Iranian Journal of Chemical Engineering (IJChE)

Abstract Maintaining a constant superficial gas velocity (Usg) is the most common criterion for scaling aerated photobioreactors, yet whether it preserves gas–liquid hydrodynamics is rarely tested directly. Euler–Euler CFD was used to characterize two baffled airlift reactors, a 9.7 L laboratory unit and a 106 L scaled-up unit, over Usg = 0.025–0.10 m·s⁻¹, evaluating gas holdup, gas-phase velocity, and the volumetric mass transfer coefficient (kLa) alongside Reynolds number, Froude number, and power input per unit volume (P/V). Across this range, gas holdup rose 2.4–2.6-fold and kLa rose 1.3–1.6-fold in both reactors, but mean gas velocity increased more in the larger unit (1.4-fold vs. 1.1-fold). Extended-range simulations of the large reactor showed continued but progressively less proportional gains. Froude number was not conserved across scales, and P/V remained consistently higher in the larger reactor. These results show that Usg alone is an insufficient scale-up criterion, gas holdup, kLa, Froude number, and P/V should be evaluated jointly.

Abstract Liquid Composite Molding (LCM), particularly the Resin Infusion (RI) process, has become an attractive manufacturing technique for producing lightweight composite vessel hulls with improved structural performance and reduced production costs. Nevertheless, achieving rapid and uniform resin impregnation while preventing dry spots and premature gelation remains a major challenge. This study presents a numerical investigation of the resin flow behavior in the manufacturing of small composite vessel hulls using a two-phase computational fluid dynamics model based on the Level-Set Method. Five resin injection configurations, including cylindrical, fishbone, radial, parallel, and alternating arrangements, were systematically evaluated in terms of the resin flow pattern, filling time, pressure distribution, and gelation behavior. The numerical model was validated against an analytical gelation-time correlation, resulting in the prediction errors of only 2.60% for the cylindrical configuration and 1.35% for the fishbone configuration. Compared with the conventional cylindrical arrangement, the fishbone configuration reduced the gelation time from 127 min to 96 min, corresponding to an improvement of approximately 24%, while achieving complete mold filling before gelation. Among all investigated strategies, the alternating and radial configurations exhibited the shortest filling times of approximately 30 min and 35 min respectively, whereas the parallel configuration required nearly 120 min. Furthermore, the cylindrical configuration filled only about 90% of the mold before gelation. The results demonstrate that optimized inlet configurations significantly improve the resin distribution uniformity, reduce filling time, and enhance manufacturing efficiency, providing practical guidelines for the design and optimization of resin infusion processes for composite marine structures.

Abstract Modern steam turbines employ extended low-pressure blades, subjecting root connections to severe centrifugal and thermal loads. As a result of these loadings, various and severe dynamic stresses are formed in the structure. Understanding this distribution of stresses and conducting studies on it will greatly help determine the lifespan of items and how to manage them. This study evaluates stress and strain distributions in Ti-6Al-4V turbine roots, specifically comparing BLISK and fir-tree designs under operational conditions. Using nonlinear Finite Element Analysis (FEA) and Local Plastic Stress and Strain Analysis (LPSA), peak von Mises stresses were identified as 890.76 MPa for the BLISK and 390.82 MPa for fir-tree roots. Advanced damage frameworks, including the Modified Mohr-Coulomb and Lemaitre's CDM models, are discussed conceptually to identify critical stress triaxiality states, thereby establishing a reliable baseline for subsequent fracture analyses. The findings establish a reliable baseline for fatigue studies, identifying root-blade transition fillets as critical sites for low- cycle fatigue failure. Understanding material behavior under fatigue loading can help in better determining the scope of application and optimizing the design.

Abstract This study employs classical molecular dynamics simulations using the OPLS-AA force field to systematically investigate the influence of the length of alkyl chain on the structural, thermodynamic, and dynamical properties of a homologous series of pyridinium-based ionic liquids (methyl- to pentyl-pyridinium bromide). The main objective is to elucidate how the gradual elongation of the alkyl chain affects intermolecular interactions and ion transport behavior at the molecular level. The model demonstrates good agreement with available experimental density data, confirming its reliability for predicting physicochemical trends in these systems. The results indicate that increasing the length of the alkyl chain weakens electrostatic interactions and enhances free volume, leading to a systematic reduction in density and cohesive energy density. The structural analysis reveals well-defined cation–anion coordination shells, reflecting strong local ionic organization across all systems. The dynamical analysis shows a consistent decrease in the ionic mobility with the elongationof chains, due to stronger van der Waals interactions and steric effects, which in turn reduce diffusion and ionic conductivity. Importantly, the ionic transference numbers calculated from ion mobilities clearly demonstrate that cations contribute more to charge transport than anions in all investigated systems. This cation-dominated transport behavior provides a direct molecular-level explanation for the observed decrease in ionic conductivity by increasing the length of chains.

Abstract The present study numerically investigates the removal of hydrogen sulfide (H₂S) from crude oil using natural gas as a stripping medium in a T-junction microchannel through three-dimensional computational fluid dynamics (CFD) simulations. The microchannel geometry was adapted from a previously reported experimental configuration and further optimized to reduce natural gas consumption and operating temperature. The Volume of Fluid (VOF) model coupled with the SIMPLE algorithm was implemented in ANSYS Fluent to simulate the gas–liquid two-phase flow and evaluate mass transfer characteristics. Simulations were conducted for gas flow rates of 200–1200 mL/min and oil temperatures in the range of 20–40 °C. The results showed that the H₂S removal efficiency increased with crude oil temperature and gas flow rate but decreased with higher oil flow rate. The predicted efficiencies ranged between 65.7% and 77.8%, in close agreement with experimental data (maximum relative error: 5.6%). The cold-stripping configuration achieved high desulfurization performance even at low gas temperatures (about 18 °C) while reducing gas consumption by nearly one-third compared with conventional units. This study proposes validated correlations and optimized operating parameters for efficient desulfurization of sour crude oil using a microchannel-based cold stripping process.

Abstract This study presents a numerical investigation into the influence of the magnet position and its distance from the channel inlet on heat transfer and flow behavior of ferrofluid (FF), including Fe₃O₄/water flowing through a horizontal channel under a constant wall heat flux. Three magnet positions were considered—at the inlet, middle, and outlet of the channel—to identify the best configuration for heat transfer enhancement. Permanent magnets with a remanent magnetic flux density of 0.4 T were modeled. The nanoparticle concentration was 5 Vol.%, and the Reynolds number was 100. The effects of magnet positions on the local magnetic flux density, Kelvin force, streamlines, velocity and temperature distributions, and Nusselt number (Nu) were investigated. The problem was solved by assuming incompressible, laminar, and steady-state flow. The Galerkin weighted residual finite element method was used to solve the governing equations simultaneously. Results revealed that when magnets were positioned at the inlet or outlet, the magnetic field effects were localized and produced minimal impact on the flow and temperature fields. Conversely, when the magnets were located in the middle of the channel, the most substantial magnetic field gradients and Kelvin forces were generated, which created recirculation zones and increased fluid mixing, resulting in a more uniform temperature distribution and a significant enhancement in the local Nu and an average Nu of 5.31. Finally, this study proposes placing the magnet in the middle of the channel as the most effective configuration for enhancing convection heat transfer.

Abstract This study presents a neuro-fuzzy inference system for predicting the pressure loss in coiled flow inverter (CFI) tubes. Computational fluid dynamics (CFD) simulations were conducted to obtain the amounts of the pressure loss across nine distinct configurations of CFI. The neuro-fuzzy model utilized three key input parameters of the Reynolds number (Re), number of 90° bends (N), and tube-to-coil diameter ratio (L/D). Following CFD validation, the dataset was partitioned into training (two-thirds) and testing (one-third) subsets. The model achieved an outstanding mean relative error (MRE) of 0.549%, demonstrating its high predictive accuracy and reliability for the estimation of the pressure loss in coiled flow inverter systems. These results highlight the neuro-fuzzy approach as a suitable tool for optimizing CFI designs in industrial applications. This study ultimately demonstrates how the strategic combination of numerical simulation and machine learning can accelerate development cycles while maintaining rigorous accuracy standards, providing engineers with a powerful tool for system design and optimization. 

Abstract The synthesis of methanol is a key industrial process, but its performance is constrained by equilibrium conversion, heat dissipation, and energy inefficiencies. This study simulated the multi-bed adiabatic reactor of the Methanol and Derivatives Complex (CP1Z) located in Arzew, Algeria by Aspen HYSYS. Two reactor models were evaluated: the Equilibrium Reactor (ER), based on Gibbs free energy minimization, and the Plug Flow Reactor (PFR), which incorporates detailed kinetics. Both models were validated against industrial plant data to assess predictive accuracy. The ER model demonstrated better agreement with industrial data, particularly for the concentration of methanol (0.36% deviation), and was therefore selected for process improvement studies. Two modifications were introduced. First, recycling unreacted syngas increased the production of methanol from 613 kmol/h to 1800 kmol/h, a 193% improvement. Second, replacing air coolers with a heat exchanger–steam turbine system enabled the recovery of 1100 kW of electricity without reducing the methanol yield. When both modifications were applied simultaneously, the methanol output rose to 1917 kmol/h (+213%), and electricity generation increased to 1763 kW. The integration of the recycling of syngas and waste heat recovery substantially enhances the conversion efficiency, energy utilization, and sustainability of the production of methanol. Since these modifications require no major hardware changes, they offer a practical and scalable strategy for improving the technical, economic, and environmental performance of existing industrial methanol plants. 

Abstract Centrifugal pumps are extensively employed in mining, petrochemical, and wastewater treatment industries, where handling solid–liquid two-phase flows often results in the erosive wear of internal components. This study investigates slurry-induced erosion in a single-stage centrifugal pump through a three-dimensional CFD model developed in COMSOL Multiphysics. The model integrates Lagrangian particle tracking with an empirical erosion correlation and is validated with experimental data reported in the literature, showing good agreement with an average relative error of below 5%. Parametric simulations were conducted to examine the effects of two key operating parameters: flow rate and particle concentration. The results indicate that at sub-design flow rates, the prolonged particle residence time increases impact frequency, leading to severe localized erosion near the blade leading edges. Conversely, operating at rates close to the design flow rate and up to 1.4 Qd reduces erosion intensity and promotes a more uniform wear distribution. Increasing particle concentration produces a nearly linear rise in the maximum erosion rate—from approximately 3 mm/year at 0.5% to over 22 mm/year at 3%—while also expanding the affected blade area. Moreover, larger particles intensify erosion severity and shift erosion zones toward the downstream blade regions, altering the wear mechanism. Overall, the validated CFD framework provides a robust and predictive tool for evaluating both erosion intensity and spatial distribution in slurry-handling centrifugal pumps. The findings emphasize the importance of optimizing operational parameters and applying wear-resistant materials to enhance pump durability and reduce maintenance costs. 

Abstract This research aims to study the mixing dynamics of granular materials in the Triaxe mixer and compare the effect of operating conditions on the quality of mixing. The discrete element method was used to simulate the mixer and track the motion of particles. The Johnson-Kendall-Robinson model was used for the simulation of the contact of cohesive particles. The results indicate that the most influential parameter on the mixing performance is the rotational speed since raising the rotational speed increases the transferred momentum to the grains. In the specific design of the mixer, the dead zones are reduced, so the fill-level does not have a considerable impact on the homogeneity. Also, the quality of mixing of large particles in this blender is better than the same for smaller particles. The mixer's performance for blending cohesive grains was similar to that for the non-cohesive particles. For both types of solids, the relative standard deviation reached approximately 35% after 70 s. Mixing performances of two sizes of the mixer were compared based on two criteria, the constant impeller speed and constant power per volume of the mixer. The results show that the case of the constant impeller speed can predict the mixing performance of the larger mixer more accurately.

Abstract Liners serve as both a barrier layer and an adhesive, bonding the insulation to the propellant. Plasticizer migration is a frequently observed phenomenon in solid propellants, often leading to detrimental effects on mechanical stability and performance.  Absorbent plasticizer liners have emerged as a next-generation solution, offering both anti-migration properties and adhesive capabilities. In this study, the anti-migration effects of three polyethers, including polyethylene glycol (PEG), polypropylene glycol (PPG), and polytetrahydrofuran (PTHF) as liners in the presence of plasticizers 1,2,4-butanetriol trinitrate (BTTN),  trimethylolethane trinitrate (TMETN), and triethylene glycol dinitrate (TEGDN), were studied using NPT-molecular dynamics simulation (NPT-MD) with the Compass III force field. The binding energy, solubility parameter, and radial distribution function of polyethers containing 20% plasticizers were calculated.  The mixture of PEG and TEGDN exhibited the highest binding energy and compatibility. The solubility parameter reflects the strength of non-bonded intermolecular forces, indicating compatibility. The radial distribution function analysis showed strengthened van der Waals interactions, confirming compatibility. Molecular dynamics simulation results showed that polyethylene glycol is a suitable liner with anti-migration properties in propellants.

Abstract The study examines the operational lifespan and catalytic efficiency of the acetylene hydrogenation reactor at Amirkabir Petrochemical Company in Iran, a critical component in industrial olefin production. Acetylene, an undesirable by-product in olefin synthesis, adversely impacts profitability and polymer product quality. To mitigate these effects, the acetylene concentration in the feed stream must be reduced to below 0.5 ppm through catalytic hydrogenation. However, excessive conversion leads to ethane production, thereby reducing ethylene yield. This research uses a modeling approach, supported by industrial data, to investigate the reactor’s behavior under various conditions. A major focus is placed on the reaction kinetics to optimize operational parameters and minimize ethane production, which is less desirable than ethylene. The analysis includes key variables such as temperature, pressure, and the hydrogen-to-hydrocarbon ratio. Moving average method was used to smoothing 78 operational data in this work. Results showed the average absolute selectivity is less than 10%. Additionally, the study evaluates the role of carbon monoxide (CO) as a selective agent that enhances ethylene yield while reducing operational risks. The results showed that the main conversion takes place in the beginning of the reaction (first 1 m of the bed). Additionally, findings indicate that optimal management of these parameters can greatly improve reaction selectivity and the efficiency of the hydrogenation process. The results provide significant insights for refining practices in acetylene hydrogenation, suggesting strategies for improving product quality and operational efficiency in the petrochemical industry.

Abstract Nowadays, increasing demand for sustainable energy sources has led to a growing interest in using biomass as a renewable feedstock for producing hydrogen and methanol. The main objectives of this study involve simulation and economic analysis and evaluation of synthesis gas, hydrogen, and methanol production processes from various biomass sources using Aspen HYSYS software. Three lignocellulosic sources were waste wood biomass (WWB), thin hardwood chips biomass (THWCB), and almond shells biomass (ASB). In the first part of the simulation, the unrefined synthesis gas was produced through a multi-stage biomass gasification process. The outcomes reveal that the yield and composition of synthesis gas were increased by raising the steam-to-biomass ratio (SBR). Subsequently, an integrated model for hydrogen production from various biomass sources was examined through gasification in the presence of steam and oxygen through a water-gas shift (WGS) reaction and the separation and purification of the produced hydrogen using a pressure swing adsorption (PSA) unit. Finally, the hydrogen produced in the previous step was fed to the methanol synthesis unit. The results of the simulation of the gasification process of various lignocellulosic biomasses showed that the use of WWB, THWCB, and ASB can yield annual hydrogen production of 261,000, 349,344, and 361,656 kg, respectively. Consequently, the economic analyses indicated that hydrogen and methanol production from biomass is associated with significant efficiency and profitability. Furthermore, the comparison of synthesis gases' heating values derived from three biomasses revealed that the highest heating values were generated from ASB, THWCB, and WWB, respectively.

Abstract This study investigated sarin gas dispersion in an indoor environment using transient three-dimensional Computational Fluid Dynamics (CFD) and Artificial Neural Network (ANN) approaches. To achieve this, the CFD model was first verified and validated. Then, random locations in the indoor environment were considered as inlets of airflow with sarin gas, and the dangerous times were calculated using the CFD model. Finally, these results of the CFD model were used as inputs to train the ANN model. The results of this study demonstrated that the present model exhibited strong agreement with experimental data. Also, the results of training the ANN showed that for all sections, the training, validation, and testing data and model results were consistent with a high R-squared value. Moreover, the results of different air inlet locations showed that if the air inlet was placed in the corner sections of the indoor environment, the danger time increased. Additionally, if the air inlet was placed near the open region, the danger time also increased, which is an important result for designing indoor environments.

Abstract In the current research, heat transfer within a pilot scale shell and tube heat exchanger is investigated. The heat exchanger consist of a shell and five copper tubes. Water as the cold stream and Boehmite-water nanofluid as the hot stream passes through the shell and tube side, respectively. The effect of nanofluid concentration (0.35, 0.7, and 1.5 %wt.), volume flowrate of the cold stream (0.6, 3, and 6 L/min), and the inlet temperature of the hot stream (40, 50, 60  were investigated on the overall heat transfer coefficient. Moreover, the computational fluid dynamics (CFD) modeling of heat transfer within the pilot scale was performed to study the hydrodynamics of flow inside the heat exchanger. The experimental results and CFD predictions indicates that as the concentration of the nanofluid increases, the overall heat transfer coefficient will increase. This can be attributed to higher thermal conductivity of nanoparticles and the Brownian motion of the particles in the base fluid. Moreover, when the volume flowrate of the fluid increases, Reynolds number will increase, which cause the convection heat transfer coefficient and consequently the overall heat transfer coefficient to be enhanced. Also, at higher inlet temperature of the hot fluid, higher overall heat transfer coefficient was resulted. The maximum deviation between the overall heat transfer coefficients evaluated base on the CFD predictions and its value based on experimental measurements was 16.7%. This proves the ability of CFD technique in pursuing the experimental data. CFD simulation provide a meaningful knowledge about the hydrodynamics of each stream in the heat exchanger, which help us to optimize the performance of heat exchanger.

Abstract The research on the Research Octane Number (RON) of the Light Naphtha Isomerization (LNI) process has significant implications for the quality of gasoline and RON, which are crucial issues in the refinery. In this study, the isomerization unit in an existing 420,000-barrel-per-day gas condensate refinery was investigated to increase RON and decrease total costs. The research involved selecting equipment (means column) to replace the existing ones in an isomerization unit to improve RON and decrease total costs for specific feedstocks. The Deisopentanizer-Deisohexanizer DIP-DIH isomerization unit was chosen as the base case. Three scenarios were simulated and studied to predict product specifications: Deisopentanizer-Depentanizer DIP-DP, Deisopentanizer-Dehexanizer DIP-DH, and Deisopentanizer-Depentanizer-Deisohexanizer DIP-DP-DH isomerization units. To increase RON and study energy consumption, we designed and simulated these scenarios using Aspen HYSYS V9. The energy consumption of the Heat Exchanger Network (HEN) was analyzed using the Aspen Energy Analyzer. The results show that by replacing the equipment and adding new ones, the RON and total cost were significantly altered. The DIP-DP isomerization unit exhibited a higher multiply flow rate by RON, compared to the base case (DIP-DIH) and other scenarios. The results indicate that the DIP-DP isomerization unit improves RON by 6.6% and the total cost by 7.9%.

Abstract  This study investigates the two-phase flow simulation in a Y-type  micromixer with a circular pit at the junction with a 1.7 MHz ultrasonic (US) transducer. A CFD simulation is conducted on the micromixer under varying fluid flow rates. Initially, the simulation is performed without US waves, and subsequently, the US waves are applied. The influence of US waves on flow behavior, mass transfer coefficient (KLa), and extraction efficiency (E) is assessed and contrasts with the same in the scenario where no ultrasound is applied. The simulation outcomes exhibit strong agreement with the experimental findings of a reliable reference. The findings indicate that the flow pattern for both aqueous and organic phases is parallel within the micromixer when ultrasound is absent.   However, applying the US waves alters the flow pattern and enhances the mixing. Under the US field, the interface between the two phases is completely disrupted and the contact between them increases. It is concluded that applying US waves into the liquid medium enhances turbulence, mixing, and the mass transfer rate inside the micromixer.  The influence of the flow rate of the aqueous phase at different US powers on KLa and E was investigated. The decreasing trend of KLa is observed. The effect of the power of ultrasound (P=3.5, 5.25, and 7W) on KLa and E is investigated and results show that P= 7 W has the more ability to enhance the mass transfer rate. The maximum error that is obtained for KLa is 5.43 %, which shows the high accuracy of the CFD model.

Abstract Most of the reactions that occur in microreactors take place on the surface, so it is important to keep the reactants close to the reactive wall. One effective technique in this field is the single-phase hydrodynamic focusing. However, this method has a drawback: a high percentage of reactants penetrate into the sheath fluid. To address this issue, the concept of the two-phase hydrodynamic focusing is introduced in this study. The main idea is to use a highly viscous sheath fluid to create a barrier against reactant penetration into the sheath flow. To demonstrate the effectiveness of this method, a 3D numerical simulation was performed with an irreversible second-order reaction. The results show that the two-phase hydrodynamic focusing increases reaction rates, particularly in downstream regions where the Sherwood number can increase by several orders of magnitude with the use of a highly viscous sheath of liquids. Additionally, it was observed that the use of the two-phase hydrodynamic focusing improves the efficiency, which is defined as the ratio of the solute in the sample flow to the total solute in each cross-section..

Abstract Time-consuming and costly experiments to measure the cetane number (CN) of biodiesel make computations even more valuable. In the current study, two artificial intelligence (AI) models have been used to predict the biodiesel CN by using comprehensive datasets (440 datasets). They were the gradient-based artificial neural network (GB-ANN) and the multi-layer-perceptron ANN optimized by the genetic algorithm (GA-ANN) for the first time. The three input variablesof the model for predicting the target variable of the biodiesel CN are the average number of carbon atoms, average number of double bonds, and average molecular weight of the fatty acid methyl esters. The learning function, transfer function, number of hidden layers, and number of neurons in the hidden layers are some of the optimized parameters in the current AI-models. The developed models were compared using statistical criteria such as the coefficient of determination (R²), mean square error (MSE), average absolute relative deviation (AARD), standard deviation (STD) and mean absolute percentage error (MAPE). The resulting outcomes revealed that the highest R² and the lowest MSE were related to the GB-ANN model with two hidden layers, trainbfg learning method and logsig-tansig-purelin transfer function. The R² and MSE for the optimized model are equal to 0.9296 and 0.0005 respectively. Although the GA-ANN achieved acceptable outcomes, its statistical analyses produced weaker outcomes than the AI-model based on GB-ANN.

Abstract In this paper, modeling approaches were given for explaining mass transfer during solid-liquid extraction in continuous fixed, expanded, and fluidized-bed extractors. The first approach utilizes a differential mass balance-based model, focusing on the differential mass conservation within an element of fixed and expanded-bed columns. The second approach employs a model by applying a mass balance concept to a control volume of the fluidized-bed column. The differential mass balance method segments the column into well-mixed stages, with the fluid flowing axially in an ideal plug flow regime. The solute diffusion inside the porous particles is modeled using Fick's second law of diffusion. Modeling parameters like the effective diffusivity and equilibrium concentration were estimated using the batch extraction experiments. These models were developed and validated using experimental column data involving the extraction of potassium bicarbonate from polyamide 6 pellets with distilled water as the solvent. The modeling results show a good agreement with experimental data.

Abstract Metal-organic frameworks (MOFs) have emerged as extended-network, highly tunable, crystalline hydrogen storage adsorbents. The uptake of H₂ on Zn₄O-based MOFs with different linkers was studied in the current work. The binding energies, consecutive binding energy and step energy of H₂ adsorption on MOF-177, MOF-200 and a newly defined MOF (named NEW-MOF) have been calculated on different possible sorption sites, using DFT/Dmol³/PBE. The linkers have the same benzene ring in center, but different numbers of phenyl rings, including 3, 6 and 9 phenyl rings in MOF-177, MOF-200 and NEW-MOF around the center ring, respectively. Our study results showed that the binding energy of the H₂ molecules with the linker NEW-MOF was -4.165 kcal/mol, more negative than those obtained for MOF-177 (-3.276 kcal/mol) and MOF-200 (-3.438 kcal/mol). The obtained thermo-favorability may be attributed to the less steric hindrance for adsorption of H₂ on the MOF with the larger linker. Step energy results showed that the linkers of MOF-177, MOF-200 and NEW-MOF could adsorb 7, 9 and 12 number of H₂ molecules, respectively. Results also disclosed adsorbed moles of H₂ per 1×1×1 unit cell of the MOFs decreases with increasing the linker length according to the order of 0.263 (for MOF-177), 0.16 (for MOF-200) and 0.137 (for NEW-MOF), mainly due to reduced packing density of the active sites in the MOFs with larger linkers. The most negative binding energy was also tabulated for the perpendicular approaching of H₂ molecules to the node of the central phenyl ring with the bonding distance of 3.19 Å from the linker.

Abstract This research presents the performance of bladeless wind turbines. It also familiarizes readers with the phenomenon of eddy current, which serves as the foundation for bladeless turbines. In this direction, these kinds of bladeless turbines have been designed, modeled, and simulated. Firstly, a two-dimensional vibrational movement of the cylinder with a natural frequency of 2 Hz was modeled at Re = 51000. Additionally, it was noted that the values of the displacement amplitude, and lift coefficient are -0.1-0.1, and -1.5-1.5  respectively. After that, using 2D simulation, the impacts of two different geometries, horizontal and vertical ellipsoids, on displacement amplitude are examined. Investigations were conducted on important factors such as lift coefficients and displacement amplitude, as well as the vortex flow pattern formed behind these shapes. It was discovered that the vertical ellipsoid shape had the maximum values for the height of the displacement amplitude, and lift coefficient. The most important factor influencing the performance of this type of geometry was examined, namely the dimensionless Reynolds number, which ranges from 15000 to 90000. It was determined that the intended geometry exhibited a larger displacement response as the Reynolds number increased.

Abstract In the present study, a new method has been suggested to solve the problems of the very low solubilityof sulfide ores in acidic solution and also the production of toxic impurities for the first time. In this work, the polyoxometalate (POM) oxidizer was applied for the dissolution of sulfide ores, extraction of metals, and removal of toxic and harmful wastes. In this procedure, POMs were used as strong oxidizers of sulfur compounds to dissolve sulfide ores. Also, acid was applied as a solvent and catalyst to increase the reaction rate. The Taguchi experimental design along with the ProMax simulation software was applied for studying the leaching of sulfide ores by POM oxidizers as a novel plan in experimental to industrial scales. The optimum data achieved by the Taguchi method was used as the input data to the simulation and sensitivity analysis of the process was executed by the ProMax software. The effects of curicital operating parameters such as the concentration of acid (C_A) in the 60-90 g/l range, the  reaction temperature (T_R) with the values of 60-90 ºC, the rotation rate (R) with the amounts of 50- 300 rpm, the retention time (τ) in the 0.5-2.0 h range, the concentration of polyoxometalate oxidizer with the values of 0.1- 0.5 g/l, the acid types of H₂SO₄, HNO₃, HCl, H₃PO₄, the grain sizes of sulfide ores (Sparticle) in the 0.5-3.0 mm range and polyoxometalate with the types of [Mo₆O₁₉]^2-, [Mo₈O₂₆]^4-, [V₁₀O₂₈]^6- and [H₂W₁₂O₄₀]^10- on the extraction efficiency of metals and removal of toxic heavy metals from sulfide ores by polyoxometalates were investigated. The optimum conditions to extract maximize metals from the sulfide ores were obtained as the C_A; 80 g/l, T_R; 90 ºC, R; 300 rpm, τ; 1.0 h, m POMs; 0.5g/l, acid type of H₂SO₄, S_grain;1.0 mm and POMs type of [H₂W₁₂O₄₀]^10-. Under optimized conditions, the extraction efficiency of zinc, copper, and lead and the removal of toxic heavy metals from sulfide ores were determined as above 85%, 81%, 83%, and 99.9% receptivity.

Abstract The Ethanol-water separation involves a well-known azeotrope that confines the achievement of the ethanol purity to the values higher than 95 wt% using straightforward distillation. Many attempts have been made to identify how it can be possible to produce ultra-pure ethanol (99.95 wt%) for various valuable applications. In practice, minimizing the total cost of the process is of high importance beside having the finished product with utmost purity. As a consequence, finding the best process conditions imposed to apply the simulation and statistical optimization methods in combination. Numerical optimization provides the best trade-offs to achieve the goals. In this research, the separation of the ethanol/water mixture (87 wt%) was simulated using azeotropic distillation in Aspen plus^© environment. Indeed, cyclohexane was chosen as an effective azeotrope-former. The UNIQUAC equation was used to describe the phase behavior. The two-column arrangement, in which the first column was used to dehydrate ethanol and the second to recover the entrainer, was applied in this simulation. The effect of important process variables, including the number of the trays in columns and the feed-tray position in each tower on the total capital cost were investigated. Finally, the process variables were optimized via the Response Surface Methodology to minimize the total cost of the process. The results uncovered that the total capital cost would be minimized if the number of the trays in the azeotropic (C1) and recovery (C2) columns were set to 34 and 40, whereas, the feed-tray numbers were adjusted to 19 and 9 respectively.

Abstract In this study, the fluid flow together with solid particles has been studied using Computational Fluid Dynamics (CFD). The gas-solid flow (air and sand particles with the size of 150 µm) inside a 76.2 mm diameter pipe with various bend angles including 45, 60, 90, 120, 135, and 180° was modelled at the fluid flow velocity of 11 m/s. The k-ω turbulence model was employed to model the flow turbulence and the E/CRC erosion model have been used to predict erosion rates. The hydrodynamics of the flow, the particles motion as well as the probable erosion regions were predicted. The CFD simulation results showed that increasing the curvature angle increases the erosion rate. While, increasing the pipe diameter, decreases the erosion rate. The maximum erosion rate was predicted at the end part of the curvature for 45 and 60 ° angles, while it was observed in the middle region for 120 and 135 ° curvatures. Finally, the maximum erosion rate for the 180 ° curvature was observed in two regions at the end of the first and second half. Using these results, precautionary considerations for the erosion, and the suitable plans for the repair and maintenance of the equipment can be offered.