فهرست مطالب

Chemical Engineering - Volume:16 Issue: 2, Spring 2019

Iranian journal of chemical engineering
Volume:16 Issue: 2, Spring 2019

  • تاریخ انتشار: 1398/03/11
  • تعداد عناوین: 7
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  • M.R Omidkhah *, H. Azami, L. Ghaheri Pages 3-13
    Nowadays, forward osmosis (FO) with many advantages in water treatment, are so attractive for researchers and investigators that the studies are going to optimize and increase its efficiency. However one of the most controversial operating malfunctions of FO process is fouling that limits the FO global application. In the following research, vertically aligned carbon nanotube (VACNT) on alumina membrane is introduced with high water permeability and less biofouling potential in forward osmosis for seawater osmotically dilution systems. VACNT membranes were prepared via pyrolysis of polymer into the pores of alumina. The effect of the temperature of pyrolysis process on CNT’s structure are assessed which indicated crystallinity of the CNTs increase in higher pyrolysis temperature of 800 °C. A small scale setup is designed for FO analysis and measurements of biofouling, flux and the effect of osmotic pressure were measured. Furthermore, all analysis were compared with commercial TFC membrane and results demonstrated that VACNT membrane has 40% less biofouling potential and 2 times better flux results.
    Keywords: Forward Osmosis, Membrane, Vertically Aligned Carbon Nanotube, biofouling, Permeate, Draw Solution
  • M. Etebarian, K. Movagharnejad * Pages 14-40
    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.
    Keywords: critical pressure, critical temperature, Artificial Neural Network, Support Vector Machine, binary hydrocarbon mixture, Particle Swarm Optimization
  • M. Rasteh * Pages 41-56
    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.
    Keywords: fluidized bed, CFD Simulation, Multi fluid model, Ternary mixture, Segregation
  • R. Beigzadeh * Pages 57-69
    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.
    Keywords: flat, discontinuous fin, heat transfer, Pressure drop, Computational Fluid Dynamic (CFD), adaptive neuro–fuzzy inference system (ANFIS)
  • H. Sanaeepur *, A. Ebadi Amooghin, A. Kargari, Mohammadreza Omidkhah, A. Fauzi Ismail, S. Ramakrishna Pages 70-94
    A new method is developed to enhance the gas separation properties of mixed matrix membranes (MMMs) by interior modification of an inorganic nano-porous particle. Ship-in-a-bottle (SIB), as a novel synthesis strategy, is considered to encapsulate a polyaza macrocyclic Ag-ligand complex into the zeolite Y, which is resulted in a new host-guest nano-composite. It is consequently incorporated into a glassy polymer matrix to fabricate a novel MMM for CO2 separation. Accordingly, cellulose acetate (CA) with relatively low gas permeability is selected as the membrane polymeric matrix to provide an appropriate opportunity for better tracking the effect of incorporating the new synthesized nano-porous hybrids. The results showed a promising increase in both the CO2 permeability (45.71%) and CO2/N2 selectivity (40.28%) of the prepared MMM over its pristine CA membrane. It can be concluded that the proposed method makes it possible to fabricate novel MMMs with significant intensification in performance of the current MMMs.
    Keywords: Ship-in-a-bottle (SIB), Macrocyclic Ag-ligand complex, Nano-porous hybrid filler, mixed matrix membrane, Gas Separation
  • A. Jafarizad *, H. Hazrati, A.M. Jabbari Pages 95-102
    In this work, for eliminating the (RR1346), considered to be a waste in wastewater from dye industries electrochemical advanced oxidation process has been used. Graphene oxide coated carbon cloth (GO/CC) and Fe3O4 /GO coated carbon cloth (Fe3O4/GO/CC) electrodes has been fabricated by synthesized GO and Fe3O4 nanoparticles. Characteristic properties such as surface morphology as the main reason of utilizing Fe2O3/GO/CC as electrodes has been investigated determined by various instrumental analysis including, Atomic Force Microscopy (AFM), Field Emission Scanning Electron Microscopy (FESEM), Cyclic Voltammetry (CV), Cathodic polarization, and also for investigating the process yield by utilization of mentioned electrodes, UV-vis spectrophotometric analysis has been used to determine dye concentration in sample waste water, after comparing fabricated electrodes removal efficiency in same time intervals, by determining the concentration of RR1346 dye in samples after oxidation process in different time intervals, results indicated better removal efficiency Fe3O4/GO/CC fabricated electrode than the other two electrodes, which this conclusion was proved by AFM,FESEM and UV-vis results.
    Keywords: RR1346, Carbon cloth, graphene oxide, Fe3O4 Nps, Dye removal
  • A. Sinkakarimi, A. Ghadi * Pages 103-118
    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.
    Keywords: Concave blade, Rushton turbine, Power Consumption, Mixing time, Optimum impeller