Islamic Azad University at Gachsaran
Do Gonbadan, Iran
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Ghaedi A.M.,Islamic Azad University at Gachsaran | Vafaei A.,Islamic Azad University at Gachsaran
Advances in Colloid and Interface Science | Year: 2017

Artificial neural networks (ANNs) have been widely applied for the prediction of dye adsorption during the last decade. In this paper, the applications of ANN methods, namely multilayer feedforward neural networks (MLFNN), support vector machine (SVM), and adaptive neuro fuzzy inference system (ANFIS) for adsorption of dyes are reviewed. The reported researches on adsorption of dyes are classified into four major categories, such as (i) MLFNN, (ii) ANFIS, (iii) SVM and (iv) hybrid with genetic algorithm (GA) and particle swarm optimization (PSO). Most of these papers are discussed. The further research needs in this field are suggested. These ANNs models are obtaining popularity as approaches, which can be successfully employed for the adsorption of dyes with acceptable accuracy. © 2017.

Mohammadi S.,Islamic Azad University at Gachsaran | Soleymani S.,Islamic Azad University at Tehran | Mozafari B.,Islamic Azad University at Tehran
International Journal of Electrical Power and Energy Systems | Year: 2014

In this paper, an efficient stochastic framework is proposed to investigate the effect of uncertainty on the optimal operation management of MicroGrids (MGs). The proposed stochastic framework would concurrently consider the uncertainties of load forecast error, Wind Turbine (WT) generation, Photovoltaic (PV) generation and market price. The proposed stochastic method consists of two main phases. In the first phase, by the use of Probability Distribution Function (PDF) of each uncertain variable and roulette wheel mechanism, several scenarios are generated. Now by the use of scenario reduction process, the most probable and dissimilar scenarios are selected. By means of this strategy, the stochastic problem is converted to a number of deterministic problems with different probabilities. In this regard, the Weibull and normal PDFs are utilized to model the stochastic random variables. In the second phase, a new optimization strategy based on Adaptive Modified Firefly Algorithm (AMFA) is employed to solve each of the deterministic problems generated in the first phase. The stochastic optimization problem is investigated while meeting different equality and equality constraints. In order to see the efficiency and satisfying performance of the proposed method, a typical grid-connected MG including WT/PV/Micro-Turbine/Fuel Cell and Energy Storage Devices is studied as the test system. © 2013 Elsevier Ltd. All rights reserved.

Ghaedi M.,Yasouj University | Sharifpour E.,Islamic Azad University at Gachsaran
Desalination and Water Treatment | Year: 2012

A new selective solid phase extractor was prepared based on modification of silica gel with 2-((3silylpropylimino) methyl)-2-hydroxy-1-naphthol (SPIMHN). The solid phase extractor is stable in 6 mol/L HCl, common organic solvents, and buffer solutions at pH 2.0-8.0. This new sorbent was successfully applied for the enrichment of trace amount of Fe3+, Pb2+, Cu2+, Ni2+, Co2+, and Zn2+ ions subsequent their determination by flame atomic absorption spectrometry. The influences of the analytical parameters including pH, ratio of aminopropylsily late to 2-hydroxy-1-naphthaldehyde and amount of solid phase, sample flow rate, eluent solution conditions (type, concentration, and volume), and sample volume on the metal ions recoveries were investigated. The method has high sorption-preconcentration efficiency even in the presence of various interfering ions (recoveries between 98 and 99.4 and detection limits in the range of 1.3-2.8). The proposed method is applicable for understudied analytes with recoveries more than 95% and relative standard deviation < 4.2%, especially for real sample analysis. © 2012 Desalination Publications. All rights reserved.

Mansourizadeh A.,Islamic Azad University at Gachsaran | Mansourizadeh A.,University of Technology Malaysia | Ismail A.F.,University of Technology Malaysia
International Journal of Greenhouse Gas Control | Year: 2011

Carbon dioxide (CO2), the main greenhouse gas, has been associated with global climate change. Therefore, it is important to develop technologies to mitigate this issue. In present study, porous hydrophobic polyvinylidene fluoride (PVDF) hollow fiber membranes with developed structure for CO2 absorption were prepared via a wet spinning process. The prepared membranes were characterized in terms of morphology examination, gas permeability, critical water entry pressure (CEPw) and mass transfer resistance. From the morphology examination, the membrane showed an almost sponge-like structure with inner skinless layer and ultra-thin outer skin layer. Results of gas permeation test indicated that the membrane possess very small mean pore size (3.96nm) with high surface porosity. The CO2 absorption experiment demonstrated a significant improvement in the CO2 flux of the prepared PVDF membrane compared to the commercial porous polytetrafluoroethylene (PTFE) hollow fiber membrane. At the absorbent flow rate of 200ml/min, CO2 flux of the PVDF membrane (4.10×10-4mol/m2s) was approximately 68% higher than the CO2 flux of the PTFE membrane. In addition, the results indicated that an approximate 25% CO2 flux reduction was gradually occurred at initial 26h, then the CO2 flux maintained constant over 140h of the operation. © 2010 Elsevier Ltd.

Mansourizadeh A.,Islamic Azad University at Gachsaran | Mansourizadeh A.,University of Technology Malaysia | Ismail A.F.,University of Technology Malaysia
Desalination | Year: 2012

Wetting resistance and gas permeability are the main factors for membrane contactor applications, which can be optimized according to the membrane morphology. In present study, three different types of the membrane morphology were obtained via a dry-wet spinning technique. By measuring cloud point data and viscosity, the polymer dope composition was adjusted to produce the different morphologies. The membranes with large finger-like, small finger-like and almost sponge-like morphology were obtained. The plain PVDF membrane with large finger-likes morphology presented the higher N 2 permeance, lower wetting pressure and larger mean pore size (0.08μm). By addition of phosphoric acid into the spinning dope, the prepared sponge-like morphology resulted in the high surface porosity with small pore sizes, which demonstrated good permeability and wetting pressure. It was found that the mean pore size measured by gas permeation method was approximately three times larger than those from FESEM examination. CO 2 stripping from water was conducted through the gas-liquid membrane contactors. The membranes with smaller pore sizes and higher wetting pressure presented higher stripping performance. In conclusion, a structurally developed PVDF hollow fiber membrane for gas-liquid contactor applications can be achieved by controlling the membrane morphology. © 2011 Elsevier B.V.

Mansourizadeh A.,Islamic Azad University at Gachsaran
Chemical Engineering Research and Design | Year: 2012

Gas-liquid hollow fiber membrane contactor can be a promising alternative for the CO 2 absorption/stripping due to the advantages over traditional contacting devices. In this study, the structurally developed hydrophobic polyvinylidene fluoride (PVDF) hollow fiber membranes were prepared via a wet spinning method. The membranes were characterized in terms of morphology, permeability, wetting resistance, overall porosity and mass transfer resistance. From the morphology analysis, the membranes demonstrated a thin outer finger-like layer with ultra thin skin and a thick inner sponge-like layer without skin. The characterization results indicated that the membranes possess a mean pore size of 9.6nm with high permeability and wetting resistance and low mass transfer resistance (1.2×10 4s/m). Physical CO 2 absorption/stripping were conducted through the fabricated gas-liquid membrane contactor modules, where distilled water was used as the liquid absorbent. The liquid phase resistance was dominant due to significant change in the absorption/stripping flux with the liquid velocity. The CO 2 absorption flux was approximately 10 times higher than the CO 2 stripping flux at the same operating condition due to high solubility of CO 2 in water as confirmed with the effect of liquid phase pressure and temperature on the absorption/stripping flux. © 2011 The Institution of Chemical Engineers.

Khodabakhshi S.,Islamic Azad University at Gachsaran | Karami B.,Islamic Azad University at Gachsaran
Catalysis Science and Technology | Year: 2012

A novel silica tungstic acid (STA) as a green catalyst has been prepared and employed for the solvent-free synthesis of novel benzopyrazines. Catalyst loadings as low as 2 mol% could be used leading to high yields of pure products. The STA was characterized by X-ray fluorescence (XRF), X-ray diffraction (XRD), inductively coupled plasma (ICP-OES) and Fourier transform infrared spectroscopy (FT-IR). © 2012 The Royal Society of Chemistry.

Asoodeh M.,Petroleum University of Technology of Iran | Bagheripour P.,Islamic Azad University at Gachsaran
Rock Mechanics and Rock Engineering | Year: 2012

Measurement of compressional, shear, and Stoneley wave velocities, carried out by dipole sonic imager (DSI) logs, provides invaluable data in geophysical interpretation, geomechanical studies and hydrocarbon reservoir characterization. The presented study proposes an improved methodology for making a quantitative formulation between conventional well logs and sonic wave velocities. First, sonic wave velocities were predicted from conventional well logs using artificial neural network, fuzzy logic, and neuro-fuzzy algorithms. Subsequently, a committee machine with intelligent systems was constructed by virtue of hybrid genetic algorithm-pattern search technique while outputs of artificial neural network, fuzzy logic and neuro-fuzzy models were used as inputs of the committee machine. It is capable of improving the accuracy of final prediction through integrating the outputs of aforementioned intelligent systems. The hybrid genetic algorithm-pattern search tool, embodied in the structure of committee machine, assigns a weight factor to each individual intelligent system, indicating its involvement in overall prediction of DSI parameters. This methodology was implemented in Asmari formation, which is the major carbonate reservoir rock of Iranian oil field. A group of 1,640 data points was used to construct the intelligent model, and a group of 800 data points was employed to assess the reliability of the proposed model. The results showed that the committee machine with intelligent systems performed more effectively compared with individual intelligent systems performing alone. © 2011 Springer-Verlag.

Bagheripour P.,Islamic Azad University at Gachsaran
Journal of Applied Geophysics | Year: 2014

Quantitative formulation between conventional well log data and rock permeability, undoubtedly the most critical parameter of hydrocarbon reservoir, could be a potent tool for solving problems associated with almost all tasks involved in petroleum engineering. The present study proposes a novel approach in charge of the quest for high-accuracy method of permeability prediction. At the first stage, overlapping of conventional well log data (inputs) was eliminated by means of principal component analysis (PCA). Subsequently, rock permeability was predicted from extracted PCs using multi-layer perceptron (MLP), radial basis function (RBF), and generalized regression neural network (GRNN). Eventually, a committee neural network (CNN) was constructed by virtue of genetic algorithm (GA) to enhance the precision of ultimate permeability prediction. The values of rock permeability, derived from the MPL, RBF, and GRNN models, were used as inputs of CNN. The proposed CNN combines results of different ANNs to reap beneficial advantages of all models and consequently producing more accurate estimations. The GA, embedded in the structure of the CNN assigns a weight factor to each ANN which shows relative involvement of each ANN in overall prediction of rock permeability from PCs of conventional well logs. The proposed methodology was applied in Kangan and Dalan Formations, which are the major carbonate reservoir rocks of South Pars Gas Field-Iran. A group of 350 data points was used to establish the CNN model, and a group of 245 data points was employed to assess the reliability of constructed CNN model. Results showed that the CNN method performed better than individual intelligent systems performing alone. © 2014 Elsevier B.V.

Mansourizadeh A.,Islamic Azad University at Gachsaran | Pouranfard A.-R.,Islamic Azad University at Gachsaran
Chemical Engineering Research and Design | Year: 2014

In order to develop the structure of microporous PVDF membranes, PEG-400 was introduced into the polymer dope as a non-solvent additive. The hollow fiber membranes were prepared via a wet phase-inversion process and then used in the membrane contactor modules for CO2 stripping from water. By addition of different amounts of PEG-400, cloud points of the polymer dope were obtained to examine phase-inversion behavior. From FESEM analysis, the membrane structure changed from a finger-like to an approximately sponge-like morphology with the addition of 4wt.% of PEG-400. The prepared membranes presented smaller mean pore size (0.13μm) and significantly higher wetting pressure (550kPa) compared to the plain membrane. From CO2 stripping test, at water velocity of 0.4m/s, the PVDF membranes prepared by 4% PEG-400 demonstrated an approximate CO2 stripping flux of 4.5×10-5(mol/m2s) which is 125% higher than the flux of the plain membrane. It could be concluded that structurally developed hydrophobic PVDF hollow fiber membranes can be prepared by a controlled phase-inversion process to enhance the performance of gas-liquid membrane contactor. © 2013 The Institution of Chemical Engineers.

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