Abstract
Open-pit coal mining often employs loosening blasting, with perforation blasting accounting for a significant portion of the coal seam mining costs. For coal of the same quality, the price of lump coal is much higher than that of crushed coal. Therefore, reducing the percentage of crushed coal in the blasting process is an important means to improve quality and efficiency in open-pit coal mining. How to develop a reasonable blasting scheme based on actual geological conditions has been a hot topic among scholars. In response to this issue, this study combines numerical simulation and field tests. Using the LS-DYNA software’s fluid–solid coupling algorithm, the effects of charge structure, explosive type, intermediate medium, and hole spacing parameters on blasting results are analyzed. An optimized blasting scheme is determined, with specific parameters including a charge spacing of 7 m, hole spacing of 11 m, charge structure with a 5 m blocking length, 4 m upper charge length, 2 m intermediate coal powder spacing, and 5 m lower charge length, using low-density explosives. This optimized scheme is applied in field tests, and a comparison with the control group shows that the fines rate decreased from 30.10 to 24.17%, a reduction of 5.93%; the lump coal proportion increased from 59.33 to 68.41%, an increase of 9.08%; and the proportion of large coal lumps decreased from 10.57 to 7.42%, a decrease of 3.15%. The fines rate and large lump rate decreased in the experimental group compared to the control group, improving blasting efficiency and effectively reducing the downtime of the surface production system due to blockages. This study not only provides theoretical guidance for blasting in soft coal seams of open-pit coal mines but also offers scientific support for practical engineering applications, demonstrating significant engineering value and broad application prospects.
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Introduction
Loosening blasting is one of the key stages in open-pit coal mining, primarily aimed at using explosive energy to loosen and break the rock or soil structure without causing significant throwing phenomena. Compared with traditional throwing blasting, loosening blasting requires about half the amount of explosives, effectively reducing the vibration, noise, and flying debris produced by blasting, thereby minimizing the impact on the surrounding environment. In the mining process, coal seams have relatively soft mechanical properties, and perforation blasting accounts for a significant portion of the coal seam mining costs1,2,3. With the same coal quality, lump coal is priced much higher than crushed coal. Therefore, reducing the percentage of crushed coal during the blasting process is an important measure for improving quality and efficiency in open-pit coal mining. Consequently, in coal seam loosening blasting, the aim is to maximize the lump coal yield and minimize the fines percentage. Currently, research on coal seam blasting is relatively limited, with most studies focusing on rock blasting, particularly the optimization and mechanism of medium-hard rock blasting. The issue of unreasonable blasting parameter design in coal seam mining has become increasingly prominent, leading to a lower lump coal ratio and decreased economic benefits in mining operations. Therefore, it is essential to conduct blasting parameter optimization studies for different coal seam geological conditions to achieve precise control over coal seam fragmentation.
Many scholars have conducted extensive research on loosening blasting. Xu et al.4 used theoretical analysis and numerical simulations to determine that the radius of the fracture zone formed by loosening blasting increases linearly with the hole radius. Xia et al.5 developed a loosening blasting scheme and conducted seismic wave monitoring, using the HHT method to study spectral characteristics and signal energy distribution. They found that the linear component of the measurement point and the explosion source was the largest among the vibration velocity components in the three directions. Xiang et al.6 optimized the original blasting parameters for the perforation loosening blasting method, calculated the time intervals between blasting rows and holes, and successfully reduced blasting vibrations and eliminated flying debris on-site using the “V”-shaped initiation method. Ding et al.7 analyzed the transmission effects, conduction effects, and bubble pulsation phenomena of water medium in the blasting process based on its mechanical properties, and verified through numerical simulations and field tests that water medium blasting could improve the blasting effect and effectively reduce dust. Li et al.8 established a nonlinear numerical model considering the coupling of factors like in-situ stress and gas migration to analyze the gas migration influence range and determine the effective impact range of loosening blasting. Shi et al.9 developed a prediction formula for fly-rock distance based on field tests, considering the impact of blasting parameters on fly-rock distance. Wang Wei et al. discussed the non-coupling charge effect in deep rock loosening blasting, solving applicable reflection wave equations for explosive products and shock wave equations for media in the rock, and obtained initial parameters for media around the explosive package. Zheng et al.10 simulated and tested loosening blasting mechanisms and parameters, revealing the relationship between blasting effects and cut angle and spiral angle of ascent. They found that cracks generated at the cutting edge propagated in the direction of the cutting edge. Yin et al.11 proposed a decoupled top face windboard charge structure for loosening blasting and analyzed the physical mechanism of stress wave attenuation in rocks based on the HJC constitutive model. The results showed that the top gap structure reduced the slope top stress and eliminated throwing phenomena, optimizing the blasting effect. Li et al.12 applied loosening blasting parameters and techniques to achieve non-reopen cutting in comprehensive mining, reducing fault coal pillar losses and increasing coal recovery rate.
The existing research on loosening blasting still has numerous shortcomings, especially in coal seam blasting parameter optimization. How to reasonably select blasting parameters based on actual geological conditions and engineering needs to achieve optimal loosening effects remains a significant challenge. Many scholars have studied the optimization of blasting parameters under different geological conditions, as summarized below:
Ziyi et al.13 used LSDYNA to establish numerical models with different hole diameters and hole spacings, analyzing stress wave propagation patterns, peak stress changes, and rock fracture states under different conditions. They proposed and verified an optimization formula for hole network relationships on-site. Ma et al.14 analyzed the blasting mechanism of large hole spacing and small row spacing using the interference effect of stress waves and explosion gas expansion theory, providing a calculation formula for the relationship between large hole spacing and small row spacing. Dai et al.15 simulated the blasting effect under three different slope top distances and three different hole spacings to address the issue of high lump coal rate at the Heishan open-pit coal mine. They compared the peak tensile stress at the hole mouth, slope surface, and slope top line, and determined the optimal blasting parameters for actual conditions, improving the blasting effect. Ding et al.16 used ANSYS/LSDYNA to verify the blasting effect of two optimization schemes, concluding that increasing hole spacing and row spacing could effectively control dust pollution and increase coal yield through on-site blasting optimization tests in open-pit mines. Yang et al.17 achieved blasting parameter optimization for a copper mine in Canada by introducing the MBF Model and the MSW Blasting Vibration Model. Zhang et al.18 proposed a three-hole simultaneous blasting technology, and the experimental results showed a reduction in flying rocks and an optimization of blasting fragmentation. Yin et al.19 proposed and verified a large-spacing parameter loosening blasting scheme using numerical simulations, which effectively improved hole enlargement efficiency and reduced economic costs. Ling et al.20 conducted a comprehensive study to assess the impact of repeated blasting on accumulated damage in interlayer rocks, using LS-DYNA to simulate the damage accumulation process caused by millisecond-delay blasting. Yang et al.21 designed and optimized blasting parameters based on geophysical parameters and geological age information from the mining area, verifying the feasibility of the optimization scheme through multiple blasting tests. Zhao et al.22 optimized bench drilling and blasting parameters using an enhanced gray wolf algorithm, improving the effectiveness of bench blasting mining. Guo et al.23 proposed a multi-parameter hybrid intelligent model based on fragmentation degree as the predictive indicator, which effectively improved the prediction accuracy of blasting effects. Bahraini et al.24 introduced a new intelligent 3D vision method that utilized the deep learning model YOLOv8 to predict blasting fragmentation and optimize blasting parameters.
In summary, the research on optimizing blasting parameters in open-pit mining faces numerous challenges, including the diversity of geological conditions, the complex interactions between blasting parameters, and the multidimensionality of blasting effect evaluation. Based on these challenges, research on optimizing blasting parameters for different geological conditions not only contributes to a deeper understanding of the blasting process in open-pit coal seams but also provides crucial technical support and guidance for improving coal mine quality and efficiency. While there has been considerable research in this field both domestically and internationally, there are still many gaps and shortcomings, especially in accurately evaluating blasting effects and developing optimization strategies under diverse geological conditions. Therefore, conducting research on blasting parameter optimization based on different geological conditions is of great significance for improving the theoretical framework of open-pit coal mine blasting. It also holds substantial practical value for enhancing coal mine production efficiency, reducing costs, and promoting green, low-carbon development.
The Shengli No. 1 open-pit coal mine, located in Inner Mongolia, primarily extracts lignite, which has poor physical and mechanical properties and is prone to fragmentation. The original blasting scheme was inadequate, leading to poor blasting results, high fines rates, and low lump coal rates. Therefore, this study focuses on the soft coal seam blasting in Shengli No. 1 open-pit coal mine, using LS-DYNA simulation software to explore the impact of different blasting parameters on blasting quality and determine the optimized blasting scheme. This optimized scheme is then applied to actual field blasting operations, which is of significant importance for improving the economic benefits of open-pit mining.
Indoor numerical simulation experiments
This paper takes the coal seam loosening blasting of the Shengli No.1 open-pit coal mine as the research object. A combination of numerical simulation and field tests is used to study the breaking effect of the coal seam under different blasting parameters using the ANSYS/LS-DYNA software. The stress variation is monitored to ultimately determine the optimized blasting parameters. The optimized scheme will be applied to field blasting experiments to evaluate its effectiveness. The research framework of the paper is shown in Fig. 1 below.
research framework.
Numerical simulation parameters setup
For this simulation, the LSDYNA numerical simulation software is used, employing the ALE method from the fluid–solid coupling algorithm. The model consists of the coal seam, air, explosives, and blocking materials. The impact of the charge structure, spacing media, type of explosives, and hole network parameters on the blasting effect will be explored.
The coal seam is modeled using the RHT model, with specific parameters provided by the production unit, as shown in Table 1.
The explosive model uses the MAT HIGH EXPLOSIVE_BLUE model, and the energy released by the explosive follows the JWL equation. Specific parameters are shown in Table 2.
The air model uses the MAT-NULL model, and the specific parameters are shown in Table 3.
The blocking material uses the MAT_SOIL_AND_FOAM model, and the specific parameters are shown in Table 4.
Analysis of the impact of charge structure on blasting quality
The model construction is shown in the Fig. 2. The simulation scheme is shown in Table 5.
Diagram of model parameters. (a) front view of the model, (b) side view of the model, and (c) gunnel arrangement.
Analysis of the impact of interval charge medium on blasting quality
The model construction is shown in Fig. 1 in Sect. "Analysis of the impact of charge structure on blasting quality". Different interval media have varying effects on the interval function. For the non-hard coal seam of the Shengli No. 1 open-pit coal mine, the interval medium that can absorb and disperse some of the explosive energy and reduce the range of destruction caused by the explosion is more suitable for practical engineering applications. Therefore, in this section, the charge structure from Scheme 2 in Sect. "Analysis of the Impact of charge structure on blasting quality" is used, with water and coal powder as the interval media, to explore the more suitable interval medium for the field. The parameters are shown in Tables 6 and 7 below:
Analysis of the impact of explosive type on blasting quality
The model construction is shown in Fig. 1 in Section "Analysis of the impact of charge structure on blasting quality". The density of the explosive plays a significant role in the blasting quality. Changes in density can affect the energy release, propagation speed, and stress waves of the explosion. In this section, the charge structure and interval medium from Scheme 2 in Sect. "Analysis of the impact of charge structure on blasting quality" are retained, but explosives with lower density are used for the simulation. The parameters are shown in Table 8 below:
Analysis of the impact of hole network parameters on blasting quality
The model construction is shown in the Fig. 3:
Diagram of model parameters. (a) side view of the model, (b) front view of the model, and (c) gunnel arrangement.
The model consists of 5 boreholes arranged in a triangular pattern, with a delay of 100 ms between rows of holes and 51 ms between adjacent holes. The blasting sequence for the boreholes is shown in Fig. 4 below:
Diagram of the detonation network.
This section studies the impact of hole network parameters on blasting quality. Based on the current hole network parameters used in the mine, with a row spacing of 8m and hole spacing of 10m, two new hole network designs are proposed, with all other conditions remaining the same. The designs are as follows in Table 9:
Results and discussion
Analysis of the impact of loading structure on blasting quality
Scheme 1
The variation of the stress cloud map during the blasting process is shown in Fig. 5 below:
Variation of stress cloud diagrams.
The model initiates detonation at the center of the upper and lower charge sections, and the explosive stress waves propagate outward. The surrounding coal is damaged by the stress waves, with coal closer to the charge column being compressed due to the high compressive stress, while coal farther from the charge column is fractured due to the tensile stress wave.
From the stress cloud maps at different stages shown in the figure above, it can be observed that: (1) At T = 50 μs, the explosion releases a large amount of energy, generating a shockwave that crushes the coal near the borehole, forming a crushed zone. The shockwave propagates deeper into the coal layer, gradually losing energy and converting into compressive stress waves. These, combined with the expansion of the explosion gas products, continue to damage the coal along the propagation path. (2) At T = 150 μs, the explosive has fully detonated, and the compressive stress waves are reflected off the free surface, converting into tensile stress waves that cause secondary damage to the previously affected coal. (3) At T = 500 μs, the stress waves have decayed into seismic waves, with much lower intensity. These waves can no longer fracture the coal and only cause elastic vibrations in the coal particles. The energy is completely absorbed as it propagates deeper into the coal. (4) At T = 2000 μs, the explosion reaction is essentially complete. Four monitoring points were selected at the back of the model, and the force process during the explosion was output using Pre-Post software. The stress-time curves are shown in the following Fig. 6.
Plot of stress changes at monitoring points.
From the Table 10 above, it can be seen that the maximum effective stress at point B is higher than at the other three monitoring points, approximately 7.61 times the minimum value at point A. This indicates that the closer the point is to the explosive column, the greater the effective stress. The effective stress at points B and C stabilizes above 20 MPa in the later stages, which exceeds the maximum tensile strength of coal, and can still cause coal fracturing.
Scheme 2
The variation of the stress contour map during the blasting process is shown in Fig. 7 below:
Variation of stress cloud diagrams.
The model is detonated at the center of the explosive charge in both the upper and lower parts, and the explosive reaction proceeds along the direction of the explosive column. The explosive stress wave propagates outward, causing damage to the surrounding coal due to the stress wave. Coal closer to the explosive column is compressed and damaged by the large compressive stress, while coal farther from the explosive column is stretched and damaged by the tensile stress wave.
From the stress contour maps at different stages shown in the figure above, it can be seen that when T = 50 μs, the explosion reaction just begins. The detonated explosives generate enormous energy, crushing the coal around the borehole and forming a crushed zone. The explosion continues along the direction of the explosive column. The shock wave propagates deeper into the coal seam, and when T = 150 μs, the explosive has fully detonated. The compressive stress wave reaches the model’s free surface, and upon reflection at the free surface, it transforms into a tensile stress wave, causing secondary damage to the coal along the propagation path. At T = 500 μs, the stress wave decays into seismic waves with lower intensity, unable to break the coal but only inducing elastic vibrations in the coal particles. At T = 2000 μs, the seismic wave energy is fully absorbed during propagation, and the explosive reaction is essentially complete.
Four monitoring points are selected on the back of the model, and the explosive force process at these points is output using Pre–Post software. The stress-time variation curves are plotted as shown in Fig. 8 below and the statistics of maximum stress at monitoring points are shown in Table 11.
Effective stress change.
Scheme 3
The changes in the stress contour map during the blasting process are shown in Fig. 9 below:
Variation of stress cloud diagrams.
The model is initiated from the center of the upper and lower explosive charge sections, with the explosive shock waves propagating radially outward. The surrounding coal body is damaged by the stress waves, with coal near the explosive charge experiencing compressive damage due to the high compressive stress, while coal farther from the charge is pulled apart by the tensile shock waves.
From the stress contour maps at different stages, it can be observed that at T = 50 μs, the explosion begins, and the explosives release a strong shock wave that crushes the coal around the explosive charge, forming a crushing zone. The explosive reaction continues from the center of the upper and lower charge sections, propagating toward the unignited areas. The shock wave propagates deeper into the coal seam, gradually transforming into compressive stress waves. By T = 150 μs, the explosives are fully detonated, and the compressive stress waves reach the free surface of the model, where they are reflected and converted into tensile stress waves, causing secondary damage to the coal along the propagation path. At T = 500 μs, the stress waves decay into seismic waves, which no longer cause significant damage to the coal body. By T = 2000 μs, the energy of the seismic waves is completely absorbed during propagation, and the explosive reaction is essentially complete.
Four monitoring points are selected on the rear surface of the model. The explosive loading process is output using Pre–Post software, and the stress-time curves are drawn as shown in the Fig. 10 below and the statistics of maximum stress at monitoring points are shown in Table 12.
Effective stress change.
From the Table 13, it can be concluded that the stress distribution trends are similar across all three schemes. The maximum stress occurs at point B, followed by points C, D, and A, indicating that the closer the point is to the explosive charge, the greater the effective stress. The average stress values for schemes two and three are lower than those for scheme one, suggesting that reducing the length of the upper charge section and increasing the length of the lower charge section helps to reduce the overall stress on the coal layer, preventing excessive damage to the coal and improving the blasting effect.
In scheme two, the stress values at points B, C, and D are lower than those in scheme one, while in scheme three, the stress values at points C and D are higher than in scheme one, indicating that adjusting the lengths of the upper and lower charge sections can improve the stress distribution in the coal layer. However, when the lower charge section length is too large, the stress in the lower half of the coal increases, which is detrimental to the improvement of the blasting effect.
Therefore, considering the goal of improving the blasting effect, the charge structure in scheme two should be chosen.
Analysis of the impact of interval charge and interval medium on blasting quality
Water medium
The changes in the stress cloud diagram during the blasting process are shown in the Fig. 11 below:
Variation of stress cloud diagrams.
The model is initiated from the center of the upper and lower charge segments, and the explosive shock wave propagates radially outward. The surrounding coal is damaged by the stress wave, with coal closer to the charge column being compressed due to the large compressive stress, while coal farther from the charge column is pulled apart due to tensile stress waves.
From the stress cloud diagrams at different stages shown in the figure above, we can observe the following: (1) At T = 50 μs, the explosive reaction has just begun, with a small portion of the explosive being detonated, releasing a huge shock wave that crushes the surrounding coal, forming an explosion cavity. The shock wave propagates radially outward from the center of the explosion, attenuating into a compressive stress wave. (2) At T = 100 μs, the compressive stress wave reaches the free surface, and upon reflection, it converts into a tensile stress wave, causing tensile damage to the surrounding coal, initiating the “rockfall” phenomenon. (3) At T = 130 μs, the stress wave reaches the water interval, where the water absorbs part of the explosive energy, reducing the intensity of the shock wave generated by the explosion. (4) At T = 150 μs, the explosive has fully detonated, and the stress wave, along with the expanding gases, continues to damage the coal. After this, the stress wave continuously attenuates into seismic waves, which can no longer break the coal, marking the end of the explosive reaction. Four monitoring points are selected at the back of the model, and their explosive force process is output using Pre–Post software. The stress vs. time curves are shown in the Fig. 12 and the statistics of maximum stress at monitoring points are shown in Table 14.
Effective stress change.
Coal powder medium
The changes in the stress cloud diagram during the explosion process are shown in the Fig. 13:
Variation of stress cloud diagrams.
The explosion model initiates detonation from the center of the top and bottom charge sections, with the explosion shockwaves spreading outward. The surrounding coal is damaged by the shockwaves; the coal closer to the charge column is compressed due to the massive compressive stress, while the coal further away is torn apart by the tensile shockwaves.
From the stress cloud diagrams at different stages shown above, the following observations can be made: (1) At T = 50 μs: The explosion has just started, and a small portion of the explosive is detonated, releasing a huge shockwave that crushes the surrounding coal and spreads outward from the explosion center. The shockwave gradually attenuates into a compressive stress wave. (2) At T = 100 μs: The compressive shockwave reaches the free surface and is reflected, converting into a tensile shockwave that causes surrounding coal to be torn apart. The “scattering phenomenon” begins. (3) At T = 130 μs: The stress wave reaches the coal powder medium, and the friction between the coal powder particles effectively reduces the propagation of the shockwave, limiting the extent of the damage caused by the explosion. (4) At T = 150 μs: The explosive has fully detonated, and the stress wave, along with the expansion of the explosive gases, continues to damage the coal. After this point, the stress wave continues to attenuate into seismic waves, which can no longer fracture the coal, signaling the end of the explosion reaction. At four monitoring points on the rear side of the model, the explosion force process is output using Pre–Post software, and the stress-time curve is plotted, as shown in the Fig. 14 and the statistics of maximum stress at monitoring points are shown in Table 15.
Effective stress change.
From the Table 16, it can be seen that the effectiveness of the interval media is ranked as follows: coal powder interval, air interval, and water interval. Among them, the stress difference between the air interval and water medium at the four monitoring points is not significant, while in the coal powder interval, the stress at points B and C shows a noticeable decrease, indicating that coal powder can effectively reduce the propagation of shock waves. In the interval charge structure blasting process, the air interval, water, and coal powder serve different functions, summarized as follows:
Air interval: An air interval is a segment of air placed in the borehole to separate the explosive charge into two parts, preventing interference between them. Its characteristic is its low density, which can effectively prevent the interaction between the upper and lower explosive sections.
Water medium: In the interval charge structure, water serves as an interval medium to provide cooling, buffering, and energy dissipation. The high density and specific heat capacity of water allow it to absorb and dissipate explosive energy, reducing the shock waves and vibrations generated by the blast.
Coal powder medium: During the charging process, coal powder serves as an interval medium for isolation and damping. The high density of coal powder and the friction between its particles allow it to effectively isolate the explosive charge and reduce the propagation of shock waves. Additionally, coal powder can dissipate some of the explosive energy, thereby reducing the blast’s damage radius and impact.
In conclusion, the air interval is mainly used to prevent interference between the explosive charges, the water medium is primarily used for cooling and energy dissipation, and the coal powder medium is primarily used for isolation and damping. For the Shengli No. 1 open-pit coal mine, which has relatively soft coal seams, coal powder medium can effectively isolate the upper and lower explosive charges, disperse the energy released during the explosion, and reduce the blast’s damage range, making it more suitable for practical engineering applications.
Analysis of the impact of explosive types on blasting quality
The variation of stress contour maps during the blasting process is shown in the Fig. 15:
Variation of stress cloud diagrams.
The model initiates detonation at the center of the explosive charge in both the upper and lower parts, and the explosive stress waves propagate outward. The surrounding coal is damaged by the stress waves, with coal close to the explosive column being compressed due to the high compressive stress, and coal farther away from the explosive column being pulled apart by tensile stress waves.
From the stress contour maps at different stages shown in the figure above, it can be seen that: when T = 50 μs, the explosive reaction has just started, and most of the explosive charge has not been detonated yet. The detonated explosives release a large energy shock wave that crushes the coal near the borehole, forming a crushed zone around the blast cavity. The shock wave propagates deeper into the coal seam, gradually losing energy and converting into compressive stress waves. Together with the expansion of the gases generated by the explosion, it continues to damage the coal along the propagation path. At T = 150 μs, the explosive is fully detonated, and the compressive stress wave reflects off the free surface, transforming into tensile stress waves, which cause secondary damage to the coal along the propagation path. At T = 500 μs, the stress waves have attenuated into seismic waves, and their intensity is too low to break the coal. At T = 2000 μs, the explosive reaction has essentially ended.
Four monitoring points were selected on the back of the model. The stress history at these points was output using Pre–Post software, and the stress-time curves are shown in the Fig. 16 and the statistics of maximum stress at monitoring points are shown in Table 17.
Effective stress change.
As shown in the Table 18, after switching to low-density explosives, the stress values at the four monitoring points have decreased to varying degrees compared to the previous results. This indicates that low-density explosives help reduce the overall stress on the coal seam, prevent excessive damage to the coal, and improve the blasting effect.
Compared to high-density explosives, low-density explosives contain less explosive material in the same volume, which effectively reduces the released energy, detonation velocity, and the stress waves generated by the explosion. Additionally, from a safety perspective, high-density explosives are more susceptible to external conditions (such as temperature, pressure, etc.), making them more sensitive during storage and use. In contrast, low-density explosives are safer. Therefore, in order to improve the blasting effect, the use of low-density explosives should be preferred.
Analysis of the effect of hole network parameters on blasting quality
Four monitoring points (A, B, C, D) are selected around the #2 blast hole in the model to measure the stress variation process at these points in three different models. The layout diagram of monitoring points is shown in Fig. 17. The stress change process at the monitoring point is shown in Fig. 18.
Layout of monitoring points.
Stress change process at model monitoring points.
Based on Table 19 above, we can conclude:
Plan 2 with a 7 × 11 hole network, compared to Plan 1 with an 8 × 10 hole network, shortens the burden distance and increases the hole spacing. As a result, the average stress peaks at points C and D in Plan 2 are higher than in Plan 1, while the average stress peaks at points A and B are lower. Moreover, the reduction in stress peaks at points A and B is greater than the increase at points C and D. The overall stress distribution in the model is lower than in Plan 1. Additionally, the stress distribution across points in Plan 2 is more uniform, indicating more efficient use of explosive energy, a more even distribution of fragment sizes, and improved blasting performance.
Plan 3 with a 9 × 9 hole network, compared to Plan 1 with an 8 × 10 hole network, shortens the hole spacing and increases the burden distance. Consequently, the average stress peaks at points A and B in Plan 3 are higher than in Plan 1, while the average stress peaks at points C and D are lower. The decrease in stress peaks at points C and D is smaller than the increase at points A and B. The overall stress distribution in the model is higher than in Plan 1. Furthermore, the stress distribution at points in Plan 3 is uneven, indicating inefficient use of explosive energy, uneven fragment size distribution, and poorer blasting performance.
Based on the simulation results and the investigation of the effects of charge structure, interval medium, type of explosive, and hole network parameters on blasting quality, the final optimized blasting plan is determined to be:
Charge structure: sealing length of 5 m, upper charge length of 4 m, coal powder interval length of 2 m, lower charge length of 5 m.
Low-density explosives, and hole network parameters with a hole spacing of 11 m and burden distance of 7 m.
Field test
The blasting parameter optimization test was conducted at the Shengli No. 1 open-pit coal mine. The Shengli coalfield is located in the northern suburbs of Xilin Hot, with geographic coordinates ranging from 115° 30′ E to 116° 26′ E longitude and 43° 57′ N to 44° 14′ N latitude. The coalfield is distributed in a northeast–southwest belt, with a strike length of 45 km and an average dip width of 7.6 km, covering a coal-bearing area of 342 square kilometers. The coalfield is associated with valuable minerals (germanium, petroleum). Of the 15 coal seams in the coalfield, the majority of the sections above seam No. 6 are suitable for large-scale open-pit mining.
Test plan design
The blasting parameter optimization test was conducted in the southern 855 Flat area of the Shengli No. 1 open-pit coal mine. The 855 Flat blast zone consists of a total of 260 blast holes, with 100 holes selected as the experimental area and the remaining holes serving as the control area. The blast holes were arranged in a triangular pattern, with sequential initiation. The layout of the blast area is shown in the Fig. 19 below. The hole filling is shown in Fig. 20.
Explosive area layout.
Charging Structure. (a) control group: continuous loading, (b) test group: spaced loading.
On-site construction process and result records
The experimental area used segmented loading. The construction process involved first placing the electronic detonators, loading the lower section of the blast holes, followed by filling the interval with coal powder. Then, electronic detonators were placed again, the upper section of explosives was loaded, and finally, the holes were sealed and filled. Once all the blast holes were filled, the wiring was connected, delay times were set, a safety perimeter was established, and the detonation command was awaited. The experimental process record is shown in Fig. 21.
Construction flowchart.
After the detonation in the blasting area, the construction personnel entered to inspect the blasting results. They could only enter the area for recording after confirming that everything was in order. Since the Victory No. 1 open-pit coal mine uses loosening blasting, the explosion only leaves cracks on the surface of the plateau and does not form a distinct blast pile. The records are as follows in Fig. 22:
Site crack diagram.
After the blasting operation was completed, the electric shovel began excavation work, forming the excavation profile. The profiles of both the experimental and control sections were photographed and analyzed. The analysis was conducted using Split-Desktop block size analysis software. This software divides objects in the input image and processes the pixels. It calculates the lengths of other objects based on the known length of an object in the image. The excavation profile conditions for both the control group and the experimental group are as follows in Fig. 23:
Excavation cross-section on site. (a) is the control group and (b) is the test groupl.
The block size distribution of the coal pile after blasting obtained from image recognition is as follows:
As shown in the Table 20, after blasting, the reject coal rate in the control group is 30.10%, the proportion of lump coal is 59.33%, and the proportion of large-diameter coal is 10.57%. The original loading structure used continuous loading, with the explosives concentrated in the lower half of the coal seam. Due to the relatively soft coal layers in the mining area, this caused the explosion energy to focus on the lower half, resulting in excessive damage to the coal layer, while the upper half was insufficiently damaged. This led to higher reject coal rates and large-diameter coal percentages in the final results.
According to the size distribution histogram (Fig. 24), the relationship between the percentage of coal and particle size follows a quadratic distribution trend. That is, as the particle size increases, the percentage first increases and then decreases. Among the 7 particle size groups in the 45–300 mm range, the distribution is relatively uniform, with each group accounting for about 6.07%. The particle size range of 25–35 mm has the highest percentage, accounting for 9.1%. The majority of the lump coal particle sizes are distributed in the 25–300 mm range, accounting for 59.33%.
Histogram of blockiness for control group.
The statistics of block size of the test group are shown in Table 21 above.Compared with the control group, the percentage of fine coal decreased from 30.10 to 24.17%, a reduction of 5.93%; the percentage of lump coal increased from 59.33 to 68.41%, an increase of 9.08%; and the percentage of large-diameter coal decreased from 10.57 to 7.42%, a reduction of 3.15%. The decrease in fine coal rate and large-diameter coal rate in the test group compared to the control group indicates an improvement in blasting efficiency. According to the particle size distribution histogram, the relationship between the coal percentage and particle size follows a quadratic function trend, where the percentage of coal first increases and then decreases as the particle size increases. In the 0–35 mm range, the percentage of coal increases with particle size. However, between 35 and 300 mm, the percentage begins to decline, and above 300 mm, it decreases rapidly. The highest percentage of coal falls within the 25–35 mm particle size range, at 9.13%. The majority of lump coal has particle sizes ranging from 25 to 300 mm, with a percentage of 68.41%.
The Victory No.1 open-pit coal mine crushing station performs daily lump coal crushing and lump coal rate data collection. As the electric shovel begins excavation in the blasted area, crushing station data is simultaneously collected for comparison between the control group and the test group. The results are shown in the Table 22 below:
From the comparison in the table above, it can be observed that the lump coal rate and the overall average lump coal rate of the test group are both higher than those of the control group on a daily basis.
Conclusion
This study focuses on the loosening blasting of coal seams at the Victory No.1 open-pit coal mine. Using LS-DYNA simulation software, the effects of charging structure, intermediate media, explosive types, and blasthole parameters on blasting quality were studied. An optimized blasting scheme was determined and verified through a field engineering test at the Victory No.1 open-pit coal mine. The specific conclusions are as follows:
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1.
Using LS-DYNA software and the ALE method within the fluid–structure coupling algorithm, simulations were performed for different charging structures, intermediate media, explosive types, and blasthole parameters. Monitoring points were selected to analyze the stress process. The optimized blasting scheme was determined with a blasthole spacing of 7 m, a hole spacing of 11 m, a charging structure consisting of 5 m blocking length, 4 m upper charge length, 2 m coal powder interval length, 5 m lower charge length, and the use of low-density explosives.
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2.
Field tests were conducted at the Victory No.1 open-pit coal mine, analyzing the excavation cross-section lump size distribution and lump coal rate statistics from the crushing station. The results show that compared to the control group, the test group exhibited a decrease in both the fine coal and large coal ratios, with an increase in lump coal rate. Specifically, the fine coal rate decreased from 30.10 to 24.17%, a reduction of 5.93%; the lump coal percentage increased from 59.33 to 68.41%, an increase of 9.08%; and the large coal ratio decreased from 10.57 to 7.42%, a reduction of 3.15%. In addition, the test group effectively reduced the downtime caused by blockages in the ground production system.
Data availability
The data presented in this study are available on request from the corresponding author due to the confidentiality of production data related to the test site, the Shengli No. 1 Open Pit Coal Mine.
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Acknowledgements
The authors thank the Shengli No. 1 Open Pit Coal Mine for providing a research base for this paper.
Funding
This paper was supported by the National Natural Science Foundation of China (Grant No. 52174131; 52474153), the National Key Research and Development Program of China (2023YFC2907305), the Jiangsu Provincial Graduate Student Research and Practice Innovation Program Project (KYCX24_2868), and the China University of Mining and Technology Graduate Student Innovation Program Project (2024WLKXJ035).
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Z.L.: Methodology, Writing—original draft preparation, Visualization. X.D.: Conceptualization, Writing—original draft preparation. M.L.: Formal analysis, Writing—review and editing. J.L.: Validation, Writing—review and editing. Z.Y.: Investigation. X.L.: Investigation. B.L.: Resources. Y.Z.: Data curation. All authors have read and agreed to the published version of the manuscript.
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Liao, Z., Ding, X., Liang, M. et al. Research on the optimization of optimal blasting parameters and fragmentation control based on coal seam geological conditions. Sci Rep 15, 12238 (2025). https://doi.org/10.1038/s41598-025-94278-6
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DOI: https://doi.org/10.1038/s41598-025-94278-6
