Model development for prediction of autogenous mill power consumption in Sangan iron ore processing plant

The variables including ore hardness based on the SAG power index (SPI), particle size of mill product (P80), trunnion pressure of the mill free head (p) and working time period of mill liner (H) were considered as variables for development of an adequate model for the prediction of autogenous (AG) mill power consumption in Sangan iron ore processing plant. The one-parameter models (SPI as variable) showed no adequate precision for the prediction of Sangan AG mill power consumption. Two-parameter models (SPI and P80 as variables), proposed by Starkey and Dobby, showed no adequate precision for the Sangan AG mill power consumption. Nonetheless, by exerting an adjustment factor in the model (0.604513 which obtained by what-if analysis using Solver Add-Ins program), the model precision increased significantly (an error of 7.11%). Finally, a four-parameter model in which the Sangan AG mill power consumption is predicated as a function of SPI, P80, p, and H was developed. Hence, initially the relationship between the mill power consumption and each of the variables was obtained and then the four-parameter model was developed by summation of these four equations and applying a similar coefficient of 0.25 for all of them. This model was modified through finding the best coefficients by what-if analysis using solver Add-Ins program through minimizing the ARE error function. The error function for the training and testing data sets was determined to be 2.93% and 2.39%, respectively

Application of adaptive neuro-fuzzy inference system for prediction of dissolved oxygen concentration in the gold cyanide leaching process

An adaptive neuro-fuzzy inference system (ANFIS) model has been developed for the prediction of the dissolved oxygen concentration (DOC) as a function of the solution temperature (0-40oC), salinity based on conductivity (0-59000 µS/cm), and atmospheric pressure (600-795 mmHg). The data set was randomly divided into two parts, training and testing sets. 80% of the data points (80% = 11556 datasets) were utilized for training the model and the remainder data points (20% =2889 datasets) were utilized for its testing. Several indices of performance such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of correlation (R) were used for checking the accuracy of data modeling. ANFIS models for the prediction of DOC were constructed with various types of membership functions (MFs). The model with the generalized bell MF had the best performance among all of the given models. The results indicate that ANFIS is a powerful tool for the accurate prediction of DOC in the gold cyanidation tanks

Incorporation of SiC ceramic nanoparticles into the aluminum matrix by a novel method: production of a metal matrix composite

SiC ceramic nanoparticles were incorporated into the A356 aluminum matrix with different compositions using a combination of stir casting and semisolid extrusion. The microstructure and mechanical properties of the produced nanocomposites were evaluated. The results showed that the presence of Nickel acts as an appropriate metallic carrier for SiC nanoparticles, which causes uniform dispersion and spherical grains. Consequently, the coexistence of SiC nanoparticles and Nickel resulted in UTS of above 304 MPa and elongation of 5.8%. However, the addition of Titanium caused the formation of flake-like intermetallics, which decreased the elongation of the nanocomposites. The method introduced in this study for the incorporation of SiC ceramic nanoparticles can be used as a promising process instead of conventional methods, which are expensive and time-consuming

Estimation of coal proximate analysis factors and calorific value by multivariable regression method and adaptive neuro-fuzzy inference system (ANFIS)

The proximate analysis is the most common form of coal evaluation and it reveals the quality of a coal sample. It examines four factors including the moisture, ash, volatile matter (VM), and fixed carbon (FC) within the coal sample. Every factor is determined through a distinct experimental procedure under ASTM specified conditions. These determinations are time consuming and require a significant amount of laboratory equipment. The calorific value is one of the most important properties of a solid fuel and its experimental determination requires special instrumentation and highly trained analyst to operate it. This paper develops mathematical and ANFIS models for estimation of two factors of proximate analysis based on the other two factors. Furthermore, the estimation of calorific value of coal samples based on proximate analysis factors is performed using multivariable regression, the Minitab 16 software package, and the ANFIS, Matlab software package. The results indicate that ANFIS is a more powerful tool for estimation of proximate analysis factors and calorific value than multivariable regression method. The following equation estimates the calorific value of coal samples with high precision: Calorific value (btu/lb)= 12204 - 170 Moisture + 46.8 FC - 127 As

Strength-ductility trade-off via SiC nanoparticle dispersion in A356 aluminium matrix

A process was developed to disperse β-SiC nanoparticles (NPs), with a high propensity to agglomerate, within a matrix of A356 aluminum alloy. A suitable dispersion of 1 wt% SiC NPs in the A356 matrix was obtained through a hybrid process including a solid-state modification on the surface of the NPs, a two-step stirring process in the semi-solid and then the liquid-state, and a final hot-rolling process for fragmentation of the brittle eutectic silicon phase and porosity elimination. Titanium and nickel where used as the nanoparticle SiC surface modifiers. Both modifiers were found to improve the mechanical properties of the resulting material, however, the highest improvement was found from the nickel surface modification. For the nickel modification, compared to the non- reinforced rolled alloy, more than a 77%, 85%, and 70% increase in ultimate tensile strength (UTS), yield strength (YS), and strain % at the break, respectively were found with respect to the unreinforced rolled A356. For the rolled nanocomposite containing 1 wt % SiCnp and nickel modification, an average YS, UTS, and strain % at the break of 277 MPa, 380 MPa, and 16.4% were obtained, respectively, which are unique and considerable property improvements for A356 alloy

The pathological evaluation of nonneoplastic kidney disorder in tumor nephrectomy specimens

Renal cell carcinoma (RCC) comprises 2%-3% of all visceral and 80%-85% of all adult kidney malignancies. Nephrectomy is the treatment of choice for renal tumors. The accurate pathological evaluation of nonneoplastic renal parenchyma in nephrectomy specimens is important for subsequent management. Eighty-two patients with RCC who underwent surgery at Imam Khomeini Hospital, Urmia, Iran, from April 2006 to February 2015 were studied. Paraffin blocks of the hospital archives were stained by hematoxylin and eosin (H and E) and periodic acid-Schiff staining. Microscopic examination was performed on nontumoral portions that were in the farthest possible distance from the tumor. Out of total 82 cases, 24 (29.3%) had normal renal parenchyma and 58 (70.7%) had pathological changes in renal parenchyma. The most frequent pathological findings were vascular sclerosis with parenchymal scarring and pyelonephritis. Other findings include focal and diffuse mesangial hypercellularity, eight; focal segmental glome-rulonephritis, five; membranoproliferative glomerulonephritis, three; and membranous glome-rulonephritis, two. Parenchymal scarring and vascular change included 36% of clear cell type, 41% of papillary type, and 53.8% of chromophobe type. Although there is not any statistical relation between the gender of patients and pathological findings, there was an obvious correlation between age and pathological findings. Before the age of 55 years, vascular sclerosis with parenchymal scarring and glomerular diseases and then chronic pyelonephritis are more prevalent.Evaluation of pathological changes in nonneo-plastic renal parenchyma is an essential step in recognizing patients at risk of accelerated functional failure of the single remaining kidney, particularly in patients with a background of chronic vascular injury associated with diabetes or hypertension