Blast Parameters Research Articles

Grain erosion wear properties and grinding performance of porous aggregated cubic boron nitride abrasive wheels

Cubic boron nitride (cBN) superabrasive grinding wheels exhibit unique advantages in the grinding of difficult-to-cut materials with high strength and toughness, such as titanium alloys and superalloys. However, grinding with multilayered metallic cBN superabrasive wheels faces problems in terms of grain wear resistance, the chip storage capability of the working layers and the stability and controllability of the dressing process. Therefore, in this work, novel metallic cBN superabrasive wheels with aggregated cBN (AcBN) grains and open pore structures were fabricated to improve machining efficiency and surface quality. Prior to the grinding trials, the air-borne abrasive blasting process was conducted and the abrasive blasting parameters were optimized in view of wear properties of cBN grains and metallic matrix materials. Subsequently, the comparative experiments were performed and then the variations in grinding force and force ratio, grinding temperature, tool wear morphology and ground surface quality of the multilayered AcBN grinding wheels were investigated during machining Ti–6Al–4V alloys. In consideration of the variations of grain erosion wear volume and material removal rate per unit of pure metallic matrix materials as the abrasive blasting parameters changes, the optimal abrasive blasting parameters were identified as the SiC abrasive mesh size of 60# and the abrasive blasting distance and time of 60 mm and 15 s, respectively. The as-developed AcBN grains exhibited better fracture toughness and impact resistance than monocrystalline cBN (McBN) grains because of the existence of metal-bonded materials amongst multiple cBN particles that decreased crack propagation inside whole grains. The metallic porous AcBN wheels had lower grinding forces and temperature and better ground surface quality than vitrified McBN wheels due to the constant layer-by-layer exposure of cBN particles in the working layer of AcBN wheels.

Comprehensive index of compound blast furnace smelting

An actual direction in the development of blast-furnace smelting technology is the implementation of stable operating modes of blast furnaces in terms of the parameters of the used charge materials and hot combined blast. For this purpose, complex indicators characterizing the thermal and reduction modes of blast furnace smelting, and integral indicators of iron ore raw materials (IORM) quality are being studied. The object of the study is the blast furnace process under the conditions of PJSC NLMK. The database of the main indicators of the operation of blast furnaces No. 4, 6 and 7 for the period 2013–2018 was analyzed. The furnaces operate under raw material conditions, with similar combined blast parameters and coke consumption. When the consumption of natural gas, pulverized coal and process oxygen changes, the values of the degree of compensation (the ratio of the consumption of reducing additives to the consumption of process oxygen) are in the range of 0.9–1.1. This provides a constant level of hearth heating, stability of the gas-dynamic mode of melting and coke consumption. At the same time, the different level of development of the processes of indirect (Ri) and direct (rd) reduction in blast furnaces No. 4, 6 and 7 makes it possible to perform correct studies of the features of blast furnace smelting in a wide range of Ri and rd values. It has been established that under the conditions of stable operation of blast furnaces on raw materials from sinter and pellets using combined blast, the type of dependence of the sulfur and silicon content in pig iron on the values of the integrated iron ore raw materials quality index is determined by degree development level of direct reduction processes rd. It has been established that the mode of blast furnace smelting with natural gas, pulverized coal and process oxygen, characterized by the level of rd values less than 20–25 %, is distinguished by the presence of a pronounced extreme dependence of coke consumption and productivity on the parameters of the combined blast.

Prediction of Peak Particle Velocity of Blast-induced Ground Vibrations using Boosted Regression Trees Authored

Loosening of rockmass during its excavation in an infrastructure project is carried by rock blasting. The blast-induced ground vibrations pose a major challenge to the blasting engineers, whose main objective is to control their potential to cause any damage to the buildings in the vicinity. The research reported in this paper explains how the error in the prediction of the Peak Particle Velocity (PPV) by the United States Bureau of Mines (USBM)-based approach can be minimised using machine learning techniques. The complex correlation between the blast parameter and the PPV value has been modelled using the least square boosted decision tree approach after the selection of the best suitable feature has been selected based on the correlation matrix. The proposed model automatically maps the input blast feature (SD) with the target PPV values by aggregating the decision of various weak learners. The generalization of the proposed model has been validated through a 5-fold cross-validation approach using a dataset comprising of two hundred blast records generated by monitoring the blasts at International airport site, Navi Mumbai, India. The assessment of the prognostic ability of the proposed model demonstrates that it has outperformed the USBM-based approach for PPV prediction. The results establish that the predictions by the proposed model are closer to the measured values than the other regression models.

Numerical simulation of the line of least resistanceduring the explosion of charges

Purpose. To establish the analytical regularity of the calculation of the maximum value of the line of least resistance (LLR) of the explosive (E), taking into account the physical and mechanical properties of the rock mass and the detonation characteristics of the explosive. The methodology of research. Numerical modeling by the finite element method (FEM) to change the stress-strain state of the model established the value of the LLR at different diameters of the charge cavity, the pressure of explosion products and the tensile strength of rocks. Regression analysis obtained an empirical pattern of changes in the LLR depending on the physical and mechanical properties of the rock mass and the detonation characteristics of explosives. Mathematical modeling establishes analytical regularities of LLR calculation for zones of crack formation and intensive fragmentation. Findings. According to the change in the stress state of the model material around the charging cavity, the empirical regularity of changing the maximum value of the LLR depending on the diameter of the charging cavity and the diameter of the explosive charge, the density and rate of detonation of explosives, the compressive and shear strength. According to the developed calculation scheme, analytical regularities of LLR calculation for zones of crack formation and intensive fragmentation are obtained. By comparing the results of LLR calculation according to the obtained regularities, the most correct formula for LLR calculation was chosen, which turned out to be the analytical regularity of LLR calculation for the zone of intensive fragmentation. The originality. The power law is established for determining the LLR of an E, which comprehensively takes into account the radius of the crush zone, the diameter of the charging cavity and charge, the density and detonation velocity of E, the compressive strength of rocks, their fracturing and compaction under the action of rock pressure, which makes it possible to calculate the parameters of drilling and blasting (D&B) for breaking massif along the zone of intensive fragmentation. Practical implications. According to the results of the research, an analytical regularity of the calculation of the LLR of the explosive charge in the zone of intensive fragmentation was obtained, the use of which will allow to rationalize the D&B parameters in ore mining with the help of industrial explosives.

XG Boost Algorithm to Simultaneous Prediction of Rock Fragmentation and Induced Ground Vibration Using Unique Blast Data

The two most frequently heard terms in the mining industry are safety and production. These two terms put a lot of pressure on blasting engineers and crew to give more while consuming less. The key to achieving the optimum blasting results is sophisticated bench analysis, which must be combined with design blast parameters for good fragmentation and safe ground vibration. Thus, a unique solution for forecasting both optimum fragmentation and reduced ground vibration using rock mass joint angle and blast design parameters will aid the blasting operations in terms of cost savings. To arrive at a proper understanding and a solution, 152 blasts were carried out in various mines by adjusting blast design parameters concerning the measured joint angle. The XG Boost, K-Nearest Neighbor, and Random Forest algorithms were evaluated, and the XG Boost outputs were shown to be superior in terms of Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE), and Co-efficient of determination (R2) values. Using XG Boost, the decision-tree-based ensemble Machine Learning algorithm that uses a gradient-boosting framework and a simultaneous formula was developed to predict both fragmentation and ground vibration using joint angle and the same set of parameters.

Prediction of flyrock throw distance in quarries by variable selection procedures and ANFIS modelling technique

This study suggests application of variable reduction procedures for flyrock prediction. It was aimed to create robust and non-complex predictive models. Eleven operational blast parameters and rock mass properties were measured in an aggregate quarry. Dominant parameters for flyrock occurrence were determined by multivariate statistical methods. Two parallel ANFIS models were developed for flyrock prediction. The first ANFIS model was constructed based on the results of stepwise regression. Burden–hole diameter ratio, in-situ block size and specific charge are the input parameters of ANFIS 1. The second ANFIS model was created based on the results obtained by factor analysis. Burden–hole diameter ratio, bench height–burden ratio, number of holes and charge weight are used as input parameters for ANFIS 2. The calculated mean absolute percentage errors are lower than eight percent for the ANFIS predictions. The median absolute errors are lower than 5 m. The study also investigates alternative accuracy measures to evaluate forecasting performance. Standardized errors, normalized errors and Nash–Sutcliffe Efficiency were found to be useful for model validation. It is concluded that more than a single model can be created for a specific site. Pre-statistical analysis for variable reduction increases performance of the predictive models. Burden appeared to be a significant parameter for flyrock throw.

Novel hybrid machine learning approach for predicting structural response of RC beams under blast loading

Explosions have inflicted colossal human and economic losses. However, existing response prediction methods for blast-loaded reinforced concrete (RC) structures are complex and suffer from several limitations. The novelty of this study consists of developing a hybrid machine learning model to predict the maximum displacement of RC beams under blast loading. The model was developed using a database compiled from published studies and considers influential features of RC beams and blast parameters. Hybrid gradient-boosted regression trees algorithm coupled with Henry gas solubility optimization algorithm was developed and validated using multiple statistical metrics, feature importance analyses, and comparisons to traditional methods. A failure mode and crack pattern classification model was also developed to predict the post-blast condition of RC beams. It was scrutinized using multi-class confusion matrix and feature importance analysis. The displacement prediction model achieved superior performance with MAE of 4.48 mm and R2 of 93.4%. The classification model attained adequate performance with binary-class accuracy of 93.1% and multi-class accuracy of 83.74%. Both models captured features’ importance, while strongly correlating to experimental studies. The model opens the door for creating an improved and integrated machine learning model for predicting the quantitative and qualitative behavior of RC beams under blast loading in future research.

Fragility analysis of masonry wall subjected to blast loading

The present research focuses on developing the Fragility Curves (FC) of masonry panels subjected to various blast scenarios considering extensive parameters such as the effect of variation in types of masonry (unreinforced and reinforced) and blast explosion (air and surface). The Fragility Curve (FC) is a suitable way of illustrating the vulnerability of structure against blast load. Herein; fragility analysis of Solid Brick Masonry (SBM), Hollow Brick Masonry (HBM) and Reinforced Hollow Brick Masonry (RHBM) wall panels were carried out to assess their vulnerability against blast load using explicit finite element approach. The FC(s) were plotted considering uncertainties in blast parameters viz., weight of charge (W) and standoff distance (R). Two types of FC(s) were plotted: FC-1, with Probability of Failure (PF) as ordinate and W as abscissa; and FC-2, with PF on ordinate-axis and scaled distance Z [f (W, R)] on abscissa. Monte Carlo simulation (MCS) was adopted to generate random sample sets of variables based on the mean value and coefficient of variation. The failure criterion assumed in this study is based on the inelastic tension damage curve generated for the masonry in accordance with the experimental results. Also, a Damage Index was established having four levels of damage- Minor Damage (MD), Repairable Damage (RD), Non-Repairable Damage (NRD) and Total Damage (TD). In addition, limit state function was defined in terms of cracking strain for which the threshold values corresponding to each damage level was specified on the basis of tension damage curve. The various critical values of W and Z corresponding to the probability of TD being 90% were reported from the FC(s). It was found that percentage increase in demand of W critical for RHBM was about 100%–400% approximately for various standoff distances between 5 m and 40 m. Also, due to strengthening value of Z critical decreased to 21% and 27.5% respectively for surface and air blast scenario respectively.

Time of arrival as a diagnostic for far-field high explosive blast waves

The ability to accurately determine blast loading parameters will enable more fundamental studies on the sources of blast parameter variability and their influence on the magnitude and form of the loading itself. This will ultimately lead to a better fundamental understanding of blast wave behaviour, and will result in more efficient and effective protective systems and enhanced resilience of critical infrastructure. This article presents a study on time of arrival as a diagnostic for far-field high explosive blasts, and makes use of the results from a large number of historic tests and newly performed experiments where the propagating shock front was filmed using a high-speed video (HSV) camera. A new method for optical shock tracking of far-field blast tests is developed and validated, and full-field arrival time results are compared against those determined from the historic data recorded using traditional pressure gauges. Arrival time variability is shown to be considerably lower than peak pressure and peak specific impulse, and is shown to decrease exponentially with increasing scaled distance. Further, the method presented in this article using HSV cameras to determine arrival time yields further reductions in variability. Finally, it is demonstrated that the method can be used to accurately determine far-field TNT equivalence of high explosives.

A deep‐hole microblasting technique for controlling coal wall spalling during mining of a vertically jointed seam

AbstractThe vertically‐jointed coal seam, especially after water drainage, is easy to lead to large‐area coal wall spalling (CWS). To alleviate the problem, a strut subjected to equivalent central‐concentrated force was proposed for elaborating critical conditions for coal instability based on CWS characteristics, determining the main control factors. The sensitivity analysis of factors driving CWS revealed that the coal between 3.3 and 4.56 m was the most vulnerable. A microblasting technique was proposed for controlling CWS by increasing the friction coefficient at the weakened‐primary coal interface, improving the coal stress, and reducing the equivalent mining height. The paper presented the application of universal distinct element code models to simulate the CWS mechanism with different joint mechanical parameters and microblasting heights. The reduction of spalling intensity indicates that the microblasting weakening of the upper part coal could improve the overall stability of the coal. LS‐DYNA is employed for simulating the fractures development between blasting holes, and the rationality of optimized blasting parameters is revealed. The fracture characteristics of the observation hole in field demonstrated that the hole was effectively fractured by microblasting. The spalling parameters including depth, width and frequency were obviously reduced, which showed the rationality in microexplosion controlling spalling.

Study on parameter optimization of deep hole cumulative blasting in low permeability coal seams

Coal seam gas extraction is an important means of exploiting and utilizing gas resources, as well as a means of preventing coal mine disasters. To improve gas extraction efficiency in high gas and low permeability coal seams while ensuring blasting security, deep hole cumulative blasting parameters were optimized. ANSYS/LS-DYNA software is used to establish a 3-dimensional cumulative blasting model. By comparing and analyzing the blasting stress nephograms, stress time-history curves, and crack expansion curves, the optimal blasthole diameter, charge position, and charge length are obtained. Based on the numerical simulation results, a field test was carried out in the No. 10 coal seam of the Pingdingshan coal mine. The test results show that after cumulative blasting, the gas concentration was increased by an average of 2.25 times, the gas purity was increased by an average of 3.78 times, the permeability coefficient of the coal seam was increased by 21 times, and the effective radius of blasting was up to 7 m. The positive effects of deep hole cumulative blasting parameter optimization on the pressure relief and permeability enhancement of a high gas and low permeability coal seam were determined, which can provide a reference for other similar working faces to implement this technology.

Application of logistic regression, CART and random forest techniques in prediction of blast-induced slope failure during reconstruction of railway rock-cut slopes

Drilling and blasting operation is often required to excavate the infrastructure slopes for enhancing their stability or creating space for upgradation. While conducting blasting, there are many incidents of slope failure or rockfall. Thus, proper planning and careful designing of different blasting parameters are essentially required to reduce the incidents of slope failure or rockfall. In the present research, the efficacies of three machine learning (ML) techniques; Logistic Regression (LR), Classification and Regression Tree (CART) and Random Forest (RF) were examined for predicting the blast-induced slope failure (BISF) or blast-induced rockfall during reconstruction of slopes on railway route. 490 databases with thirteen variables were considered for the prediction of BISF. By applying Multicollinearity and LR technique based on minimum Akaike Information Criterion values, the six most influential input parameters were identified. With the selected input datasets, fivefold cross-validation was carried out on randomly selected five sub-groups of datasets using LR tool. Then, the best LR model having the highest prediction rate was selected and with the same training and testing datasets of the selected model, the CART and RF models were also developed. The various performance indices such as correctness, recall rate, precision, specificity, F-beta score, receiver operating characteristics (ROC) and area under the curve (AUC) were calculated to evaluate the developed models' accuracy and applicability. The developed models showed good prediction abilities, with the RF model having highest performance in terms of recall rate (90%), accuracy (96.94%) and F-beta score (0.882). The LR model has higher precision (88.9%) and AUC value (0.96) than CART and RF models. The findings of the research work demonstrate the applicability of all three models in selecting the blast design parameters to prevent BISF during blasting. The use of developed models would result in saving the commuter’s lives, avoiding traffic delays and minimising property damages in similar situations.

Numerical Simulation Study on Dust Suppression Mechanism of Burning Rock Blasting in Open-Pit Mine

In an open-pit mine in Xinjiang, part of the stripped area is covered by burnt rock. Due to the low strength and fragility of burnt rock, dust is more easily generated during blasting. Taking the mining area as the research background, the mechanical property parameters of burnt rock were tested, and the blasting parameter design of on-site operation was understood. The blasting numerical simulation of burnt rock step was carried out by using a numerical simulation software (LS-DYNA). From the angle of stress on rock, the stress cloud and stress curve of numerical simulation are analyzed, and it is concluded that the fundamental reason for the large dust production in blasting operation is that the burnt rock is crushed excessively after the action of explosion wave, and the explosive energy is too large, which is converted into kinetic energy to drive the dust to escape. In order to improve the utilization rate of explosives and reduce the output of blasting dust, the original blasting parameters were optimized as 8-m hole spacing, 6.5-m row spacing, 0.21-kg/m³ unit explosive consumption, 1-m interval charge, and 55-ms short-delay blasting through numerical simulation and orthogonal experiment. In the mining area, the measures of dustproof and dust reduction by blasting protection blanket and dust absorption cotton are adopted. Combined with the optimized blasting parameters, the field test proves that the dust removal efficiency is up to 82.4%.

Assessing the explosion effect on rock mass pre-destruction

Introduction. Theoretical and empirical research into rock blasting proved that detonation wave propagation results in the development of destruction and pre-destruction zones around the explosive cavity. In the destruction zone, rock crushes. In the pre-destruction zone, stresses set up by the detonation wave are concentrated on rock mass structure defects, giving rise to new micro defects and the development of the existing ones. Rock fracturing and cavitation increase, lowering its strength properties; this is called rock pre-destruction. There are works devoted to the qualitative analysis of rock in the pre-destruction zone, but the problem requires elaboration to offer possibilities for practical application. Research aims to quantify rock mass pre-destruction to use the parameters of rock blasting by borehole charges under opencast mining in engineering calculations. Methods of research. To assess the degree of rock mass pre-destruction at a distance from the charge axis, a pre-destruction intensity coefficient is used. The destruction zone radius is determined by a well-known method. In the destruction zone, the value of the pre-destruction intensity coefficient is higher than one, i. e. there is discontinuity of the rock mass. Beyond the destruction zone, there is a pre-destruction zone where the value of the pre-destruction intensity coefficient is less than one. The pre-destruction zone boundary is at distances of the order of 200–250 charge radii. The pre-destruction intensity coefficient of a particular zone attained after all charges have been fired is determined by summing the pre-destruction intensity coefficient from every charge. According to the energy approach, rock strength can be assessed by the value of the specific drilling energy intensity. In order to determine the reduction value of the specific drilling energy intensity in a particular zone, it is essential to know the drilling specific energy capacity of this zone in the natural state, the pre-destruction intensity coefficient attained after a large-scale blast of borehole charges, and specific drilling energy intensity of completely disintegrated rock. The effect made by another borehole charge explosion on the rock mass is weaker due to its pre-destruction by previous blasts. So we propose the impact multiplicity coefficient that reflects the accumulation of pre-destruction in a particular zone under the sequence blasting of borehole charges. Results. The expected value of the specific drilling energy intensity has been calculated for the individual arbitrarily spaced wells within the pre-destruction zone of a particular rock mass zone. The calculation results were compared with the practical values measured during blasting preparation in the preset rock mass zone. Conclusions. The findings of this study have made it possible to quantify the impact of explosions on rock mass pre-destruction. The developed technique makes it possible to predict the value of drilling energy intensity in the pre-destruction zone and, as a result, establish the required specific energy intensity of detonation and hence the consumption of explosives. Thus, it becomes possible to reduce the consumption of explosives under the existing blasting scheme at the enterprise and model other charge initiation types to select the least expensive one.

Probabilistic analysis of blast–obstacle interaction in a crowded internal environment

Recent terror events such as the Manchester Arena bombing and Brussels and Istanbul airport attacks featured improvised explosive devices detonated in crowded internal spaces. A blast wave that propagates in the presence of obstacles will have fundamentally different properties to those of an unimpeded blast wave. Physical processes such as reflection, diffraction, and superposition of multiple wave fronts result in highly complex and situational-dependent loading characteristics which cannot be predicted using simple tools such as those for predicting free-field blast parameters. The influence of blast–obstacle interaction within an internal environment has not yet been studied. This article uses computational fluid dynamics within a probabilistic framework to quantify the influence of obstacle density and positioning on blast loading characteristics. Two mechanisms which alter the properties of a blast wave are studied: ‘channelling’ and ‘shielding’. It is shown that channelling effects are highly localised and result in increased loading near the explosive, the effect of which increases with obstacle density. Shielding is shown to be a cumulative effect which increases with distance from the explosive, and with increasing obstacle density. Whole-domain cumulative density functions are used to derive quantitative descriptors of the loading characteristics and how they vary relative to simple benchmark cases, with a view to providing clear guidance on the development of future predictive tools.

A ribosomal operon database and MegaBLAST settings for strain-level resolution of microbiomes.

Current methods to characterize microbial communities generally employ sequencing of the 16S rRNA gene (<500bp) with high accuracy (∼99%) but limited phylogenetic resolution. However, long-read sequencing now allows for the profiling of near-full-length ribosomal operons (16S-ITS-23S rRNA genes) on platforms such as the Oxford Nanopore MinION. Here, we describe an rRNA operon database with >300 ,000entries, representing >10 ,000prokaryotic species and ∼ 150, 000 strains. Additionally, BLAST parameters were identified for strain-level resolution using in silico mutated, mock rRNA operon sequences (70-95% identity) from four bacterial phyla and two members of the Euryarchaeota, mimicking MinION reads. MegaBLAST settings were determined that required <3s per read on a Mac Mini with strain-level resolution for sequences with >84%identity. These settings were tested on rRNA operon libraries from the human respiratory tract, farm/forest soils and marine sponges ( n = 1, 322, 818 reads for all sample sets). Most rRNA operon reads in this data set yielded best BLAST hits (95± 8%). However, only 38-82% of library reads were compatible with strain-level resolution, reflecting the dominance of human/biomedical-associated prokaryotic entries in the database. Since the MinION and the Mac Mini are both portable, this study demonstrates the possibility of rapid strain-level microbiome analysis in the field.

Effect of SiC Abrasive Blasting Parameters on the Quality of the Ceramic and Ni-Cr Dental Alloy Joint.

The SiC abrasive blasting parameters are vital in ensuring a suitable bond between dental ceramics and the Ni-Cr alloy. The purpose of this in vitro test was to examine the strength of the joint between the Ni-Cr alloy and fused dental ceramics for SiC abrasive blasting at a specific pressure (400, 600 kPa) and particle size (50, 110, 250 µm) in order to determine the optimal treatment parameters. The test also accounted for thermal loads (5000 cycles, 5–55 °C) to which the metal-ceramic joint is subjected during use. One hundred and forty-four Ni-Cr cylinders were divided into six groups (n = 12) and subjected to the airborne-particle abrasion with SiC with various pressure and grit size parameters. After treatment, the specimens were rinsed, dried, fused to dental ceramics, and examined for their shear strength using the Zwick/Roell Z020 machine. The results were statistically analysed using the ANOVA analysis of variance (α = 0.05). The highest metal-ceramic joint strength was obtained for abrasive blasting with 110 and 250 µm SiC grit at a pressure of 400 kPa. This relationship was also observed after the joint was subjected to thermal loads (5000 thermocycles). Additionally, thermal loads did not significantly reduce the joint’s strength compared with non-loaded joints. For small SiC abrasive grit sizes (50 µm) under pressure 400 kPa, the treatment pressure had a significant effect on the strength of the joint (p < 0.05). For larger particle sizes, the pressure had no effect. After abrasive blasting using SiC, the Ni-Cr metal-ceramic joint retained its properties, even under thermal load, ensuring the joint properties’ stability during use.

Influence of dry ice blasting process properties on surface roughness and residual stresses of machined and additive manufactured workpieces

Dry ice blasting has shown the potential to remove metallic burrs after machining processes and support structures after additive manufacturing. During blasting, process parameters need to be chosen depending on the material and the geometric properties of the burr. However, dry ice blasting affects the local material properties on a micro level and improper blasting parameters may lead to changes in the part surface. In this article, correlations and interactions between dry ice blasting parameters and resulting specimen roughness and residual stresses are identified for machined and additive manufactured metallic materials.

Analysis and Optimization of Blasting Practices at the Sangaredi Mine

Generally, the Mos hardness of bauxite is 2.5 to 3.5. According to the specific conditions of the Sangaredi bauxite deposit, that is, the rock hardness coefficient is between 3 and 6, and there is a clayey zone in the bauxite mining area, it is necessary to carry out blasting work before mining. This article mainly analyzes and optimizes the blasting practice of the Sangaredi open pit bauxite mine. The subject was finally extended to the reduction of nuisances due to blasting, that is to say essentially due to vibrations: this presupposed a study around the vibration data available, and the proposal of methods to limit these vibrations. The bottom conditions of the Sangaredi bauxite ore zone are studied. Bauxite reserves are very rich and the market is huge. The analysis of mine blasting practices, mainly the types of explosives, the selection and analysis of explosives and blasting equipment and choosing the mode of longitudinal blasting, the link of the blasting site of the mining area, further study the optimization of mining blasting practice, the choice of drilling and process to determine reasonable blasting parameters, which improving the drilling method. The experimental results show that this optimization scheme improves efficiency blasting of the bauxite mine but also promotes an increase in production.

Investigation of the blast furnace process using multicomponent blast

An urgent direction of the development of blast-furnace smelting technology is the use of multicomponent fuel-enriched blast of high parameters, in particular, the combined use of natural gas, pulverized coal fuel (PCF) and process oxygen. The object of the research is the blast-furnace process using reducing blowing additives in PJSC &ldquo;NLMK&rdquo;. The database of the main indicators of the operation of blast furnaces number 6 and 7 during 2013&ndash;2018 has been formed and analyzed. The furnaces operate with similar raw material, parameters of fuel enriched blast and coke consumption. With a change in the consumption of natural gas, PCF and process oxygen, the values of the degree of compensation (the ratio of the consumption of reducing additives to the consumption of process oxygen) are in the range 0,9&ndash;1,1. This provides a stable level of values of the theoretical combustion temperature and the amount of reducing components of the hearth gas, a constant level of heating of the hearth, stability of the gas-dynamic melting mode and the consumption of coke. At the same time, different level of development of the processes of indirect (Ri) and direct (rd) reduction in blast furnaces number 6 and 7 indicates a different composition of hearth gases. This circumstance makes it possible to perform correct studies of the features of the blast furnace process in a wide range value of Ri (from 65 to 92%) and rd (from 12 to 42%). It has been established that the mode of blast furnace smelting using natural gas, PCF and process oxygen, characterized by rd values less than 20&ndash;25%, is distinguished by the presence of a pronounced extreme dependence of coke consumption and productivity on the parameters of combined blast.