions (initial pH 7.0, temperature 45◦C, biosorbent concentration 0.1 g/100ml, and initial cobalt concentration 300mg/l for Mg-treated biomass) the biosorption capacity of the algae for cobalt was found to be 80.55 mg/g. The Langmuir and Freundlich isotherms were applied to the equilibrium data. The results are best fitted by the Freundlich model. Evaluation of the experimental data in terms of biosorption dynamics showed that the biosorption of cobalt (II) onto algal biomass followed the pseudo-second-order dynamics well. Using the thermodynamic equilibrium coefficients obtained at different temperatures, the thermodynamic parameters (ΔG◦, ΔH◦ and ΔS◦) were also evaluated.

Abstract In this study, forced convection heat transfer of non-Newtonian nanofluids in a horizontal tube with constant wall temperature under turbulent flow conditions was investigated using computational fluid dynamics tools. For this purpose, non-Newtonian nanofluids containing three types of nanoparticles (Al2O 3, TiO 2 and CuO) with carboxymethylcellulose aqueous solution as a liquid single phase with three average particle sizes of 10, 25 and 40 nm nanofluids were investigated. Effects of nanoparticle type and Peclet number on the convective heat transfer coefficient were investigated in fully turbulent region of a horizontal tube. A correlated equation was obtained for Nusselt number using the dimensionless numbers by applying the simulation results. Results showed that the correlated data were in very good agreement with the experimental ones obtained from the literature. The maximum error was 12%.

Abstract In this work, the surface tension (σ ) of aqueous solutions of PEGs (poly ethylene glycol) with molecular weights of 200, 300 and 6000 in water, and poly (propylene glycol) (PPG) with a molecular weight of 2000 in ethanol, were measured in the (293.2-338.2) K temperature range and atmospheric pressure. The results of the measurements were modeled by an Artificial Neural Network(ANN) with input of mass fraction of polymer and solution temperature. The predictions of the artificial neural network model fit the experimental data perfectly.

Abstract Due to wide application of styrene for production of different materials, it is considered as an important product in industry. Therefore, optimizing styrene production conditions is of great importance in petrochemical industry. In this paper, styrene production reactors of Tabriz Petrochemical Complex are modeled using Artificial Neural Network (ANN) model and Adaptive Neuro Fuzzy Inference System (ANFIS). Comparison of two models revealed that the neural networks are more reliable. The process of design and evaluation of models are carried out using industrial data which show credibility of designed models. The neural networks are designed to predict the styrene output from reactors as a function of effective input parameters on the styrene production. Predictions of designed neural networks were used to study the effect of each variable, such as oxygen flow rate and steam oil ratio, on the amount of styrene produced. Also, the optimal values of effective variables for maximum production of styrene were obtained. Furthermore, in order to obtain accurate results, catalyst deactivation of styrene reactors has been modeled using Fuzzy Inference System. As a result, catalyst activity as a function of time is obtained.

Abstract In this study, the Langmuir adsorption isotherm has been coupled with activity coefficient models for prediction of surface tension of single and mixed electrolyte solutions. Various activity models such as Meissner, Pitzer and extended UNIQUAC have been used and coupled with Langmuir adsorption isotherm. The model parameters were determined through mathematical optimization using experimental surface tension data of single electrolyte solutions. Absolute average deviation was used as objective function in optimization procedure. The results showed that in the case of single
electrolyte solutions different activity coefficient models have similar capability while in the case of mixed electrolyte solutions, extended UNIQUAC model gives better results.

Abstract In this work, five different thermodynamic models for correlating the fugacity of water and Tetrahydrofuran (THF) in liquid phase in equilibrium with hydrogen hydrate phase, based on the van der Waals–Platteeuw (vdW-P) statistical thermodynamic model are used and the equilibrium pressures of hydrogen hydrate at different temperatures are calculated. The dissociation pressure of binary hydrogen hydrates is determined by using the Zele–Lee–Holder cavity distortion model. The studied models in liquid phase are NRTL excess Gibbs energy, Peng-Robinson (PR) equation of state (PR EOS), Peng-Robinson-Steryjek-Vera EOS with the Wong-Sandler mixing rule (PRSV-WS), Dashtizadeh EOS (DPTG), and Ghotbi-Vera Simple SAFT (GV-SSAFT) EOS. The results show that the GV-SSAFT model correlates more accurately the experimental dissociation pressure of binary hydrogen hydrate. Additionally, hydrogen storage capacity of binary hydrogen hydrates is calculated.

Abstract In this work a simplified model based on perturbation theory is presented for prediction of activity coefficient of amino acids and electrolytes in aqueous electrolyte solution. In comparison with previous works, in this model a new hard sphere equation of state has been utilized as a reference term while other interactions such as charge-charge, charge-dipole, dipole-dipole and dipole-induced dipole have been considered as perturbation terms. For simplification, solvent has been considered as dielectric continuum. Finally, aqueous electrolyte solutions containing amino acids have been modeled just using two adjustable parameters. The results have been compared with similar models and it is shown that new hard spheres equation of state shows an improvement in accuracy of the model.

Abstract In this work, a dynamic model has been developed for prediction of biofilters performance. The model includes most of the phenomena occurring in a biofilter. For biodegradation of pollutants in the biofilm, the Michaelis-Menten kinetic has been considered. The model equations including gas phase and biofilm partial differential equations were solved simultaneously using finite difference and method of lines. The model parameters were evaluated by sensitivity analysis to determine their respective effects on the model performance. The model predictions were validated by experimental data for mixture of methyl propyl ketone, toluene, p-Xylene and n-Butyl acetate. The simulation results of empty bed  residence times 30, 60, 90 seconds were compared with experimental data. The comparison of results showed the model
predictions had a good agreement with experimental data. The sensitivity analysis of the model parameters showed that Henry's constant and specific area of biofilter had the strongest influence on biofilter performance.

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Abstract The gelling of waxy crudes and the deposition of wax on the inner walls of pipelines present a costly problem in the production and transportation of oil. The object of the present study is to investigate the factors that affect the deposition of the paraffin wax on the pipe surface under different conditions using a flow loop system. A series of experiments on wax deposition from a mixture of waxy oil have been performed in a 65cm by 1cm ID flow loop in both laminar and turbulent flow regime. These experiments were done to study the effect of some important factors on the amount of deposited wax on the pipe wall. These factors consist of flow rate, residence time, wax concentration and temperature difference between mixture and pipe wall. It was found that the wax deposition increases with increasing temperature difference and residence time, but the effect of flow rate depends on flow regime. The other goal is mathematical modeling of wax deposition for a multi-component hydrocarbon mixture. The procedure for generating the model is described in detail. Finally, the results obtained from the model were compared with experimental data. It was found that there is an acceptable match between experimental and theoretical data and to some extent, this confirms the validity of the model and also the ability of the developed model to predict the wax deposition on pipelines under different operational condition.

Abstract In this research, reactive absorption of hydrogen sulfide using diglycolamine solution in an industrial tray column was investigated. A nonequilibrium stage model has been developed based on dynamic film model for modeling of hydrogen sulfide reactive absorption into diglycolamine solution. In the model, simultaneous heat and mass transfer and reactions rate were considered. The model equations including partial and ordinary differential equations were solved numerically using the method of lines technique. The simulation results are presented in steady and unsteady state conditions. An industrial absorption column was employed to obtain the experimental data in both low and high pressure. The model results were evaluated using the steady state experimental data. A comparison of the experimental and simulation results showed that the average of correlation coefficient error for high pressure absorption process is 8.5 percent whereas the average of correlation coefficient error for low pressure absorption process is 7 percent.

Abstract In this study, simulation of cyclic adsorption process for mercaptan removal from natural gas in non-isothermal and non-adiabatic conditions is presented. This process is used in mercaptan removal unit of South Pars Gas Refinery Phase 1. Six adsorption fixed beds used in this plant contain molecular sieve type zeolite 13X. Three beds are in the process for adsorption purposes and the other three beds are being used for regeneration simultaneously. Regeneration cycle involves two steps for heating and one step for cooling. In modeling of this process, linear driving force (LDF) is used for estimation of adsorption rate. For equilibrium relation between solid and gas phases, the extended Langmuir isotherm is used. The energy balance around the gas phase in the bed includes heat transfer to solid as well as axial heat dispersion. The set of partial differential equations is solved using implicit finite difference. Cyclic steady state (CSS) is obtained using cyclic simulation procedure and the variation of concentrations and temperatures along the bed and at different times.
A good agreement was obtained between the simulation results and those obtained from plant operational data. The effect of various operational parameters, such as regeneration steps, temperature and regeneration flow rate on process product was investigated. With increasing the first heating stage temperature, the concentration of water and mercaptan in the bed outlet decreases, but the decrease in mercaptan concentration is more significant. By increasing the second heating stage temperature, the water concentration in the bed outlet decreases significantly.

Abstract Water flooding, the oldest and most common EOR method, increases the displacement efficiency in a reservoir and also maintains the reservoir pressure for a long period of time. In Iran, water injection is widely used as a method to enhance recovery from oil reservoirs. Defining the optimized injection rates and injection patterns, dependent on the geological structure of the reservoir, is essential in operational and economical decisions for reservoir management. In this paper, the Capacitance-Resistive Model is used to find interwell connectivity, and optimized injection rates in a synthetic field. In this approach, the reservoir receives injector rate variations as an input signal, while the producer responses determine the injector/producer pair connectivity quantitatively. This model is used to predict oil production for a specific reservoir, if the production/injection rate and bottomhole pressure data are available. The results show that the Capacitance-
Resistive model has the capability to be used for the production history matching and to optimize the injection rate in different wells of a reservoir during the immiscible flooding to maximize the oil production. Moreover, they show that any change in oil and water prices can significantly influence the optimized water injection rates.

Abstract Stability analysis of miscible displacement has several applications in industries such as oil recovering and ground water tables. In this article an analytical solution is presented based on Tan and Homsy’s results for stability analysis in t = 0. Moreover, a novel semi analytical solution is used, based on weighted residual method, to solve the Fourier space equations. The results are shown as σ (disturbance growth rate) – k (wave number); profiles for different values of mobility ratios and times. A comparison with the results of the other researches is also presented.

Abstract In this study, adsorption data for the case of energetically heterogeneous solid surface are modeled using artificial neural network. A neural network with three hidden neurons, including the bias, was able to predict very accurately the temperature dependency of adsorption data. The results were compared with experimental data (over temperature range 273-313 K and 0-2 MPa pressure) and it was found that the predictions of the artificial neural network model fit the experimental data very accurately.

Abstract Soil bioremediation, especially in the rhizosphere area, is the result of interaction between plant roots and microorganisms. It can be considered as one of the remarkable ways to eliminate pollutants. Various factors control the process with special relationships in the rhizosphere environment; changing each of them can impress on the system destination. With mathematical modeling, behavior of the process can be predicted and controlled, and improved by appropriate changes in the model. In this study, the effects of different parameters of a simple mathematical model, represented to predict microbial growth and necessary substrate changes in the rhizosphere have been studied using numerical finite difference method. Influences of the parameters on biomass and substrate concentrations were evaluated at different times. A number of variables directly, some negatively, and others neutrally impacted on the biomass and substrate concentrations. Investigating variables differently affecting on a model is important since perfectly tuning them can optimize the system performance, and achieve higher efficiency.

Abstract Knowledge of mixing time is of fundamental importance for investigation of mixing efficiency in agitation systems. The mixing time obtained by using the correlation and formula in large scale mixing systems was incorrect. Again, the number of available correlations in this scale of mixing systems is limited. To predict the mixing time of stirred tanks with dual impellers commonly used in industry, a third-compartment mixing model was used. The time of homogenization of the charge (mixing time) was calculated from the time dependency of the local concentration of tracer measured at various locations. Experimental data on mixing time were obtained with a conductivity technique. In the present study distribution of tracer in the bulk of the liquid was described by compartment model (CM) as well as for stirred vessel with dual Rushton impellers. As for the model, a good agreement between the experimental data and the calculated values was apparent.

Abstract Addition of impurities has an important role on the kinetic crystallization. Therefore, influence of impurities on the crystallization kinetics of NaCl, KBr, ADP and Sucrose solutions was investigated in a fluidized bed crystallizer. The growth and dissolution rates were related to the super saturation and impurity concentration. A strong mathematical model is applied to describe crystal growth rates within aqueous solutions as a function of impurity concentration. The model tries to relate the step velocity to the useful parameters such as the surface coverage (θeq), as well as the effectiveness factor of impurity, α. When α>1, the step velocity is stopped at θeq <1 (incomplete coverage of the active sites for adsorption). In the case of α=1, the velocity reaches zero just at θeq=1 (complete coverage) but approaches a limiting value. The value of α is changed by stereo chemical factors and decreases as the supersaturation is increased. The Langmuir adsorption isotherm is used to relate the relative step velocity with the impurity concentration in solution. Experimental results show that increasing the amount of impurity concentration leads to a decrease in the step velocity. Experimental data and model predictions have been compared to show that the agreement between them is very good. The obtained results are suitable for designing and quality control of the crystallization processes in chemical industries.

Abstract In this work, a new thermodynamic model based on the perturbation theory is presented. A new hard spheres equation of state as a reference term is applied to correlate the activity coefficient of amino acids and peptides in binary aqueous
solutions. The new hard sphere equation of state has been recently proposed by Dehghani and Modarress [11] and has been applied for different theories and showed excellent capability. In this model dipole-dipole and Lennard-Jones interactions are considered. The results have been compared with similar models and it is shown that application of the new hard spheres equation of state has caused an improvement in the results of perturbation model.

Abstract Turbulent flow field in a 200 m3 industrial suspension polymerization reactor, which is a baffled agitated vessel, was simulated using CFD. Multi-reference frame (MRF) methods and k-Â turbulence model were used to solve turbulent flow equations. It was found that turbulent flow field in reactor is non-homogenous. This non-homogeneity is especially common among three compartments of a reactor based on turbulent kinetic energy (TKE) dissipation rate. A compartment around the impeller with very high rate of TKE dissipation (impeller zone), a compartment around the baffles with a relatively high rate of TKE dissipation (baffle zone) and a relatively big compartment in bulk of flow with low TKE dissipation rate (circulation flow). Therefore a three-compartment model was used to explain the non-homogeneity of turbulent flow field. The parameters of this model are compartment volume ratios (Ïi and Ïb), compartment energy
dissipation ratios (Îb and Îi) and exchange flow rates (Qi and Qb), which were obtained from simulations for different agitation rates.

Abstract The partial differential equations describing reaction of a trace component in the gas stream in a packed bed of solid reactant or adsorbent are solved by Rayleigh-Ritz finite element method. These equations consist of a PDE along the reactor which is accompanied with semi time dependent diffusion-reaction equation in each pellet. Two gas-solid reaction models have been considered as the reaction rate expression of the pellets in this work. These reaction rates provide nonlinearity in the PDEs of the pellets. Reactions with considerable structural changes such as sulfation of calcined limestone in packed column have been considered too. The finite element method analyzed the PDEs equations, even in the presence of steep gradients associated with nonlinearities along the packed column and the pellets equations.

Abstract Electricity generation in a duel chamber microbial fuel cell (MFC) consisting of graphite anode electrode, platinum cathode electrode and Nafion 117 membrane was investigated. Anaerobic sludge was used as the source of microorganisms in the anode chamber. Acetic acid as the sole carbon source along with other nutrients was added to
the anode chamber in a batch or repeated-batch modes. System curves and polarization curves were obtained in different operational conditions and the internal resistance of the system was calculated. Electricity generation by MFC in both batch and repeated-batch modes was modeled using a biofilm based hypothesis and the results were compared with experimental data.