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 Investigation of iron ores based on the bond grindability test(American Institute of Physics Inc. subs@aip.org, 2020) Hanumanthappa, H.; Vardhan, H.; Raj, G.R.; Kaza, M.; Sah, R.; Sinha, A.; Shanmugam, B.K.Grinding is a process of reduction of lumps to powder depending on the requirement of particle size and particle shape. The present investigation involves the identify the physical properties of three different types of iron ores by using Bond ball mill. The result shows that the maximum Bond work index of 14 KWh/mt was obtained for 'A' type iron ore sample. The Bond work index for 'B' and 'C' type iron ore sample are of 11 and 10 KWh/mt. The variation of BWI of three iron ore sample may be varied during the geological formation of each iron ore sample. The output product of three iron ore sample composed of three different size fractions when ground in Bonds ball mill. Based on the BWI and output product size of three iron ore samples are classified as hard ore ('A' type iron ore sample), medium hard ore ('B' type iron ore sample) and soft ore ('C' type iron ore sample). The classification of different types of iron ore helps to run the plant scale ball mill by setting suitable operating parameters to the ball mill. © 2020 Author(s).Item Investigation on grinding wear behaviour of austempered ductile iron as media material during comminution of iron ore in ball mills(2011) Hebbar, R.An attempt has been made to assess the grinding wear behaviour of austempered ductile iron (ADI) as media material in comminution of Kudremukh haematite iron ore in a ball mill. Spheroidal graphite (S.G) iron balls were austenitised at 900°C for one hour and austempered at 280°C and 380°C for different time durations. These materials were characterized by measuring hardness, carrying out X-ray diffraction analysis, studying microstructures using scanning electron microscope (SEM). Grinding wear behaviour of ADI was assessed during wet grinding at different pH of the mineral slurry. The wear resistance of ADI was compared with that of forged En 31 steel balls under similar grinding conditions. It was found that ADI balls austempered at 280°C for 30 minutes which contains lower bainite registered superior wear resistance. It was also noted that the wear resistance of ADI was more at higher pH range of the slurry. © 2011 TIIM, India.