Journal Articles
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Item Sound level produced during rock drilling vis-à-vis rock properties(2011) Rajesh Kumar, B.; Vardhan, H.; Govindaraj, M.The process of drilling, in general, always produces sound. Though sound is used as a diagnostic tool in mechanical industry, its application in predicting rock property is not much explored. In this study, an attempt has been made to estimate rock properties such as uniaxial compressive strength, Schmidt rebound number and Young's modulus using sound level produced during rotary drilling. For this purpose, a computer numerical controlled vertical milling centre was used for drilling holes with drill bit diameters ranging from 6 to 20. mm with a shank length of 40. mm. Fourteen different rock types were tested. The study was carried out to develop the empirical relations using multiple regression analysis between sound level produced during drilling and rock properties considering the effects of drill bit diameter, drill bit speed and drill bit penetration rate. The F-test was used to check the validity of the developed models. The measured rock property values and the values calculated from the developed regression model are fairly close, indicating that the developed models could be efficiently used with acceptable accuracy in prediction of rock properties. © 2011 Elsevier B.V.Item A critical review on estimation of rock properties using sound levels produced during rotary drilling(CAFET INNOVA Technical Society cafetinnova@gmail.com 1-2-18/103, Mohini Mansion, Gagan Mahal Road, Domalguda, Hyderabad 500029, 2012) Masood; Vardhan, H.; Mangalpady, M.; Rajesh Kumar, B.This paper summarizes the critical review on estimation of rock properties using sound levels produced during rotary drilling. In this paper an overall emphasis has been made to summarize the importance of sound level produced during drilling by considering various parameters like drill bit speed, penetration rate, drill bit diameter, type of drill bit and equivalent sound level produced during drilling for the estimation of rock properties. Further an attempt has also made to include the application of ANN modeling and acoustic emission in estimating rock properties. © 2012 CAFET-INNOVA TECHNICAL SOCIETY.Item Modelling operating speed and speed differential on intermediate lane rural roads(2012) Sowmya, N.J.; Ravi Shankar, A.U.; Anjaneyulu, M.V.L.R.Geometric design elements play an important role in defining the operational efficiency of any roadways. Considerable research has been undertaken worldwide to explore the design consistency concept including identifying potential consistency measures and developing models to estimate them. The main objective of this study is to investigate the design consistency of intermediate lane highways existing in Dakshina Kannada district of Karnataka state based on operating speed and speed differential models. The speed measurements are taken at the mid of tangent section and start of the curve during daylight, off-peak periods and under dry weather conditions. The multiple linear regression analysis technique in SPSS (Statistical Package for Social Sciences) software is used for model estimation. Both operating speed (85th percentile speed) and 85th percentile speed differential measures are used with geometric data to identify the design consistency of horizontal curves. A comparative study is performed to identify the variation between these two speed measures. Operating speed and speed differential models for intermediate lane rural roads are presented in this paper. © 2012 CAFET-INNOVA TECHNICAL SOCIETY.Item Regression analysis and ANN models to predict rock properties from sound levels produced during drilling(Elsevier Ltd, 2013) Rajesh Kumar, B.; Vardhan, H.; Govindaraj, M.; Vijay, G.S.This study aims to predict rock properties using soft computing techniques such as multiple regression, artificial neural network (MLP and RBF) models, taking drill bit speed, penetration rate, drill bit diameter and equivalent sound level produced during drilling as the input parameters. A database of 448 cases were tested for determination of uniaxial compressive strength (UCS), Schmidt rebound number (SRN), dry density (?), P-wave velocity (Vp), tensile strength (TS), modulus of elasticity (E) and percentage porosity (n) and the prediction capabilities of the models were then analyzed. Results from the analysis demonstrate that neural network approach is efficient when compared to statistical analysis in predicting rock properties from the sound level produced during drilling. © 2012 Elsevier Ltd.Item Quarter circular breakwater: Prediction of transmission using multiple regression and artificial neural network(Marine Technology Society Inc. mtsdir@erols.com, 2014) Goyal, R.; Singh, K.; Hegde, A.V.The physical model study of coastal structures is a nonlinear process influenced by innumerable parameters. As a result of a lack of definite systems, intricacies, and high costs involved in the physical models, we need a simple mathematical tool to predict wave transmission through quarter circular breakwater (QBW). QBW is a state-of-theart breakwater essentially based on the exploitation of the concepts of semicircular breakwater. This paper discusses the use of soft computing tools such as MATLAB based multiple regression (MR) and artificial neural network (ANN) to predict the wave transmission coefficient of QBW. To assess the accuracy of the proposed model and its ability to forecast, correlation coefficient and mean squared error are availed. On comparing the results obtained from MR and ANN, it is concluded that ANN gives more accurate results and can be used as a powerful tool for the modeling of hydrodynamic breakwater transmission through QBW. It serves as a viable alternative to the conventional physical model to simulate the hydrodynamic transmission performance of QBW.Item Prediction of peak particle velocity using multi regression analysis: case studies(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2017) Ram Chandar, K.; Sastry, V.R.; Hegde, C.; Shreedharan, S.Ground vibrations produced from blasting operations cause structural vibrations, which may weaken structure if it occurs at the resonant frequency. Measurable parameters associated with ground vibrations are peak particle velocity (PPV), amplitude and dominant frequency (frequency of highest PPV amongst translational, vertical and horizontal vibrations). In this paper, an attempt is made to correlate measurable parameters associated with ground vibrations with scaled distance. Using the correlated data, it was found that a predictor equation can be determined for the amplitude and PPV, but not for dominant frequency as it is dynamic and depends upon infinitesimal changes that occur within a number of other parameters. Another analysis of the same is made using multiple linear regression analysis. This included predicting the PPV using scaled distance, maximum charge per delay, amplitude as predictors. A considerable improvement is seen in the prediction on adding the interaction of the predictors in multiple regressions. A comparison of different combination of predictors is made so as to assess the best combination giving the best R2 value for the given mine. Frequency is also plotted using the aforementioned method. However, it was found that the dominant frequency cannot be predicted with high accuracy even with this method. © 2016 Informa UK Limited, trading as Taylor & Francis Group.Item Assessment of coastal water quality along south west coast of India using multile regression analysis on satellite data(National Institute of Rural Development Rajendranagar Hyderabad 500 030, 2018) Jose, D.M.; Mandla, V.R.; Subbarao, S.S.V.; Rao, N.S.; Moses, S.A.The coastal waters being the ultimate receiver of all the wastes, shows a declining trend in its quality. It is of immense importance to know the extent of pollution for its monitoringandmanagemenlMeasurementofdissolvedoxygen (DO), biologicaloxygen demand (BOD), pH and fecal coliform (FC) are vital in water quality monitoring and assessment studies. Usually these parameters are determined by analysing water samples collected from various locations. Since this is tedious and expensive, it is limited to small scales. In this paper, an effort has been made to quickly assess the quality of coastal waters of Kerala directly from the satellite imagery by estimating National Sanitation Federation Water Quality Index (NSFWQI) along with DO, BOD, pH and FC. Multiple linear regression is used to develop statistically significant models using Sea Surface Temperature (SST) and Remote Sensing Reflectance (Rrs) from Moderate Resolution Imaging Spectroradiometer (MODIS) and in-situ data available on DO, BOD, pH and FC. The models when validated showed good correlation between in situ values and predicted values with r values ranging from 0.73 (p=0.001) for DO to 0.89 for NSFWQI (p=0.018). Spatial maps are generated showing the distribution of these parameters along the coast. The parameters in the study are checked to see if they are in compliance with the standards. The study gives models to estimate the daily distribution of these parameters along the coast using MODIS data. Thus, appropriate control measures could be adopted to limit the effect on susceptible rural population. © 2019 JPR Solutions. All rights reserved.Item Experimental and Statistical Evaluations of Strength Properties of Concrete with Iron Ore Tailings as Fine Aggregate(American Society of Civil Engineers (ASCE) onlinejls@asce.org 1801 Alexander Bell DriveGEO Reston VA 20191 Alabama, 2020) Gayana, G.B.; Ram Chandar, R.C.Iron ore tailings (IOT) are the by-products of iron ore beneficiation, and these tailings are disposed of in several tons annually in quarries, landfills, and tailings dams, causing environmental issues. Various researchers have attempted to study the properties of IOT and the use of them in concrete as a building material. The present research aims to investigate the potential use of alccofine, a microfine particle of slag, as a cement replacement and IOT as fine aggregates in concrete. Experimental results indicated that the concrete workability decreased with an increase in the IOT-alccofine content and the maximum compressive strength (CS) obtained was 70.00, 68.67, and 65 MPa respectively at 40%, 30%, and 20% IOT-alccofine dosage for varying water-to-cement (w/c) ratios of 0.35, 0.40, and 0.45 respectively. Similarly, the flexural strength (FS) and splitting tensile strength (STS) increased with an increase in IOT-alccofine content. A statistically fitted multiple regression analysis was performed for all the mechanical properties to evaluate the significant level of concrete containing alccofine and IOT in concrete. These prediction models have high accuracy and low bias and the validation process represented that the equations can perform excellently in predicting the IOT-alccofine concrete properties. © 2019 American Society of Civil Engineers.Item Multiple regression model for prediction of rock properties using acoustic frequency during core drilling operations(Taylor and Francis Ltd., 2020) Vijaya Kumar, V.; Vardhan, H.; Murthy, C.S.N.The primary purpose of this study is the quantification of rock properties uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), density and abrasivity, using sound signal dominant frequencies produced during diamond core drilling operations. Rock drilling operations were performed on seven different types of rock samples, using a computer numerical control (CNC) drilling machine. Using the multiple regression analysis, satisfactory mathematical equations were developed for various physico-mechanical rock properties, as well as dominant frequencies of the sound level were generated during diamond core drilling operations. The developed prediction models demonstrated a good regression coefficient between the rock properties and dominant frequencies i.e. the R2 values are 82.50%, 78.41%, 79.40%, and 93.24% for UCS, BTS, density and abrasivity, respectively. The performances indices are: (i) root-mean-square error (RMSE) are 0.102754, 1.241652, 0.396727, and 0.697889 for UCS, BTS, density and abrasivity, respectively; (ii) values account for (VAF) is 82.50008%, 78.41137%, 79.40137%, and 93.23596% for UCS, BTS, density and abrasivity, respectively. Presently, it is in the early stages of development towards the prediction of rock properties using dominant frequencies with the help of audio signal processing in the rock drilling operation. The developed prediction models can be utilised at the early stages of mining and civil engineering projects, for the quantification of rock properties using sound signal dominant frequencies. © 2019 Informa UK Limited, trading as Taylor & Francis Group.Item Development of an equation to predict blast induced ground vibrations of open cast lime stone mine by using Multiple Linear Regression (MLR)(World Researchers Associations, 2025) Appani, R.; Harsha, V.; Subrahmanyam, S.K.V.This study focuses on predicting ground vibrations generated by blasting activities in open cast limestone mining by integrating blast design parameters with conventional variables. Blasting is a critical operation for the effective removal of overburden and mineral extraction, but it can lead to significant adverse effects, particularly ground vibrations, which pose challenges for both mining and environmental engineers. Conventional methods for estimating these vibrations typically focus on the distance from the blast site and the maximum charge per delay as key independent variables. Recognizing the substantial impact of blast design on vibration levels, this research employs multiple linear regression analysis to incorporate additional factors such as blast design elements. By developing a more comprehensive predictive model, the study aims to enhance the accuracy of ground vibration forecasts, ultimately contributing to safer and more sustainable mining practices. © 2025, World Researchers Associations. All rights reserved.