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Moghadassi A.R.,Arak University | Amini N.,Arak University | Fadavi O.,Arak Petrochemical Company | Bahmani M.,Kharazmi University
Petroleum Science and Technology | Year: 2011

The authors investigated the kinetic modeling of heavy fraction hydrocracking based on the discrete lumping approach. For this kinetic model, the authors considered a parallel reaction scheme to describe the conversion of feed into products (gases, gasoline, and diesel) advanced by D. I. Orochko and I. Khimiya (1970). The different industrial data sets were analyzed statistically. Then product distribution and kinetic parameters were fine-tuned using available industrial data. An optimization code in Matlab software was written to fine-tune these parameters. The model ability in prediction of product distribution was tested for other industrial data, and the authors found good agreement between the model predictions and these data. © 2011 Copyright Taylor and Francis Group, LLC.

Ramezani M.,Islamic Azad University of Arak | Davoodi A.,Islamic Azad University of Arak | Malekizad A.,Arak Petrochemical Company | Hosseinpour-Mashkani S.M.,Islamic Azad University of Arak
Journal of Materials Science: Materials in Electronics | Year: 2015

A novel modified sol–gel method was used in order to synthesize of Fe2TiO5 nanoparticles with aid of Fe(NO3)3·9H2O and Ti(OC3H7)4 as the starting reagents in the presence of ethanol as the solvent. To the best of author knowledge, it is first time that oxalic acid was used as a chilate agent in produce Fe2TiO5 nanoparticles. Besides, to examine the effect of different surfactants such as oleic acid, oleylamine, sodium dodecyl sulfate and cetyltrimethylammonium bromide on the particle size of final products several tests were performed. The as-synthesized Fe2TiO5 nanoparticle was utilized as photocatalyst for decolorisation of Rhodamine-B (RhB) and Methylen blue (MB) to investigate its light harvesting application. The photocatalyst results reveal that the maximum decolorization of 93 and 95 % for RhB and MB occurred with Fe2TiO5 nanoparticle catalyst in 40 min of reaction time under ultraviolet light irradiation, respectively. © 2015, Springer Science+Business Media New York.

Nazari M.,Petroleum University of Technology of Iran | Behbahani R.M.,Petroleum University of Technology of Iran | Goshtasbi A.,Arak Petrochemical Company
Energy Sources, Part A: Recovery, Utilization and Environmental Effects | Year: 2014

The effects of three key parameters of feed temperature, pressure, and flow rate were investigated on the catalytic reaction of methanol dehydration to dimethyl ether in a large-scale fixed bed. A one-dimensional mathematical model was employed for development of the optimum design and evaluation of temperature and concentration profiles. The study of the temperature profiles considering the catalyst behavior revealed that a maximum conversion is obtained under the feed temperature range of 523 to 533 K and operating pressures range of 1 to 1.5 Mpa. The inlet temperature was found to be the most major factor controlling the yield and rate of reaction. Also, the Rate-Conversionerature chart was plotted to appraise and determine the optimal reactor volume at operating conditions. © Taylor & Francis.

Movagharnejad K.,Babol Noshirvani University of Technology | Zareei F.,Arak Petrochemical Company | Mehdizadeh B.,National Iranian Oil Company | Salahi S.,Islamic Azad University at Shahrood | Lashkenari M.S.,Amol University of Special Modern Technologies
Petroleum Science and Technology | Year: 2015

Prediction of the surface tension of hydrocarbons is required in many chemical engineering calculations. In this work a robust artificial neural network code has been used in MATLAB software (The MathWorks, Natick, MA) to predict the surface tension prediction of 61 hydrocarbons. Experimental data is divided into two parts (70% for training and 30% for testing). Optimal configuration of network is obtained with minimization of prediction error on testing data. The accuracy of our proposed model is compared to four well-known empirical equations. Results showed that artificial neural network was more accurate than these empirical equations. Average relative deviation of our artificial neural network model is 0.93 while average relative deviation of the Brock-Bird, Pitzer, Zuo-Stenby, and Sastri-Rao equations are 6.30, 6.48, 5.73, and 6.33, respectively. © 2015 Copyright Taylor & Francis Group, LLC.

Asleshirin S.,Arak University | Bahmani M.,Kharazmi University | Fazlali A.,Arak University | Fadavi O.,Arak Petrochemical Company
Petroleum Science and Technology | Year: 2012

Actual hydrogen plant data consisting of temperatures and partial pressures of inlet and outlet gases of the reformer were collected over a five-year period. Subsequently a one-dimensional pseudohomogeneous reactor model comprising the Langmuir-Hinshelwood-Hougen-Watson reaction kinetic has been developed. Established intrinsic kinetic parameters from literature were used and the effect of intraparticle gradients was accounted for by incorporation of effectiveness factor. The validated model was used to predict the actual plant conversions and temperature profiles in the reformer tube. The steady-state one-dimensional pseudohomogeneous model was then extended to include the temporal variation of heat and mass transfer phenomena and then the dynamic response of the reformer under sudden disturbances in the feed conditions were studied. © 2012 Copyright Taylor and Francis Group, LLC.

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