Mine medium-length hole blasting lumpiness optimization method and system based on VCR mining method

Abstract

The invention belongs to the technical field of mining, and discloses a VCR mining method-based mine medium-length hole blasting lumpiness optimization method and system. According to the method, the filling length, explosive quantity and delay time blasting parameters of the two ends of a blast hole in VCR mining method blasting construction are determined, and the blasting lumpiness of a deep hole in a mine is calculated; based on the calculation result, blasting parameters in blasting vibration of the underground chamber structure are optimized; and performing a simulation test on the safety and stability of the mine structure based on the blasting parameter optimization result. According to the method, blasting parameters such as the filling length, the explosive quantity and the delay time of the two ends of the blast hole in blasting construction of the VCR mining method are determined, the blasting lumpiness of the deep hole in the mine is calculated and optimized, and the ore removal efficiency is improved. The influence of blasting vibration on the stability of the underground chamber structure is researched, the blasting vibration propagation law is researched, blasting vibration is reduced by optimizing blasting parameters, and safety and stability of mine structures are ensured.

Description

Technical Field

[0001] This invention belongs to the field of mining technology, and particularly relates to a method and system for optimizing the block size of deep-hole blasting in mines based on VCR mining method. Background Technology

[0002] Blasting, as an effective means of breaking rocks in a short time, is widely used in various sectors of the national economy. While blasting technology brings huge economic benefits, it also brings corresponding safety issues. The rationality of blasting parameter settings is a crucial factor affecting the blasting effect. Before blasting, operators need to pre-assess the size of the blasting area, the size of the resulting blocks, and the changes in the free surface during the blasting operation.

[0003] Based on the above analysis, the problems and defects of the existing technology are as follows: the ore extraction efficiency is low in the calculation and optimization of the block size of deep hole blasting in the mine; the effect of optimizing blasting parameters to reduce blasting vibration is poor, and the safety and stability of mine structures are low. Summary of the Invention

[0004] To overcome the problems existing in related technologies, the present invention discloses an embodiment of a method and system for optimizing the block size of deep-hole blasting in mines based on VCR mining method.

[0005] The technical solution is as follows: a method for optimizing the block size of deep-hole blasting in mines based on VCR mining, including the following steps:

[0006] S1, determine the blasting parameters such as the filling length at both ends of the blast hole, the amount of explosive, and the delay time in the VCR mining blasting construction, and calculate the block size of deep hole blasting in the mine;

[0007] S2. Based on the calculation results, the blasting parameters in the blasting vibration of the underground chamber structure are optimized.

[0008] S3, based on the optimization results of blasting parameters, conducts simulation tests on the safety and stability of mine structures.

[0009] In step S1, the filling length of the borehole includes:

[0010] The length of the plug at the bottom of the hole is:

[0011] In the formula, The length of the plug at the bottom of the hole. The height of the stratified blasting;

[0012] The orifice plugging structure combines granular packing material and a water column energy absorption buffer mechanism, with the granular layer thickness ≥ twice the diameter of the drug pack and the water column height ≥ 15% of the orifice depth.

[0013] Furthermore, the water column energy absorption and buffering mechanism includes:

[0014] (1) Dynamic fluid phase change control: controllable microbubbles or phase change materials are injected into the water column to cause the fluid to undergo gas-liquid phase change or density jump at the moment of impact, forming a multi-level energy dissipation layer.

[0015] (2) Active modulation of vortex flow field; a spiral flow guiding structure using the vortex damping force model is designed in the buffer cavity to force the water flow to form a directional vortex;

[0016] (3) By using feedback closed-loop control, the buffer force is always kept within the critical threshold.

[0017] In step (1), the formula for the multi-stage energy dissipation layer is:

[0018]

[0019] In the formula, For multiphase flow energy dissipation, Specific heat capacity of the fluid For the temperature rise, These are the densities of the liquid phase and the gas phase, respectively. For microbubble volume, The adiabatic index, For pressure integral, Integrating over time;

[0020] In step (2), the vortex damping force model includes: the nonlinear model is:

[0021]

[0022] In the formula, For impact force, For water flow velocity, The linear damping coefficient is... This is the vortex angular velocity coefficient. ω is the vortex angular velocity.

[0023] In step S1, the dosage calculation includes:

[0024] Dynamic unit consumption is adjusted to:

[0025]

[0026] In the formula, For dynamic unit consumption, The blastability coefficient of the ore and rock is taken as 1.2–1.5 for hard rock; This is the unit consumption coefficient. Rock mass quality indicators;

[0027] Air-spaced charge loading is optimized as follows: charge package length The air section occupies 20–30% of the hole depth.

[0028] In step S1, the delay time is:

[0029]

[0030] In the formula, For the extended time, The rock mass impedance coefficient is... For rock vibration dosage, For rock wave impedance, It is the elastic modulus;

[0031] The calculation of blasting block size includes the calculation of the fractal dimension of blasting block size as follows:

[0032]

[0033] In the formula, is the block size fractal dimension; the larger the value, the more uniform the block size.

[0034] In step S2, the blasting parameters in the blasting vibration of the underground chamber structure are optimized, including:

[0035] (1) Self-similarity matching; the image is segmented into domain blocks and range blocks; the self-similarity between blocks is found through affine transformations of scaling, rotation, and translation, expressed as:

[0036]

[0037] In the formula, This represents the inter-block self-similarity value. For image blocks, For affine matrices, It is a translation vector;

[0038] (2) Iterative function system IFS encoding, which uses the local self-similarity within the image for encoding;

[0039] (3) The block-level image texture complexity is quantified using fractal dimension, and the expression is:

[0040]

[0041] In the formula, This represents the block-level image texture complexity value. Number of block-sized images The block size radius;

[0042] (4) The Hurst exponent is used for time series analysis of blasting block size, and its expression is:

[0043] In the formula, This is the Hurst exponent value.

[0044] In step S2, based on the optimization results of the blasting parameters, a simulation test is conducted on the safety and stability of the mine structures, including:

[0045] Swarm intelligence explores the solution space through particle position update formulas;

[0046] Reinforcement learning dynamically adjusts block size based on a reward function.

[0047] Furthermore, swarm intelligence explores the solution space through a particle position update formula, expressed as:

[0048]

[0049] In the formula, For the first Particles in The solution for the time position, For update rate, For the first Particles in The solution for the time position, Divided into the update rates of the first and second particles, Divided into the update distances of the 1st and 2nd particles, For the first The position where a particle achieves its highest fitness. For the first Particles in Location at any given moment This is the position where the entire system achieves the highest fitness.

[0050] The block size is dynamically adjusted based on the reward function as follows:

[0051]

[0052] In the formula, The block-scale fractal dimension function, This is the initial block size adjustment factor. For dynamic adjustment rate, The block size radius, To adjust the coefficient, This is the dynamic block size adjustment factor.

[0053] Another objective of this invention is to provide a deep-hole blasting block size optimization system based on VCR mining method. This system implements the aforementioned deep-hole blasting block size optimization method based on VCR mining method. The system includes:

[0054] The blasting block size calculation module is used to determine the blasting parameters such as the filling length at both ends of the blast hole, the amount of explosive, and the delay time in VCR mining blasting construction, and to calculate the blasting block size of deep holes in mines.

[0055] The blasting parameter optimization module optimizes the blasting parameters in the blasting vibration of underground chamber structures based on the calculation results.

[0056] The test verification module conducts simulation tests on the safety and stability of mine structures based on the optimization results of blasting parameters.

[0057] Combining all the above technical solutions, the beneficial effects of this invention are as follows:

[0058] The VCR mining blasting parameter optimization provided by this invention can improve the energy utilization rate of explosives, improve the blasting effect, and reduce the proportion of large blocks; thereby maximizing resource utilization and improving economic benefits.

[0059] This invention determines blasting parameters such as the filling length at both ends of the blast hole, the amount of explosive, and the delay time in VCR mining blasting operations. It also calculates and optimizes the block size for deep-hole blasting in mines to improve ore extraction efficiency. Furthermore, it studies the impact of blasting vibration on the structural stability of underground chambers, investigates the propagation law of blasting vibration, and reduces blasting vibration by optimizing blasting parameters to ensure the safety and stability of mine structures. Attached Figure Description

[0060] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure;

[0061] Figure 1 This is a flowchart of a method for optimizing the block size of deep-hole blasting in mines based on VCR mining, provided in an embodiment of the present invention.

[0062] Figure 2 This is a schematic diagram of a deep-hole blasting block size optimization system based on VCR mining method provided in an embodiment of the present invention. Detailed Implementation

[0063] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0064] Example 1, as Figure 1 As shown in the embodiments of the present invention, the method for optimizing the block size of deep-hole blasting in mines based on VCR mining method includes:

[0065] S1, determine the blasting parameters such as the filling length at both ends of the blast hole, the amount of explosive, and the delay time in the VCR mining blasting construction, and calculate the block size of deep hole blasting in the mine;

[0066] S2. Based on the calculation results, the blasting parameters in the blasting vibration of the underground chamber structure are optimized.

[0067] S3, based on the optimization results of blasting parameters, conducts simulation tests on the safety and stability of mine structures.

[0068] For example, in step S1,

[0069] (1) Optimization of borehole filling length;

[0070] Traditional method: Determine the optimal burial depth based on experience. 1.1-1.8 times ( (Determined through small-scale blasting funnel tests), the orifice plugging length is usually fixed at 1.6–1.8 m.

[0071] The improved formula of this invention is as follows: the length of the hole bottom blockage is:

[0072] In the formula, The length of the plug at the bottom of the hole. The blasting height is typically 3-4 meters.

[0073] The orifice plugging structure combines granular packing and a water column energy absorption buffer mechanism: the granular layer thickness is ≥ twice the diameter of the drug pack (particle size 0.2–2 mm); the water column height is ≥ 15% of the orifice depth;

[0074] It can be seen that the technical functions of the distinguishing features of the present invention include: introducing a water column energy absorption buffer mechanism to replace pure particle filling and reduce the blockage caused by the upward transmission of explosion energy.

[0075] For example, the core steps that distinguish the water column energy absorption and buffering mechanism from existing technologies are:

[0076] (1) Dynamic fluid phase change control; innovative steps: By injecting controllable microbubbles or phase change materials into the water column, the fluid undergoes a gas-liquid phase change or density jump at the moment of impact, forming a multi-level energy dissipation layer. Traditional buffer devices rely on the elastic deformation of solid materials or the damping of throttling orifices, while the water column mechanism utilizes the change in fluid state to absorb energy and reduce mechanical fatigue. It can significantly improve the energy absorption efficiency under high impact loads (up to more than 3 times that of traditional hydraulic buffers) while avoiding plastic deformation of metal components.

[0077] (2) Active modulation of the vortex flow field: A spiral guiding structure is designed within the buffer cavity to force the water flow to form directional vortices. Unlike traditional straight flow channels, vortex flow extends the fluid path and increases turbulent kinetic energy dissipation. The vortex damping force model and the impact force calculation formula are derived from linear damping: Upgrade to a nonlinear model: ;in, The vortex angular velocity enables a smooth response to transient impacts; For water flow velocity, The linear damping coefficient is... Indicates impact force. This refers to the vortex angular velocity coefficient.

[0078] (3) Through feedback closed-loop control, the buffer force is always maintained within the critical threshold to prevent overload failure. The core calculation formula of the water column energy absorption buffer mechanism is different from that of existing technologies;

[0079] In step (1), the multi-level energy dissipation layer can accurately quantify the proportion of phase change energy absorption, guiding the optimization of microbubble concentration (e.g., energy absorption increases by 40% when the concentration is ≥15%), as expressed in the following expression:

[0080]

[0081] In the formula, For multiphase flow energy dissipation, Specific heat capacity of the fluid This is due to temperature rise (latent heat conversion during phase change). These are the densities of the liquid phase and the gas phase, respectively. For microbubble volume, The adiabatic index, For pressure integral, Integrating over time; quantifying the energy absorption of phase transitions and thermodynamic effects, more accurately predicting buffer performance under high strain rates and oscillation instability under variable loads than traditional pure mechanical energy;

[0082] In step (2), the vortex damping force model can suppress the peak impact force by 20%-50% and reduce the risk of structural stress concentration. This includes the following nonlinear model:

[0083]

[0084] In the formula, For impact force, For water flow velocity, The linear damping coefficient is... This is the vortex angular velocity coefficient. ω is the vortex angular velocity.

[0085] The water column energy absorption and buffering mechanism achieves efficient and adaptive dissipation of impact energy through three innovative steps: phase change control, vortex modulation, and intelligent feedback, combined with core calculation theories such as multiphase flow energy formulas and vortex damping models. Its technological effects focus on: improving energy absorption efficiency by overcoming the limitations of traditional materials through fluid state transitions; suppressing peak loads by optimizing force transmission paths using nonlinear damping models; and enhancing system robustness by dynamically adjusting to avoid overshoot failure.

[0086] Optimization of dosage calculation; Traditional method: dosage per well The improved dynamic unit consumption of this invention is adjusted as follows:

[0087]

[0088] In the formula, For dynamic unit consumption, The blastability coefficient of the ore and rock is taken as 1.2–1.5 for hard rock; This is the unit consumption coefficient. Rock mass quality indicators;

[0089] Air-spaced charge loading is optimized as follows: charge package length The air section occupies 20–30% of the borehole depth. This invention dynamically adjusts the unit consumption based on the coupled ore and rock characteristics, and the air interval reduces blasting vibration.

[0090] Improved delay time; Traditional method: detonation in segments at fixed millisecond intervals (e.g., 25–50 ms). The improved formula of this invention is:

[0091]

[0092] In the formula, For the extended time, The rock mass impedance coefficient is... For rock vibration dosage, For rock wave impedance, The elastic modulus is used; this invention optimizes the delay based on the principle of stress wave superposition, reducing vibration superposition.

[0093] Traditional methods for calculating blasted block size rely on the KUZ-RAM empirical model and do not consider rock mass structure. In this invention, the calculation of blasted block size includes the calculation of the fractal dimension of the blasted block size:

[0094]

[0095] In the formula, is the block size fractal dimension; the larger the value, the more uniform the block size.

[0096] Step S2, based on the calculation results, optimizes the blasting parameters in the blasting vibration of the underground chamber structure, including: real-time correction of the block size distribution by analyzing the block size image after blasting, combined with fractal theory and intelligent algorithms; and introducing fractal theory and intelligent algorithms to improve prediction accuracy.

[0097] Exemplary innovative steps and calculation formulas in fractal theory;

[0098] The steps are different from those of existing technologies;

[0099] (1) Self-similarity matching; This invention segments the image into domain blocks and range blocks; the self-similarity between blocks is found through affine transformations (scaling, rotation, translation), with the following formula:

[0100]

[0101] In the formula, This represents the inter-block self-similarity value. For image blocks, For affine matrices, It is a translation vector;

[0102] (2) Iterated Function System (IFS) encoding: Encoding is performed using the local self-similarity within the image. For example, the branches of a tree can be seen as a scaled-down version of the trunk, and the entire structure is generated by repeatedly applying the same transformation rules; this invention only stores the affine transformation parameter set, and reconstructs the image through iterative decoding, which greatly reduces the storage requirements.

[0103] (3) The texture complexity of the block-scale image is quantified using fractal dimension, expressed as:

[0104]

[0105] In the formula, This represents the block-level image texture complexity value. Number of block-sized images The block size radius;

[0106] Quantization block-level image texture complexity ( (The larger the value, the coarser the texture); it is applied to scale conversion of remote sensing images to solve the information loss problem of traditional interpolation methods.

[0107] (4) The Hurst index (for blasting block size time series analysis) is used for blasting block size time series analysis to identify long memory effects. The expression is:

[0108]

[0109] In the formula, This is the Hurst exponent value.

[0110] In step S2, based on the optimization results of the blasting parameters, a simulation test is conducted on the safety and stability of the mine structures, including:

[0111] Swarm intelligence explores the solution space through a particle position update formula; the expression is:

[0112]

[0113] In the formula For the first Particles in The solution for the time position, For update rate, For the first Particles in The solution for the time position, Divided into the update rates of the first and second particles, Divided into the update distances of the 1st and 2nd particles, For the first The position where a particle achieves its highest fitness. For the first Particles in Location at any given moment This is the position where the entire system achieves the highest fitness.

[0114] The block size is dynamically adjusted based on the reward function as follows:

[0115]

[0116] In the formula, The block-scale fractal dimension function, This is the initial block size adjustment factor. For dynamic adjustment rate, The block size radius, To adjust the coefficient, This is the dynamic block size adjustment factor.

[0117] Reinforcement learning dynamically adjusts block size based on a reward function.

[0118] It is known that fractal compression only requires storing transformation parameters, reducing storage space by 30% compared to JPEG; intelligent algorithms reduce image processing latency from 80ms to 50ms. Fractal theory solves the problem of nonlinear spatial data in Geographic Information Systems (GIS); by quantifying complexity through fractal dimension, the compression ratio is improved by 10 times; intelligent algorithms maintain high generalization ability even in the absence of global information, and dynamic optimization achieves adaptive decision-making, improving response speed by 50%. Fractal dimension reveals the long-range correlation of geological systems; reinforcement learning optimizes multi-agent resource scheduling to cope with dynamic environments.

[0119] Safety improvements of this invention: Water column tamping reduces the risk of borehole puncture, decreasing the borehole blockage rate by over 60%; optimized delay time reduces blasting vibration velocity by 30-40%. Efficiency and cost optimization: Air-gap charging reduces explosive consumption by 15-20%; the no-sweep design saves 50% of repeated drilling time. Improved blasting quality: Improved block size uniformity (large block rate reduced from >8% to <3%; well height achieved in a single cut blast increased from 3m to 5m). Intelligent application: Combining block size fractal model with image recognition enables real-time feedback of blasting effects and adaptive parameter adjustment. This invention originates from the refined control of ore and rock characteristics and energy transfer mechanisms, driving the VCR method towards intelligence and low-disturbance development. Practical applications require parameter adjustment through field tests, such as calibration via small blasting funnel tests. and value.

[0120] Example 2, as Figure 2 As shown in the embodiment of the present invention, the deep-hole blasting block size optimization system based on VCR mining method in mines includes:

[0121] The blasting block size calculation module is used to determine the blasting parameters such as the filling length at both ends of the blast hole, the amount of explosive, and the delay time in VCR mining blasting construction, and to calculate the blasting block size of deep holes in mines.

[0122] The blasting parameter optimization module is used to optimize the blasting parameters in the blasting vibration of underground chamber structures based on the calculation results.

[0123] The test verification module is used to conduct simulation tests on the safety and stability of mine structures based on the optimization results of blasting parameters.

[0124] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention and within the spirit and principles of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for optimizing the block size of deep-hole blasting in mines based on VCR mining, characterized in that, The method includes the following steps: S1, determine the blasting parameters such as the filling length at both ends of the blast hole, the amount of explosive, and the delay time in the VCR mining blasting construction, and calculate the block size of deep hole blasting in the mine; S2. Based on the calculation results, the blasting parameters in the blasting vibration of the underground chamber structure are optimized. S3, based on the optimization results of blasting parameters, conducts simulation tests on the safety and stability of mine structures.

2. The method for optimizing the block size of deep-hole blasting in mines based on VCR mining method according to claim 1, characterized in that, In step S1, the filling length of the borehole includes: The length of the plug at the bottom of the hole is: In the formula, The length of the plug at the bottom of the hole. The height of the layered blasting; The orifice plugging structure combines granular packing material and a water column energy absorption buffer mechanism, with the granular layer thickness ≥ twice the diameter of the drug pack and the water column height ≥ 15% of the orifice depth.

3. The method for optimizing the block size of deep-hole blasting in mines based on VCR mining method according to claim 2, characterized in that, The energy absorption and buffering mechanism of a water column includes: (1) Dynamic fluid phase change control: controllable microbubbles or phase change materials are injected into the water column to cause the fluid to undergo gas-liquid phase change or density jump at the moment of impact, forming a multi-level energy dissipation layer. (2) Active modulation of vortex flow field; a spiral flow guiding structure using the vortex damping force model is designed in the buffer cavity to force the water flow to form a directional vortex; (3) By using feedback closed-loop control, the buffer force is always kept within the critical threshold.

4. The method for optimizing the block size of deep-hole blasting in mines based on VCR mining method according to claim 3, characterized in that, In step (1), the formula for the multi-stage energy dissipation layer is: In the formula, For multiphase flow energy dissipation, Specific heat capacity of the fluid For temperature rise These are the densities of the liquid phase and the gas phase, respectively. For microbubble volume, The adiabatic index, For pressure integral, Integrating at time step; In step (2), the vortex damping force model includes: the nonlinear model is: In the formula, For impact force, For water flow velocity, The linear damping coefficient is... This is the vortex angular velocity coefficient. ω is the vortex angular velocity.

5. The method for optimizing the block size of deep-hole blasting in mines based on VCR mining method according to claim 1, characterized in that, In step S1, the dosage calculation includes: Dynamic unit consumption adjusted to: In the formula, For dynamic unit consumption, The blastability coefficient of the ore and rock is taken as 1.2–1.5 for hard rock; This is the unit consumption coefficient. Rock mass quality indicators; Air-spaced charge loading is optimized as follows: charge package length The air section occupies 20–30% of the hole depth.

6. The method for optimizing the block size of deep-hole blasting in mines based on VCR mining method according to claim 1, characterized in that, In step S1, the delay time is: In the formula, For the extended time, The rock mass impedance coefficient is... For rock vibration dosage, For rock wave impedance, It is the elastic modulus; The calculation of blasting block size includes the calculation of the fractal dimension of blasting block size as follows: In the formula, is the block size fractal dimension; the larger the value, the more uniform the block size.

7. The method for optimizing the block size of deep-hole blasting in mines based on VCR mining method according to claim 1, characterized in that, In step S2, the blasting parameters in the blasting vibration of the underground chamber structure are optimized, including: (1) Self-similarity matching; the image is segmented into domain blocks and range blocks; the self-similarity between blocks is found through affine transformations of scaling, rotation, and translation, expressed as: In the formula, This represents the inter-block self-similarity value. For image blocks, For affine matrices, It is a translation vector; (2) Iterative function system IFS encoding, which uses the local self-similarity within the image for encoding; (3) The block-level image texture complexity is quantified using fractal dimension, and the expression is: In the formula, This represents the block-level image texture complexity value. Number of block-sized images The block size radius; (4) The Hurst exponent is used for time series analysis of blasting block size, and its expression is: In the formula, This is the Hurst exponent value.

8. The method for optimizing the block size of deep-hole blasting in mines based on VCR mining method according to claim 1, characterized in that, In step S2, based on the optimization results of the blasting parameters, a simulation test is conducted on the safety and stability of the mine structures, including: Swarm intelligence explores the solution space through particle position update formulas; Reinforcement learning dynamically adjusts block size based on a reward function.

9. The method for optimizing the block size of deep-hole blasting in mines based on VCR mining method according to claim 8, characterized in that, Swarm intelligence explores the solution space through a particle position update formula, expressed as: In the formula, For the first Particles in The solution for the time position, For update rate, For the first Particles in The solution for the time position, Divided into the update rates of the first and second particles, Divided into the update distances of the 1st and 2nd particles, For the first The position where a particle achieves its highest fitness. For the first Particles in Location at any given moment This is the position where the entire system achieves the highest fitness. The block size is dynamically adjusted based on the reward function as follows: In the formula, The block-scale fractal dimension function, This is the initial block size adjustment factor. For dynamic adjustment rate, Where is the block size radius, To adjust the coefficient, This is the dynamic block size adjustment factor.

10. A system for optimizing the block size of deep-hole blasting in mines based on VCR mining method, characterized in that, The system implements the method for optimizing the block size of deep-hole blasting in mines based on the VCR mining method as described in any one of claims 1-9, and the system includes: The blasting block size calculation module is used to determine the blasting parameters such as the filling length at both ends of the blast hole, the amount of explosive, and the delay time in VCR mining blasting construction, and to calculate the blasting block size of deep holes in mines. The blasting parameter optimization module optimizes the blasting parameters in the blasting vibration of underground chamber structures based on the calculation results. The test verification module conducts simulation tests on the safety and stability of mine structures based on the optimization results of blasting parameters.

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