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Author: search.filters.author.Harish, P.Subject: search.filters.subject.Stability analyze

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    A review on stability analysis of coal mine dumps
    (Inderscience Publishers, 2024) Harish, P.; Chandar, K.R.
    Opencast mines are increasingly extracting deeper coal seams in large quantities, leading to a rise in mine depth and generation of substantial waste. Disposal of this waste becomes challenging due to the need for additional land, resulting in dumping excess waste on existing dumps, posing risks of dump failure, property damage, and loss of life. This paper aims the critical review of the stability of dump slope structures that are present on the weak or disturbed foundations which further leads the dumps to fail. Many researchers have concentrated on the irregular base, loose material presence in the foundation, sloping floors, improper compaction at the foundation level, presence of black cotton soil, etc., stating load of the dumps over the weaker foundations exerts more pressure on the foundation and causing the dumps to fail. It synthesises key findings on stability analysis approaches, design criteria, optimisation techniques, and critical parameters involved in numerical modelling-based design for secure dump slope structures. © © 2024 Inderscience Enterprises Ltd.
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    Stability Analysis of Overburden Dumps over Old Underground Workings Using Artificial Neural Networks
    (Pleiades Publishing, 2024) Harish, P.; Chandar, K.R.
    Abstract: Stability of overburden dump slopes is a crucial aspect in designing secure and cost-effective dumps. The Strength Reduction Factor (SRF) serves as a widely used term to assess dump stability. This paper focuses on developing an Artificial Neural Network (ANN) model capable of predicting SRF for overburden dumps situated above existing underground workings. To construct the model, a dataset comprising 96 numerical simulations of overburden dumps generated through the finite element method was utilized. A neural network architecture with three layers of forward-backward propagation was utilized, containing hidden neurons to analyze simulations during training, validation and testing stages. The input parameters for studying overburden dump slopes over underground workings included dump slope height (Sh), dump slope angle (), cohesion (C), friction angle (Ø), unit weight () of the dump material, depth of working from the surface (D), centre-to-centre pillar distance in underground workings (C-C), and gallery width (Gw). The ANN predicted results were compared with the outcomes derived from numerical simulations of overburden dump slopes above underground workings. The study highlights that the developed ANN model in this research proves highly effective in handling and designing complex overburden dump slopes. The obtained results indicate a Mean Square Error (MSE) of 0.0595 and a coefficient of determination (R) of 0.883, both of which are considered acceptable. © Pleiades Publishing, Ltd. 2024.