The concept of TNT(Trinitrotoluene,C_7H_5N_3O_6)equivalence is often invoked to evaluate the performance and predict the explosion parameters of different types of explosives.However,due to its low prediction accuracy...The concept of TNT(Trinitrotoluene,C_7H_5N_3O_6)equivalence is often invoked to evaluate the performance and predict the explosion parameters of different types of explosives.However,due to its low prediction accuracy and limited application range,the use of TNT equivalence for predicting explosion parameters in a confined space is rare.Compared with explosions in free fields,the process of explosive energy release in a confined space is closely related to various factors such as oxygen balance,combustible components content,and surrounding oxygen content.Studies have shown that in a confined space,negative oxygen balance explosives react with surrounding oxygen during afterburning,resulting in additional energy release and enhanced blast effects.The mechanism of energy release during afterburning is highly complex,making it challenging to determine the TNT equivalence for blast effects in a confined space.Therefore,this remains an active area of research.In this study,internal blast experiments were conducted using TNT and three other explosives under both air and N_2(Nitrogen)conditions to obtain explosion parameters including blast wave overpressure,quasi-static pressure,and temperature.The influences of oxygen balance and external oxygen content on energy release are analyzed.The author proposes principles for determining TNT equivalence for internal explosions while verifying the accuracy of obtained blast parameters through calculations based on TNT equivalence.These findings can serve as references for predicting blast performance.展开更多
The present study considers the so-called air deck blasting,one of the most commonly used techniques for the improvement of blasting efficiency in mining applications.In particular,it aims to improve the operating con...The present study considers the so-called air deck blasting,one of the most commonly used techniques for the improvement of blasting efficiency in mining applications.In particular,it aims to improve the operating conditions of large-scale equipment,increase the efficiency of the slope enlarging process,and reduce the mining cost.These objectives are implemented through a two-fold approach where,first,a program for slope enlarging based on the middle air-deck charge blasting-loosening technology is proposed,and second,the physical mechanism responsible for the stress wave attenuation in the rock is analyzed in the framework of a Holmquist–Johnson–Cook constitutive model.Field test results verify that the proposed approach is highly efficient and economical when used in medium-hard rock blasting and thus provides a basis for the practical implementation of slope enlargement for high benches in Open-Pit Mines.展开更多
A layered charge composed of the JH-2 explosive enveloped by a thick-walled cylindrical casing(active aluminum/rubber and inert lithium fluoride/rubber composites) was designed and explosion experiments were conducted...A layered charge composed of the JH-2 explosive enveloped by a thick-walled cylindrical casing(active aluminum/rubber and inert lithium fluoride/rubber composites) was designed and explosion experiments were conducted in a 1.3 m3tank and a 113 m3bunker.The blast parameters,including the quasistatic pressure(ΔpQS),special impulse(I),and peak overpressure(Δpmax),and images of the explosion process were recorded,and the influence of the Al content(30% and 50%) and Al particle size(1,10,and 50 μm) on the energy release of aluminum/rubber composites were investigated.The results revealed that the use of an active layer increased the peak overpressure generated by the primary blast wave,as well as the quasistatic pressure and special impulse related to fuel burning within tens of milliseconds after detonation.When the Al content was increased from 30% to 50%,the increases of ΔpQS and I were not obvious,and Δpmaxeven decreased,possibly because of decreased combustion efficiency and greater absorption of the blast wave energy for layers with 50% Al.Compared with the pure JH-2charge,the charge with 1 μm Al particles produced the highest Δpmax,indicating that better transient blast performance was generated by smaller Al particles.However,the charge with 10 μm Al particles showed the largest ΔpQSand I,suggesting that a stronger destructive effect occurred over a longer duration for charges that contained moderate 10 μm Al.展开更多
A direct comparison is made between the effectiveness of Al,Mg,and Be powders as additional fuels in model thermobaric compositions containing 20%fuel,20%ammonium perchlorate,and 60%RDX(1,3,5-Trinitro-1,3,5-triazacycl...A direct comparison is made between the effectiveness of Al,Mg,and Be powders as additional fuels in model thermobaric compositions containing 20%fuel,20%ammonium perchlorate,and 60%RDX(1,3,5-Trinitro-1,3,5-triazacyclohexane)passivated with wax.Experimentally determined calorimetric measurements of the heat of detonation,along with the overpressure histories in an explosion chamber filled with nitrogen,were used to determine the quasi-static pressure(QSP)under anaerobic conditions.Overpressure measurements were also performed in a semi-closed bunker,and all blast wave parameters generated after the detonation of 500 g charges of the tested explosives were determined.Detonation calorimetry results,QSP values,and blast wave parameters(pressure amplitude,specific and total impulses)clearly indicate that Be is much more effective as an additional fuel than either Al or Mg in both anaerobic post-detonation reactions as well as the subsequent aerobic combustion.The heat of detonation of the RDXwax/AP/Be explosive mixture is over 40%and 50%higher than that of the mixture containing aluminum and magnesium instead of beryllium,respectively.Moreover,the TNT equivalent of the Be-containing composition due to the overpressure in the nitrogen-filled explosion chamber is 1.66,while the equivalent calculated using an air shock wave-specific impulse at a distance of 2.5 m is equal to 1.69.The high values of these parameters confirm the high reactivity of beryllium in both the anaerobic and aerobic stages of the thermobaric explosion.展开更多
With rampant growth and improvements in drilling technology, drilling of blast holes should no longer be viewed as an arduous sub-process in any mining or excavation process. Instead, it must be viewed as an important...With rampant growth and improvements in drilling technology, drilling of blast holes should no longer be viewed as an arduous sub-process in any mining or excavation process. Instead, it must be viewed as an important opportunity to quickly and accurately measure the geo-mechanical features of the rock mass on-site, much in advance of the downstream operations. It is well established that even the slightest variation in lithology, ground conditions, blast designs vis-a-vis geologic features and explosives performance, results in drastic changes in fragmentation results. Keeping in mind the importance of state-of-the-art measurement-while-drilling （MWD） technique, the current paper focuses on integrating this technique with the blasting operation in order to enhance the blasting designs and results. The paper presents a preliminary understanding of various blasting models, blastability and other related concepts, to review the state-of-the-art advancements and researches done in this area. In light of this, the paper highlights the future needs and implications on drill monitoring systems for improved information to enhnnrp th~ hl^tin~ r^HIt~展开更多
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...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.展开更多
In the traditional blast furnace(BF)ironmaking process in China,a notable deviation exists between the theoretical and actual yield of hot metal,leading to unexpected iron loss and restricting the improvement of produ...In the traditional blast furnace(BF)ironmaking process in China,a notable deviation exists between the theoretical and actual yield of hot metal,leading to unexpected iron loss and restricting the improvement of production capacity,which cannot adapt to the increasingly intensified smelting rhythm.Focusing on a BF in a Chinese steel enterprise,a deep neural network algorithm was designed to model the impact of multiple parameters on actual yield of hot metal in a single BF smelting cycle,successfully accomplishing the theoretical computation and real-time prediction of yield of hot metal for subsequent,unknown BF smelting cycle.Test results show that the proposed algorithm demonstrates an impressive prediction accuracy of 86.7% within an error range of±10 t and can swiftly complete the training and convergence process in 32.5 s.By integrating prediction results with Nomogram,a regulatory mechanism was engineered to minimize the deviation between theoretical and actual yield of hot metal.This mechanism ensures the yield enhancement of hot metal through dynamic adjustments of BF operational parameters.Industrial-scale application experiments confirmed that the intelligent operation and optimization system,developed in the laboratory,can maintain the yield deviation of hot metal within a stable range of 30 t,achieving a maximum reduction in iron loss rate of 17.65%compared to that before system operation.The findings provide robust support for the yield increase and efficiency improvement of the experimental BF.展开更多
The accurate prediction of backbreak,a crucial parameter in mining operations,has a significant influence on safety and operational efficiency.The occurrence of this phenomenon is detrimental to the safety,capital and...The accurate prediction of backbreak,a crucial parameter in mining operations,has a significant influence on safety and operational efficiency.The occurrence of this phenomenon is detrimental to the safety,capital and human resources of a mine.This framework applies machine learning algorithms to predict backbreak.An enhanced precision will be explored specifically employing gradient boosting decision trees(GBDT),light gradient boosting machines(LightGBM),backpropagation neural network(BPNN),Graph Neural Networks(GNNs)and Kolmogorov-Arnold Network(KAN)algorithm.The study utilises a comprehensive dataset from the Goldfields Ghana Limited,Damang Mine comprising geomechanical,drilling,and blasting parameters(burden,spacing,stemming height,geometric stiffness,and powder factor)as well as backbreak data.The potential of each algorithm to learn the intricate relationships between the input features and backbreak values is investigated.To quantitatively assess the predictive performance of the models,the evaluation metrics,coefficient of determination(R^(2)),mean absolute error(MAE),and mean square error(MSE)are employed.The results revealed that GBDT and BPNN algorithms exhibited robust predictive capabilities,capturing the complex non-linear patterns in the dataset,achieving higher R^(2)values(97%and 92%respectively)and lower MAE scores(0.2603 and 0.456,respectively)and MSE scores(0.1456 and 0.3798,respectively).The LightGBM and KAN models also showed their predictive potential and captured the complex nonlinear patterns in the dataset but not as efficiently as GBDT and BPNN.GNN showed the least performance in backbreak prediction.The findings highlighted the potential of the GBDT model to enhance backbreak prediction accuracy,thereby aiding in safer and more efficient excavation practices.展开更多
文摘The concept of TNT(Trinitrotoluene,C_7H_5N_3O_6)equivalence is often invoked to evaluate the performance and predict the explosion parameters of different types of explosives.However,due to its low prediction accuracy and limited application range,the use of TNT equivalence for predicting explosion parameters in a confined space is rare.Compared with explosions in free fields,the process of explosive energy release in a confined space is closely related to various factors such as oxygen balance,combustible components content,and surrounding oxygen content.Studies have shown that in a confined space,negative oxygen balance explosives react with surrounding oxygen during afterburning,resulting in additional energy release and enhanced blast effects.The mechanism of energy release during afterburning is highly complex,making it challenging to determine the TNT equivalence for blast effects in a confined space.Therefore,this remains an active area of research.In this study,internal blast experiments were conducted using TNT and three other explosives under both air and N_2(Nitrogen)conditions to obtain explosion parameters including blast wave overpressure,quasi-static pressure,and temperature.The influences of oxygen balance and external oxygen content on energy release are analyzed.The author proposes principles for determining TNT equivalence for internal explosions while verifying the accuracy of obtained blast parameters through calculations based on TNT equivalence.These findings can serve as references for predicting blast performance.
文摘The present study considers the so-called air deck blasting,one of the most commonly used techniques for the improvement of blasting efficiency in mining applications.In particular,it aims to improve the operating conditions of large-scale equipment,increase the efficiency of the slope enlarging process,and reduce the mining cost.These objectives are implemented through a two-fold approach where,first,a program for slope enlarging based on the middle air-deck charge blasting-loosening technology is proposed,and second,the physical mechanism responsible for the stress wave attenuation in the rock is analyzed in the framework of a Holmquist–Johnson–Cook constitutive model.Field test results verify that the proposed approach is highly efficient and economical when used in medium-hard rock blasting and thus provides a basis for the practical implementation of slope enlargement for high benches in Open-Pit Mines.
基金funded by the National Natural Science Foundation of China(Grant No.11972018)the Defense Pre-Research Joint Foundation of Chinese Ordnance Industry(Grant No.6141B012858)。
文摘A layered charge composed of the JH-2 explosive enveloped by a thick-walled cylindrical casing(active aluminum/rubber and inert lithium fluoride/rubber composites) was designed and explosion experiments were conducted in a 1.3 m3tank and a 113 m3bunker.The blast parameters,including the quasistatic pressure(ΔpQS),special impulse(I),and peak overpressure(Δpmax),and images of the explosion process were recorded,and the influence of the Al content(30% and 50%) and Al particle size(1,10,and 50 μm) on the energy release of aluminum/rubber composites were investigated.The results revealed that the use of an active layer increased the peak overpressure generated by the primary blast wave,as well as the quasistatic pressure and special impulse related to fuel burning within tens of milliseconds after detonation.When the Al content was increased from 30% to 50%,the increases of ΔpQS and I were not obvious,and Δpmaxeven decreased,possibly because of decreased combustion efficiency and greater absorption of the blast wave energy for layers with 50% Al.Compared with the pure JH-2charge,the charge with 1 μm Al particles produced the highest Δpmax,indicating that better transient blast performance was generated by smaller Al particles.However,the charge with 10 μm Al particles showed the largest ΔpQSand I,suggesting that a stronger destructive effect occurred over a longer duration for charges that contained moderate 10 μm Al.
基金financed by the Military University of Technology under research project UGB 2024the Ludwig-Maximilian University of Munich (LMU)。
文摘A direct comparison is made between the effectiveness of Al,Mg,and Be powders as additional fuels in model thermobaric compositions containing 20%fuel,20%ammonium perchlorate,and 60%RDX(1,3,5-Trinitro-1,3,5-triazacyclohexane)passivated with wax.Experimentally determined calorimetric measurements of the heat of detonation,along with the overpressure histories in an explosion chamber filled with nitrogen,were used to determine the quasi-static pressure(QSP)under anaerobic conditions.Overpressure measurements were also performed in a semi-closed bunker,and all blast wave parameters generated after the detonation of 500 g charges of the tested explosives were determined.Detonation calorimetry results,QSP values,and blast wave parameters(pressure amplitude,specific and total impulses)clearly indicate that Be is much more effective as an additional fuel than either Al or Mg in both anaerobic post-detonation reactions as well as the subsequent aerobic combustion.The heat of detonation of the RDXwax/AP/Be explosive mixture is over 40%and 50%higher than that of the mixture containing aluminum and magnesium instead of beryllium,respectively.Moreover,the TNT equivalent of the Be-containing composition due to the overpressure in the nitrogen-filled explosion chamber is 1.66,while the equivalent calculated using an air shock wave-specific impulse at a distance of 2.5 m is equal to 1.69.The high values of these parameters confirm the high reactivity of beryllium in both the anaerobic and aerobic stages of the thermobaric explosion.
文摘With rampant growth and improvements in drilling technology, drilling of blast holes should no longer be viewed as an arduous sub-process in any mining or excavation process. Instead, it must be viewed as an important opportunity to quickly and accurately measure the geo-mechanical features of the rock mass on-site, much in advance of the downstream operations. It is well established that even the slightest variation in lithology, ground conditions, blast designs vis-a-vis geologic features and explosives performance, results in drastic changes in fragmentation results. Keeping in mind the importance of state-of-the-art measurement-while-drilling （MWD） technique, the current paper focuses on integrating this technique with the blasting operation in order to enhance the blasting designs and results. The paper presents a preliminary understanding of various blasting models, blastability and other related concepts, to review the state-of-the-art advancements and researches done in this area. In light of this, the paper highlights the future needs and implications on drill monitoring systems for improved information to enhnnrp th~ hl^tin~ r^HIt~
文摘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.
基金the financial supports from the National Natural Science Foundation of China(52004096)Natural Science Foundation of Hebei Province(E2024209101)+2 种基金Hebei Province Science and Technology R&D Platform Construction Project(23560301D)Tangshan Science and Technology Bureau Project(23130202E)Graduate Student Innovation Fund of North China University of Science and Technology(CXZZBS2025150).
文摘In the traditional blast furnace(BF)ironmaking process in China,a notable deviation exists between the theoretical and actual yield of hot metal,leading to unexpected iron loss and restricting the improvement of production capacity,which cannot adapt to the increasingly intensified smelting rhythm.Focusing on a BF in a Chinese steel enterprise,a deep neural network algorithm was designed to model the impact of multiple parameters on actual yield of hot metal in a single BF smelting cycle,successfully accomplishing the theoretical computation and real-time prediction of yield of hot metal for subsequent,unknown BF smelting cycle.Test results show that the proposed algorithm demonstrates an impressive prediction accuracy of 86.7% within an error range of±10 t and can swiftly complete the training and convergence process in 32.5 s.By integrating prediction results with Nomogram,a regulatory mechanism was engineered to minimize the deviation between theoretical and actual yield of hot metal.This mechanism ensures the yield enhancement of hot metal through dynamic adjustments of BF operational parameters.Industrial-scale application experiments confirmed that the intelligent operation and optimization system,developed in the laboratory,can maintain the yield deviation of hot metal within a stable range of 30 t,achieving a maximum reduction in iron loss rate of 17.65%compared to that before system operation.The findings provide robust support for the yield increase and efficiency improvement of the experimental BF.
文摘The accurate prediction of backbreak,a crucial parameter in mining operations,has a significant influence on safety and operational efficiency.The occurrence of this phenomenon is detrimental to the safety,capital and human resources of a mine.This framework applies machine learning algorithms to predict backbreak.An enhanced precision will be explored specifically employing gradient boosting decision trees(GBDT),light gradient boosting machines(LightGBM),backpropagation neural network(BPNN),Graph Neural Networks(GNNs)and Kolmogorov-Arnold Network(KAN)algorithm.The study utilises a comprehensive dataset from the Goldfields Ghana Limited,Damang Mine comprising geomechanical,drilling,and blasting parameters(burden,spacing,stemming height,geometric stiffness,and powder factor)as well as backbreak data.The potential of each algorithm to learn the intricate relationships between the input features and backbreak values is investigated.To quantitatively assess the predictive performance of the models,the evaluation metrics,coefficient of determination(R^(2)),mean absolute error(MAE),and mean square error(MSE)are employed.The results revealed that GBDT and BPNN algorithms exhibited robust predictive capabilities,capturing the complex non-linear patterns in the dataset,achieving higher R^(2)values(97%and 92%respectively)and lower MAE scores(0.2603 and 0.456,respectively)and MSE scores(0.1456 and 0.3798,respectively).The LightGBM and KAN models also showed their predictive potential and captured the complex nonlinear patterns in the dataset but not as efficiently as GBDT and BPNN.GNN showed the least performance in backbreak prediction.The findings highlighted the potential of the GBDT model to enhance backbreak prediction accuracy,thereby aiding in safer and more efficient excavation practices.
