Faculty Publications

Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736

Publications by NITK Faculty

Browse

Author: search.filters.author.Kunar, B.M.Has files: No

Search Results

Now showing 1 - 10 of 27
  • No Thumbnail Available
    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.
  • No Thumbnail Available
    Item
    Study of Electronic Permit to Work System at Limestone Mining and Cement Industry to Control Accident and Injuries
    (Springer Nature, 2025) Mahanta, M.; Kunar, B.M.
    An internationally recognized method of limiting hazardous activity particular high-risk maintenance, is the permit to work system. The permit-to-work is a formal process that grants permission to particular individual to perform particular task during a designated window of time. It is difficult to control large number of worker’s safety database by using traditional paper Permit to Work System. To remove all unforeseen manual mistake ePTW (Electronic Permit to Work) system was introduced by using customized computer network operated webpage by programming language such as HTML (hypertext markup language), CSS (Cascading Style Sheets), JavaScript Language etc. The objective of the study to be make suggestion and implement various measure to improvement in current ePTW system and comparison of accessibility, control, and decreases in accident rate during paper based PTW versus electronic based PTW. History data studied of a Cement industry of India of 40 different locations and found that, on the year 2010, 09 nos. of fatal accidents occurred before implementation of ePTW, now gradually decreases to 02 as on the year 2022 by implementing ePTW. The scope of the study is included both limestone quarry and cement manufacturing process, because most of the workers are working in mining, auxiliary mining activities like electrical sub-station in mines, underground cabling in mines pit, haul road lighting, limestone crushers, mechanical HEMM Maintenance, civil works, IT support services, instrumentation and telecom, pipe line workers, and pump operator. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
  • No Thumbnail Available
    Item
    Effect of thermal response on physical properties during drilling operations-A case study
    (Elsevier Ltd, 2018) Vijay Kumar, S.; Murthy, Ch.S.N.; Kunar, B.M.
    The temperature induced or generated during deep hole drilling operations is due to the heat generated between the interface of work piece surface and the tool surface. Several research study have been conducted to predict the temperature involved while drilling process as a predominant functions of many parameters like feed rate, torque, depth of cut etc. Similarly many experimental procedures have been conducted by several researchers to measure temperature directly by using thermocouples, infrared measurement, pyrometer, and thermisters etc. There is no precise experimental method is available to measure analytical value of energy, power, heat flux etc, while drilling process. The temperature rigma depends on material compositions and physical properties. This paper presents the influence of temperature on physical properties of some study samples during drilling operations. © 2017 Elsevier Ltd.
  • No Thumbnail Available
    Item
    Comparison of the particle size distribution in marble and granite rock samples subjected to ball milling process
    (Society for Mining, Metallurgy and Exploration theng@smenet.org 12999 E Adam Aircraft Circle Englewood,Colorado 80112 Colorado, 2019) Kunar, B.M.; Murthy, C.S.N.; Rao, B.K.
    Rock particle size has a very important significance in the mining industry, starting from blasting till the mineral processing. The present study was carried out to understand the particle size distribution in various sieves after conducting the ball milling process. The time of the grinding process was varied at different intervals. It was observed that 80% of the particles of both granite and marble rock samples passed through the 4800 μm sieve when subjected to grinding time of 40 minutes. Also, it was observed the number of particles that were retained in the smallest sieve of <75 μm was higher in the case of granite sample when compared to a marble sample. © © 2019 by SME.
  • No Thumbnail Available
    Item
    Temperature Measurement During Rotary Drilling of Rocks - A Statistical Approach
    (Springer Nature, 2020) Vijay Kumar, S.; Kunar, B.M.; Murthy, C.S.N.
    This paper discusses a statistical analysis to measure the temperature during rotary drilling of fine-grained sandstone (pink) using embedded thermocouple method. The regression models consist of three input variables such as diameter of the bit, rpm and rate of penetration for different depth of thermocouples. Experimental test were conducted in computer numerical control (CNC) vertical machining centre. The measured temperature has been applied to study the influencing parameter using statistical technique. Analysis of variance (ANOVA) shows that the percentage contribution ratio of each operational parameters on temperature (output response). The most influencing parameter for temperature is rate of penetration with a percentage contribution of 71.32%, followed by drill bit diameter and spindle speed which contribute 19.27% and 2.99% respectively. The ANOVA and regression models for temperature give p-values of less than 0.05. Hence the predicted regression models are statistically significant and good predictive capabilities with acceptable accuracy. © 2020, Springer Nature Switzerland AG.
  • No Thumbnail Available
    Item
    Numerical Investigation on Factors Affecting the Performance of Roof Bolts for Continuous Miner Working
    (Springer Nature, 2020) Tejeswaran, K.M.; Murthy, C.S.N.; Kunar, B.M.
    Optimum support design of roof bolts based on axial load of the bolt plays the major role for effective development of coal seam with continuous miner. Axial load on the roof bolts gives a clear understanding of the behaviour of roof bolts in different working conditions. Therefore, estimation of axial load on the bolts is important for supporting the immediate roof, helps in higher production, productivity and safety. By using the software FLAC 3D, the axial load for different gallery widths and working depths was estimated. From the simulation results, it was observed that for shallow depths of 100 and 200 m, the axial load acting on the bolt is 15% of the bolt capacity at gallery widths of 4 m and 5 m. Whereas for moderate depths 300 m and 400 m, its value is found to be 75% at gallery widths 6 m and 7 m. But, for deeper depths of 500 m and more, its values reaches maximum capacity of roof bolts. Also, the roof convergence in junction, for moderate and deeper depths is 80 mm to 150 mm, whereas for shallow depths its value is 10–25 mm, at 6 m, 7 m and 8 m gallery widths. © 2020, Springer Nature Switzerland AG.
  • No Thumbnail Available
    Item
    A Switched-Capacitor Based Nine-level Boost Inverter Circuit for Mining Applications
    (Institute of Electrical and Electronics Engineers Inc., 2022) Prudhvi Krishna, B.N.V.V.; Kunar, B.M.; Murthy, C.S.N.
    A dual boost nine-level inverter for mining applications is proposed in this work. Capacitors are used as virtual sources to boost the voltage magnitude and increase the levels. Additionally, the proposed MLI circuit inherits benefits such as self-balancing capacitors, less blocking voltage, and fewer components. A simple PD-PWM scheme is used to generate gating signals. Circuit portrayal, operating principle, modulation, and capacitor voltage ripples are studied. MATLAB software is used to carry out simulations, and the obtained outcomes prove the boosting ability under different loading circumstances. A detailed comparative review is conducted with other recent SCMLIs to illustrate the superiorities of the proposed circuit. © 2022 IEEE.
  • No Thumbnail Available
    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).
  • No Thumbnail Available
    Item
    Bifacial Solar PV Systems: A Sustainable Solution for Energy-Intensive Industries
    (Institute of Electrical and Electronics Engineers Inc., 2024) Bojja, S.K.; Kunar, B.M.; Murthy, Ch.S.N.
    Energy-intensive industries and mineral-based industries demand a considerable quantity of power for numerous uses. This is a big challenge because these procedures need a continuous and constant energy source, which requires an uninterrupted power supply. In theory, industries complement, replace, or lessen the effects of using fossil fuels by utilizing renewable energy, carbon capture, and energy recovery. However, combining renewable energy sources, such as solar power, can significantly lower overall operating costs and carbon emissions to meet the energy needs of different industrial applications. This study describes the installation, for research purposes, of a prototype bifacial solar PV system (BSPV) equipped with a pumping motor. A BSPV system is being investigated because its output energy will be higher than that of monofacial solar cells. BSPV systems use less space than monofacial ones while still producing the same power and being less expensive as well. © 2024 IEEE.
  • No Thumbnail Available
    Item
    Maximizing Power Output: MPPT and Buck-Boost Converter Analysis in PV Applications
    (Institute of Electrical and Electronics Engineers Inc., 2024) Shiva Kumar, B.; Kunar, B.M.; Saida Nayak, R.
    Maximum power point tracking (MPPT) strategies are applied in PV applications for maximizing power and continuously evaluating the whole power point of photovoltaic (PV) modules under various atmospheric conditions. For it to be possible to match the source impedance to the load impedance for MPPT, numerous DC to DC converters (such as the Buck-boost, Boost, and Buck) are inserted between PV arrays and loads in the PV system, and their efficacy and assessments will be discussed in the remainder of this paper. All these DC-DC converters and MPPT tracking (P & O) algorithm are modelled using MATLAB/Simulink and results shows that the maximum power is enhanced with Buck-Boost converter than other dc-dc converters. © 2024 IEEE.