Size Reduction Characterization of Underground Mine Tailings: A Case Study on Sandstones

Köken, Ekin

doi:10.1007/s11053-020-09707-2

Cited by 3 publications

(3 citation statements)

References 35 publications

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“…These are gravel substitutions (e.g., micro-quartzite with undulose extinction), detritic igneous constituents (e.h. Hornblende, biotite, tremolite, chlorite, and pyroxene), carbonate fragments (e.g., calcite, aragonite), and opaque minerals (magnetite, rutile etc.) [60]. The more LF is, the lower UCS values can be expected (Table 3).…”

Section: Model Comparisonmentioning

confidence: 91%

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Archives of Mining Sciences

Köken

2021

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The deformation properties of rocks play a crucial role in handling most geomechanical problems. However, the determination of these properties in laboratory is costly and necessitates special equipment. Therefore, many attempts were made to estimate these properties using different techniques. in this study, various statistical and soft computing methods were employed to predict the tangential Young Modulus (E ti , GPa) and tangential Poisson's Ratio (v ti ) of coal measure sandstones located in Zonguldak Hardcoal Basin (ZHB), nW Turkey. Predictive models were established based on various regression and artificial neural network (ANN) analyses, including physicomechanical, mineralogical, and textural properties of rocks. The analysis results showed that the mineralogical features such as the contents of quartz (Q, %) and lithic fragment (LF, %) and the textural features (i.e., average grain size, d 50 , and sorting coefficient, S c ) have remarkable impacts on deformation properties of the investigated sandstones. By comparison with these features, the mineralogical effects seem to be more effective in predicting the E ti and v ti . The performance of the established models was assessed using several statistical indicators. The predicted results from the proposed models were compared to one another. it was concluded that the empirical models based on the ANN were found to be the most convenient tools for evaluating the deformational properties of the investigated sandstones.

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Section: Model Comparisonmentioning

confidence: 91%

“…The d 50 and S c were determined based on the size parameters of the grains. Focusing on the surface area (A c ) and Feret diameters (F min , F max ) of each grain, the equivalent diameter (d e , mm) of a rock-forming mineral was determined by the following equation [60]:…”

Section: Methodsmentioning

confidence: 99%

Archives of Mining Sciences

Köken

2021

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“…Many scholars have investigated the effects of freeze-thaw on the strength, anisotropy, and other properties of rocks, and found that the strength of these rocks decreases after freeze-thaw cycles. Few of these studies have dealt with tailings as a material, and few have used numerical simulations as a method of study [4][5][6][7][8][9][10]. Some scholars also studied the effects of freeze-thaw processes on the leaching of metals from waste rock and the oxidation of sulfides [6].…”

Section: Introductionmentioning

confidence: 99%

Numerical Study on Mechanical Properties of the Freezing–Thawing Cycle of Tailings Based on Particle Discrete Element Method

Huang

Yang

et al. 2022

Minerals

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To study the effects of the number of freezing–thawing cycles (F-T cycles), the dry density, and the average particle diameter on the mechanical properties of tailings, the calibration laws of the fine-scale parameters in the discrete particle element numerical simulation software PFC2D(Particle Flow Code) were first tested, and then pre-experiments were conducted in the form of orthogonal tests. Finally, according to the results of the pre-experiments and the analysis of the pre-experimental results by SPSS (Statistical Product Service Solutions) software, uniaxial tests were carried out for different numbers of freeze–thaw cycles, different dry densities, and different average particle sizes. The tailings specimens were subjected to uniaxial compression simulations. The results showed that (1) the uniaxial compressive strength of the tailings specimens decreased with each freeze–thaw cycle, and stabilized after seven freeze–thaw cycles. (2) With a greater number of freeze–thaw actions, the porosity of the tailings increased after freeze–thawing. The peak of porosity was much higher than that of the models with fewer than seven freeze–thaw actions. (3) The contact number of tailings specimens showed a significant decrease after the number of freeze–thaw cycles reached seven. However, the amount of exposure was not the main factor affecting the strength of tailings (4). As the number of freeze–thaws increased, the tailings model was more prone to stress concentration. Previously, PFC software has been applied to tailings simulation studies, and this study verifies the feasibility of this method. This research is able to offer a reference for studying the mechanical property changes of tailings in the cold highland area.

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