Sensitivity Analysis of Coal Rib Stability for Internal Mine Dump in Opencast Mine by Finite Element Modelling

The present paper discusses the impact of the geometrical parameters of the coal rib and the mine dump on the stability of the coal rib. The geometrical parameters such as the slope angle, the height of dragline dump, the height of main dump, the gradient of seam and the thickness of coal rib have been considered as input to the numerical model for the stability analysis of the coal rib. Sensitivity analysis has been performed based on the results of the analysis in term of factor of safety of the coal rib. The input parameters have been classified in terms of significance (i.e. very high significance, high significance medium significance and low significance). The factor of safety is more influenced by highly significant parameters. The height and the slope angle of dragline dump and the thickness of the coal rib are highly significant parameters for the stability of the coal rib. The gradient of the seam is a medium significant parameter whereas, height of main dump and the number of dragline cut dump are low significant parameters for stability of coal rib.     

Depositional environment and OSL chronology of the Homeb silt deposits, Kuiseb River, Namibia

Previous studies suggest that the Homeb silts of the Kuiseb valley, Namibia (i) accumulated in a dune-dammed lake, (ii) are end-point deposits, (iii) represent an aggrading river bed, and (iv) are slackwater deposits. Thus, they have been used alternatively as evidence of past drier conditions or past wetter conditions. Lithostratigraphic analysis of two sediment sequences at Homeb indicates sedimentation by aggradation of the Kuiseb River triggered by a transition from an arid to humid climate. OSL ages for the sequences were obtained by the SAR protocol on aliquots of 9.6-mm and 4.0-mm diameter and on single grains. Four-millimeter aliquot minimum ages closely approximate the single-grain minimum ages and are younger than 9.6-mm aliquot minimum and central ages. Based on these results, the small-aliquot (4-mm) approach appears to provide ages comparable to those obtained by the more laborious and time-consuming single-grain method. Minimum ages indicate rapid deposition of the Homeb Silts in at least two episodes centered at 15 ka and 6 ka during climate transitions from arid to humid. Flash floods eroded the valley fills during slightly more arid conditions.     

Ground electrical and electromagnetic studies in Koyna-Warna region,India

The geochemistry of the mafic xenoliths from Baspa valley of Himachal Pradesh, India has been investigated to characterize their protoliths on the basis of immobile elements, especially trace elements including REE. The mafic xenoliths occur within the Kinnaur Kailash granite (KKG) and their geochemistry show that they have tholeiitic nature with basaltic composition. Compositionally, they range from ‘depleted’ to ‘enriched’ MORB as observed on the binary diagrams of Ti vs V and Zr vs Ti and on ternary diagrams of Zr-Ti-Y and Th-Zr-N. Likewise, they match with various enriched or ‘transitional’ MORB types as evident from their Zr vs Nb binary plot. Their enriched character when compared with N-MORB, E-MORB and OIB rocks on chondrite and primordial mantle normalized plots reveals that it is intermediate to that of E-MORB and OIB. The geochemistry of the rocks suggest that the enriched components are probably derived by melting of a mantle source with E-MORB or OIB rather than due to the crustal contamination. The study carried out emphasize that the mafic xenoliths have developed in rift environment, and that they are not volcanic rocks of island arc related to subduction tectonics. It is visualized that the mafic xenoliths were formed as cumulate rocks from the tholeiitic magmas that were rising to lower crust levels in a rift environment, which at a later stage got entrapped as restitic material in the host Kinnaur Kailash granite formed in a collision environment, and propose a change of regime from rift related to collision environment prior to Palaeozoic period.     

Development of machine vision-based ore classification model using support vector machine (SVM) algorithm

The product of the mining industry (ore) is considered to be the raw material for the metal industry. The destination policy of the raw materials of iron mine is highly dependent on the class of iron ores. Thus, regular monitoring of iron ore class is the urgent need at the mine for accurately assigning the destination policy of raw materials. In most of the iron ore mines, decisions on ore class are made based on either visual inspection by the geologist or laboratory analyses of the ores. This process of ore class estimation is time consuming and also challenging for continuous monitoring. Thus, the present study attempts to develop an online vision-based technology for classification of iron ores. A laboratory-scale transportation system is designed using conveyor belt for online image acquisition. A multiclass support vector machine (SVM) model was developed to classify the iron ores. A total of 2200 images were captured for developing the ore classification model. A set of 18 features (9-histogram-based colour features in red, green and blue (RGB) colour space and 9-texture features based on intensity (I) component of hue, saturation and intensity (HSI) colour space) were extracted from each image. The performance of the SVM model was evaluated using four confusion matrix parameters (sensitivity, accuracy, misclassification and specificity). The SVM model performance was also compared with the other methods like K-nearest neighbour, classification discriminant, Naïve Bayes, classification tree and probabilistic neural network. It was observed that the SVM classification model performs better than the other classification methods.