Fly Rock Research Articles

Analysis of the Influence of Burden Deviation from the Designed One on the Intensity of the Blast Vibration

This paper presents an analysis of the influence of burden deviation from the designed one on the intensity of blasting vibrations through the use of laboratory and field examinations. By definition, the burden represents the shortest distance from the axis of an explosive column charge to the free surface. It should be measured along the entire hole length, although, in practice, it is often measured only on the bench surface as the shortest distance from the axis of the explosive column charge to the crest. The real surface of the bench slope (free face) can be very irregular and should be considered during every blast. The deviation of burden in the blast pattern represents a serious problem in the field during blasting operation. Burden deviation from the designed one can be greater or lesser, affecting the results of blasting through poor fragmentation and sometimes causes unwanted effects like increased blasting vibrations or fly rock. The influence of burden deviation on the intensity of blasting vibrations was tested on a laboratory model, where 8 mm diameter holes were drilled into blocks with certain dimensions. The small explosive charges placed in blastholes were initiated. The design burden was set at 30 mm, as the distance from blastholes to the free face of the blocks. Any deviation in distance greater than the designed burden was taken as a parameter for comparison. During each initiation, vibrations were measured using a seismic instrument at a distance of 150 mm from the borehole. At the same time, the free face in the front of the blastholes was photographed to create a detailed 3D model of the blasted surface of the blocks for each blasting. Each measurement is presented on a diagram and classified depending on the values of the burden in the cases where the value of the burden is equal to the designed one, as well as any deviation that is smaller or larger than 30 mm. A total of 55 tests were carried out. The results were analyzed, and the model of dependence of each burden deviation from the designed one on the intensity of blasting vibrations was established under laboratory conditions. To verify the model, the same experiments were also applied in the field. The basic parameter of the model, the coefficient K, which represents the ratio of peak particle velocity and the surfaces of the blasted material from laboratory and field testing, indicates that there is a connection between these values. The deviation of the coefficient K, obtained from laboratory and field measurements, was 5.5%.

A newly developed blasting cut in tunnels; application of “combined method” in small to medium-sized tunnels

Drilling and blasting method have been widely used for driving tunnels in hard rock. When designing a blast operation especially in case of long tunnels, the primary objective of contractors is to ensure optimized blast parameters for achieving the most economical and time-saving technique of excavation. Choosing a proper blasting cut has a crucial role in the successfulness of the whole blast round in terms of quality, time and cost. The first aim of cut is to break and throw rocks and create a cavity for the upcoming production detonators. An attempt has been made here to test and develop an innovative cutting system for small to medium-scale tunnels where classical wedge cut is physically difficult to execute; what is called in this paper “combined or quasi-wedge method”. Proposed drilling and blasting patterns have been first put in computerized drilling machines and then tested in the tunnels located in Rishikesh-Karnaprayag Railway Project, Package 2, driven in sedimentary rock mass. After thorough investigation of trial-and-error blasts economically and technically, necessary changes have been made to guarantee optimization and find proper design configurations. In comparison to conventional parallel cut, the newly developed cut leads not only to the betterment of cycle time for excavation but also improvement of specific drilling and specific charge, the two main performance indicators of blast operations. Vibration, fragmentation, pull length, fly rock and profile quality, as pro-blast parameters, were also found highly satisfactory.

WALL CONTROL AND BLAST PATTERN ANALYSIS USING BLAST VISION® TECHNOLOGY

Wall control and blasting are two major activities that significantly impact the productivity and safety of open-pit mining operations. Although many monitoring equipment are used for improving slope stability, there is still a need for understanding slope behaviour during a blast. This paper describes a new technology called Blast Vision®, developed by Ground Probe, for monitoring the interaction between blasting and slope stability with a temporal resolution in the range of milliseconds. This technology represents an innovative departure from standard blast vibration sensors by measuring ground luminance changes on the ground surface through drone-based computer vision. Blast Vision application for slope stability, misfires and fly rocks is investigated in this publication.

STUDY OF OCCUPATIONAL SAFETY AND HEALTH ON BLASTING PROCESS IN ANDESITE STONE MINING AREA WITH HIRAC METHOD IN CV. ARTHA AGUNG BERSAMA, HULU GURUNG SUB-DISTRICT, KAPUAS HULU REGENCY

CV. Artha Agung Bersama is an andesite mining company that uses a blasting system. This mining activity can harm workers if they do not apply good K3 management in blasting activities. One of the hazards of blasting activity is flying rock. For this reason, it is necessary to identify potential hazards, assess the level of accident risk, and recommend risk control efforts. The method in this study is the HIRAC (hazard identification risk assessment and control) method. This activity has five potential hazards: broken drum straps, worker negligence, explosive sounds, fly rock, and workers walking in a hurry in locations with a lot of gravel. There are five risks of accidents from potential hazards: being hit by a drum, scratched hands, pinched fingers forming a critical cover, slipping, exposure to diesel fuel, hearing loss, and being hit by a rock. Of the five hazard risks, three risks are included in the priority one category, namely: scratched hands, pinched fingers forming key covers, slipping, exposure to diesel fuel, and being hit by rocks. One risk is included in priority category three: being hit by a drum. One risk category is very high, namely being hit by a rock. The recommended risk control hierarchy for blasting activities is engineering control, administration, and personal protective equipment.

Application of Bayesian Neural Network (BNN) for the Prediction of Blast-Induced Ground Vibration

Rock blasting is one of the most common and cost-effective excavation techniques. However, rock blasting has various negative environmental effects, such as air overpressure, fly rock, and ground vibration. Ground vibration is the most hazardous of these inevitable impacts since it has a negative impact not only on the environment of the surrounding area but also on the human population and the rock itself. The PPV is the most critical base parameter practice for understanding, evaluating, and predicting ground vibration in terms of vibration velocity. This study aims to predict the blast-induced ground vibration of the Mikurahana quarry, using Bayesian neural network (BNN) and four machine learning techniques, namely, gradient boosting, k-neighbors, decision tree, and random forest. The proposed models were developed using eight input parameters, one output, and one hundred blasting datasets. The assessment of the suitability of one model in comparison to the others was conducted by using different performance evaluation metrics, such as R, RMSE, and MSE. Hence, this study compared the performances of the BNN model with four machine learning regression analyses, and found that the result from the BNN was superior, with a lower error: R = 0.94, RMSE = 0.17, and MSE = 0.03. Finally, after the evaluation of the models, SHAP was performed to describe the importance of the models’ features and to avoid the black box issue.

CONTROL MEASURES AND SAFETY PRACTISES USED FOR FLY ROCK ISSUES IN MINING DUE TO BLASTING

Blasting involves the breaking of rocks using explosive that rapidly change due to chemical reaction forming huge volumes of gases with high pressure and temperature causing kinetic energy. The blasting process is primarily a rock–explosive interaction that entails application of pressure generated by detonation of explosives, on rock mass, over a few milliseconds. This rock–explosive interaction results in rock breakage and heaving of the broken rock mass (muck). In comparison to the mechanical methods that rely predominantly on the compressive breakage, blasting exploits the tensile strength of the rock mass. This is probably the reason that blasting is still the most prevalent and economical method for rock breakage. Blasting, in general, results in ‘desired’ and ‘undesired’ outcomes that may be ‘regular’ or ‘random’ in nature. Any mismatch between the energy available and the work done will increase the adverse or undesired blast results like excessive throw and fly rock. Fly rock and excessive throw occur due to deviations in blast design execution, use of excessive explosive energy than the required levels to fragment and throw the rock mass, and/or presence of rock mass features, not accounted for during blasting

Оценка качества капсюлей-детонаторов (с пиротехническим замедлением) неэлектрических систем инициирования по времени их срабатывания

Blasting operations in surface and underground mining are characterized by the need to protect the environment from harmful effects of the detonation products of explosives, the fly rock zone, the seismic manifestations of the blast, as well as airborne shock waves. Non-electric blasting systems by various manufacturers are used in Russia, but all of them have certain advantages and disadvantages. It can be stated that the blasting caps of the applied blasting system do not always correctly execute the firing times specified by their manufacturer. Mismatches of the actual firing times from the rated ones might be so great that the applied blasting systems sometimes produce disturbances in the order of charge firing, which, in turn, may cause detonation failure in the boreholes. Studies have shown that in order to reduce the risk of detonation failures, regardless of their causes, it is recommended to initiate the borehole at two points with placing the second primer in the upper part of the borehole, or using extended priming charges.

Analisis Flyrock Untuk Mengurangi Radius Aman Alat Pada Peledakan Batuan Andesit Di Kecamatan Margaasih, Kabupaten Bandung, Provinsi Jawa Barat

Bandung regency known to have had to scatter material which be potential sources of revenue of them are material andesit mining sand and also .Research objectives is measuring the estimation of the distance the throw rocks due to maximum blasting , restudying in the determination of a radius of secure at blasting activities by counting the radius of safe to an instrument based on a theory that is compared with actual that had broken out and get constant k in signification fly rock according to alan b.richards and adrian j.moore to adjust to those of the rocks and stemming used .The research was done by counting the throw of maximum rock theoretically menutut alan b .Ricahrds and adrian j .Moore coupled with the observation actual fly rock in the field with the observation use video and the naked eye .Trial done by moving a radius of safe instrument less than 300 m. From the trial data, it is obtained that the maximum throw of the actual rock and the prediction with the theoretical calculation is in accordance with the recommendation of Adrian J. Moore and Alan B. Richard, so the radius to secure the tool is at least 2 times that of the actual throw. With the provision of using stemming, the safe radius for blasting is reduced to 200 m.

Support Vector Machines for the Estimation of Specific Charge in Tunnel Blasting

Mine tunnels, short transportation tunnels, and hydro-power plan underground spaces excavations are carried out based on Drilling and Blasting (D&B) method. Determination of specific charge in tunnel D&B, according to the involved parameters, is very significant to present an appropriate D&B design. Suitable explosive charge selection and distribution lead to reduced undesirable effects of D&B such as inappropriate pull rate, over-break, under-break, unauthorized ground vibration, air blast, and fly rock. So far, different models are presented to estimate specific charge in tunnel blasting. In this study, 332 data sets, including geomechanical characteristics, D&B, and specific charge are gathered from 33 tunnels. The data are related to three dams and hydropower plans in Iran (Gotvand, Masjed-Solayman, and Siah-Bishe). Specific charge is modeled in inclined hole cut drilling pattern. In this regard, Support Vector Machine (SVM) algorithm based on polynomial Kernel function is used as a tool for modeling. Rock Quality Designation (RQD) index, Uniaxial Compressive Strength (UCS), tunnel cross-section area, maximum depth of blast hole, and blast hole coupling ratio are considered as independent input variables and the specific charge is considered as a dependent output variable. The modeling results confirm the acceptable performance of SVM in specific charge estimation with minimum error.

A New Technical and Economic Model to Calculate Specific Charge and Specific Drilling Using Hole Diameter, Bench Height, Uniaxial Compressive Strength, and Joint Set Orientation

Calculation of the specific charge and specific drilling before a blasting operation plays a significant role in the design of a blasting pattern and the reduction of the final extraction cost of minerals. In this work, the information from the Sungun, Miduk and Chah-Firouzeh copper mines in Iran was assessed, and it was found that there was a significant relationship between the specific charge and specific drilling and the hole diameter, bench height, uniaxial compressive strength and joint set orientation. After finding a technical and economic model to calculate the specific charge and specific drilling, this model was tested on the Sungun copper mine. Due to the insufficient consideration during the design of a blast pattern and because of the high hardness of the rocks in some parts of the mine, lots of destructive events such as boulders, back break, bench toe, high specific charge and high specific drilling, fly rock, and ground vibration in the blast operations were observed. The specific charge and specific drilling were found to be the most important technical and economic parameters involved in designing a blasting pattern, and they were found to play an important role in reducing the blasting cost. The blasting cost could be largely controlled by the accurate examination and computation of these parameters. An increase in the rock strength and the angle between the bench face and the main joint set would increase the specific charge and specific drilling. On the other hand, a specific charge and a specific drilling would decrease when the hole diameter increased in every range of the uniaxial compressive strength.

Effect of Water-Decked Blasting on Rock Fragmentation Energy

Fragmentation energy ratio is an important index to evaluate whether an explosive is used efficiently. This paper discusses the effect of water-decked blasting on fragmentation energy based on theory and numerical simulation, and three blasting tests were performed to measure the actual fragmentation energy at a granite-based field. Results show that at the same charge amount, the maximum borehole pressure of water-decked blasting is much greater than that of normal blasting in theory, which facilitates rock breaking. In numerical simulation, water-decked blasting is more beneficial to the transmission of explosive energy; therefore, the damage distribution is more uniform and the damage level is higher. The specific surface area and fragment size distribution were obtained by three-dimensional laser scanning and image analysis in field tests; therefore, the fragmentation energy could be measured, which showed that the fragmentation energy could be increased by 10% in water-decked blasting. In addition, water-decked blasting can reduce fly rocks and ensure the safety of rock blasting.

SELECTION OF THE MOST PROPER DRILLING AND BLASTING PATTERN BY USING MADM METHODS (A CASE STUDY: SANGAN IRON ORE MINE, IRAN)

Drilling is the first stage of open pit mining that has a considerable effect on the other stages of mining, including blasting, loading, hauling and crushing. An unsuitable drilling pattern may lead to undesirable results such as poor fragmentation, back break and fly rock that not only results in technical and safety issues but also increases the operating cost of the mine. Multi-Attribute Decision-Making (MADM) methods can be useful approaches to select the appropriate drilling pattern among various alternatives, performed previously. This paper aims to select the most proper drilling and blasting pattern for Sangan Iron Mine, Iran. To achieve this, in the first step, rock fragmentation, back break, fly rock, specific charge and specific drilling were considered as the decision criteria and their degree of importance was calculated using the AHP method under a fuzzy environment. Then, TOPSIS and PROMETHEE methods were used to select the most proper alternative. The results of this study show that the drilling pattern with a spacing of 5 m, burden 4 m, hole depth 10 m, and hole diameter 15 cm is the most suitable one. The stemming length and powder factor of the suggested pattern are 2.3 m and 2.6 gr/cm3, respectively.

Prediction of Blasting Cost in Limestone Mines Using Gene Expression Programming Model and Artificial Neural Networks

The use of blasting cost (BC) prediction to achieve optimal fragmentation is necessary in order to control the adverse consequences of blasting such as fly rock, ground vibration, and air blast in open-pit mines. In this research work, BC is predicted through collecting 146 blasting data from six limestone mines in Iran using the artificial neural networks (ANNs), gene expression programming (GEP), linear multivariate regression (LMR), and non-linear multivariate regression (NLMR) models. In all models, the ANFO value, number of detonators, Emolite value, hole number, hole length, hole diameter, burden, spacing, stemming, sub-drilling, specific gravity of rock, hardness, and uniaxial compressive strength are used as the input parameters. The ANN model results in the test stage indicating a higher correlation coefficient (0.954) and a lower root mean square error (973) compared to the other models. In addition, it has a better conformity with the real blasting costs in comparison with the other models. Although the ANNs method is regarded as one of the intelligent and powerful techniques in parameter prediction, its most important fault is its inability to provide mathematical equations for engineering operations. In contrast, the GEP model exhibits a reliable output by presenting a mathematical equation for BC prediction with a correlation coefficient of 0.933 and a root mean square error of 1088. Based on the sensitivity analysis, the spacing and ANFO values have the maximum and minimum effects on the BC function, respectively. The number of detonators, Emolite value, hole number, specific gravity, hardness, and rock uniaxial compressive strength have a positive correlation with BC, while the ANFO value, hole length, hole diameter, burden, spacing, stemming, and sub-drilling have a negative correlation with BC.

Optimization of blasting cost in lime stone mines using PSO metaheuristic algorithm

The prediction and optimization of blasting cost to achieve optimal fragmentation is significant, considering the control of the adverse consequences of the blast. In this study, by collecting blasting data in six limestone mines in Iran, a model was developed to predict the cost of blast using nonlinear multivariate regression. Compared to linear regression model, this model has a higher correlation coefficient (0.913) and root mean square error (1089) and in comparison, with the linear model, the nonlinear model shows a better match with the actual cost of the blast. Based on sensitivity analysis, spacing and number of holes had the highest and the least effect on the cost model of the blast, respectively. In addition, in this study along with achieving the blast cost function, the restrictive functions of the blast include fragmentation, fly rock and back break was modeled using nonlinear multivariate regression method, and these functions as inputs in the metaheuristic algorithm of Particles Swarm Optimization (PSO) were used to optimize the cost of blast. Using this method of spacing, the number and length of holes as design parameters of blast are 3.6 meters, 462 loops, and 13 meters respectively and fragmentation fly rock and back break as blasting limitations are 44 cm, 84.5 meters and 3.6 meters and blasting cost was 6235 Rials per ton, which results in a 12.9 percent reduction in the cost of blast and optimal control of the adverse consequences of the blast.

Application of simulated annealing for optimization of blasting costs due to air overpressure constraints in open-pit mines

Estimating the costs of blasting operations is an important parameter in open-pit mining. Blasting and rock fragmentation depend on two groups of variables. The first group consists of mass properties, which are uncontrollable, and the second one is the drill-and-blast design parameters, which can be controlled and optimized. The design parameters include burden, spacing, hole length, hole diameter, sub-drilling, charge weight, charge length, stemming length, and charge density. Blasting costs vary depending on the size of these parameters. Moreover, blasting brings about some undesirable results such as air overpressure, fly rock, back-break, and ground vibration. This paper proposes a mathematical model for estimating the costs of blasting operations in the Baghak gypsum mine. The cost of blasting operations in the objective function is divided into three parts: drilling costs, costs of blasting system, and costs of blasting labours. The decision variables used to minimize the costs include burden, spacing, hole diameter, stemming length, charge density, and charge weight. Constraints of the model include the boundary and operational limitations. Air overpressure in the mine is also anticipated as one of the model constraints. The non-linear model obtained with consideration of constraints is optimized by simulated annealing (SA). After optimizing the model by SA, the best values for the decision variables are determined. The value obtained for the cost was obtained to be equal to 2259 $ per 7700 tons for the desired block, which is less than the blasting costs in the Baghak gypsum mine.

Evaluating and predicting blast-induced ground vibration in open-cast mine using ANN: a case study in Vietnam

Blasting is one of the cheapest and effective methods for breaking rock mass in open-pit mines. However, its side effects are not small such as ground vibration (PPV), air overpressure, fly rock, back break, dust, and toxic. Of these side effects, blast-induced PPV is the most dangerous for the human and surrounding environment. Therefore, evaluating and accurately forecasting blast-induced PPV is one of the most challenging issues facing open-pit mines today. In this paper, a series of artificial neural network models were applied to predict blast-induced PPV in an open-pit coal mine of Vietnam; 68 blasting events were used in this study for development of the ANN models. Of the whole dataset, 80% (approximately 56 observations) were used for the training process, and the rest of 20% (12 observations) were used for the testing process. Five ANN models were developed in this study with the difference in the number of hidden layers. The ANN 2-5-1; ANN 2-8-6-1; ANN 2-5-3-1; ANN 2-8-6-4-1; and ANN 2-10-8-5-1 models were considered in this study. An empirical technique was also conducted to estimate blast-induced PPV and compared to the constructed ANN models. For evaluating the performance of the models, root-mean-squared error (RMSE) and determination coefficient (R2) were used. The results indicated that the ANN 2-10-8-5-1 model (10 neurons in the first hidden layer, 8 neurons in the second hidden layer, and 5 neurons for the third hidden layer) yielded a superior performance over the other models with an RMSE of 0.738 and R2 of 0.964. In contrast, the empirical performed poorest performance with an RMSE of 2.670 and R2 of 0.768. This study is a new approach to predict blast-induced PPV in open-cast mines aim to minimize the adverse effects of blasting operations on the surrounding environment.

Without Fly Rock Blasting Technology of Railway Reconstruction

The paper considers the problem of hard rock blasting in confined space of railway reconstruction with widening of side-hill cuts or shelves. To ensure reliable blasting without fly rock to construct the secondary railway tracks, it is proposed to use a combination of borehole cushioned charge construction in overdrilling, large delays in explosive initiation, as well as installation of permeable convertible shelters from elastic elements.

Predicting Blast-Induced Air Overpressure: A Robust Artificial Intelligence System Based on Artificial Neural Networks and Random Forest

Blasting is the most popular method for rock fragmentation in open-pit mines. However, the side effects caused by blasting operations include ground vibration, air overpressure (AOp), fly rock, back-break, dust, and toxic are the critical factors which have a significant impact on the surrounding environment, especially AOp. In this paper, a robust artificial intelligence system was developed for predicting blast-induced AOp based on artificial neural networks (ANNs) and random forest (RF), code name ANNs-RF. Five ANN models were developed first; then, the RF algorithm was used to combine them. An empirical technique, ANN, and RF models were also developed to predict and compare with the ANNs-RF model. For this aim, 114 blasting events were recorded at the Nui Beo open-pit coal mine, Vietnam. The maximum explosive charge capacity, monitoring distance, vertical distance, powder factor, burden, spacing, and length of stemming were used as the input variables for predicting AOp. The quality of the models is evaluated by root-mean-square error (RMSE), determination coefficient (R2), mean absolute error (MAE), and a simple ranking method. The results indicated that the proposed ANNs-RF model was the most superior model with RMSE of 0.847, R2 of 0.985, MAE of 0.620 on testing dataset, and total ranking of 40. In contrast, the best ANN model yielded a slightly lower performance with RMSE of 1.184, R2 of 0.960, MAE of 0.809, and a total ranking of 39; the RF model yielded a performance with RMSE of 1.550, R2 of 0.939, MAE of 1.222, and total ranking of 22; the empirical model provided the lowest accuracy level with RMSE of 5.704, R2 of 0.429, MAE of 5.316 on the testing dataset, and total ranking of 6.

Assessment of Blast-induced Ground Vibration using Different Predictor Approaches- A Comparison

Blasting is a mechanism of rock fragmentation. Usages of high explosive causes ground vibration, air noise, back breaks, over breaks as well as fly rock. Excessive blast-induced vibrations cause severe damage to nearby structures and residents in and around mine. So, it is essential to the precise prediction of ground vibration to reduce the ecological damage. Vibrations are expressed in terms of peak particle velocity (PPV). The aim of this study was to assess and predict the ground vibration at different explosive quantities and distances, applications of generalized regression neural network (GRNN) as well as empirical predictors were used. A total of fourteen blast events were collected at various strategic and valuable locations in the site, out of these ten blast events were considered for training and reaming for validate of the GRNN model. A three-layer GRNN with 2-14-1 architecture was developed and trained with Levenberg–Marquardt algorithm. Five emphircal predictor equations were proposed by the United States Bureau of Mines (USBM), Ambraseys-Hendron, Langefors- Kihlstrom, Central Mining Research Institute (CMRI) predictor and Bureau of Indian standard were applied to governing a relation between peak particle velocity and its influencing parameters. The obtained results reveal that the proposed GRNN model can predict the PPV accurately as compared to the other predictor models available. Obtained results were compared based on evaluation performance models such as coefficient of determination (R2) and mean square error (MSE) between monitored and predicted values of PPV. It was observed that GRNN approach provides high R2 (0.9988) and low MSE (0.0001) among all other empirical predictor approaches for accurate prediction of ground vibration.

Evaluation of initiating system by measurement of seismic energy dissipation in surface blasting

Enhanced demand for coal and minerals in the country has forced mine operators for mass production through large opencast mines. Heavy blasting and a large amount of explosive use have led to increased environmental problems, which may have potential harm and causes a disturbance. Ground vibrations generated due to blasting operations in mines and quarries are a very important environmental aspect. It is clear that a small amount of total explosive energy is being utilized in blasting for breakage of rock mass, while the rest is being wasted. The amount of energy which is wasted causes various environmental issues such as ground vibrations, air overpressure, and fly rock. Ground vibrations caused by blasting cannot be eliminated entirely, yet they can be minimized as far as possible through a suitable blasting methodology. A considerable amount of work has been done to identify ground vibrations and assess the blast performance regarding the intensity of ground vibrations, i.e., peak particle velocity and frequency spectrum. However, not much research has done into reducing the seismic energy wasted during blasting leading to ground vibrations. In this paper, the blast-induced ground vibrations in three orthogonal directions, i.e., transverse, vertical, and longitudinal, were recorded at different distances using seismographs. An attempt has been made for the estimation of the percentage of explosive energy dissipated in the form of seismic energy with electronic and non-electric (NONEL) initiation system. signal processing techniques with the help of DADiSP software is used to study the same.