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Showing 4 results for Azizi

A. Azizi, S. Z. Shafaei, M. Noaparast, M. Karamoozian,
Volume 10, Issue 4 (december 2013)

This paper was aimed to address the modeling and optimization of factors affecting the corrosive wear of low alloy and high carbon chromium steel balls. Response surface methodology, central composite design (CCD) was employed to assess the main and interactive effects of the parameters and also to model and minimize the corrosive wear of the steels. The second-order polynomial regression model was proposed for relationship between the corrosion rates and relevant investigated parameters. Model fitted to results indicated that the linear effects of all of factors, interactive effect of pH and grinding time and the quadratic effects of pH and balls charge weight, were statistically significant in corrosive wear of low alloy steel balls. The significant parameters in the corrosive wear of high carbon chromium steel balls were the linear effects of all factors, the interactions effect of solid concentration, mill speed, mill throughout, grinding time, and the quadratic effects of pH and solid content. Also, the results showed that within the range of parameters studied, the corrosion rate of 78.38 and 40.76 could be obtained for low alloy and high carbon chromium steel balls, respectively.
M. Azizi, M. Soltanieh,
Volume 11, Issue 3 (september 2014)

In the present research, to form niobium carbide coating on the surface of AISI L2 steel Thermo-Reactive Deposition method (TRD) in a molten bath was used. Niobium carbide coating treatment was carried out at 1173 K, 1273 K, and 1373 K for 2, 4, and 8 hours. The molten bath contained 20wt.% borax (Na2B4O7), 5 wt.% boric acid (B2O3), and 75 wt.% ferro-niobium. The presence and properties of the coated layer were studied by means of Optical Microscopy (OM), Scanning Electron Microscopy (SEM), and X-Ray Diffraction (XRD) analysis. The thickness of coating ranged between 6.6 µm to 33µm depending on treatment time, and temperature. The effects of treatment time and temperature on the coating thickness were studied. Kinetic study of the formation of NbC coating showed that growth of the coating is under the control of diffusion. The activation energy of the process was estimated to be 122 kJ/mol. A practical formula to estimate the coating thickness was suggested.
A. Azizi, S.z. Shafaei, R. Rooki,
Volume 13, Issue 2 (June 2016)

Nowadays steel balls wear is a major problem in mineral processing industries and forms a significant part of the grinding cost. Different factors are effective on balls wear. It is needed to find models which are capable to estimate wear rate from these factors. In this paper a back propagation neural network (BPNN) and multiple linear regression (MLR) method have been used to predict wear rate of steel balls using some significant parameters including, pH, solid content, throughout of grinding circuit, speed of mill, charge weight of balls and grinding time. The comparison between the predicted wear rates and the measured data resulted in the correlation coefficients (R), 0.977 and 0.955 for training and test data using BPNN model. However, the R values were 0.936 and 0.969 for training and test data by MLR method. In addition, the average absolute percent relative error (AAPE) obtained 2.79 and 4.18 for train and test data in BPNN model, respectively. Finally, Analysis of the predictions shows that the BPNN and MLR methods could be used with good engineering accuracy to directly predict the wear rate of steel balls.


R. Katal, A. Azizi, M. Gharabaghi,
Volume 17, Issue 2 (June 2020)

Present paper investigates the dissolution behavior of copper from chalcopyrite concentrate sample using cupric chloride solution in detail. Response surface modeling (RSM) in combination with d-optimal design (DOD) was utilized for modeling and optimizing the cupric chloride leaching process. At first, a quadratic polynomial model was developed for the relationship between the recovery of copper and influential factors. The predictions indicated an excellent agreement with the experimental data (with R2 of 0.9399). Then, the effects of main factors including pH (1-4), liquid/solid ratio (2-7 mL/g), temperature (70-90 °C), CuCl2 concentration (6-35 g/L), and leaching time (0.5-16) were determined. The findings demonstrated that the temperature and CuCl2 concentration were the most effective factors on the dissolution rate of copper from chalcopyrite sample, while liquid/solid ratio had the lowest impact. The recovery of copper increased linearly with an increment in the liquid/solid ratio and the decrease in the pulp pH. Additionally, the recovery enhanced by increasing the temperature and CuCl2 concentration owing the generation of Cu–Cl complexes species and reached a plateau point and then almost remained unchanged. Meanwhile, it was found out that the recovery of copper was independent of the interaction between factors. Moreover, the optimization of leaching process was carried out by Design Expert (version 7) software and desirability function method and the highest recovery of copper was found to be about 86.1% at a pH of ~1.4, temperature of 89 °C, liquid/solid ratio of 6.8 mL/g, CuCl2 concentration of 21.79 g/L and leaching time of ~8 h.

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