Mine Blasts Research Articles

Machine learning based prediction of flyrock distance in rock blasting: A safe and sustainable mining approach

Flyrock is a significant environmental and safety concern in mining and construction. It arises from various geological and blast design factors, posing risks to workers, machinery, and nearby structures. This study examined how these factors affect the rate and distance of flyrock projections caused by blasts. To address this issue, advanced machine learning (ML) models were used to predict flyrock distances in the Akoko Edo dolomite quarries. The models examined included bidirectional recurrent neural networks (BRNNs), support vector regression (SVR) with different kernels (SVR-S, SVR-RBF, SVR-L, SVR-P), long short-term memory (LSTM) networks, and random forest (RF) algorithms. A case study was conducted using 258 blasting data samples to develop these models. Key factors influencing flyrock were identified: blast hole burden distance, maximum instantaneous charge, and rock brittleness index. Using these factors, a flyrock possibility assessment chart was created to enhance the safety of small-scale mining operations. The model’s prediction accuracy was evaluated using correlation coefficients and four performance metrics. The LSTM model stood out, achieving the highest coefficient of correlation (R2 = 0.99) for both training and testing datasets. This indicates that the LSTM model accurately predicts blast-induced flyrock distance. The study also revealed that the Gaussian-RBF kernel SVR has high prediction accuracy when compared to other SVR variants (SVR-S, SVR-L, and SVR-P). In conclusion, the study compared various ML models for flyrock reduction and found that the LSTM model was the most effective in estimating blast-induced flyrock distances.

Experimental study on dynamic response of hard rock blasting under in-situ stress

Deep mine rock mass is in high static stress and dynamic disturbance coupling conditions, its mechanical properties and failure mode is different from the shallow rock mass, which leads to low rock blasting efficiency and engineering geology hazards. In-depth research on the dynamic response of rock blasting under in-situ stress will help to optimize the blasting design, improve the blasting efficiency and safety of blasting operations, and provide theoretical support for rock blasting in deep mines. In this study, the blasting experiment was conducted on granite specimens under different biaxial static stress conditions. Meanwhile, the dynamic response of rock blasting was monitored, collected, and analyzed using a high-speed digital image correlation (DIC) measurement system, a strain wave acquisition system, and an acoustic emission (AE) system. The results show that small and medium pre-static loads inhibit blast crack propagation, at which time the cumulative AE hits from dynamic loads (CAECd) are more than those from pre-static loads (CAECs), but large pre-static loads promote crack propagation, at which time CAECs are more than CAECd. Secondly, as pre-static load increases, the specimen's maximum strain (εmax) decreases first and then increases, but as lateral pressure coefficient (K) increases, the εmax in the direction of lower static stress decreases gradually and the εmax in the direction of higher static stress remains constant. In addition, the confining pressure magnitude and K affect the area and shape of the failure zone of the specimen, as well as the size and propagation direction of the radial crack. Especially when the confining pressure is high, the specimen will undergo shear failure, and the smaller K is the more serious the shear failure. Finally, the failure criterion of rock under dynamic-static coupling conditions is proposed based on the energy index, and different failure types of rock are discussed.

Case Study on the Advancements in Diagnosis and Treatment Technologies for Military Personnel with Complex Explosive Injuries

Case(s): A 51-year-old military personnel with severe limb injury from mortar shelling, admitted to Orthopedic Traumatology Department, Ternopil Regional Hospital, Ukraine.Conclusions: Explosive injuries typically arise from the detonation of devices such as landmines, improvised explosive devices, or grenades, causing harm through blast, fragmentation, and thermal effects. Despite a delayed presentation to medical care, the patient underwent multiple debridement procedures, including Vacuum-Assisted Closure therapy, and vascular reconstruction, leading to limb salvage. This case underscore needs for timely medical care, addressing risks of mine blasts and cold weather injuries through training.

Artificial Intelligence Models for Predicting Ground Vibrations in Deep Underground Mines to Ensure the Safety of Their Surroundings

Ground vibrations induced by underground mining blasting has a significant impact on the stability and safety of surface buildings near mines. Due to the thick rock layers overlying underground mines, there is presently limited accuracy in regard to predicting ground vibrations induced by underground mine blasting. Therefore, this study aims to improve the accuracy of predicting ground vibrations induced by underground blasting by comprehensively measuring the peak particle velocity (PPV) in all three directions and independently considering on the impact of vertical distance. Random forest regression (RFR), bagging regression (BR), and gradient boosting regression (GBR) were used to regress the X-axis PPV (X-PPV), Y-axis PPV (Y-PPV), and Z-axis PPV (Z-PPV) based on blasting records measured at an iron mine. In addition, a genetic algorithm, gray wolf optimizer (GWO), and a particle swarm optimization were used to optimize the parameters of the RFR, BR, and GBR. The comparison results show that GWO-GBR is the optimal model for the prediction of the X-PPV (R2 = 0.8072), Y-PPV (R2 = 0.9147), and Z-PPV (R2 = 0.9265), respectively. Thus, the GWO-GBR model proposed in this study is considered a highly reliable model for predicting ground vibrations induced by underground mine blasting to ensure the safety of the mines’ surroundings.

Experimental study on decoupled charge blasting-induced crack propagation with parabolic shaped charge

In this study, a new parabolic shaped charge structure is proposed to realize bidirectional blasting in coal mines. To examine the fracture characteristics of rock mass induced by shaped charge structure under explosion load, a dynamic caustic experimental system is adopted. Further, the blasting-induced damage distribution characteristics of rock mass caused by different decoupling coefficients are investigated. Using polymethyl methacrylate (PMMA) as the experimental material, a two-dimensional model is established. AUTODYN, an explicit dynamics simulation program, is used to examine the initial crack generation process under shaped charge blasting. The stress wave propagation rule and the relationship between blasting damage and decoupling coefficient are explored. The results show that the parabolic shaped charge structure can control the explosion energy distribution and reduce the surrounding rock damage. When the decoupling coefficient is 2, the main crack length is optimum. During the crack propagation process, the growth rate and stress intensity factor of the main crack of the specimen show an oscillatory downward trend. Two stress concentration points are generated on either side near the main crack, forming the initial crack. When the decoupling coefficient is less than 2, long cracks exist in both the shaped and non-shaped charged directions, and the energy gathering effect is poor. When the decoupling coefficient is greater than 2, the energy gathering effect is obvious, but the main crack length is shorter.

Inferring the Focal Depths of Small Earthquakes in Southern California Using Physics-Based Waveform Features

ABSTRACT Determining the depths of small crustal earthquakes is challenging in many regions of the world, because most seismic networks are too sparse to resolve trade-offs between depth and origin time with conventional arrival-time methods. Precise and accurate depth estimation is important, because it can help seismologists discriminate between earthquakes and explosions, which is relevant to monitoring nuclear test ban treaties and producing earthquake catalogs that are uncontaminated by mining blasts. Here, we examine the depth sensitivity of several physics-based waveform features for ∼8000 earthquakes in southern California that have well-resolved depths from arrival-time inversion. We focus on small earthquakes (2<ML<4) recorded at local distances (<150 km), for which depth estimation is especially challenging. We find that differential magnitudes (Mw/ML–Mc) are positively correlated with focal depth, implying that coda wave excitation decreases with focal depth. We analyze a simple proxy for relative frequency content, Φ≡log10(M0)+3log10(fc), and find that source spectra are preferentially enriched in high frequencies, or “blue-shifted,” as focal depth increases. We also find that two spectral amplitude ratios Rg 0.5–2 Hz/Sg 0.5–8 Hz and Pg/Sg at 3–8 Hz decrease as focal depth increases. Using multilinear regression with these features as predictor variables, we develop models that can explain 11%–59% of the variance in depths within 10 subregions and 25% of the depth variance across southern California as a whole. We suggest that incorporating these features into a machine learning workflow could help resolve focal depths in regions that are poorly instrumented and lack large databases of well-located events. Some of the waveform features we evaluate in this study have previously been used as source discriminants, and our results imply that their effectiveness in discrimination is partially because explosions generally occur at shallower depths than earthquakes.

Migration time prediction and assessment of toxic fumes under forced ventilation in underground mines

This study aims to predict the migration time of toxic fumes induced by excavation blasting in underground mines. To reduce numerical simulation time and optimize ventilation design, several back propagation neural network (BPNN) models optimized by honey badger algorithm (HBA) with four chaos mapping (CM) functions (i.e., Chebyshev (Che) map, Circle (Cir) map, Logistic (Log) map, and Piecewise (Pie) map) are developed to predict the migration time. 125 simulations by the computational fluid dynamics (CFD) method are used to train and test the developed models. The determination coefficient (R2), the variance accounted for (VAF), the Willmott’s index (WI), the root mean square error (RMSE), the mean absolute percentage error (MAPE), and the sum of squares error (SSE) are utilized to evaluate the model performance. The evaluation results indicate that the CirHBA-BPNN model has achieved the most satisfactory performance by reaching the highest values of R2 (0.9945), WI (0.9986), VAF (99.4811%), and the lowest values of RMSE (15.7600), MAPE (0.0343) and SSE (6209.4), respectively. The wind velocity in roadway (Wv) is the most important feature for predicting the migration time of toxic fumes. Furthermore, the intrinsic response characteristic of the optimal model is implemented to enhance the model interpretability and provide reference for the relationship between features and migration time of toxic fumes in ventilation design.

Analysing Slope Stability in Response to Blast-Induced Dynamic Loading by Pseudo-Static Approach

Regular blasting in opencast coal mines generates significant ground vibrations, impacting mine slope stability and posing risks to life and property. This study focuses on monitoring ground vibrations in an opencast coal mine through near-field monitoring and investigating the impact of blast-induced seismic loading on slope stability. The approach involves a pseudostatic method utilising Strength Reduction Factor (SRF), based on Finite Element (FE) numerical modelling software. The study examines a pit slope with a tension crack under seismic loading, varying the intensity of seismic coefficients (Ks) from 0 to 0.5. These coefficients are determined through field vibration monitoring during production blasts. In numerical modelling, seismic loading is considered in both horizontal (outward of slope face) and vertically downward (in-line with gravity). Numerical modelling incorporates dimensionless horizontal seismic coefficient (Kh) and vertical seismic coefficient (Kv), and both directions which is expressed as Seismic Coefficient Ratio (SCR) which is the ratio of Kv and Kh for interpretation of results. Although SCR induces changes in the Factor of Safety (FoS), its impact is minimal compared to seismic loading solely in the horizontal direction. Consequently, increasing SCR leads to a decrease in FoS. The study observes that Peak Ground acceleration (PGA) in the longitudinal direction has greater dominance than in the transverse direction. Additionally, the seismic wave in the horizontal direction destabilises the slope more than the corresponding vertical seismic wave. These findings are elucidated in the context of the Critical Slip Surface (CSS).

Numerical Evaluation of Vibration Induced by Explosive Blasting in the Bauxite Mines of Sangarédi, Guinea

During rocks blasting by explosives in mines and quarries, Vibration phenomena appear in the surrounding environment, often causing significant damage to neighboring structures such as: buildings, bridges, tunnels and dams. This is why mining companies using the technique of the explosion are often faced with constraints of limiting the vibration level in order to minimize or eliminate potential damage to neighboring structures or reduce neighbor complaints.
 This paper presents a new numerical prediction model for vibration level induced by explosive blasting in the Bauxite mines of Sangarédi, Guinea. The dynamic damage law is associated with vibration phenomena analyses to determine numerical value of the particle velocities of different points located at different distances from the explosion hole for the explosion of a single charge hole, in order to compare to the vibration level required by the specifications of the Guinea mining company, which authorizes a vibration level of 10 mm/s in an inhabited area. The prediction of the vibration level gives particle velocities of 11m/s at a distance of 10 m from the explosion hole. Based on the results of the model, one could estimate that this required vibration level would be reached at a distance of 80 m from the blast hole.

Failure mechanism and treatment of mine landslide with gently-inclined weak interlayer: a case study of Laoyingzui landslide in Emei, Sichuan, China

The landslide of mine is of great harm and wide influence, which can easily cause huge economic losses and endanger the life safety of workers. Therefore, landslide failure mechanism and more efficient landslide treatment methods have been the focus of landslide research. Laoyinzui landslide with a volume of 250,000 m3 occurred along the gently inclined weak interlayer at 6:00 (UTC + 8) on 5 January 2019 in Huangshan Limestone Mine, Emei City, Sichuan Province, China. The deformation history and failure mechanism of the landslide were analyzed based on the field investigation and geological conditions of landslide area. The treatment method of using excavators to remove all sliding body within the arm length by excavating the small-bench in the bedrock was proposed. The slope stability after treatment was analyzed based on the monitoring data. The results showed that the landslide was triggered by rainfall and earthquake after long-term creep deformation under the action of various factors. Weak interlayer was the potential sliding surface of landslide. The tensile cracks at the back edge of the landslide and the joint fissures and karst caves of the upper limestone provided convenient conditions for rainwater infiltration. Mining activities, including excavation and blasting, resulted in deterioration of mechanical properties of rock mass. Rainfall was the main trigger for the landslide. Water accumulated in weak interlayer, leading to increase of pore water pressure and decrease of anti-sliding force. Earthquake was the trigger for the landslide, which resulted in the reduction of rock mass structural strength. The Laoyingzui landslide consisted of two stages. First, a traction landslide of + 825 m–915 m occurred, and then a push landslide of + 725 m–+ 825 m occurred under the compression of the upper rock mass. The slope displacement was small and the deformation tended to be stable. The treatment method was safe and efficient. This paper can provide reference for the failure mechanism research and treatment of similar landslides.

Deformation and failure characteristic of open-pit slope subjected to combined effects of mining blasting and rainfall infiltration

Accelerated deformation and slope instability commonly occur within open-pit mines, indicating the action of potential triggering events such as mining disturbances or rainfall. However, limited studies have been conducted on the deformation behavior of open-pit slopes subjected to the combined effects of mining blasting and rainfall infiltration. This study proposes an integrated approach that combines satellite Interferometric Synthetic Aperture Radar (InSAR), coupled numerical analyses, and field monitoring for systematic evaluation of the deformation behavior and failure characteristic of a massive landslide that occurred on November 8, 2019 in the Qidashan open-pit mine, China. The InSAR data were reviewed aiming at characterizing the surface deformation fields over the mine site via small baseline subsets technique, as well as identifying unstable slopes and revealing their high susceptibility to mining operations and rainfall. Finite-difference modeling was performed to investigate the response mechanisms and factor of safety of the unstable slope, which were validated by using field data monitored with the global navigation satellite system. The simulation results indicate that the Qidashan landslides were triggered by intense rainfall causing a gradual reduction of shear strength, and mining activities promoted failure by providing stress relaxation and blasting disturbance. Furthermore, this study contributes critical insight into the identification of deformation and early warning of unstable slopes in frequent mining environments, and allows for a back-analysis of the failure mechanism of landslide reactivation. This study highlights how important it is to account for the combined effects of mining and rainfall infiltration when assessing the stability of open-pit slopes, which can mitigate the failure risk.

Обеспечение сейсмической безопасности строительных объектов при массовых промышленных взрывах с учетом предельных состояний первой группы

In certain situations, seismic safety during open-pit mine blasts can be ensured only on the condition of coordination of the explosion technology regulatory documents with the provisions of the construction field regulatory documents. The distinctive feature of the construction documents is the application of probabilistic approaches to load specification. The limit state method is used to calculate the structures. The probability of non-exceeding the design values of the main loads is adopted as not less than 0.98 for the calculations of the first group of limit states. The explosion technology regulatory documents take into account the second group limit states at which the operation of protected objects is possible but hampered, for example, as a result of the increased frequency of objects’ repairs. At the same time, the probability of minor damages is 0.9–0.95. The methodology to ensure the seismic safety of protected objects during open-pit mine blasts, based on regression analysis of the experimental data and considering the probabilistic nature of such effects, is presented. The methodology considers all features of explosion technology applied at a given enterprise, as well as the structure of the geological environment along the way of seismic wave propagation, and other factors. Despite many advantages, however, the probabilistic approaches limit the minimum number of experimental points required to build a regression line and the limits of confidence intervals. Therefore, the increase in the confidence level of peak particle velocity from 0.95 to 0.98 must be accompanied by the increase in the minimum number of experimental points used to build the regression from 80 to 200, which significantly increases the scope and cost of the required experimental studies. The article considers the possibility of an increase in the confidence level of peak particle velocity caused by open-pit mine blasts from 0.95 to 0.98 without increasing the volume of the experimental sample; the conditions under which it becomes possible are analyzed as well.

Investigating the Impact of Short Burden and Spacing on Blasting Output in Zeberced Quarry

Blasting has been adjudged as the cheapest method of hard rock fragmentation. The itinerary of rock breakage through blasting in open pit mines is a complex portent which is measured via various variables and parameters. This research investigates the impact of short burden and spacing on blasting output with the aim of establishing a more suitable and economically viable approach. Trials and proposed methods were adopted to investigate blasting geometry results. Results obtained showed that the trials method of 1.2 m by 1.2 m and proposed blasts method of 2.0 m by 2.0 m burden and spacing at 9m depth, covered areas were 80.64 m2 and 99.36 m2 respectively, while at 12 m depth with same blasting geometry covered 224 m2 and 276 m2 respectively. The first trial and proposed blasts methods using burden and spacing of 1.2 m by 1.2 m produced 2,583.71 tons and 2,387.62 tons respectively. Hence, with the use of 2.0 m by 2.0 m burden and spacing, the blasts operations produced 7,176.96 tons and 6,632.28 tons respectively. Meanwhile, the results revealed that, short burden (≤ 1.2 m by 1.2 m) threatens safety in which flyrocks are spawned and it’s dangerous to equipment and personnel, at the same time, the areas covered, quantity produced (i.e. volume) and the tonnage were small compared to the engineering control methods. However, it was found that the trials blast methods were not economically worthwhile in terms of explosive consumption compared to the proposed measure of the geometry.

Evaluating the efficacy of air-decking technique for surface mine blasts

Evaluating the efficacy of air-decking technique for surface mine blasts

Enhancing Orebody Knowledge using Measure-While-Drilling Data: A Machine Learning Approach

Due to limited resource definition and grade control drilling, conventional bench-scale geochemical exploration is frequently plagued by uncertainty, resulting in diminished processing plant efficiencies. The Measure-While-Drilling (MWD) system comprises a set of sensors designed to gather data pertaining to the performance of mining blast hole drill rigs. Previous MWD research primarily relied on penetration rate to identify rock type and estimate grade. This investigation uses Data Fusion and Machine Learning (ML) algorithms to characterize geochemical orebody quality values, such as iron percentage, phosphorous, sulfur, alumina, and silica content, based on MWD data collected at the field-scale, thereby facilitating efficient mine planning and excavation. Feature importance algorithms identified novel significant MWD variables, such as force on bit and ratio of bit air pressure to penetration rate, which provide valuable insights into subsurface geochemical properties. The performance of various ML algorithms was compared, with the Random Forest algorithm demonstrating the highest coefficients of determination (up to 0.96), indicating accurate field or laboratory results prediction. As a result, this work demonstrates that MWD data can be used to obtain high-resolution orebody knowledge prior to mining, improving subsurface geochemistry prediction. This knowledge can optimize the excavation of high-grade material by minimizing dilution from lower-grade or waste rock entering the processing plant.

Evaluating the Efficacy of Air-Decking Technique for Surface Mine Blasts

Evaluating the Efficacy of Air-Decking Technique for Surface Mine Blasts

Influence of Joint Orientation and Spacing on Induced Rock Mass Damage due to Blasting in Limestone Mines

Influence of Joint Orientation and Spacing on Induced Rock Mass Damage due to Blasting in Limestone Mines

EVALUATION OF GROUND VIBRATION AND AIR BLAST MEASUREMENTS INDUCED BY BLASTING IN A QUARRY MINE

The energy released during blasting in underground and surface mines for excavation purposes can cause flyrock, excessive level of ground vibration and air blast. In this study, ground vibration and air blast induced by blasting were measured and evaluated for a quarry mine in the Kangal district of Sivas province. Within the scope of this study, observations and measurements were made before, during, and after two blasting operations in a quarry mine to evaluate the environmental effects of blasting. The environmental effects of blasting were assessed by considering both the blasting parameters and the ground vibration and air blast measurement results.

Field test of blasting vibration and adjacent slope stability under the influence of blasting vibration in mining

Blasting mining in open-pit has a significant impact on the adjacent slope, which often causes the rock mass cracking and spalling of the slope to form a landslide disaster. In order to explore the impact of blasting vibration on the adjacent slope, field tests were carried out with professional testing equipment, and several blasting vibration data were measured. Sadovsky formula was used for fitting analysis, and the influence coefficient of blasting vibration was obtained. The slope stability analysis was carried out by using the limit equilibrium SLIDE analysis software, and the slope safety factor under the influence of blasting vibration was obtained. The results show that: The maximum blasting vibration speed monitored in this blasting is 2.1987 cm/s, and the main vibration frequency is 14.6484 Hz. Therefore, according to the standards in the regulations, the impact of this blasting on the slope meets the corresponding requirements. In this slope stability analysis, the blasting vibration influence coefficient Kc= 0.032, when 40 m away from the final slope is used. Morgen Prince method and Spencer method generally have higher safety factors than Bishop method. The safety factor of the analysis section at the 45° slope angle is 1.217. The slope can maintain stability under the influence of blasting vibration.

Source time functions and interference from blast arrays

AbstractIn this study, we review the principles of blast array design for vibration reduction and we present a parametric Laplace‐domain model to predict source time functions for mine blasts that accounts for the relation between charge weight and frequency. We developed the model for one of Europe's largest iron ore mines, Mt. Erzberg, Austria, where we repeatedly monitored production blasts with arrays of 80–125 seismic sensors. Our model enables us to simulate not only resonance modes and Doppler shifts but also time‐domain waveforms. We use the normalized cross‐correlation coefficient of observed and synthetic waveforms to calibrate the model. The overall good match of our predictions suggests that our modelling of the source time functions could be used for more advanced predictions of the peak ground velocity, which is essential to designing charge weight distributions in modern mining operations.