Recent Submissions

  • Analysis of cation-treated clay microstructure using zeta potential and x-ray diffraction

    Guo, Rui; Darrow, Margaret .; Metz, Paul A.; Trainor, Thomas P. (2018-12)
    Unfrozen water within cation-treated, fine-grained frozen soils is a key element in cold regions engineering, and is heavily influenced by the surface charge of the soil's clay component. This study investigated the effects of the surface charge of cation-treated clay soils by measuring the zeta potential as a function of temperature, and measuring changes in the micro-structure of frozen cation-treated clays using the x-ray diffraction (XRD) method. I tested five treatments (untreated, and Ca²⁺, Mg²⁺, Na⁺, and K⁺ treatments) of six soils (montmorillonite, kaolinite, illite, illite-smectite, chlorite, and Copper River soil). The zeta potential demonstrated a negative relationship with temperature change for both above-freezing and sub-freezing conditions (-1 to 20 °C). Temperature had a greater effect on the monovalent-treated soils that contain smectite minerals, which included montmorillonite, illite-smectite, and the Copper River soil. Monovalent cation-treated soils demonstrated large negative trends and more negative zeta potential, whereas divalent cation-treated soils demonstrated less negative trends that were less dependent on temperature. The cation treatment will affect the Debye-length, also affecting the zeta potential and arrangement of clay particles. More negative zeta potential (i.e., soil dominated by monovalent cations) will lead to a dispersed structure, whereas less negative zeta potential (i.e., soil dominated by divalent cations) will lead to a flocculated structure. XRD research indicated that the montmorillonite samples demonstrated decreased dspacing compared with the International Center for Diffraction Data (ICDD) standard. The K⁺- treated montmorillonite, untreated montmorillonite, and untreated illite-smectite samples demonstrated donut-shaped pole figure results, which may indicate that the results are an artifact of sample preparation rather than a reflection of the cation effects on the structure of the clay. Improved could be made in sample preparation to eliminate ice lens formation during freezing, which may improve the success with the XRD method. Scanning electron microscopy (SEM) should be used to observe the frozen clays, especially montmorillonite, illite-smectite, and the Copper River soil, as it may reveal the internal geometry of voids and the possible relationship between ice and the clay structure, increasing our understanding of the clay structure at the microaggregate scale.
  • Analysis and evaluation of fragment size distributions in rock blasting at the Erdenet Mine

    Dondov, Erdenebaatar; Дондов, Эрдэнэбаатар; Chen, Gang; Ghosh, Tathagata; Ganguli, Rajive (2015-08)
    Rock blasting is one of the most important operations in mining. It significantly affects the subsequent comminution processes and, therefore, is critical to successful mining productions. In this study, for the evaluation of the blasting performance at the Erdenet Mine, we analyzed rock fragment size distributions with the digital image processing method. The uniformities of rock fragments and the mean fragment sizes were determined and applied in the Kuz-Ram model. Statistical prediction models were also developed based on the field measured parameters. The results were compared with the Kuz-Ram model predictions and the digital image processing measurements. A total of twenty-eight images from eleven blasting patterns were processed, and rock size distributions were determined by Split-Desktop program in this study. Based on the rock mass and explosive properties and the blasting parameters, the rock fragment size distributions were also determined with the Kuz-Ram model and compared with the measurements by digital image processing. Furthermore, in order to improve the prediction of rock fragment size distributions at the mine, regression analyses were conducted and statistical models w ere developed for the estimation of the uniformity and characteristic size. The results indicated that there were discrepancies between the digital image measurements and those estimated by the Kuz-Ram model. The uniformity indices of image processing measurements varied from 0.76 to 1.90, while those estimate by the Kuz-Ram model were from 1.07 to 1.13. The mean fragment size of the Kuz-Ram model prediction was 97.59% greater than the mean fragment size of the image processing. The multivariate nonlinear regression analyses conducted in this study indicated that rock uniaxial compressive strength and elastic modulus, explosive energy input in the blasting, bench height to burden ratio and blast area per hole were significant predictor variables in determining the fragment characteristic size and the uniformity index. The regression models developed based on the above predictor variables showed much closer agreement with the measurements.
  • TEST Master's Projects 9/25/17

    CHISUM (2017-09)
    TEST Master's Projects 9/25/17
  • Data mining for mine-mill ore grade reconciliation at Erdenet Mining Corporation

    Sarantsatsral, Narmandakh (2016-11)
    This project investigates the relationship between the mined ore and the produced copper at the Erdenet Mining Corporation (EMC) surface copper mine in Mongolia. Four and half years of data (from 2011-2015) was obtained from the open pit mine and mineral processing plant of EMC. The mine-mill data was collected on a shift basis. The data was examined carefully using process knowledge and exploratory data analysis techniques to detect and eliminate errors. Ultimately, two years of data (2013-2014) was selected for further analysis. As is common in all mines, the material flow between the mine and mill is complicated by numerous stockpiles. The copper grade going into a stockpile may not be directly related to the copper grade exiting a stockpile. Therefore, data mining techniques applied to detect the relationship between mined ore and milled copper had to overcome the complications introduced by the presence of stockpiles. Multiple data sets were created by aggregating the original dataset by different periods. For example, in one case, data was aggregated by three shifts, to convert the data from shift-basis to daily-basis. Aggregation is an ideal way to absorb variations in material flow (tonnage and grade) between mine and mill. Data was aggregated by 3, 4, 5, 6, 7, 8, 9, 10, 11 and 12 shifts ("aggregated widths" or AW). Correlation analysis was then conducted on each version of the data to determine if a relationship existed between mine data and mill data. Correlation was computed for various period lengths, but not exceeding 28 days. Therefore, in a given year, several correlation plots were produced at each aggregated width. The number of times the correlation coefficient exceeded 0.8 in a year was measured. Results showed that correlation improved with aggregation width. The highest correlations occurred at AW of 7 or 8. This suggests that the stockpiles aggregate material for 2-3 days. Correlation analysis also included examining a time shift ("lag") between mine data and mill data. This is useful to detect whether material takes a certain amount of time before it is processed and produced as copper. However, results indicated that once the data was aggregated, a time lag greater than 0 only worsened correlation.