اسفوردی

In this study, a hybrid approach is established for clustering the most favorable regions  in association with magnetite-apatite mineralization at the Esfordi district in the central Iran. An optimum number of clusters is derived from a data-driven methodology through a concentration-area (C-A) fractal model of a synthesized geospatial data set. According to the metallogenic characteristics of the sought deposits, nine evidential layers deriving from geological, geochemical, geophysical, and remote sensing data were extracted. Prediction-area curve (P-A) was used as a data-driven method to determine the weight and importance of those evidences; then an index overlay method integrated them into a single propsectivity map. The number of clusters significantly affects the mineral potential modeling results in clustering algorithms. To determine an optimum number of clusters, the C-A fractal curve of the overlaid map indicated the correct population within this district, and then used as the optimal number to run the unsupervised clustering algorithms. Assuming five clusters, three clustering algorithms, including K-means, fuzzy C-means, and self-organizing map (SOM), were used to identify and localize iron-bearing favourable areas. The K-means algorithm had the highest accuracy in identifying those potential areas, by which 8% of the whole area could predict 65% of known deposits in the main favorable region.

This paper presents the results of first stage investigation of phosphate recovery from fine particles in Esfordi phosphate beneficiation plant. The aim of this investigation was the optimization of flotation process for increasing the phosphate recovery and decreasing the Iron content of concentrate. Experimental design, Taguchi method, was applied to investigate the effects of 8 factors namely, collectors ratio, collectors dosage, pH, starch dosage, pulp density, conditioning time for starch, conditioning time for collectors and frothing time. 4 responses, namely phosphate recovery, phosphate grade, iron recovery and iron grade were measured and evaluated to determine the optimum conditioning of each response. The orthogonal array L27(313) was used for the evaluation of the above factors on the responses of design. Statistical analysis of results showed that starch dosage, pulp density an frothing time had more impact on the phosphate recovery. The optimum condition for each response was introduced and the best condition for phosphate grade in concentrate was compared with the ruling condition in beneficiation plant. The comparison of results showed acceptable improvement in concentrate quality.