Browsing by Author "Kunar, B.M."

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A Comparative Study and Regression Analysis on Physico-Thermal Properties using Pongamia Pinnata - Waste Cooking Oil Methyl Ester Mixture
(Taylor and Francis Ltd., 2025) Khale, B.R.; Kunar, B.M.; Murthy, C.S.
Development of alternative fuels over the past three decades is trending research for the replacement or supplement of the mineral-based fuels. In the present study, a combined biodiesel mixture was prepared volumetrically from methyl esters of pongamia pinnata and waste cooking oil (50:50). Physico-thermal properties (Density, viscosity and calorific value) for blends varying from 5 to 30% were determined, for both combined biodiesel blends and their respective sources. Further, a comparative study on the physico-thermal properties of combined biodiesel blends with their respective sources was made. Similar trends were observed between the combined biodiesel blends and their respective sources. i.e., density and kinematic viscosity increased with increase in blend percentage. Alternatively, a decreasing trend was observed in the calorific value. Statistical analysis using Minitab was carried out. Backward elimination method was used to develop a regression model to determine the coefficient of determination between the properties and the volumetric contribution of blends. The models were significant at a confidence interval of 95%. The R-Square value for predicting density, kinematic viscosity and the calorific value was 99.37%, 99.05% and 99.84% respectively. © 2021 Taylor & Francis Group, LLC.
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 Youngâ€™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 Youngâ€™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. Â© 2024 The Author(s).
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. Â© 2022 IEEE.
An adaptive modeling for bifacial solar module levelized cost and performance analysis for mining application
(John Wiley and Sons Ltd, 2024) Shiva Kumar, B.S.; Kunar, B.M.; Murthy, C.S.N.
Power density and efficiency typically dominate design approaches for power electronics. However, cost optimality is in no way guaranteed by these strategies. A design framework that minimizes the (i) levelized cost of electricity (LCOE), (ii) collection of light, and (iii) irradiance of the generation system is proposed as a solution to this flaw. From an improvement of the swarm behavior optimization model to get a minimum LCOE of solar panel, we design to optimize height, tilt angle, azimuth angle, and some parameters to solve the objective function and LCOE improvement problem to obtain the optimal design problem. In adaptive salp swarm optimization (ASSO), this change's proposed model producer swarm behavior is regarded as an adaptive process that keeps the algorithm from prematurely converging during exploration. The proposed algorithm's performance was confirmed using benchmark test functions, and the results were compared with those of the salp swarm optimization (SSO) and other efficient optimization algorithms. LCOE condition as far as “land-related cost” and “module-related cost” demonstrates that the optimal design of bifacial farms is determined by the interaction of these parameters. This proposed model can be used to evaluate visibility on building surfaces that are suitable for mining applications like crushing. Experimentation results show Minimum LCOE AS 0.05 (€/Kw)minimum irradiance and collection light as 336.23(w/m2) and 83.02%n proposed framework model. The swarm optimization method is contrasted with the optimal parameters derived from a conventional solver. © 2023 John Wiley & Sons Ltd.
An analytical hierarchy approach for studying the impact of human error, environmental factors, and equipment failure on mine accidents: a case study in India
(Springer, 2024) Kar, M.B.; Mangalpady, M.; Kunar, B.M.
This paper presents a study using the Analytical Hierarchy Process (AHP) to understand and prioritize the accidents that have occurred in the Indian mining industry. The data for the study was collected from accident reports submitted to the Directorate General of Mines Safety from 2011 to 2020. The accident information was divided into six categories (i.e., accidents due to ground movement, transport machinery, machinery other than transport, explosives, electricity shock, and fall-of-person). These accidents were considered alternatives in the AHP analysis. Three risk factors (i.e., environment, equipment fault, and human error) that caused the accident were considered as criteria in the AHP analysis. The safety expert carefully examined the pattern of accidents and ranked the relative importance of the alternatives with respect to each criterion. This rank was used to build the AHP model using the R programming language and the AHP library (version 0.2.8). The results revealed that the highest number of accidents occurred due to the transport machinery (0.306), followed by accidents due to ground movement (0.232), falls of individuals (0.206), machinery other than transportation (0.122), electricity (0.082), and explosives (0.048). In order to identify the contributing risk factors for each type of mining accident, the weight and the rank of the criteria were determined. The result showed that the most accidents in the six accident categories are due to human error (0.26), followed by environmental (0.25) and equipment faults. The finding of the study provides valuable insights for the mining industry to develop effective strategies to mitigate mine accidents. © The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2024.
ANN model for prediction of bit–rock interface temperature during rotary drilling of limestone using embedded thermocouple technique
(Springer Science and Business Media B.V., 2020) Vijay Kumar, V.K.; Kunar, B.M.; Murthy, C.S.N.
In the present work, an artificial neural network (ANN) model has been developed to predict the bit–rock interface temperature using a newly fabricated grounded K-type thermocouple (range 0–1250 °C) during rotary drilling in a CNC vertical machining center. The data have been taken from experimental observation using an embedded thermocouple technique in the laboratory at room temperature (28 °C) using a masonry drill bit. The observations were made using four different operational conditions, namely drill bit diameter (6, 8, 10, 12 and 16 mm), spindle speed (250, 300, 350, 400 and 450 rpm), rate of penetration (2, 4, 6, 8 and 10 mm min?1) and depth (6, 14, 22 and 30 mm). The ANN has been developed based on the multi layer perceptron neural network (MLPNN) with four different input parameters. A Levenberg–Marquardt (LM) algorithm with feed-forward and backward propagation has been used in this model. The predicted value of the bit–rock interface temperature with the highest R2 value provides a satisfactory result with the experimental data. The training value of RMSE is 1.2127, MAPE is 0.0196 and R2 is 0.9960, while the testing value of RMSE is 1.2770, MAPE is 0.0170 and R2 is 0.9978. The ANN model shows that the proposed MLPNN model successfully predicts the bit–rock interface temperature during the rotary drilling of limestone. © 2019, Akadémiai Kiadó, Budapest, Hungary.
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. Â© 2024 IEEE.
Comparison of the particle size distribution in marble and granite rock samples subjected to ball milling process
(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 ?m 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 ?m was higher in the case of granite sample when compared to a marble sample. Copyright � 2019 by SME.
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 Î¼m 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 Î¼m was higher in the case of granite sample when compared to a marble sample. Â© Â© 2019 by SME.
Effect of thermal response on physical properties during drilling operations-A case study
(2018) Vijay, Kumar, S.; Murthy, C.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.
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. Â© 2017 Elsevier Ltd.
Experimental investigation and statistical analysis of operational parameters on temperature rise in rock drilling
(International Information and Engineering Technology Association info@iieta.org, 2018) Vijay Kumar, V.K.; Kunar, B.M.; Murthy, C.S.
Heat generated during rock drilling, due to friction at the bit-rock interface. Due to which temperature increases, which can influence the thermal stress and subsequent rock failure. In this paper, an attempt is made to present results related to the temperature assessment during rotary drilling of rocks on medium-grained sandstone under controlled laboratory conditions. The experiments were conducted by using embedded thermocouple technique, the thermocouple was placed at a distance of 0.5mm (horizontal) from the bit-rock interface. The influence of operational parameters, i.e., the diameter of the drill bit, spindle speed and rate of penetration of rise in temperature was studied using multiple regression and data analysis was carried out using analysis of variance (ANOVA). The temperature was measured by using embedded thermocouple technique at a depth of 6mm, 14mm, 22mm and 30mm respectively. Regression models were developed for the prediction of temperature at the bit-rock interface. It was observed that the increase in temperature for medium-grained sandstone was from 49 0 C to 74 0 C (51.08%) with an increase in the diameter of the drill bit, spindle speed and rate of penetration. © 2018 International Information and Engineering Technology Association.
Fuzzy Logic-Based Rapid Upper Limb Assessment: A Novel Approach to Evaluate the Postural Risk of Dumper Operators
(Springer, 2023) Kar, M.B.; Mangalpady, M.; Kunar, B.M.
It is proved that the accuracy of the standard Rapid Upper Limb Assessment (RULA) method for evaluating the risk of work-related musculoskeletal disorders (WRMSDs) is often poor. In this paper, a fuzzy logic-based RULA system was developed to address this issue using the MATLAB software package. To evaluate the developed system, 15 dumper operators working in the surface iron ore mine were randomly selected. Video footage of their driving postures was recorded while they were performing different job cycles, such as loading, full-load travel, unloading, and empty travel. The video footage was examined to identify the most frequent driving postures. From this posture, the range of motion of both the axial and appendicular body parts was measured. The measured data were used as input parameter for the fuzzy model to calculate the fuzzy RULA score. The result revealed that 20% of the driving postures adopted by the dumper operators correspond to the medium risk of WRMSDs. Furthermore, the interquartile range of the fuzzy RULA score during dynamic operations was found to be small. This indicates that the fuzzy RULA score remained consistent throughout the dynamic operations. In contrast, the interquartile range exhibited large magnitude in the static operations, thus indicating a greater level of variation in fuzzy RULA score. The correlation test and Bland–Altman analysis were performed to compare the standard and fuzzy RULA scores. This analysis proved that the fuzzy logic-based method is a reliable alternative to the standard method for assessing RULA scores among dumper operators. © 2023, The Institution of Engineers (India).
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. Â© 2024 IEEE.
Measurement of bit-rock interface temperature and wear rate of the tungsten carbide drill bit during rotary drilling
(Tsinghua University Press wyl-dhh@tsinghua.edu.cn, 2020) Vijay Kumar, V.K.; Kunar, B.M.; Murthy, C.S.; Ramesh, M.R.
Rock drilling is an essential operation in mining industries. Temperature at the bit-rock interface plays a major role in the wear rate of the drill bit. This paper primarily focuses on the wear rate of tungsten carbide (WC) drill bit and the interrelationship between temperature and wear rate during rotary drilling operations conducted using a computer numerical control (CNC) machine. The interrelationship between the temperature and wear rate was studied with regard to three types of rock samples, i.e., fine-grained sandstone (FG) of uniaxial compressive strength (UCS) that is 17.83 MPa, medium-grained sandstone (MG) of UCS that is 13.70 MPa, and fine-grained sandstone pink (FGP) of UCS that is 51.67 MPa. Wear rate of the drill bit has been measured using controlled parameters, i.e., drill bit diameter (6, 8, 10, 12, and 16 mm), spindle speed (250, 300, 350, 400, and 450 rpm), and penetration rate (2, 4, 6, 8, and 10 mm/min), respectively. Further, a fully instrumented laboratory drilling set-up was utilized. The weight of each bit was measured after the bit reached 30 mm depth in each type of the rock sample. Furthermore, effects of the bit-rock interface temperature and operational parameters on wear rate of the drill bits were examined. The results show that the wear rate of drill bits increased with an increase in temperature for all the bit-rock combinations considered. This is due to the silica content of the rock sample, which leads to an increase in the frictional heat between the bit-rock interfaces. However, in case of medium-grained sandstone, the weight percentage (wt%) of SiO2 is around 7.23 wt%, which presents a very low wear rate coefficient of 6.33×10?2 mg/(N·m). Moreover, the temperature rise during drilling is also minimum, i.e., around 74 °C, in comparison to that of fine-grained sandstone and fine-grained sandstone pink. In addition, this paper develops the relationship between temperature and wear rate characteristics by employing simple linear regression analysis. © 2019, The Author(s).
Miners’ return to work following injuries in coal mines; Powrót do pracy górników poszkodowanych w wypadkach w kopalni w?gla
(Nofer Institute of Occupational Medicine ul. sw. Teresy od Dzieciatka Jezus 8 Lodz 91-348, 2016) Bhattacherjee, A.; Kunar, B.M.
Background: The occupational injuries in mines are common and result in severe socio-economical consequences. Earlier studies have revealed the role of multiple factors such as demographic factors, behavioral factors, health-related factors, working environment, and working conditions for mine injuries. However, there is a dearth of information about the role of some of these factors in delayed return to work (RTW) following a miner’s injury. These factors may likely include personal characteristics of injured persons and his or her family, the injured person’s social and economic status, and job characteristics. This study was conducted to assess the role of some of these factors for the return to work following coal miners’ injuries. Material and Methods: A study was conducted for 109 injured workers from an underground coal mine in the years 2000-2009. A questionnaire, which was completed by the personnel interviews, included among others age, height, weight, seniority, alcohol consumption, sleeping duration, presence of diseases, job stress, job satisfaction, and injury type. The data was analyzed using the Kaplan-Meier estimates and the Cox proportional hazard model. Results: According to Kaplan-Meier estimate it was revealed that a lower number of dependents, longer sleep duration, no job stress, no disease, no alcohol addiction, and higher monthly income have a great impact on early return to work after injury. The Cox regression analysis revealed that the significant risk factors which influenced miners’ return to work included presence of disease, job satisfaction and injury type. Conclusions: The mine management should pay attention to significant risk factors for injuries in order to develop effective preventive measures. © 2016, Nofer Institute of Occupational Medicine. All rights reserved.
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 200Â m, the axial load acting on the bolt is 15% of the bolt capacity at gallery widths of 4Â m and 5Â m. Whereas for moderate depths 300Â m and 400Â m, its value is found to be 75% at gallery widths 6Â m and 7Â m. But, for deeper depths of 500Â m and more, its values reaches maximum capacity of roof bolts. Also, the roof convergence in junction, for moderate and deeper depths is 80Â mm to 150Â mm, whereas for shallow depths its value is 10â€“25Â mm, at 6Â m, 7Â m and 8Â m gallery widths. Â© 2020, Springer Nature Switzerland AG.
Performance analysis of a 50 MW grid-connected solar PV system for sustainable mining operations
(World Researchers Associations, 2025) Shiva Kumar, B.S.; Kunar, B.M.; Murthy, C.S.N.
The strategic use of renewable resources has become essential for guaranteeing energy security in response to rising energy demands. Mining operations require creative solutions to provide steady energy delivery because of their high energy needs and dependence on continuous power. A technically sound and financially advantageous option for extensive energy integration in these industries is grid-connected photovoltaic (PV) system. The performance of 50 MW grid-connected solar PV power plant in Peddapalli, a major mining hub with ideal solar conditions, is assessed in this study. With an average yearly temperature of 27.3°C and a mean solar insolation of 4.97 kWh/m2, the plant uses a seasonal tilt approach to maximize solar energy capture. A quarterly energy yield of 15,798.192 MWh, a capacity utilization factor (CUF) of 17.68% and a performance ratio (PR) of 86.12% are examples of key performance measures. By successfully integrating solar PV technology into mining operations, operational expenses and carbon emissions are decreased while issues with energy stability are resolved. This study provides helpful insights for utilizing renewable energy in energy-intensive businesses by highlighting the necessity of robust architecture, stable buildings and efficient energy management to maintain a consistent power supply. © 2025, World Researchers Associations. All rights reserved.
Performance Evaluation and Machine Learning Analysis of 3 kW Grid-Connected Bifacial Solar Photovoltaic Systems
(Springer, 2025) Shiva Kumar, B.S.; Kunar, B.M.; Murthy, C.S.N.
Rooftop solar panels with dual functions are a promising sustainable energy source given the world’s rapid urbanization, particularly in densely populated nations like India. Numerous studies have shown how well the System Advisory Model (SAM) performs when estimating the energy yield of bifacial solar photovoltaic (BSPV) systems. This study uses a popular photovoltaic design software to compare the output of a 3 kW grid-connected BSPV system. The SAM simulation forecasts a production of 4864.5 kWh, whereas the empirical data shows that the system’s yearly energy output is 4321.7 kWh. The operational plant’s performance ratio is about 81.6%, which closely agrees with the 81.2% that SAM projected. Further, the relationship between various input parameters and power output of a BSPV generated from SAM simulation results was investigated using machine learning (ML) models. Among the ML models tested, the linear regression (LR) model delivered the best performance for a 3 kW BSPV system in a specific location. © The Institution of Engineers (India) 2025.
Postural analysis of dumper operators and construction workers – a case study
(Books and Journals Private Ltd., 2021) Kunar, B.M.; Mangalpady, M.; Kar, M.B.
This case study aims at assessing and understanding the level of ergonomics in manual material handling tasks (loading, granite cutting, concrete mixing, brickwork, and plastering) of civil construction workers and dump truck drivers working in Indian opencast mines. The study involves the determination of the level of musculoskeletal disorder and predicting the most affected body parts due to incorrect working posture. The comprehensive methodology involved in this study includes rapid upper limb assessment (RULA) and rapid entire body assessment (REBA) techniques to find the risk involved in the working posture of the construction workers and dump truck drivers. The study showed that posture adopted in civil construction work and dump truck operators (loading and unloading task) are ergonomically incorrect and may cause musculoskeletal disorder (MSD) related problems in the future. This study also showed that the trunk and wrist are the most affected parts of the body in construction workers and the neck and wrist in case of the dumper operator while performing different tasks. © 2021, Books and Journals Private Ltd.. All rights reserved.