Browsing by Author "Ram Chandar, K."

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A Critical Comparison of Regression Models and Artificial Neural Networks to Predict Ground Vibrations
(Springer International Publishing, 2017) Ram Chandar, K.; Sastry, V.R.; Hegde, C.
Blasting is important and an essential prerequisite in any opencast mine for fragmenting hard deposits. Blasting always produces unwanted effects like ground vibrations, noise and fly rock; among which ground vibrations effect is more on surrounding structures. Propagation of ground vibrations can lead to destruction of surrounding structures. Prediction of ground vibrations especially in terms of peak particle velocity is beneficial as opposed to conventional data monitoring techniques which can be expensive as well as time consuming. This paper uses predictors to estimate the intensity of ground vibrations and compares different methods of prediction methods like linear regression, multiple linear regression, non linear regression (NLR) and artificial neural networks. Intensity of ground vibrations generated from blasting operations was monitored in three different mines of limestone, dolomite and coal; obtaining about 168 ground vibration recordings in total. The statistical modelling or data-driven modeling has shown promise in the prediction of blast vibrations. Proposed a system of introducing site specific rock parameters like poison’s ratio, uniaxial compressive strength of rock and Young’s modulus to improve the correlation coefficient using statistical modelling (commonly called feature engineering in machine learning circles). © 2016, Springer International Publishing Switzerland.
A study on suitability of iron ore overburden waste rock for partial replacement of coarse aggregates in concrete pavements
(Institute of Physics Publishing helen.craven@iop.org, 2018) Gayana, B.C.; Ram Chandar, K.
Concrete is the most widely used construction material, several sustainable materials are under investigation to reduce the impact of its production processes, by considering partial replacement of natural constituents with the waste materials without compromising the durability and strength of concrete in view to reduce both the demand of raw material and effective waste disposal of millions of tons from different sources. There has been a constant research to substitute the natural aggregates with other waste materials to develop sustainable pavements. In the process, the waste produced from Mining industry is one of such source. The aim of this study is to evaluate the suitability of iron ore waste as partial replacement of coarse aggregates in concrete with reference to the conventional materials. Physico-chemical properties and aggregate tests such as crushing, abrasion, impact, shape test, the specific gravity and water absorption were determined as per Standards and the results were within the limits indicating their applicability as a pavement material. Partial replacement by 20%, 40%, 60%, 80% and 100% with waste rock was tested for its mechanical properties and it was found that, 40% replacement of waste rock yielded highest compressive strength compared to the control mix. Regression analysis was carried out to predict the performance analysis of the compressive strength of the samples with IOT.The performance prediction analysis shows that curing days influencing more compared to % replacement with IOT. Â© Published under licence by IOP Publishing Ltd.
An experiment investigation on physical and mechanical properties of high strength concrete with suitable admixture
(Trans Tech Publications Ltd ttp@transtec.ch, 2019) Gayana, B.C.; Shashanka, M.; Rao, A.N.; Ram Chandar, K.
Concrete is an essential construction material. Even-though conventional concrete performs and satisfy the structures under normal conditions, a few special situations require very high compressive strength of concrete. An experimental investigation is done to develop high strength concrete with suitable admixtures and steel fibers. The properties of fresh and hardened concrete with alccofine as partial replacement for binder and poly-carboxylate ether (Glenium 8233) and steel fibers is investigated for the workability and mechanical properties i.e., compressive, splitting tensile and flexural strength of concrete. Based on the results, the strength increased with the addition of alccofine compared to the control mix. Hence, by optimum percentage of alccofine, high strength of concrete of 112 MPa can be obtained. Â© 2019 Trans Tech Publications Ltd, Switzerland.
Assessment of blast performance based on energy distribution
(2008) Sastry, V.R.; Ram Chandar, K.
Effective utilization of explosive energy in and around the blasthole gives better fragmentation with reduced unwanted results. Ineffective utilization of energy leads to dissipation of energy in the form of ground vibrations, noise, fly rock, back break etc. An attempt is made in this paper to present the results of the study on blast performance based on the energy dissipated into ground vibrations by analyzing the wave forms and estimating the energy distribution around blastholes by simulating blast patterns using JkSimBlast software.Generally, ground vibrations generated due to blasting operations are monitored at a known distance from blast site with a geophone / ground vibration monitor, in three mutually orthogonal, i.e longitudinal, transverse and vertical directions. Using such wave forms, the work done (energy) was estimated for all the signals in three directions, based on the principle that the area within the curve is 'work done'. Summation of energy in all three directions was considered to estimate the total work done (energy) from each blast event. Fourteen blasts were conducted in a limestone mine in southern India in 7 pairs. In each pair, one blast was conducted with shocktube initiation and other one with detonating cord initiation, keeping initiation patterns and all other parameters constant. Ground vibrations monitoring distance was also kept constant in each pair of blasts. The events were analyzed and the work done was estimated for each event. It was found that the detonating cord initiated blasts dissipated higher energy in the form of ground vibrations compared to shocktube initiated blasts. The blast performance was assessed based on the energy distribution around the blastholes. A comparative analysis was done with both the initiation systems. Once the blasthole is initiated, the explosive energy dissipates into the rock mass in the form of strain waves. The energy will be high at the vicinity of the blastholes, and it dissipates gradually with distance. If the energy is higher than the breaking strength of the rock mass the rock mass gets fragmented. Based on this concept, the blast patterns were simulated using JkSimBlast software. Around the blastholes, the energy distribution was divided into four zones / ranges. It was found that the area of highest energy zone around the blastholes is larger for shock tube initiated blasts than the detonating cord initiated blasts, which indicates effective energy utilization with shocktube initiation system.
Assessment of blast performance based on energy distribution
(2008) Sastry, V.R.; Ram Chandar, K.
Effective utilization of explosive energy in and around the blasthole gives better fragmentation with reduced unwanted results. Ineffective utilization of energy leads to dissipation of energy in the form of ground vibrations, noise, fly rock, back break etc. An attempt is made in this paper to present the results of the study on blast performance based on the energy dissipated into ground vibrations by analyzing the wave forms and estimating the energy distribution around blastholes by simulating blast patterns using JkSimBlast software.Generally, ground vibrations generated due to blasting operations are monitored at a known distance from blast site with a geophone / ground vibration monitor, in three mutually orthogonal, i.e longitudinal, transverse and vertical directions. Using such wave forms, the work done (energy) was estimated for all the signals in three directions, based on the principle that the area within the curve is 'work done'. Summation of energy in all three directions was considered to estimate the total work done (energy) from each blast event. Fourteen blasts were conducted in a limestone mine in southern India in 7 pairs. In each pair, one blast was conducted with shocktube initiation and other one with detonating cord initiation, keeping initiation patterns and all other parameters constant. Ground vibrations monitoring distance was also kept constant in each pair of blasts. The events were analyzed and the work done was estimated for each event. It was found that the detonating cord initiated blasts dissipated higher energy in the form of ground vibrations compared to shocktube initiated blasts. The blast performance was assessed based on the energy distribution around the blastholes. A comparative analysis was done with both the initiation systems. Once the blasthole is initiated, the explosive energy dissipates into the rock mass in the form of strain waves. The energy will be high at the vicinity of the blastholes, and it dissipates gradually with distance. If the energy is higher than the breaking strength of the rock mass the rock mass gets fragmented. Based on this concept, the blast patterns were simulated using JkSimBlast software. Around the blastholes, the energy distribution was divided into four zones / ranges. It was found that the area of highest energy zone around the blastholes is larger for shock tube initiated blasts than the detonating cord initiated blasts, which indicates effective energy utilization with shocktube initiation system.
Assessment of objective based blast performance: Ranking system
(2013) Sastry, V.R.; Ram Chandar, K.
Rock fragmentation using chemical energy is commonly followed for fragmenting and displacing the rock mass in mining, civil and other excavation projects. In case of mines, the objective of rock fragmentation is to get a uniform sized material to suit the subsequent operations like loading, hauling and crushing. In case of civil engineering projects like canals, tunnels, it is to provide the space for some facilities and the material produced may not be having a specific use. In case of blasting near to the human habitats or important structures like dams, ground vibrations generated should be within permissible safe limits, along with proper fragmentation. Cost reduction is also a prime factor in all the cases. In general, assessment of blast performance refers to fragmentation assessment. However, based on the objective, the approach to blast design may be different. An attempt is made through this paper to discuss different blast performance assessment methods, through a case study and a ranking system is proposed. Field studies were carried out in a limestone mine in southern India, using eight controlled blasts by changing the initiation system, initiation pattern and maintaining same blast geometry parameters. Blast performance was assessed based on fragmentation using digital image processing technique, energy distribution, and productive yield and powder factors resulting from the blasts. Rankings were given to different blasts as per the performance.
Classification of Stability of Highwall During Highwall Mining: A Statistical Adaptive Learning Approach
(Kluwer Academic Publishers, 2015) Ram Chandar, K.; Hegde, C.; Yellishetty, M.; Gowtham Kumar, B.
The depleting coal deposits day by day required the introduction of novel methods of mining like highwall mining. Highwall mining is a method of extraction of coal blocked in the highwall. The method involves considerable challenges in the area of roof control and most importantly the stability of the highwall itself. Highwall mining has gained considerable importance all over the world, owing to the fact that the coal otherwise would not be extracted forever. This paper aims to assess the influence of varying conditions which can affect the stability of the highwall during highwall mining. The effect of gallery length, width of pillar and number of galleries are systematically studied through field investigations where a highwall mining was adopted first time in India. Initially, assessment was carried out using a numerical modelling approach and then the stability of the highwall is classified using multilinear regression, logistic regression and naive Bayes classifier. This will provide a mechanism to predict the stability of the highwall in future cases of similar conditions. The classification is done using statistical adaptive learning methods and a comparison of the methods is done. © 2014, Springer International Publishing Switzerland.
Computer aided slope stability analysis
(2006) Sastry, V.R.; Ram Chandar, K.; Santosh, M.
Primary purpose of slope stability analysis in most of the engineering applications is to provide safe and economic design of slopes that prevent failure. The analysis technique chosen depends on both site conditions and potential mode of failure which depends upon the rock mass characteristics. Various slope stability analysis techniques include physical, numerical and analytical methods. Physical modeling is a time consuming process and a costly affair, while analytical method involves past experiences, it is site specific and depends upon various parameters which are difficult to quantify. Numerical analysis with sophisticated softwares provides an accurate solution within short duration. This paper presents an in-house developed software package called "V-slope" to analyze and interpret the slope with options for suggesting suitable safety measures based on the nature of slope. Slip circle and tension crack techniques were considered for analysis. The slope profile for different factor of safety (FOS) values will be displayed on the screen for easy understanding. In case the FOS is lower than the required, the V-slope gives suggestive measures. In case of temporary slopes the only way by which slope failure can be prevented is by decreasing the slope angle and in such cases the program gives additional volume of material to be excavated and the likely additional cost incurred for various slope angle options. For permanent slopes, option is provided for designing the soil nails, i.e. number of bolts required, length, diameter and spacing of the bolts etc. Finally the V-slope is compared with a comprehensive commercial software package Slide and the results were found very much satisfactory.
Computer aided slope stability monitoring
(2017) Kumar D.; Ram Chandar, K.
Slope stability accidents are one of the leading causes of fatalities at surface mining operations. Monitoring of the slopes of surface mines can prevent loss of life, destruction of equipment, loss of ore reserves and closure of the mine. In this paper, an attempt is made to review the recent developments in slope stability monitoring system. Zigbee based Wireless Sensor Networks (WSNs) of short distance, low- complexity, low power consumption, low data rate, low-cost, twoway and wireless communication solution for slope stability monitoring system is discussed. A comparison of slope monitoring systems has been done by considering different parameters such as accuracy, update rate, range, slope coverage, weather conditions etc.
Experimental and Statistical Evaluations of Strength Properties of Concrete with Iron Ore Tailings as Fine Aggregate
(2020) Chinnappa, G.B.; Ram Chandar, K.
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.
Explosive energy is the most commonly used form of energy to fragment rock mass/overburden and mineral deposits in the mines. Fragmentation obtained in the blasting process influences the downstream costs like loading cost, transportation cost, processing cost, etc. Among the various factors which influence the rock fragmentation, initiation system is one of the most important because presently much research is going on in this area of rock blasting. Some field studies were taken up with conventional detonating cord initiation and shock-tube-based NONEL initiation systems to study the influence of initiation systems on rock fragmentation. Fragmentation analysis was done using the boulder count method and image analysis. It was found that the shock-tube initiation gives 33% less boulders and 31% lesser K50 value compared to detonating cord initiation. © 2004 Taylor & Francis Ltd.
(Taylor and Francis Ltd., Shock tube initiation for better fragmentation: A case study) Sastry, V.R.; Ram Chandar, K.
2004
Physico-mechanical properties of concrete with industrial waste-A case study
(Avestia Publishing info@avestia.com, 2019) Gayana, B.C.; Shashanka, M.; Rao, A.N.; Ram Chandar, K.
A few waste materials, such as demolition waste, steel slag, quarry dust, fly ash are dumped in landfills. This causes environmental issues and pollution. The present study aims to examine the effect of replacing two types of waste materials i.e., quarry dust and steel slag as partial replacement of cement and sand respectively. Cement was replaced partially with quarry dust between 5 to 20% with 5% intervals and sand was replaced by 75% steel slag consistently for all the concrete mixes. The concrete cubes, beams and cylinders were tested for their strength characteristics by measuring compressive strength, flexural strength and splitting tensile strength. The maximum increase of 4%, 34% and 38% in compressive, flexural and splitting tensile strength respectively was observed with 15% quarry dust replaced with cement and 75% steel slag replaced with sand. Based on the present experimental study, partial replacement of these waste materials shall mitigate the issues occurring due to storage and also by utilizing these materials in concrete as replacement for cement and sand resulting in higher strength properties compared to the naturally available construction materials. Â© 2019, Avestia Publishing.
Prediction of Bond's work index from field measurable rock properties
(Elsevier B.V., 2016) Ram Chandar, K.; Deo, S.N.; Baliga, A.J.
In mineral beneficiation, grinding is the final stage in the process of size reduction. The power consumed in this stage is higher when compared to other stages, owing to increased size reduction ratio. The primary purpose of grinding is to reduce the particle size to optimum so that mineral particles can be extracted more economically. Decision making plays an important role here, as it involves determining and comparing the energy that is required to perform the grinding process and also determining the amount of minerals lost as the coarser size particles are arrived at in mineral beneficiation. In general, Bond's work index is used to determine the grinding efficiency and also to calculate the power requirement. The process is very time consuming and it requires skilled labor and specialized mill. A systematic investigation was carried out to predict Bond's work index using simple field measurable properties of rocks. Tests were conducted on Basalt, Slate and Granite using a laboratory scale ball mill and rock properties namely density, Protodyakonov's strength index and rebound hardness number were determined. The results were analyzed using artificial neural networks and regression analysis. Mathematical equations were developed to predict Bond's work index based on rock properties using regression analysis, which resulted a very good correlation co-efficient values. © 2016 Elsevier B.V.
Prediction of Dust Dispersion from Drilling Operation in Surface Mines
(National Institute of Technology Karnataka, Surathkal, 2017) Nagesha, K. V.; Ram Chandar, K.; Sastry, V. R.
Dust pollution causes various problems within and outside the mine environment. Dust emanating from different activities directly affects the people working in the mines. Dust deposition on Heavy Earth Moving Machinery (HEMM) and other machinery can damage the machinery. The various activities involved in mining to extract ore from earth lead to dust pollution. Especially, Particulates Matters (PM) present in mines area lead to various human respiratory diseases. Aerodynamic diameter of particles having less than 10µm called as PM10. Among all activities involved in mining, drilling activity is more important and it produces PM particles. Dust prediction models are necessary to identify the quantity of dust expected from drilling so that dust control strategies can be taken up at mine site. In order to develop dust prediction models in surface mines, field investigations were carried out in eight opencast mines. Among them, three are opencast coal mines, two are limestone mines and the remaining are granite quarries. Two opencast mines, two granite quarries and one limestone mine data was used to develop mathematical models. One coal mine data, one granite quarry data and one limestone mine data was used to validate developed models. To develop dust prediction models, 169 sets of data for emission model and 184 sets of data for concentration model from different rock formations were considered. Field monitoring was carried out according to Central Pollution Control Board (CPCB) standards. Rock samples were collected from different locations of mines and brought to the laboratory for determining required physico-mechanical properties according to International Society for Rock Mechanics (ISRM) suggested methods. Various rock properties considered are Moisture content, Density, Compressive strength and Schmidt rebound hardness number. Artificial Neural Network (ANN) analysis was carried out for different combinations of hidden layers. Feed Forward Neural Network with back–propagation algorithm was used to train the network. Four types of algorithms were used for development of models andii their performances were evaluated using Values Account For (VAF), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). Network was trained using different types of Back-propagation algorithms such as Trainrp, Trainscg, Traincgp, Trainlm. The algorithm ‘Trainlm’ has high MAPE and less RMSE. Value of RMSE is 6.68, MAPE value is 33 and VAF value is 79.90. Trainlm algorithm was found to be the best method for prediction of PM10 from drilling operation and was used for comparison. The predicted values from ANN method and field measured values were compared. The R2 value for emission model is 0.81 and for concentration model it is 0.80, which shows very good correlation and gave better forecasting results using ANN method. Analysis showed that the field data is error free. But, ANN cannot give mathematical equations, so multi regression analysis was used for the development of models. Multiple regression analysis method was used to determine the relation between multiple independent variables (input) and single dependent variable (output). Mathematical equations were developed using statistical software, namely Statistical Package for the Social Sciences (SPSS). In order to assess the influence of input parameters on output, stepwise regression was used. Assessment of SPSS software based predicted values were evaluated by statistical parameters like coefficient of determination (R2), ANOVA, parameters coefficients and Variable Influencing Factor (VIF). The parameters chosen were found to be statistically more significant. The predicted values from multiple regression method and field measured values were compared. The R2 value for emission model is 0.82 and for concentration model it is 0.81, for 95% level of confidence, which shows very good correlation. A comparison was made between Multiple Regression Analysis Model and ANN model results. ‘Trainlm’ algorithm revealed that, MRA model gave better performance than ANN with lower RMSE and high MAPE values and higher prediction accuracy (VAF) value for all the predicted variables. The VAF values obtained for MRA is 87.1 per cent,iii RMSE is 3.22 and MAPE is 33.7 per cent. Finally, to validate developed models, field measured values were compared with SPSS model predicted values and USEPA predicted values. Analysis revealed that USEPA was giving around 99 per cent error and SPSS model was giving error of within 20 per cent. Therefore, SPSS models developed as part of this research work may be used for dust prediction from drilling activity under Indian Geo-Mining and weather conditions.
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.
A study on suitability of iron ore overburden waste rock for partial replacement of coarse aggregates in concrete pavements
(2018) Gayana, B.C.; Ram Chandar, K.
Concrete is the most widely used construction material, several sustainable materials are under investigation to reduce the impact of its production processes, by considering partial replacement of natural constituents with the waste materials without compromising the durability and strength of concrete in view to reduce both the demand of raw material and effective waste disposal of millions of tons from different sources. There has been a constant research to substitute the natural aggregates with other waste materials to develop sustainable pavements. In the process, the waste produced from Mining industry is one of such source. The aim of this study is to evaluate the suitability of iron ore waste as partial replacement of coarse aggregates in concrete with reference to the conventional materials. Physico-chemical properties and aggregate tests such as crushing, abrasion, impact, shape test, the specific gravity and water absorption were determined as per Standards and the results were within the limits indicating their applicability as a pavement material. Partial replacement by 20%, 40%, 60%, 80% and 100% with waste rock was tested for its mechanical properties and it was found that, 40% replacement of waste rock yielded highest compressive strength compared to the control mix. Regression analysis was carried out to predict the performance analysis of the compressive strength of the samples with IOT.The performance prediction analysis shows that curing days influencing more compared to % replacement with IOT. � Published under licence by IOP Publishing Ltd.
Use of iron ore mine tailings in infrastructure projects
(Inderscience Enterprises Ltd., 2019) Shubhananda Rao, P.; Gayana, B.C.; Ram Chandar, K.
Utilisation of iron ore tailings in bricks as a replacement for sand will help in sustainable and greener development. The literature shows the potential use of iron ore tailings as a replacement of natural fine aggregates. As natural sand reserves are depleting day by day, there is a need for substitution for sand in bricks. A comprehensive overview of the published literature on the use of iron ore tailings and other industrial waste is being presented. The effects of various properties such as compressive strength, thermal conductivity and durability of bricks have been presented in this paper. © 2019 Inderscience Enterprises Ltd.