Search Results (35)

In open-pit bench pre-splitting blasting, the interaction of explosion-induced stress waves between blast holes is essential for safeguarding the rear rock mass. This study utilizes the caustic method to examine the propagation velocity of explosion-induced cracks, the stress intensity factor at the crack tip, and the final morphology of cracks between adjacent blast holes with varying delay times. Field pre-splitting blasting experiments were carried out to validate these effects. The experimental results reveal that, for short inter-hole delay times (0–12 μs), a “hook-like” crack intersection zone emerges between blast holes. Changes in delay time influence the patterns of crack propagation, leading to deviations in the propagation direction of cracks in subsequent blast holes due to the combined effects of stress waves and cracks from preceding holes. The fracture mechanism evolves from pure Mode I (tensile) to a mixed Mode I-II (tensile-shear). Vibration signals from the field blasting tests were analyzed using the variational mode decomposition (VMD) method. The findings indicate that optimized inter-hole delay times can reduce peak particle velocity (PPV) by 18.7–23.4% compared to simultaneous initiation, thereby significantly minimizing damage to the rear rock mass, a crucial factor for maintaining slope stability. Full article

The dynamic response law of the vibration cavity effect in the adjacent large-section rectangular coal roadways induced by deep-hole bench blasting vibrations was deeply revealed, and the prediction accuracy of the PPV in the coal roadway was improved. The vibration equations of the coal roadway were derived based on the stress wave propagation theory and the wave-front momentum conservation theorem. Based on coal roadway vibration monitoring data and numerical simulations, the cavity effect and vibration response characteristics of the coal roadway induced by deep-hole bench blasting under varying blast source distances and relative angle conditions were analyzed. A predictive model for PPV of rectangular coal roadway surrounding rock, incorporating the relative angle as one of the key influencing factors, was developed. The results showed that the presence of cavities and changes in the relative angle enhance the asymmetry of the dynamic response of blasting stress waves near the free surfaces of the surrounding rock on each side of the coal roadway, resulting in significant differences. Moreover, as the blasting distance decreases, the cavity effect tends to promote greater PPV differences on each side of the coal roadway. The prediction model exhibited improved accuracy by about 15.6% compared to the traditional Sadovski equation for the face-blasting side of the coal roadway. It demonstrates better adaptability and predictive capability. This research provides a theoretical basis for the dynamic response of adjacent large-section rectangular coal roadways and for preventing dynamic instability failures in open-pit mining. Full article

The adjustment of delay time in open-pit bench blasting is a research hotspot in vibration control. Its core lies in utilizing the periodic characteristics of vibration waves to achieve the superposition and cancellation of wave peaks and troughs. However, due to the spatiotemporal variability in the propagation of blast-induced vibration waves, the optimal delay time determined for vibration control requirements at a specific protected area (monitoring point) makes it difficult to achieve the misalignment superposition effect simultaneously at multiple monitoring points. To address the challenge of multi-area vibration control in open-pit bench blasting, this paper proposes an adjustment method based on local delay adjustment. First, a spatiotemporal relationship model between blast holes with monitoring points is established to calculate vibration wave arrival times. This enables rapid hole identification during dense wave arrivals at monitoring points, with waveform separation achieved through initiation delay adjustments. Following the Anderson principle, reconstructed single-hole vibrations are superimposed according to the wave arrival sequence to validate control efficacy. Statistical analysis of concurrent wave arrivals across all-direction monitoring points identifies high-probability vibration hazard locations. Targeted delay adjustments for blast holes within clustering arrival periods at these locations enable comprehensive vibration reduction. Field data confirm that single-point control reduces peak vibration by >10.55% through simultaneously reducing the amount of waves in clustering arrival periods. Multi-point control resolves seven hazard locations across two directions, attaining 88.57% hazard elimination efficiency and 14.05% peak velocity attenuation. This method achieves vibration control through local delay adjustments while maintaining the fragmentation effect of the original scheme, providing a new approach to solving the challenge of vibration control in large-scale blasting areas. Full article

This study systematically analyzes the influence of the charge length-to-diameter ratio and stemming length on the radius and volume of blasting craters in coal and rock blasting crater tests to effectively address the challenge of achieving coal–rock separation in mixed blasting construction. In addition, it examines the energy distribution mechanism of blasting fragmentation and establishes characteristic equations for coal and rock blasting craters. Numerical simulations and blasting tests are conducted to investigate the casting effect of rock benches and the fragmentation characteristics of coal and rock benches under different charge structures. The results indicate that when the ratio of charge length to stemming length exceeds 0.91 and 0.74 for the coal and rock benches, respectively, the utilization rate of explosive energy for rock fragmentation gradually surpasses that for rock throwing. The charging structure is identified as a key factor in achieving coal–rock mixed blasting and separation mining. The explosive energy is effectively utilized with a bottom interval length of 2 m for rock benches and a stemming length ranging from 2.5 to 3 m for coal seams. This configuration raises the connectivity of rock damage cracks, improves the distribution of tensile cracks at the top of the coal seam, and prevents bulging or coal–rock interactions (blasting mixing) at the coal–rock interface. The findings demonstrate that the optimized charging structure effectively achieves separate mining in coal–rock mixed blasting, fulfilling the requirement of avoiding coal–rock mixing during blasting. The research provides valuable mining strategies and technical experience for achieving separate mining in coal–rock mixed blasting in open-pit coal mines and improving the recovery of thin coal seams. Full article

Bench-scale geotechnical characterization often suffers from high uncertainty, reducing confidence in geotechnical analysis on account of expensive resource development drilling and mapping. The Measure-While-Drilling (MWD) system uses sensors to collect the drilling data from open-pit blast hole drill rigs. Historically, the focus of MWD studies was on penetration rates to identify rock formations during drilling. This study explores the effectiveness of Artificial Intelligence (AI) classification models using MWD data to predict geotechnical categories, including stratigraphic unit, rock/soil strength, rock type, Geological Strength Index, and weathering properties. Feature importance algorithms, Minimum Redundancy Maximum Relevance and ReliefF, identified all MWD responses as influential, leading to their inclusion in Machine Learning (ML) models. ML algorithms tested included Decision Trees, Support Vector Machines (SVMs), Naive Bayes, Random Forests (RFs), K-Nearest Neighbors (KNNs), Linear Discriminant Analysis. KNN, SVMs, and RFs achieved up to 97% accuracy, outperforming other models. Prediction performance varied with class distribution, with balanced datasets showing wider accuracy ranges and skewed datasets achieving higher accuracies. The findings demonstrate a robust framework for applying AI to real-time orebody characterization, offering valuable insights for geotechnical engineers and geologists in improving orebody prediction and analysis Full article

Bench-scale geological modeling is often uncertain due to limited exploration drilling and geophysical wireline measurements, reducing production efficiency. Measure-While-Drilling (MWD) systems collect drilling data to analyze mining blast hole drill rig performance. Early MWD studies focused on penetration rates to identify rock types. This paper investigates Artificial Intelligence (AI)-based regression models to predict geophysical signatures like density, gamma, magnetic susceptibility, resistivity, and hole diameter using MWD data. The machine learning (ML) models evaluated include Linear Regression (LR), Decision Trees (DTs), Support Vector Machines (SVMs), Random Forests (RFs), Gaussian Processes (GP), and Neural Networks (NNs). An analytical method was validated for accuracy, and a three-tier experimental method assessed the importance of MWD features, revealing no performance loss when excluding features with less than 2% importance. RF, DTs, and GPs outperformed other models, achieving R² values up to 0.98 with a low RMSE, while LR and SVMs showed lower accuracy. The NN’s performance improved with larger datasets. This study concludes that the DT, RF, and GP models excel in predicting geophysical signatures. While ML-based methods effectively model relationships in the data, their predictive performance remains inherently constrained by the underlying geological and physical mechanisms. Model selection depends on computational resources and application needs, offering valuable insights for real-time orebody analysis using AI. These findings could be invaluable to geologists who wish to utilize AI techniques for real-time orebody analysis and prediction. Full article

The size distribution of rock fragments significantly influences subsequent operations in geotechnical and mining engineering projects. Thus, accurate prediction of this distribution according to the relevant blasting design parameters is essential. This study employs artificial intelligence methods to predict the fragmentation of open-pit bench blasting. The study employed a dataset comprising 97 blast fragment samples. Random forest and XGBoost models were utilized as base learners. A prediction model was developed using the stacking integrated strategy to enhance predictive performance. The model’s performance was evaluated using the coefficient of determination (R²), the mean square error (MSE), the root mean square error (RMSE), and the mean absolute error (MAE). The results indicated that the model achieved the highest prediction accuracy, with an R² of 0.943. In the training set, the model achieved MSE, RMSE, and MAE values of 0.00269, 0.05187, and 0.03320, while in the testing set, these values were 0.00197, 0.04435, and 0.03687, respectively. The model was validated using five sets of actual blasting block data from a northeastern mining area, which yielded more accurate prediction results. These findings demonstrate that the stacking strategy effectively enhances the prediction performance of a single model and offers innovative approaches to predicting blasting block size. Full article

Drilling and blasting is the conventional method used for rock fragmentation in open pit mining. Blast-induced damage can reduce the level of stability of benches and pit slopes. To develop an optimal blast design, an adequate knowledge of the rock properties and in situ fractures is needed. Fractures are generally the paths of least resistance for explosive energy and can affect the intensity of blast-induced damage. Discrete Fracture Networks (DFNs) are 3D representations of joint systems used for estimating the distribution of in situ fractures in a rock mass. The combined finite/discrete element method (FDEM) can be used to simulate the complex rock breakage process during a blast. The objective of this paper is to develop a methodology for assessing the influence of in situ joints on post-blast fracturing and the associated wall damage in 2D bench blast scenarios. First, a simple one-blasthole scenario is analyzed with the FDEM software Irazu 2D and calibrated based on a laboratory-scale blasting experiment available from previous literature. Secondly, more complex scenarios consisting of one-blasthole models at the bench scale were simulated. A bench blast without DFN (base case) and one with DFN were numerically simulated. The model with DFN demonstrated that the growth path and intensity of blast-induced fractures were governed by pre-existing fractures, which led to a smaller wall damage area. The damage intensity for the base case scenario is about 82% higher than for the blast model with DFN included, which highlights the significance of in situ fractures in the resulting blast damage intensity. The methodology for developing the DFN-included blasting simulation provides a more realistic modeling process for blast-induced wall damage assessment. This results in a better characterization of the blast damage zone and can lead to improved slope stability analyses. Full article

To meet the increasing demand for rapid and efficient evaluation of tunnel blasting quality, this study presents a comprehensive review of the current state of the art in tunnel blasting evaluation, organized into five key areas: Blasting Techniques and Optimization, 3D Reconstruction and Visualization, Monitoring and Assessment Technologies, Automation and Advanced Techniques, and Half Porosity in Tunnel Blasting. Each section provides an indepth analysis of the latest research and developments, offering insights into enhancing blasting efficiency, improving safety, and optimizing tunnel design. Building on this foundation, we introduce a digital identification method for assessing half porosity through 3D image reconstruction. Utilizing the Structure from Motion (SFM) technique, we re-construct the 3D contours of tunnel surfaces and bench faces after blasting. Curvature values are employed as key indicators for extracting 3D point cloud data from boreholes. The acquired postblasting point cloud data is processed using advanced software that incorporates the RANSAC algorithm to accurately project and fit the borehole data, leading to the determination of the target circle and borehole axis. The characteristics of the boreholes are analyzed based on the fitting results, culminating in the calculation of half porosity. Field experiments conducted on the Huangtai Tunnel (AK20 + 970.5 to AK25 + 434), part of the new National Highway 109 project, provided data from shell holes generated during blasting. These data were analyzed and compared with traditional onsite measurements to validate the proposed method’s effectiveness. The computed half porosity value using this technique was 58.7%, showing minimal deviation from the traditional measurement of 60%. This methodology offers significant advantages over conventional measurement techniques, including easier equipment acquisition, non-interference with construction activities, a comprehensive detection range, rapid processing speed, reduced costs, and improved accuracy. The findings demonstrate the method’s potential for broader application in tunnel blasting assessments. Full article

In the bench method of tunnel excavation, the blasting impact from upper bench blasting poses significant risks to personnel and equipment. This study employed dynamic analysis software, ANSYS/LS-DYNA, and field testing to examine the propagation characteristics and attenuation behavior of tunnel shock waves. The findings revealed that, near the central axis of the tunnel, shock wave overpressure was lower compared to areas near the tunnel wall due to reflections from the wall. As the shock wave traveled a distance six times the tunnel diameter, it transitioned from a spherical wave to a plane wave. The attenuation coefficient for the plane wave ranged from 1.03 to 1.17. A fitting formula for shock wave overpressure attenuation, based on field test results, was proposed, and it showed good agreement with the numerical simulation results. This provided valuable theoretical insights for predicting shock wave overpressure during bench method tunnel excavation. Full article

It is well known that the first stage of mine-to-mill optimization is rock fragmentation by blasting. The degree of rock fragmentation can be expressed in terms of average grain (X₅₀) size and size distribution. There are approaches in which exponential functions are used to estimate the size distribution of the pile that will be formed before blasting. The most common of these exponential functions used to estimate the average grain size is the Kuz–Ram and KCO functions. The exponential functions provide a curve from 0% to 100% using the mean grain size (X₅₀), characteristic size (X_C), and uniformity index (n) parameters. This distribution curve can make predictions in the range of fine grains and coarse grains outside the acceptable error limits in some cases. In this article, the usability of the hyperbolic tangent function, which is symmetrical at origin, in the estimation of the size distribution as an alternative to the exponential distribution functions used in almost all estimation models is investigated. As with exponential functions, the hyperbolic tangent function can express the aggregated size distribution as a percentage with reference to the variables X₅₀ and X_C. It has been shown that the hyperbolic tangent function provides 99% accuracy to the distribution of fine grains and coarse grains of the pile formed as a result of blasting data for the characteristic size (X_C) parameter and the uniformity index (n). Full article

The use of mixtures of thiol collectors has been reported to benefit the flotation of Cu-Ni-PGM ores. However, the increasing reliance on recycled water in mineral processing may alter the performance of flotation reagents. This necessitates a deeper understanding of flotation reagents into their behaviour in different components or constituents of process water. This is crucial for better decision-making when determining the quality of process water that optimises reagent performance for specific ores. Ca²⁺ and Na⁺ are common cations in process water and are known to exert various effects in both the pulp and froth phases, making them frequent subjects of recent investigations into water quality. In contrast, NO₃⁻ anions have received less research attention compared to other common ions in process water, such as Cl⁻, SO₄²⁻, and S₂O₃²⁻, despite being present in significant concentrations. NO₃⁻ ions are understood to originate from blasting chemicals used during mining, leaching into solution during milling, and thus can be considered key players in the interactions occurring in the pulp phase. Their interactions in the pulp phase and their role in flotation are therefore important to consider. This work presents results from bench-scale batch flotation tests conducted on a Cu-Ni-PGM ore from the Merensky Reef, using mixtures of thiol collectors, namely sodium isobutyl xanthate and sodium diethyl dithiophosphate, in solutions containing Ca(NO₃)₂ and NaNO₃. NaNO₃ solutions showed higher solids recoveries for all thiol collector mixtures compared to Ca(NO₃)₂ solutions, this was attributed to increased gangue entrainment in Na⁺ compared to Ca²⁺. Higher Cu and Ni recoveries were observed in NaNO₃ solutions across all thiol collector mixtures; however, higher Cu and Ni grades were achieved in Ca(NO₃)₂ solutions compared to NaNO₃. Full article

The blasting quality of open-pit mining can be enhanced and the production cost of stope reduced by establishing a mathematical model for step drilling and blasting costs based on stope consumption. By enhancing the Gray Wolf algorithm, the parameters for step drilling and blasting are optimized, resulting in improved effectiveness for step blasting mining, as demonstrated through modeling and calculation. The enhanced Gray Wolf algorithm effectively enhances the blasting performance, reduces production costs, and increases production efficiency. Taking a limestone mine as an example, the optimized drilling and blasting parameters are as follows: hole spacing of 4.62 m, row spacing of 4 m, and explosive consumption rate of 0.23 kg/t; based on these parameters, the stope’s production cost is reduced to CNY 7.7. Full article

The evaluation of blasting vibrations primarily hinges on two physical quantities: velocity and acceleration. A significant challenge arises when attempting to reference the two types of vibration data in relation to one another, such as different types of seismometers, noise, etc., necessitating a method for their equivalent transformation. To address this, a transformation method is discussed in detail with a case study, and equations for the ratio (Ra) of the particle peak velocity (PPV) to the particle peak acceleration (PPA) are proposed. The findings are twofold: (1) The conventional data conversion processes often suffer from low accuracy due to the presence of trend terms and noise in the signal. To mitigate this, the built-in MATLAB function is used for trend term elimination, complemented by a combined approach that integrates CEEMDAN with WD/WDP for noise reduction. These significantly enhance the accuracy of the transformation. (2) This analysis reveals a positive power function correlation between Ra and the propagation distance of the blast vibrations, contrasted by a negative correlation with the maximum charge per delay. Intriguingly, the Ra values observed in pre-splitting blasting operations are consistently lower than those in bench blasting. The established Ra equations offer a rapid, direct method for assessing the transformation between the PPV and PPA, providing valuable insights for the optimization of blasting design. Full article

Blasting technology is widely applied in various engineering applications due to its cost-effectiveness and high efficiency, such as in mining, transport infrastructure construction, and building demolition. However, the occurrence of cracking in the rear row has always been a major problem that disrupts mining bench blasting. To address this issue, a three-hole simultaneous blasting technology is proposed in this study. Both numerical simulations and onsite blasting experimental testing were conducted. To aid this endeavor, the three-hole simultaneous blasting and the hole-by-hole blasting methods were adopted to comparatively analyze the severity of the damage caused to the original rock and the effect of rock fragmentation in the rear row. The obtained results highlighted that the outcome of the blast produced by the three-hole simultaneous blasting method is satisfactory, with fewer flying stones and concentrated blasting piles required. Additionally, the original rock in the rear row showed no obvious sign of tensile damage and had uniform fragmentation. It was also found that a block size of less than 60 cm accounts for 100%, while a block size of less than 50 cm accounts for 98.7% of the whole blocks, with no large blocks reported. Moreover, a penetrating horizontal crack occurred in the direction of the connection of the blast hole center when the three-hole simultaneous blasting method was adopted. This resulted in a smooth and flat rear part of the rocks at the interface. Compared to the hole-by-hole blasting method, the three-hole simultaneous blasting method improved the effective stress and displacement at each measurement point. At the measurement point directly at the front of the borehole, the maximum effective stress attained 67.9 GPa, and the maximum displacement reported was 31.9 cm. Overall, it was shown that the three-hole simultaneous blasting technology is applicable in similar applications of mine bench blasting, which is conducive to addressing the rear row original rock strain for onsite bench blasting. Full article