Flying gangue dynamic damage characteristic inversion method and system based on mechanical behavior calibration
By using dynamic-static rock mechanics testing and numerical simulation inversion analysis, a large-angle mining model was reconstructed, solving the problem of predicting flying rock disasters and realizing reliable simulation of flying rock movement patterns and disaster prevention and control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-25
- Publication Date
- 2026-03-27
AI Technical Summary
In steeply inclined coal seam mines, rockfall disasters are difficult to predict and control, and existing technologies are unable to obtain the intrinsic laws governing their dynamic damage, leading to frequent safety accidents.
By conducting dynamic-static rock mechanical behavior tests, numerical simulation inversion analysis, and flying rock motion experiments, a steeply inclined mining area model was reconstructed to obtain the micromechanical parameters and global control parameters of flying rock motion. The flying rock motion process was then simulated and calibrated to reveal its spatiotemporal evolution law.
It has enabled reliable simulation and prediction of the flying coal movement process, provided data support for the prevention and control of flying coal disasters, and reduced the probability of accidents.
Smart Images
Figure CN121744574A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of coal mining technology, and in particular to a method and system for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration. Background Technology
[0002] Slinging coal hazards are dynamic phenomena in longwall mining of steeply inclined coal seams, caused by coal falling, coal wall spalling, roof collapse, or floor slippage, resulting in the rolling and splashing of coal and rock fragments within the mining space, which can cause injury or damage to workers and equipment. These coal and rock fragments roll down the working face, typically ranging in size from 0.1 to 0.5 m, in mass from 1 to 103 kg, and with energy reaching up to 100 kJ. The migration trajectory of slinging coal is highly random, and its energy undergoes non-steady-state abrupt changes, making its dynamic damage difficult to predict and effectively control. Slinging coal hazards account for more than 80% of mining accidents in steeply inclined coal seams, causing significant economic losses and casualties for enterprises for a long time, and are one of the important problems that must be solved in such mining areas.
[0003] The problem of flying rock hazards restricts the mining practice of steeply inclined coal seams, yet related basic theoretical research started relatively late. On the one hand, the unfavorable mining environment—darkness, dampness, coal dust, and confined spaces—makes it difficult to conduct on-site monitoring with high-definition cameras and other precision instruments, hindering the acquisition of the intrinsic laws governing flying rock dynamic damage. On the other hand, research methods are also problematic. The randomness of flying rock trajectories is enhanced by multiple uncertainties such as coal and rock characteristics and mining boundaries. Finding the controlling factors among these complex uncertainties and obtaining the intrinsic laws governing flying rock dynamic damage on an experimental platform that reflects the actual mining motion characteristics has remained unsolved. Research on the characteristics of flying rock impact damage is increasingly failing to meet the practical needs of safety and production improvement in steeply inclined coal seams. Summary of the Invention
[0004] To address the problems existing in the prior art, this invention provides a method and system for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration. This method overcomes the difficulty in measuring the intrinsic laws of the spatiotemporal evolution of flying coal, and provides a reliable approach to revealing the intrinsic laws of the spatiotemporal evolution of flying coal.
[0005] To achieve the above objectives, this invention provides a method for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration, comprising: The experimental design parameters and test results for dynamic-static rock mechanical behavior testing were obtained; the dynamic-static rock mechanical behavior testing was carried out using coal and rock samples from steeply inclined mining areas. A stope model was constructed based on the experimental design parameters, and a simulation experiment of the dynamic-static rock mechanical behavior test was conducted using the stope model to obtain simulation results. Based on the test results and simulation results, the micromechanical parameters of the digital core in the stope model are determined by numerical simulation inversion analysis, and the initial stope model is obtained. Based on the flying coal test data, the flying coal motion effect in the initial stope model was calibrated using numerical simulation inversion analysis to obtain the calibrated stope model; the flying coal test data was obtained by conducting flying coal motion test experiments; the flying coal test data includes: natural angle of repose, fall velocity recovery coefficient, and collision velocity recovery coefficient; A simulated rockfall motion experiment was conducted using a calibrated stope model to obtain statistical characteristics of the trajectory and energy of the rockfall motion process. These statistical characteristics were then compared and verified with the measured characteristics of rockfall disasters in steeply inclined stopes in order to optimize the global control parameters of the stope model. An optimized mining site model was used to simulate the spatiotemporal evolution of flying coal movement and determine the dynamic damage characteristics of flying coal. The dynamic damage characteristics of flying coal include the spatial distribution law of the trajectory of flying coal and the law of energy evolution.
[0006] Optionally, the coal and rock samples include: the roof and floor of the steeply inclined mining face, as well as coal and rock blocks in the coal and rock strata.
[0007] Optionally, the dynamic-static rock mechanics behavior test includes quasi-static rock mechanics experiments and dynamic rock mechanics experiments; the quasi-static rock mechanics experiments include uniaxial compression, shear, and indirect tension experiments; the dynamic rock mechanics experiments include the split Hopkinson bar test.
[0008] Optionally, based on the test results and simulation results, the micromechanical parameters of the digital core in the stope model are determined using numerical simulation inversion analysis, including: The micromechanical parameters of the digital core in the mining model are cyclically adjusted until the error between the simulation results and the corresponding experimental results is less than the preset value; the simulation results include the stress-strain curve and macroscopic failure mode of the digital core; the experimental results include the stress-strain curve and macroscopic failure mode of the coal and rock samples.
[0009] Optionally, the flying debris motion test experiment includes a collapse test, a drop test, and a collision test; by conducting the flying debris motion test experiment, flying debris test data is obtained, including: By conducting collapse experiments, the natural angle of repose of the fractured coal and rock blocks after natural collapse was obtained; By conducting drop tests, the fall velocity recovery coefficient of the spherical coal rock related to the fall height was obtained, as well as the collision velocity recovery coefficient after the spherical coal rock collided with the coal wall or fully mechanized mining equipment. By conducting collision experiments, the collision velocity recovery coefficient after a spherical coal rock collides with the coal wall or fully mechanized mining equipment is obtained.
[0010] Optionally, the flying rock motion effect includes flying rock sliding effect, flying rock rebound effect, and flying rock offset effect; based on the flying rock test data, the flying rock motion effect of the digital core is calibrated and designed using numerical simulation inversion analysis, including: Numerical experiments on slab collapse, corresponding to the collapse experiments, were conducted using the initial mining model to obtain the simulated natural angle of repose. Based on the natural angle of repose and the simulated natural angle of repose, the internal friction angle of the contact surface of the digital core in the mining model is determined by numerical simulation inversion analysis in order to complete the calibration design of the flying rock sliding effect. A numerical drop experiment corresponding to the drop experiment was conducted using the initial mining field model to obtain the simulated drop velocity recovery coefficient. Based on the aforementioned fall velocity recovery coefficient and the simulated fall velocity recovery coefficient, the damping coefficient of the mining area model is determined by numerical simulation inversion analysis, and a functional relationship between the aforementioned fall velocity recovery coefficient and the simulated fall velocity recovery coefficient is established to complete the calibration design of the flying coal rebound effect. A numerical collision experiment corresponding to the collision experiment was conducted using the initial mining field model to obtain the simulated collision velocity recovery coefficient. Establish a functional relationship between the collision velocity recovery coefficient and the simulated collision velocity recovery coefficient to complete the design of the flying debris offset effect calibration.
[0011] Optionally, by conducting collapse experiments, the natural angle of repose of the fractured coal and rock blocks after natural collapse can be obtained, including: The broken coal and rock blocks in the steeply inclined mining area are collected and loaded into a cylinder. The cylinder is moved upward at a preset speed to allow the broken coal and rock blocks to collapse naturally. The natural angle of repose is then measured.
[0012] Optionally, drop tests can be conducted to obtain the velocity recovery coefficient of the spherical coal / rock as a function of its drop height, including: Obtain floor rock blocks with a volume within a preset range from the steeply inclined stope to serve as the impact bed surface; A high-speed camera was used to record the impact and rebound process of spherical coal and rock falling at different heights into the impact bed surface, and to obtain falling image data. Based on the falling image data, the falling velocity recovery coefficient of the spherical coal rock is obtained in relation to the falling height.
[0013] Optionally, collision velocity recovery coefficients can be obtained by conducting collision experiments after the spherical coal rock collides with the coal wall or fully mechanized mining equipment, including: Obtain coal face rock blocks from the steeply inclined mining area, and steel plates with the same material properties as the fully mechanized mining equipment in the steeply inclined mining area; A high-speed camera was used to record the process of the spherical coal rock falling at different heights and colliding with the coal wall rock blocks or steel plates to obtain collision image data. Based on the collision image data, the collision velocity recovery coefficient of the spherical coal and rock is obtained.
[0014] This invention also provides a system for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration, comprising: The data acquisition module is used to acquire the experimental design parameters and test results of the dynamic-static rock mechanical behavior test; the dynamic-static rock mechanical behavior test is carried out using coal and rock samples from steeply inclined mining areas; The model building module is used to build a stope model according to the experimental design parameters, and to conduct a simulation experiment of the dynamic-static rock mechanical behavior test using the stope model to obtain simulation results; The inversion analysis module is used to determine the micromechanical parameters of the digital core in the stope model based on the test results and simulation results, and to obtain the initial stope model. The calibration design module is used to calibrate the motion effect of flying coal in the initial stope model based on flying coal test data and using numerical simulation inversion analysis to obtain a calibrated stope model. The flying coal test data is obtained by conducting flying coal motion test experiments. The flying coal test data includes: natural angle of repose, fall velocity recovery coefficient, and collision velocity recovery coefficient. The parameter optimization module is used to conduct a simulated experiment of flying rock movement using the calibrated stope model, obtain statistical characteristics of the trajectory and energy of the flying rock movement process, and compare and verify the statistical characteristics with the measured characteristics of flying rock disasters in steeply inclined stopes, so as to optimize the global control parameters of the stope model. The flying waste rock analysis module is used to simulate the spatiotemporal evolution of flying waste rock movement using an optimized mining model, and to determine the dynamic damage characteristics of flying waste rock; the dynamic damage characteristics of flying waste rock include the spatial distribution law of the trajectory of flying waste rock and the law of energy evolution.
[0015] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects: The present invention provides an inversion method for the dynamic damage characteristics of flying rock based on mechanical behavior calibration. This method reconstructs the space of a steeply inclined stope, conducts dynamic and static rock mechanical behavior tests on separated coal and rock blocks in the stope, and then uses inversion analysis technology to reconstruct the stope model in numerical software. This determines the model parameters (microscopic mechanical parameters and global control parameters) characterizing the dynamic and static mechanical behavior of the flying rock movement process, thus achieving a "cloning" of the actual flying rock movement process in the stope. The constructed numerical simulation model is then used to study the spatiotemporal evolution of flying rock, thereby revealing the intrinsic laws governing its spatiotemporal evolution. This invention overcomes the shortcomings of current research methods, such as small sample sizes, discrete results, low visualization levels, and difficulty in obtaining intrinsic laws. It provides a reliable approach to revealing the intrinsic laws of the spatiotemporal evolution of flying rock and provides strong data support for the formulation of subsequent flying rock disaster prevention and control strategies and the development of flying rock control equipment. Attached Figure Description
[0016] The above and other objects, features and advantages of the present invention will become more apparent from the more detailed description of exemplary embodiments of the invention in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same parts.
[0017] Figure 1 This is a flowchart illustrating the method for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration, as shown in an embodiment of the present invention. Figure 2 This is a flowchart illustrating the process of calibrating and determining the micromechanical parameters of the model mining field in an embodiment of the present invention. Figure 3 This is a schematic diagram illustrating the analytical approach for the motion process of flying debris based on dynamic-static behavior calibration, as shown in an embodiment of the present invention. Figure 4 This is a schematic diagram of the module structure of the inversion system for dynamic damage characteristics of flying coal based on mechanical behavior calibration, as shown in an embodiment of the present invention. Detailed Implementation
[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0019] To address the challenges of accurately measuring the intrinsic laws governing the spatiotemporal evolution of flying rock in steeply inclined coal seams and obtaining its damage characteristics, this invention provides a method and system for inverting the dynamic damage characteristics of flying rock based on mechanical behavior calibration. This method can reveal the dynamic damage characteristics of flying rock, thereby enabling timely identification and proactive prevention and control before disasters occur.
[0020] Please see Figure 1 , Figure 1 This is a flowchart illustrating the method for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration. The method includes the following steps: Step 101: Obtain the experimental design parameters and test results for dynamic-static rock mechanical behavior testing.
[0021] The dynamic-static rock mechanics behavior test was conducted using coal and rock samples from steeply inclined mining faces. These samples specifically included the roof and floor of the steeply inclined mining face, as well as coal and rock blocks within the coal and rock strata. The dynamic-static rock mechanics behavior test included quasi-static and dynamic rock mechanics experiments; the quasi-static rock mechanics experiments included uniaxial compression, shear, and indirect tensile tests; the dynamic rock mechanics experiments included the Split Hopkinson Pressure Bar (SHPB) test.
[0022] In applications, samples can be taken from steeply inclined mining areas to prepare coal and rock specimens (coal and rock blocks from the roof, floor, and coal and rock strata) required for testing. Dynamic and static rock mechanics experiments are then conducted, and macroscopic failure modes are recorded to obtain test results. The collected coal and rock specimens can be processed, with two types of specimens available: discs (diameter × height = 50 × 25 mm) and cylinders (diameter × height = 50 × 100 mm).
[0023] See Figure 2 When conducting mechanical behavior tests, at least three specimens are selected for each test, and uniaxial compression (standard specimen), shear and indirect tension (disc) tests are conducted to test the static properties of coal and rock. At least five specimens are selected for each test to conduct SHPB (disc) tests to test the dynamic properties of coal and rock.
[0024] Step 102: Construct a stope model based on the experimental design parameters, and use the stope model to conduct a simulation experiment on the dynamic-static rock mechanical behavior test to obtain simulation results.
[0025] In the application, based on the external shape and volume of each coal and rock specimen during mechanical behavior testing, corresponding proportional digital cores are generated in numerical simulation software, and corresponding numerical rock mechanics experiments such as uniaxial compression, shear, indirect tension and SHPB tests are carried out to obtain simulation results.
[0026] Step 103: Based on the test results and simulation results, the micromechanical parameters of the digital core in the stope model are determined by numerical simulation inversion analysis to obtain the initial stope model.
[0027] The simulation results include stress-strain curves and macroscopic failure modes of digital cores; the experimental results include stress-strain curves and macroscopic failure modes of coal and rock samples. In application, the micromechanical parameters of the digital cores in the mining model can be cyclically adjusted until the error between the simulation results and the corresponding experimental results is less than the preset value.
[0028] See Figure 2 The micromechanical parameters of digital cores are cyclically adjusted, and the test results are used as the standard to comprehensively invert and determine the micromechanical parameters suitable for various types (different experiments) of digital cores. When the stress-strain curves and macroscopic failure modes of all digital cores and coal and rock specimens are in good agreement, the micromechanical parameters at this time take into account both the dynamic and static mechanical behavior of the flying rock (coal and rock blocks). Then, the obtained micromechanical parameters can be used in the next step of numerical simulation analysis of the flying rock movement process.
[0029] This invention utilizes inversion analysis technology to reconstruct a mining area model in numerical software. Historical process extrapolation or extended calculations are then performed on the verified model. This overcomes the shortcomings of current research methods, such as small sample sizes, discrete results, low visualization levels, and difficulty in obtaining intrinsic laws. It is particularly suitable for analyzing the flying rock movement process under the influence of multiple uncertain factors. Flying rock disasters are a process from quasi-static initiation to dynamic impact. This invention determines model parameters that adapt to the dynamic-static behavior of the flying rock movement process through comprehensive inversion, achieving a "cloning" of the actual flying rock movement process in the mining area.
[0030] Step 104: Based on the flying coal test data, the flying coal motion effect in the initial stope model is calibrated using numerical simulation inversion analysis to obtain the calibrated stope model.
[0031] The data from the flying debris test was obtained through flying debris motion test experiments; these experiments included collapse, drop, and collision tests; the data included the angle of repose, fall velocity recovery coefficient, and collision velocity recovery coefficient; and the effects of the flying debris motion included sliding, rebound, and offset effects. Figure 3 As shown, by conducting flying rock motion test experiments and numerical simulation experiments in the mining area model, inversion analysis is used to calibrate and design the flying rock motion effect in the mining area model, thereby restoring the real flying rock motion process in the mining area model.
[0032] When designing the calibration of the flying waste rock sliding effect, the following operations can be performed as an example: By conducting collapse experiments, the natural angle of repose of the broken coal and rock blocks after natural collapse was obtained. Specifically, broken coal and rock blocks were collected from steeply inclined mining areas, loaded into a cylinder, and the cylinder was moved upward at a preset speed to allow the broken coal and rock blocks to collapse naturally. The natural angle of repose was then measured. Numerical experiments on slab collapse, corresponding to collapse experiments, were conducted using the initial stope model to obtain the simulated natural angle of repose. Based on the natural angle of repose and the simulated natural angle of repose, the internal friction angle of the contact surface of the digital core in the stope model is determined by numerical simulation inversion analysis, so as to complete the calibration design of the flying rock sliding effect.
[0033] In applications, the internal friction angle φ of the contact surface is a control parameter for block sliding. Numerical experiments on the collapse of loose blocks can be carried out sequentially under conditions of φ being θ, θ-5, θ-10, θ-15, θ-20, and θ-25, and the results can be compared with laboratory test results; where θ represents the angle of repose. The value of φ is cyclically adjusted based on the simulated angle of repose obtained from the numerical experiments until the simulated angle of repose is the same as that obtained from the indoor collapse experiments, thus determining the value of φ; based on this, it can be ensured that the sliding effect of flying rock along the bottom plate in the stope model is the same as that in the actual stope.
[0034] When designing the calibration of the rebound effect of flying debris, the following operations can be performed as an example: By conducting drop experiments, the fall velocity recovery coefficient of spherical coal and rock as a function of fall height was obtained. Numerical drop experiments corresponding to drop experiments were conducted using the initial mining site model to obtain the simulated drop velocity recovery coefficient. Based on the fall velocity recovery coefficient and the simulated fall velocity recovery coefficient, the damping coefficient of the mining area model is determined by numerical simulation inversion analysis, and a functional relationship between the fall velocity recovery coefficient and the simulated fall velocity recovery coefficient is established to complete the calibration design of the flying coal rebound effect.
[0035] In applications, sufficiently large and intact floor rock blocks can be obtained from steeply inclined stopes to serve as the impact surface for the falling debris (ensuring the conservation of momentum before and after the collision). Drop experiments are conducted in the laboratory, using high-speed cameras to record the impact and rebound of the spherical debris at different heights, thereby establishing the relationship between the fall velocity recovery coefficient and the fall height. Specifically, the fall velocity recovery coefficient can be obtained by performing the following operations: Obtain floor rock blocks with a volume within a preset range in a steeply inclined mining area to serve as the impact bed surface; use a high-speed camera to record the process of spherical coal and rock falling at different heights, colliding with the impact bed surface, and rebounding, to obtain falling image data; based on the falling image data, obtain the falling velocity recovery coefficient of the spherical coal and rock related to the falling height.
[0036] Furthermore, numerical drop experiments were conducted using the initial stope model under different drop heights. By increasing the model damping coefficient from 0 to 1.0 (with intervals of 0.1), the simulated drop velocity recovery coefficient was made to approximate the drop velocity recovery coefficient of the indoor drop experiment, thereby establishing the relationship between the drop velocity recovery coefficient and the drop height and damping coefficient. Based on this, the functional relationship of the velocity recovery coefficient between the two types of experiments was determined, so as to achieve the predetermined flying rock rebound effect in the numerical simulation of the stope model.
[0037] Regarding the trajectory deviation during the movement of flying waste rock, the following operations can be performed as an example when designing the calibration of flying waste rock deviation effects: By conducting collision experiments, the collision velocity recovery coefficient after the spherical coal rock collides with the coal wall or fully mechanized mining equipment is obtained. Numerical collision experiments corresponding to the collision experiments were conducted using the initial mining field model to obtain the simulated collision velocity recovery coefficient. Establish a functional relationship between the collision velocity recovery coefficient and the simulated collision velocity recovery coefficient to complete the calibration design of the flying debris offset effect.
[0038] Specifically, to conduct collision experiments and obtain the collision velocity recovery coefficient, the following operations can be performed: Obtain coal face blocks and steel plates with the same material properties as the fully mechanized mining equipment in the steeply inclined mining area; use a high-speed camera to record the process of spherical coal and rock falling at different heights and colliding with coal face blocks or steel plates to obtain collision image data; based on the collision image data, obtain the collision velocity recovery coefficient of the spherical coal and rock.
[0039] Since the coal wall and fully mechanized mining equipment at the boundary of the mining area affect the lateral displacement of the rockfall process, the effect of its displacement is designed. In application, the model boundary is constructed according to the constraint characteristics of the mining area, and the simulated collision velocity recovery coefficient of the collision between the spherical coal and rock and the coal wall or fully mechanized mining equipment is tested by numerical simulation. Then, the functional relationship between the simulated collision velocity recovery coefficient and the collision velocity recovery coefficient in the collision experiment is established.
[0040] Step 105: Conduct a simulated rockfall motion experiment using the calibrated stope model to obtain statistical characteristics of the trajectory and energy of the rockfall motion process. Compare and verify these statistical characteristics with the measured characteristics of rockfall disasters in steeply inclined stopes to optimize the global control parameters of the stope model.
[0041] In application, from the perspective of model stope configuration, global control parameters (damping coefficients) can be adjusted, and statistical characteristics of the trajectory and energy of a sufficient number of flying rock processes can be analyzed. These characteristics can be compared and verified with the measured characteristics of flying rock disasters in steeply inclined stopes based on specific mining technology conditions, thereby completing the "cloning" of the random motion characteristics of flying rock in real stopes.
[0042] Step 106: Use the optimized mining site model to conduct a simulation experiment on the spatiotemporal evolution of flying coal movement and determine the dynamic damage characteristics of flying coal.
[0043] The dynamic damage characteristics of flying rock include the spatial distribution pattern of flying rock trajectories and the energy evolution pattern. Simulation experiments on the movement process of flying rock swarms are conducted on a systematically calibrated stope model, integrating source characteristics and micromechanical parameters. Specifically, the spatiotemporal evolution of a single flying rock block, a certain period, and a certain number / swarm of flying rock (coal and rock blocks follow different spatial distribution characteristics) can be studied.
[0044] This invention innovates the research method for the dynamic damage of flying rock in steeply inclined longwall mining areas. By reconstructing the space of steeply inclined mining areas, establishing a mining area model, and comprehensively inverting the model parameters that characterize the dynamic-static behavior of flying rock movement, the spatiotemporal evolution process of flying rock in real mining areas can be reproduced. This invention overcomes the shortcomings of current research methods, such as small sample size, discrete results, low visualization level, and difficulty in obtaining intrinsic laws, and provides a reliable way to reveal the intrinsic laws of the spatiotemporal evolution of flying rock.
[0045] Furthermore, based on the spatial distribution pattern of flying coal trajectories, the disaster-causing range and frequency can be quantitatively delineated, the high-frequency movement paths and concentrated areas of flying coal in the mining area can be identified, and the characteristics of energy accumulation, dissipation and abnormal release during the movement of flying coal can be revealed. This will allow for a comprehensive understanding of the evolution of flying coal movement trajectories and energy, laying a data foundation for subsequent early warning and prevention of flying coal disasters.
[0046] Corresponding to the aforementioned application function implementation method embodiments, the present invention also provides a flying coal dynamic damage characteristic inversion system based on mechanical behavior calibration and corresponding embodiments.
[0047] Please see Figure 4 , Figure 4 This is a schematic diagram of the module structure of the above system. The system includes: The data acquisition module 41 is used to acquire the experimental design parameters and test results of the dynamic-static rock mechanical behavior test; the dynamic-static rock mechanical behavior test is carried out using coal and rock samples from steeply inclined mining areas; The model building module 42 is used to build a stope model according to the experimental design parameters, and to use the stope model to conduct a simulation experiment of the dynamic-static rock mechanical behavior test to obtain simulation results; The inversion analysis module 43 is used to determine the micromechanical parameters of the digital core in the stope model based on the test results and simulation results, and to obtain the initial stope model. The calibration design module 44 is used to calibrate the motion effect of flying coal in the initial mining model based on the flying coal test data and using numerical simulation inversion analysis to obtain the calibrated mining model; the flying coal test data is obtained by conducting flying coal motion test experiments; the flying coal test data includes: natural angle of repose, fall velocity recovery coefficient and collision velocity recovery coefficient; The parameter optimization module 45 is used to conduct a simulated experiment of flying rock movement using the calibrated stope model, obtain statistical characteristics of the trajectory and energy of the flying rock movement process, and compare and verify the statistical characteristics with the measured characteristics of flying rock disasters in steeply inclined stopes, so as to optimize the global control parameters of the stope model. The flying waste rock analysis module 46 is used to simulate the spatiotemporal evolution of flying waste rock movement using an optimized mining model, and to determine the dynamic damage characteristics of flying waste rock; the dynamic damage characteristics of flying waste rock include the spatial distribution law of the trajectory of flying waste rock and the law of energy evolution.
[0048] Regarding the system in the above embodiments, the specific ways in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated further here.
[0049] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.
Claims
1. A method for inverting the dynamic damage characteristics of flying coal based on dynamic-static behavior calibration, characterized in that, include: To obtain experimental design parameters and test results for dynamic-static rock mechanical behavior testing; The dynamic-static rock mechanical behavior test was conducted using coal and rock samples from steeply inclined mining areas; A stope model was constructed based on the experimental design parameters, and a simulation experiment of the dynamic-static rock mechanical behavior test was conducted using the stope model to obtain simulation results. Based on the test results and simulation results, the micromechanical parameters of the digital core in the stope model are determined by numerical simulation inversion analysis, and the initial stope model is obtained. Based on the flying coal test data, the flying coal motion effect in the initial stope model was calibrated using numerical simulation inversion analysis to obtain the calibrated stope model. The flying coal test data was obtained by conducting flying coal motion test experiments; The test data for the flying debris includes: angle of repose, fall velocity recovery coefficient, and collision velocity recovery coefficient; A simulated rockfall motion experiment was conducted using a calibrated stope model to obtain statistical characteristics of the trajectory and energy of the rockfall motion process. These statistical characteristics were then compared and verified with the measured characteristics of rockfall disasters in steeply inclined stopes in order to optimize the global control parameters of the stope model. An optimized mining site model was used to simulate the spatiotemporal evolution of flying coal movement and determine the dynamic damage characteristics of flying coal. The dynamic damage characteristics of flying coal include the spatial distribution law of the trajectory of flying coal and the law of energy evolution.
2. The method for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration according to claim 1, characterized in that, The coal and rock samples include: the roof and floor of the steeply inclined mining face, as well as coal and rock blocks in the coal and rock strata.
3. The method for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration according to claim 1, characterized in that, The dynamic-static rock mechanics behavior test includes quasi-static rock mechanics experiments and dynamic rock mechanics experiments; the quasi-static rock mechanics experiments include uniaxial compression, shear and indirect tension experiments; the dynamic rock mechanics experiments include the split Hopkinson bar experiment.
4. The method for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration according to claim 1, characterized in that, Based on the test and simulation results, the micromechanical parameters of the digital core in the mining model were determined using numerical simulation inversion analysis, including: The micromechanical parameters of the digital core in the mining model are cyclically adjusted until the error between the simulation results and the corresponding experimental results is less than the preset value; the simulation results include the stress-strain curve and macroscopic failure mode of the digital core; the experimental results include the stress-strain curve and macroscopic failure mode of the coal and rock samples.
5. The method for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration according to claim 1, characterized in that, The flying debris motion test includes a collapse test, a drop test, and a collision test; by conducting the flying debris motion test, flying debris test data is obtained, including: By conducting collapse experiments, the natural angle of repose of the fractured coal and rock blocks after natural collapse was obtained; By conducting drop tests, the fall velocity recovery coefficient of the spherical coal rock related to the fall height was obtained, as well as the collision velocity recovery coefficient after the spherical coal rock collided with the coal wall or fully mechanized mining equipment. By conducting collision experiments, the collision velocity recovery coefficient after a spherical coal rock collides with the coal wall or fully mechanized mining equipment is obtained.
6. The method for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration according to claim 5, characterized in that, The flying rock movement effects include flying rock sliding effect, flying rock rebound effect, and flying rock offset effect; based on the flying rock test data, a calibration design for the flying rock movement effects of the digital core is performed using numerical simulation inversion analysis, including: Numerical experiments on slab collapse, corresponding to the collapse experiments, were conducted using the initial mining model to obtain the simulated natural angle of repose. Based on the natural angle of repose and the simulated natural angle of repose, the internal friction angle of the contact surface of the digital core in the mining model is determined by numerical simulation inversion analysis in order to complete the calibration design of the flying rock sliding effect. A numerical drop experiment corresponding to the drop experiment was conducted using the initial mining field model to obtain the simulated drop velocity recovery coefficient. Based on the aforementioned fall velocity recovery coefficient and the simulated fall velocity recovery coefficient, the damping coefficient of the mining area model is determined by numerical simulation inversion analysis, and a functional relationship between the aforementioned fall velocity recovery coefficient and the simulated fall velocity recovery coefficient is established to complete the calibration design of the flying coal rebound effect. A numerical collision experiment corresponding to the collision experiment was conducted using the initial mining field model to obtain the simulated collision velocity recovery coefficient. Establish a functional relationship between the collision velocity recovery coefficient and the simulated collision velocity recovery coefficient to complete the design of the flying debris offset effect calibration.
7. The method for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration according to claim 5, characterized in that, By conducting collapse experiments, the natural angle of repose of fractured coal and rock blocks after natural collapse was obtained, including: The broken coal and rock blocks in the steeply inclined mining area are collected and loaded into a cylinder. The cylinder is moved upward at a preset speed to allow the broken coal and rock blocks to collapse naturally. The natural angle of repose is then measured.
8. The method for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration according to claim 5, characterized in that, By conducting drop experiments, the fall velocity recovery coefficient of spherical coal and rock was obtained in relation to the fall height, including: Obtain floor rock blocks with a volume within a preset range from the steeply inclined stope to serve as the impact bed surface; A high-speed camera was used to record the impact and rebound process of spherical coal and rock falling at different heights into the impact bed surface, and to obtain falling image data. Based on the falling image data, the falling velocity recovery coefficient of the spherical coal rock is obtained in relation to the falling height.
9. The method for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration according to claim 5, characterized in that, By conducting collision experiments, the collision velocity recovery coefficient after a spherical coal rock collides with the coal wall or fully mechanized mining equipment is obtained, including: Obtain coal face rock blocks from the steeply inclined mining area, and steel plates with the same material properties as the fully mechanized mining equipment in the steeply inclined mining area; A high-speed camera was used to record the process of the spherical coal rock falling at different heights and colliding with the coal wall rock blocks or steel plates to obtain collision image data. Based on the collision image data, the collision velocity recovery coefficient of the spherical coal and rock is obtained.
10. A system for inverting the dynamic damage characteristics of flying coal based on mechanical behavior calibration, characterized in that, The system, applicable to the method of any one of claims 1-9, comprises: The data acquisition module is used to acquire the experimental design parameters and test results of the dynamic-static rock mechanical behavior test; the dynamic-static rock mechanical behavior test is carried out using coal and rock samples from steeply inclined mining areas; The model building module is used to build a stope model according to the experimental design parameters, and to conduct a simulation experiment of the dynamic-static rock mechanical behavior test using the stope model to obtain simulation results; The inversion analysis module is used to determine the micromechanical parameters of the digital core in the stope model based on the test results and simulation results, and to obtain the initial stope model. The calibration design module is used to calibrate the motion effect of flying coal in the initial stope model based on flying coal test data and using numerical simulation inversion analysis to obtain a calibrated stope model. The flying coal test data is obtained by conducting flying coal motion test experiments. The flying coal test data includes: natural angle of repose, fall velocity recovery coefficient, and collision velocity recovery coefficient. The parameter optimization module is used to conduct a simulated experiment of flying rock movement using the calibrated stope model, obtain statistical characteristics of the trajectory and energy of the flying rock movement process, and compare and verify the statistical characteristics with the measured characteristics of flying rock disasters in steeply inclined stopes, so as to optimize the global control parameters of the stope model. The flying waste rock analysis module is used to simulate the spatiotemporal evolution of flying waste rock movement using an optimized mining model, and to determine the dynamic damage characteristics of flying waste rock; the dynamic damage characteristics of flying waste rock include the spatial distribution law of the trajectory of flying waste rock and the law of energy evolution.