Faculty Publications
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Item Predicting Rock Properties of Limestone Using Operating Parameters of Ball Mill(Springer Nature, 2025) Swamy, S.V.; Kunar, B.M.; Chandar, K.R.Rock properties are important for mining, geotechnical engineering, and other engineering projects. Accurate determination of these properties relies on high-quality samples, but challenges like sample availability, preparation of sample, cost, and time constraints have led to an increasing reliance on computational methods for prediction. Prior investigations predominantly relied on laboratory-based tests and indirect methodologies to predict properties of rocks. In contrast, this study introduces an innovative technique for predicting rock properties, specifically the P-wave velocity (Vp) and uniaxial compressive strength (UCS) by harnessing ball mill operational parameters throughout the grinding procedure an unconventional yet indirect approach. A multivariate regression model is established to connect operating parameters with the strength properties of limestone samples. The determination coefficients (R2) for Vp and UCS prediction models are 0.892 and 0.868, respectively. Moreover, an Analysis of Variance (ANOVA) is performed to ascertain the influence of significant parameters on the target variables. The accuracy and reliability of the prediction models are further validated through scatter plots and residual variations for both Vp and UCS models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.Item A machine learning framework for predicting elastic properties of sedimentary rocks from ball mill grinding characteristics data(CRC Press/Balkema, 2024) Swamy, S.V.; Harish, P.; Kunar, B.M.; Chandar, K.R.Elastic properties of rocks like Young’s modulus and compressional P-wave velocity are vital for understanding their stress-strain response in mining and rock engineering applications. Traditional methods for determining these properties involve labor-intensive, expensive and time-consuming. To address these challenges, this study proposes a novel predictive method. It utilizes a multi-layer perceptron feed forward neural network (MLP-FFNN) trained on grinding characteristics of ball mill to predict Young’s modulus and compressional Pwave velocity in sedimentary rocks. Laboratory experiments on limestone and dolomite samples generated extensive data, enabling development of prediction models using the proposed MLPFFNN. The developed models demonstrate high predictive accuracy (R values: 0.952 for E, 0.987 for Vp) in training and good generalization (0.866 for E, 0.9707 for Vp) in testing, along with low Root Mean Squared Error (RMSE) values. These findings underscore the efficacy of neural network models in predicting E and Vp from grinding characteristics of ball mill. © 2024 The Author(s).Item Effect of longwall workings on the stability of overburden dumps(CRC Press/Balkema, 2024) Harish, P.; Swamy, S.V.; Chandar, K.R.Extraction of coal is done in both opencast and underground methods. Opencast mining generates a huge amount of overburden while excavating the coal. Managing the overburden material, deposited as dumps at considerable heights to minimize ground coverage, is crucial in opencast mines, but it poses risks such as potential failures. Such failures can stop the mining activities, endanger personnel safety, and damage equipment. At times, limitations in space, the placement of overburden dumps over underground excavations, posing stability challenges due to pre-existing stresses from activities below the surface. This paper explores the stability prediction of overburden dumps above longwall workings, using Rocscience RS2 v19.2, a two-dimensional finite element analysis software. Strength Reduction Technique determines the factor of safety (FOS), revealing that the presence of underground longwall excavation induces a vertical deformation of 56.4mm for the critical strength reduction factor of 1.12, emphasizing the impact on overburden dump stability. © 2024 The Author(s).Item Investigation into the Blast-Induced Damage in Cut and Fill Stoping Operation(Books and Journals Private Ltd., 2022) Sangode, A.G.; Raina, A.K.; Bagde, M.N.; Chandar, K.R.The paper presents the results of a comprehensive monitoring carried out to study the extent of blast-induced damage experienced by rockmasses extracted by cut and fill stoping in a manganese mine. Damage is related to strain generated by the blasting and it is found to correlate well with the particle velocity. The particle velocities were measured in the studied mine with seismographs. The attenuation equation for extrapolation of vibration to the near field was derived from the data thus acquired. The site-specific damage model for designing the safe blast parameters was thus devised to minimize the extent of the blast-induced damage to protect the hanging wall, footwall and friable orebody and thus overall improving the stoping environment. The presented work aims at improving the understanding of the influence of blasting on the backfilled area and hard rock in the stoping environment. The damage predicted by different methods and the final strategy for blasting for wall control and productivity are documented in the paper. © 2022, Books and Journals Private Ltd.. All rights reserved.Item Development of an alert system in slope monitoring using wireless sensor networks and cloud computing technique – a laboratory experimentation(Inderscience Publishers, 2023) Mittapally, M.S.; Chandar, K.R.Opencast mine slope monitoring is crucial to prevent potential failures. Wireless sensor networks (WSNs) offer real-time data collection and analysis for effective slope monitoring to minimises monitoring costs and improves safety. Utilising cost-effective microelectromechanical sensors, slope conditions are wirelessly transmitted using internet of things (IoT), facilitating immediate insights. Monitoring parameters like moisture, vibration, and displacement predict slope behaviour. It is essential to test the sensors before designing and implementing a system for regular monitoring in the field to know the sensor’s performance and match them to the slope condition. The study entails moisture, vibration, and displacement measurements in clay slope models. ZigBee-enabled XBee SC2 modules transmit data to ThingSpeak, triggering PythonAnywhere alerts. As a result, if soil moisture sensor readings were over the predefined threshold value of 50%, an email alert was triggered at the time of the jump. It is concluded that the alert system was developed by using sensors in the clay model developed at a laboratory scale and suitable for field applications on a large scale. © © 2023 Inderscience Enterprises Ltd.Item An overview of the applications of soft computing methods for predicting the physico-mechanical properties of rocks from indirect methods(Inderscience Publishers, 2023) Bijay Mihir Kunar, S.; Chandar, K.R.Rocks are widely used in infrastructure constructions like roads, tunnels, buildings, and dams. Understanding physico-mechanical properties of rocks is vital for selecting suitable rocks, yet some properties pose challenges in determination. High-quality core samples and precise instruments are necessary for accurate assessment. Predicting the physico-mechanical properties of rocks is a key research area in rock mechanics. Researchers have employed diverse methods, including laboratory tests, non-destructive tests, and mineralogical and petrographical characteristics, to determine rock properties. This article reviews the use of soft computing methods, artificial intelligence, and machine learning to predict rock properties through indirect methods. Indirect methods involve engineering indices tests, mineralogical and petrographical characteristics, and additional approaches such as electrical properties, crushability indices, thermal characteristics, and grinding characteristics. The article also proposes various artificial intelligence and machine learning techniques as potential future directions in prediction of rock properties. © © 2023 Inderscience Enterprises Ltd.Item 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.Item 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.Item Estimation of Strength Properties of Some Rocks using Ball Mill Grinding Characteristics(World Researchers Associations, 2025) Sahas, S.V.; Bijay, K.M.; Chandar, K.R.The strength properties of rocks namely uniaxial compressive strength and tensile strength are important in design and stability evaluation of various mining, geotechnical engineering and other rock engineering projects. Accurate determination of these properties relies on high-quality samples, but challenges like sample availability, preparation of sample, cost and time constraints have led to an increasing reliance on computational methods for prediction. In this context, an indirect approach is proposed for predicting rock strength properties, specifically the uniaxial compressive strength (UCS) and tensile strength (TS), using grinding characteristics of ball mill, an unconventional yet indirect approach. A predictive modelling using multivariate regression is carried out to estimate the relationship between UCS, TS and the grinding characteristics of ball mill. The developed models demonstrated high accuracy with R² values of 0.93 for UCS and 0.96 for TS. Performance evaluation metrics showed an RMSE of 6.03 MPa and a VAF of 93.45% for UCS and an RMSE of 0.99 MPa and a VAF of 96.47% for TS. The validation was performed using experimental UCS and TS values of basalt rocks along with ball mill grinding test data. The error analysis revealed that UCS prediction error ranged from 5.1% to 11.61% while TS prediction error varied between 4.26% and 16.39%. © 2025, World Researchers Associations. All rights reserved.Item Influence of Underground Workings and Dump Height on the Stability of Overburden Dumps(World Researchers Associations, 2025) Harish, P.; Satyanarayana, I.; Chandar, K.R.Coal is extracted using both underground and opencast methods of working. During the coal extraction process, opencast mining produces a significant amount of overburden. In opencast mines, the removed overburden material is dumped at significant heights to reduce ground coverage. But overburden dumps with great heights are at risk and sometimes lead to failure of dumps causing loss of men and machinery. Stability issues will become more complicated when the overburden is dumped above the old underground workings. Complication arises because of redistribution of pre-existing stresses from underground activities affecting the overburden dumps. This study uses a two-dimensional finite element (FE) analysis program to understand the stability analysis of overburden dumps above old underground workings. The factor of safety (FoS) is determined using the strength reduction technique which highlights the impact of underground excavations on overburden dump stability by highlighting the required strength reduction factor (SRF). In order to analyse the overburden dumps with the presence and absence of old underground workings, numerical models were created for various dump heights. The overburden dumps with underground workings exhibited SRF values ranging from 1.78 to 2.05, while the dumps without underground workings had SRF values ranging from 1.81 to 2.55. The displacement of the overburden dump material, which results in 7 mm of horizontal displacement and 29 mm of vertical displacement, indicates a significant impact of underground workings on the stability of the overburden dumps. This study highlights the importance of considering underground workings in the design and management of overburden dumps to ensure safety and stability. © 2025, World Researchers Associations. All rights reserved.