Method and device for testing and inverting rock block fragmentation energy consumption

Abstract

The application discloses a method and device for testing and inverting rock block crushing energy consumption, and the method comprises the following steps: establishing a three-dimensional numerical calculation model for a rock block sample; performing impact crushing experiment on the rock block sample to obtain experimental particle size grading distribution data; inputting the fracture energy parameters corresponding to the particle size of the crushed rock block sample into the three-dimensional numerical calculation model for numerical inversion to obtain numerical particle size grading distribution data; judging whether the numerical particle size grading distribution data and the experimental particle size grading distribution data are within an error interval; if not, dynamically adjusting the fracture energy parameters input into the three-dimensional numerical calculation model for optimization, outputting the optimized numerical particle size grading distribution data, and repeating the judgment operation; and if yes, outputting the corresponding fracture energy parameters. The application further provides a device based on the method, and the fracture energy parameters of the rock block sample are dynamically adjusted and determined by combining experimental data and numerical inversion.

Description

Technical Field

[0001] This invention belongs to the field of testing rock crushing energy consumption, and specifically relates to a method and apparatus for testing and inverting rock crushing energy consumption. Background Technology

[0002] Rock crushing is not only a subject of theoretical research but also an important topic for practical application in production. Among various rock crushing methods, impact crushing is the most important. Moreover, rock impact crushing is a crucial step in metallurgy, mining, coal, water conservancy, construction, building materials, environmental protection, and chemical industries.

[0003] Current research on rock impact fracturing primarily focuses on monitoring the fracture mechanical properties of rocks, typically employing methods such as indoor dynamic and static experiments, seismic tests, X-ray diffraction analysis, and microscopy. However, these methods suffer from high costs, difficulty in describing the fracturing process, and challenges in data acquisition, thus failing to accurately describe the fracture energy of rock samples. Numerical simulation methods, on the other hand, offer advantages such as low cost and clear process and parameter characterization, but their accuracy is significantly affected by parameter selection.

[0004] Existing rock impact crushing test equipment is set up in conjunction with the above-mentioned test methods, such as triaxial testing apparatus, Hopkinson bar, three-dimensional vibration table, etc., which are complex in structure and high in cost. On the other hand, X-ray diffractometers, electron microscopes, etc. require the equipment itself to have high precision. Otherwise, small errors in the equipment control parameters will be amplified, thereby reducing the accuracy of the fracture energy of the test results. Summary of the Invention

[0005] This invention provides a method and apparatus for testing and inverting the energy consumption of rock fragmentation. It combines numerical inversion with experimental data to dynamically adjust and gradually determine the fracture energy parameters of rocks, which can solve the problems of the single method of rock impact crushing test and the difficulty in improving the accuracy of rock fragment fracture energy test in the prior art.

[0006] In a first aspect of the invention, a method for testing the energy consumption of inverted rock fragmentation is provided, the method comprising:

[0007] 1) Select the rock sample to be subjected to the impact crushing test, and establish a three-dimensional numerical calculation model for the rock sample.

[0008] 2) The rock block sample was subjected to an impact crushing test, the crushed rock block sample was collected, the particle size of the crushed rock block sample was counted, and the experimental particle size distribution data was obtained.

[0009] 3) Input the fracture energy parameters corresponding to the particle size of the crushed rock sample into the three-dimensional numerical calculation model for numerical inversion to obtain numerical particle size distribution data;

[0010] 4) Determine whether the numerical particle size distribution data and the experimental particle size distribution data are within the error range;

[0011] 5) If the fracture energy parameter is not within the error range, dynamically adjust the fracture energy parameter, input it into the three-dimensional numerical calculation model for optimization, output the optimized numerical granularity distribution data, and repeat steps 4)-5); if the fracture energy parameter is within the error range, output the corresponding fracture energy parameter.

[0012] Furthermore, the establishment of the three-dimensional numerical calculation model in step 1) includes:

[0013] The rock sample was scanned using three-dimensional scanning technology to establish a three-dimensional geometric model of the rock sample and to perform mesh generation in order to construct the three-dimensional numerical calculation model.

[0014] Furthermore, before performing numerical inversion, the three-dimensional numerical calculation model needs to input the calculation conditions of the rock sample, specifically the material properties, boundary conditions, calculation grid type, numerical simulation method, and mechanical constitutive model.

[0015] Furthermore, the material properties include the physical and mechanical parameters of the numerical model unit of the rock sample and the fracture energy parameters of the contact surface;

[0016] The boundary conditions are the constraints on the rock sample and the applied impact velocity in the impact crushing experiment;

[0017] The numerical simulation methods include the finite element method, finite volume method, finite difference method, block discrete element method, particle discrete element method, meshless method, and continuous and discontinuous element method;

[0018] The mechanical constitutive model includes linear elastic constitutive model and fracture energy constitutive model.

[0019] Furthermore, the content of the dynamically adjusted fracture energy parameter in step 5) is as follows:

[0020] The numerical particle size distribution data is compared with the experimental particle size distribution data to find the differences. Then, the fracture energy parameters of the sizes corresponding to the differences in the numerical particle size distribution data are adjusted to optimize the three-dimensional numerical calculation model.

[0021] Furthermore, the rock sample is a brittle rock material, which is any one of igneous rock, sedimentary rock, and metamorphic rock.

[0022] In a second aspect of the invention, an apparatus is also provided based on a method for testing and inverting the energy consumption of rock fragmentation, the apparatus comprising:

[0023] The sample chamber is used to load rock samples and conduct impact crushing tests.

[0024] A power loading device, connected to the sample chamber, provides the necessary power for launching the rock sample in the impact crushing experiment.

[0025] The crushing monitoring module is connected to the sample chamber and is used to monitor the parameter changes of the rock sample in the impact crushing experiment and to statistically analyze the particle size parameters of the rock sample after crushing.

[0026] The numerical inversion module is connected to the fracture monitoring module. It establishes a three-dimensional numerical calculation model based on the rock sample, performs numerical inversion based on the monitoring data of the fracture monitoring module, dynamically adjusts the fracture energy parameters in the three-dimensional numerical calculation model, and optimizes the three-dimensional numerical calculation model.

[0027] Furthermore, the sample chamber includes a sample fixing unit, a launching sleeve, an impact target plate, and a collection chamber. The rock sample is placed on the sample fixing unit, which is connected to the power loading device. Under the driving action of the power loading device, the rock sample passes through the launching sleeve and impacts the impact target plate located in the collection chamber. The collection chamber is connected to the breakage monitoring module to perform parameter statistics on the particle size of the broken rock sample.

[0028] Furthermore, the breakage monitoring module includes:

[0029] A velocity monitoring unit is used to measure the velocity and vibration data of the rock sample during the impact crushing experiment.

[0030] A stress monitoring unit is used to measure the stress change data of the rock block sample during the impact crushing experiment.

[0031] The crushed particle size statistics unit is used to measure and count the particle size of the crushed rock sample.

[0032] The data acquisition and interaction unit connects to and receives the data collected by the velocity monitoring unit, the stress monitoring unit, and the crushed particle size statistics unit, and outputs experimental particle size distribution data after data processing and analysis.

[0033] Furthermore, the numerical inversion module includes:

[0034] A geometric modeling unit is used to construct the three-dimensional numerical calculation model based on the calculation conditions of the rock sample.

[0035] Mesh partitioning units are used to partition the constructed three-dimensional numerical calculation model into a mesh.

[0036] The core solving unit performs numerical inversion on the three-dimensional numerical calculation model based on the monitoring data of the crushing monitoring module to obtain numerical particle size distribution data;

[0037] The dynamic parameter adjustment unit is connected to the fracture monitoring model. It inputs the monitoring data of the fracture monitoring module into the core solution unit for numerical inversion, and compares the numerical particle size distribution data obtained by the core solution unit with the experimental particle size distribution data to find differences, so as to dynamically adjust the fracture energy parameters in the three-dimensional numerical calculation model.

[0038] Compared with the prior art, the present invention has the following advantages:

[0039] 1. This invention proposes a method for testing and inverting the energy consumption of rock fragments. Using experimental monitoring data as a reference, the method dynamically optimizes the results based on multiple numerical inversions. By combining numerical inversions with experimental data, the fracture energy parameters of the rock fragment samples are determined, thereby improving the accuracy and reliability of the test results.

[0040] 2. This invention also proposes a device for testing and inverting the energy consumption of rock fragmentation. It can not only test and invert the fracture energy parameters of rock samples, but also analyze and compare the fracture energy parameters of different rock samples, providing more accurate data support for the study of rock fracture behavior. Attached Figure Description

[0041] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0042] Figure 1 This is a flowchart of the method for testing the energy consumption of rock crushing in an embodiment of the present invention;

[0043] Figure 2 This is a flowchart of the numerical inversion in an embodiment of the present invention;

[0044] Figure 3 This is a block diagram illustrating the working principle of the device for testing and retrieving rock fragmentation energy consumption in this embodiment of the invention.

[0045] Figure 4 This is a numerical model diagram of the regular spherical iron ore in Embodiment 1 of the present invention;

[0046] Figure 5This is a numerical model diagram of the irregular rock block in Embodiment 2 of the present invention. Detailed Implementation

[0047] 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.

[0048] Fracture energy parameters are important indicators of rock fracturability, but there are currently few methods and devices for testing rock fracture energy in practical engineering applications. The accuracy of fracture energy in impact crushing tests is limited by the accuracy of the testing device, making it difficult to improve and thus impossible to accurately measure the energy lost during rock crushing.

[0049] like Figure 1 As shown, this invention discloses a method for testing the energy consumption of inverted rock fragmentation, the method comprising:

[0050] 1) Select the rock sample to be subjected to the impact crushing test and establish a three-dimensional numerical calculation model for the rock sample.

[0051] In one possible embodiment, the establishment of the three-dimensional numerical computation model includes:

[0052] Select a rock sample of appropriate size, remove dust and loose fragments adsorbed on the surface of the rock sample, scan the rock sample using three-dimensional scanning technology, establish a three-dimensional geometric model of the rock sample, and use numerical software to perform mesh generation to generate a three-dimensional numerical calculation model of the rock sample.

[0053] 2) Conduct impact crushing tests on rock samples, collect the crushed rock samples, and statistically analyze the particle size distribution data of the crushed rock samples.

[0054] In one specific embodiment, the impact fracture test can be performed in the sample chamber, and the process is as follows:

[0055] First, open the sample collection chamber and adjust the positions of the launch sleeve and impact target plate to ensure the center of the impact target plate is horizontal to the centerline of the launch sleeve, preparing for the collection of crushed rock samples. Then, activate the dynamic loading device, set the impact velocity of the rock sample, and adjust the pressure value of the dynamic loading device to correspond to the preset impact velocity, maintaining stable power. Finally, launch the rock sample; the sample, held in place by the sample fixing unit, impacts the impact target plate inside the collection chamber through the launch sleeve. Collect the crushed sample in the collection chamber, analyze the particle size of the crushed rock sample, and obtain its particle size distribution data.

[0056] 3) Input the fracture energy parameters corresponding to the particle size after crushing the rock sample into the three-dimensional numerical calculation model for numerical inversion, such as... Figure 2 As shown, numerical granularity distribution data were obtained.

[0057] Before numerical inversion of the three-dimensional numerical calculation model, it is necessary to input the calculation conditions of the rock sample, specifically the material properties, boundary conditions, calculation grid type, numerical simulation method, and mechanical constitutive model.

[0058] Material properties are the physical and mechanical parameters of the rock block numerical model elements, including material density (kg / m³), elastic modulus (Pa), Poisson's ratio, cohesion (Pa), tensile strength (Pa), internal friction angle (°), and dilatation angle (°). Fracture energy parameters at the contact surface include tensile fracture energy (Pa·m) and shear fracture energy (Pa·m). Boundary conditions are the constraints on the rock block sample and the applied impact velocity during the impact crushing experiment. The computational mesh type of the model can be tetrahedral, triangular prism, pyramid, hexahedral, polyhedral, or spherical meshes. Numerical simulation methods include the finite element method, finite volume method, finite difference method, block discrete element method, particle discrete element method, meshless method, and continuous / discontinuous element method; mechanical constitutive models include linear elastic constitutive models and fracture energy constitutive models.

[0059] Inputting the calculation conditions of the rock sample into the three-dimensional numerical calculation model results in the construction of a complete three-dimensional numerical calculation model based on the working condition data of the rock sample. Combined with the impact crushing test data of the rock sample, subsequent numerical simulations are performed to improve the accuracy of the numerical simulation.

[0060] In this embodiment, the fracture energy parameters corresponding to the particle size of the crushed rock sample can be obtained by referring to the commonly used rock fracture energy parameters under the corresponding size and impact velocity, and then inputting them into the three-dimensional numerical calculation model for numerical inversion to obtain the numerical particle size distribution data under the corresponding working conditions.

[0061] 4) Determine whether the numerical particle size distribution data and the experimental particle size distribution data are within the error range.

[0062] 5) If the fracture energy parameters are not within the error range, dynamically adjust them and input them into the three-dimensional numerical calculation model for optimization. Output the optimized numerical grain size distribution data and repeat steps 4)-5). If the fracture energy parameters are within the error range, output the corresponding fracture energy parameters to realize the test of rock fragmentation energy consumption.

[0063] In this embodiment, the dynamic adjustment of the fracture energy parameters is as follows:

[0064] By comparing the numerical particle size distribution data with the experimental particle size distribution data to find the differences, and then adjusting the fracture energy parameters of the corresponding sizes of the differences in the numerical particle size distribution data, the three-dimensional numerical calculation model can be optimized. The numerical particle size distribution data is then output again, and steps 4)-5) are repeated. By continuously comparing the numerical particle size distribution data with the experimental particle size distribution data and optimizing the three-dimensional numerical calculation model based on the comparison results, more accurate fracture energy parameters can be obtained.

[0065] This invention combines experimental data with numerical simulation inversion. By inverting the fracture energy corresponding to the experimental grain size distribution data of rock samples, the numerical grain size distribution data of the three-dimensional numerical calculation model is obtained. The numerical grain size distribution data is compared with the experimental grain size distribution data, thereby optimizing the fracture energy parameters multiple times. Finally, the fracture energy parameters corresponding to the numerical grain size distribution data that best approximates the experimental grain size distribution data are obtained, thus improving the accuracy of fracture energy parameter testing. Compared with traditional fracture energy testing methods, this invention combines experimental data and numerical simulation, using experimental data to dynamically adjust the fracture energy parameters of rock samples, resulting in higher prediction accuracy.

[0066] Furthermore, the method provided by this invention can simulate the rock crushing process and adjust the impact velocity during the crushing process. Then, it can calibrate the required fracture energy through numerical simulation, providing reasonable suggestions for the impact velocity in engineering practice. By optimizing the crushing process parameters multiple times, the fracture energy parameters under the current state can be obtained, thereby improving the accuracy of testing the fracture energy of rock samples. It can be used to evaluate the fracture energy and dynamic crushing strength required for rock material crushing in fields such as metallurgy, mining, coal, water conservancy, construction, building materials, environmental protection, and chemical industry.

[0067] In another aspect of the present invention, an apparatus for testing and inverting the energy consumption of rock fragmentation based on the above-described method is also provided, such as... Figure 3 As shown, the device includes a sample chamber, a dynamic loading device, a fracture monitoring module, and a numerical inversion module. The sample chamber is used to load rock samples for impact fracture experiments. The dynamic loading device is connected to the sample chamber and provides the necessary power for launching the rock samples in the impact fracture experiment. The fracture monitoring module is connected to the sample chamber and is used to monitor the parameter changes of the rock samples during the impact fracture experiment and to statistically analyze the particle size parameters of the rock samples after fracture. The numerical inversion module is connected to the fracture monitoring module, establishes a three-dimensional numerical calculation model based on the rock samples, and performs numerical inversion based on the monitoring data from the fracture monitoring module. It dynamically adjusts the fracture energy parameters in the three-dimensional numerical calculation model and optimizes the three-dimensional numerical calculation model.

[0068] The present invention provides a device for testing and inverting the energy consumption of rock fragmentation. Impact crushing experiments can be carried out in the sample chamber. The crushing monitoring module can complete the particle size statistics of the rock fragment after crushing. Finally, the numerical inversion module performs inversion based on the experimental data. By dynamically adjusting the fracture energy parameters multiple times, the optimized fracture energy parameters that are closest to the experimental data are obtained, thereby improving the accuracy of the fracture energy parameters.

[0069] Moreover, this device can not only test and invert the fracture energy parameters of rock samples, but also analyze and compare the fracture energy parameters of different rock samples, which can provide more accurate data support for the study of rock fracture behavior.

[0070] In this invention, the sample chamber includes a sample fixing unit, a launching sleeve, an impact target plate, and a collection chamber. The sample chamber is composed of a sealed metal box, the internal size of which can be designed according to actual needs to accommodate the rock sample to be tested. A door that can be opened and closed is provided at the top of the box for inserting or removing the rock sample. The sample fixing unit, launching sleeve, and impact target plate are sequentially installed inside the box.

[0071] The sample fixing unit can fix rock block samples of different types and sizes. It includes a fixed support base plate and a movable plate that is movably coupled to the support base plate. The movable plate is connected to the power loading device through a hydraulic cylinder and guide rail system to realize the impact crushing test of the rock block sample under the action of the power loading device.

[0072] Along the direction of the rock sample's launch motion, the launch sleeve is located in front of the sample fixing unit and above the support base plate. The launch sleeve contains a level and a limiter. The limiter, located at the top of the launch sleeve, restricts the upward movement range of the moving plate of the sample fixing unit. The impact target plate and collection chamber are located in front of the launch sleeve and connected to the breakage monitoring module. The impact target plate is made of a high-hardness alloy, such as steel or aluminum alloy, and its thickness should be greater than 5 cm.

[0073] In the impact crushing experiment, the rock sample is placed on the sample fixing unit, which is connected to the power loading device. Under the driving action of the power loading device, the rock sample passes through the launch sleeve and impacts the impact target plate located in the collection chamber. The collection chamber is connected to the crushing monitoring module to perform parameter statistics on the particle size of the crushed rock sample.

[0074] The dynamic loading device in this invention is a key component of the experimental setup. It provides sufficient power as a power source to enable the rock sample to achieve a certain speed, thereby realizing the impact crushing experiment.

[0075] The power source for the dynamic loading device can be various forms, such as an electric motor, an air compressor, or hydraulic instruments. The selection of the dynamic loading device requires precise control and adjustment based on experimental requirements to ensure the accuracy and stability of the impact speed. In this invention, the power of the dynamic loading device can be precisely adjusted by controlling parameters such as the voltage and current of the motor, or by controlling parameters such as the flow rate or pressure of the pneumatic or hydraulic system.

[0076] The crushing monitoring module is used to monitor the velocity of rock samples in impact crushing experiments and to statistically analyze data such as particle size, deformation, and stress of the crushed rock samples. It includes a velocity monitoring unit, a stress monitoring unit, a crushing particle size statistics unit, and a data acquisition and interaction unit.

[0077] The velocity monitoring unit is used to measure the velocity and vibration data of the rock sample in the impact crushing experiment. It can be implemented by a piezoelectric sensor, photoelectric sensor or other types of sensor, and transmit the collected data to the data acquisition and interaction unit.

[0078] The stress monitoring unit is used to measure the stress change data of the rock sample in the impact crushing experiment. It is mainly based on stress sensors, which can be implemented using technologies such as strain gauges or pressure sensors.

[0079] The crushed particle size statistics unit is used to measure and count the particle size of the crushed rock sample. The particle size of the crushed rock sample can be measured by a laser particle size analyzer, sieve analyzer or other types of particle size measuring instruments, and the collected data is transmitted to the data acquisition and interaction unit.

[0080] The data acquisition and interaction unit connects to and receives data from the velocity monitoring unit, stress monitoring unit, and crushed particle size statistics unit. After data processing and analysis, it obtains experimental particle size distribution data. The data acquisition and interaction unit is mainly based on signal conversion equipment, including components such as analog-to-digital converters and data acquisition cards, which convert the analog signals output by the velocity monitoring unit and stress monitoring unit into digital signals, which are then processed and stored by the computer system.

[0081] The numerical inversion module includes geometric modeling units, mesh generation units, core solution units, and dynamic parameter tuning units. It mainly establishes a numerical calculation model for rock block samples and dynamically adjusts the fracture energy parameters in the numerical calculation model based on the monitoring data from the fracture monitoring module, thereby optimizing the numerical calculation model.

[0082] The geometric modeling unit is used to set parameters based on the calculation conditions of the rock sample and construct a three-dimensional numerical calculation model to simulate the rock fragmentation process, including numerical mesh model construction, numerical simulation methods, mechanical constitutive model and calculation solution.

[0083] The numerical mesh model can employ tetrahedral, triangular prism, pyramidal, hexahedral, polyhedral, and spherical meshes. Numerical simulation methods include the finite element method, finite volume method, finite difference method, block discrete element method, particle discrete element method, meshless method, and continuous / discontinuous element method. Mechanical constitutive models include linear elastic constitutive models and fracture energy constitutive models. The calculation and solution involve assigning material density (kg / m³), elastic modulus (Pa), Poisson's ratio, cohesion (Pa), tensile strength (Pa), internal friction angle (°), dilatation angle (°), tensile fracture energy (Pa·m), and shear fracture energy (Pa·m) to the numerical mesh model, and then applying constraints and impact velocities for simulation calculation.

[0084] Mesh partitioning units are used to partition the constructed three-dimensional numerical computation model into meshes.

[0085] The core solution unit performs numerical inversion on the three-dimensional numerical calculation model based on the monitoring data from the crushing monitoring module, including the velocity, deformation, stress, and rock crushing particle size distribution data of the rock sample, to obtain numerical particle size distribution data.

[0086] The dynamic parameter tuning unit connects the core solver unit and the data acquisition and interaction unit of the fracture monitoring module. It receives monitoring data from the data acquisition and interaction unit and exchanges information with each other. At the same time, it inputs the monitoring data of the fracture monitoring module into the core solver unit for numerical inversion. Based on the numerical particle size distribution data obtained by the core solver unit, it compares the numerical particle size distribution data with the experimental particle size distribution data to find differences and dynamically adjusts the fracture energy parameters in the three-dimensional numerical calculation model to optimize the accuracy and reliability of the model. Finally, it obtains reasonable fracture energy parameters for further research and application.

[0087] Fracture energy parameters are important indicators of rock fracturability, but currently, there are few rock fracture energy testing devices available for practical engineering applications, and they cannot accurately measure the energy lost during rock fracturing. Compared with traditional fracture energy testing devices, the device for testing and inverting rock fragmentation energy consumption provided by this invention can dynamically adjust the fracture energy parameters of rock samples by combining experimental data with numerical simulation inversion, resulting in higher prediction accuracy.

[0088] The method and apparatus provided by this invention, by combining experimental data and numerical simulation inversion methods, repeatedly adjusts and optimizes the fracture energy parameters in the model to gradually approach the actual situation, thereby obtaining more accurate fracture energy parameters.

[0089] It should be noted that the rock mass sample type in this invention is brittle rock material, which can be any of igneous rock, sedimentary rock, and metamorphic rock. That is, the method and apparatus provided by this invention for testing and inverting the energy consumption of rock fragmentation can test the fracture energy parameters of brittle rock materials.

[0090] Example 1: Inversion test of fracture energy consumption of impact crushing of spherical iron ore blocks based on deformable block discrete element method.

[0091] The fracture energy dissipation parameters of a 10mm diameter spherical iron ore block were tested at an impact velocity of 100m / s. First, the grain size distribution data of this block sample at this size was obtained experimentally. Figures 1-2 The process involves determining the required fracture energy parameters for crushing a spherical iron ore block at an impact velocity of 100 m / s.

[0092] First, the grain size distribution data of 10mm diameter spherical iron ore blocks were obtained experimentally. Further, a three-dimensional numerical calculation model was established based on the structure of the spherical blocks, such as... Figure 4 The figure shows a numerical model of a regular spherical iron ore block. The diameter of the 3D numerical model of the spherical iron ore block is 10 mm. The geometric model was created and meshed using the preprocessing module of BlockDyna software, resulting in a total of 79,901 tetrahedral meshes.

[0093] Next, an impact load was applied to the numerical calculation model for numerical simulation inversion. First, based on literature and experimental data, the initial parameters of the rock mass were set as follows: density 3200 kg / m³. 3 The elastic modulus is 60 GPa, Poisson's ratio is 0.25, cohesion is 36 MPa, tensile strength is 12 MPa, internal friction angle is 40°, and shear dilatation angle is 10°. The structural surface parameters are: normal contact stiffness per unit area 3.18 GPa / m, tangential contact stiffness per unit area 4.24 GPa / m, cohesion 36 MPa, internal friction angle 40°, and tensile strength 12 MPa.

[0094] Based on the impact failure characteristics of rock blocks, the tensile fracture energy and shear fracture energy on the structural surface will affect the particle size distribution and gradation curve. With a median particle size D50 of 3.19 mm, the initial tensile fracture energy and shear fracture energy are set at 200 Pa·m.

[0095] An impact velocity of 100 m / s was applied to the rigid surface of a numerical model of a spherical iron ore block, and then numerical simulation was performed using the deformable block discrete element method. The rock mass was modeled using linear elasticity constitutive modeling, and the structural surfaces were modeled using fracture capacity constitutive modeling.

[0096] After the initial numerical simulation was completed, the simulated particle size distribution results were compared with the experimental results. The experimental results showed that the particle size distribution was more fragmented. Therefore, the fracture energy parameter was dynamically reduced, and the numerical simulation was performed again. This process was repeated 10 times within the numerical model. After 10 numerical inversions, the optimized fracture energy parameter was input into the numerical model and compared with the experimental particle size distribution results for verification. The experimental results were largely consistent with the numerical simulation results.

[0097] Therefore, by dynamically adjusting the parameters, a fracture energy parameter that better matches the experimental particle size distribution data was found, and the reference fracture energy parameters of a 10 mm diameter spherical iron ore block at an impact velocity of 100 m / s were obtained, namely, the tensile fracture energy is 100 Pa·m and the shear fracture energy is 500 Pa·m.

[0098] The successful application of this embodiment demonstrates the effectiveness and practicality of the method, and provides a reference for further research in rock fracture mechanics.

[0099] Example 2: Inversion of fracture energy consumption test for impact fracturing of irregular rock blocks based on the continuous-discontinuous unit method.

[0100] The fracture energy dissipation parameters of an irregular rock block with a diameter of 10 mm were tested at an impact velocity of 50 m / s. First, the grain size distribution data of this rock block sample at this size was obtained experimentally. Figures 1-2 The process involves determining the fracture energy parameters required for the crushing of the irregular rock block at an impact velocity of 100 m / s.

[0101] First, the grain size distribution data of an irregular rock block with a diameter of 10 mm was obtained experimentally. Further, a three-dimensional numerical model was established based on the rock block structure, such as... Figure 5 The figure shows a numerical model of an irregular rock block. The diameter of the 3D numerical model of the irregular rock block is approximately 10 mm. The geometric model was created and meshed using the preprocessing module of the Gmsh software, resulting in a total of 24,960 tetrahedral meshes.

[0102] Next, an impact load was applied to the numerical calculation model for numerical simulation inversion. First, based on literature and experimental data, the initial parameters of the rock mass were set as follows: density 3200 kg / m³. 3 The elastic modulus is 60 GPa, Poisson's ratio is 0.25, cohesion is 36 MPa, tensile strength is 12 MPa, internal friction angle is 40°, and shear dilatation angle is 10°. The structural surface parameters are: normal contact stiffness per unit area 6.04 GPa / m, tangential contact stiffness per unit area 8.05 GPa / m, cohesion 36 MPa, internal friction angle 40°, and tensile strength 12 MPa.

[0103] Based on the impact failure characteristics of rock blocks, the tensile fracture energy and shear fracture energy on the structural surface will affect the particle size distribution and gradation curve. With a median particle size D50 of 4.50 mm, the initial tensile fracture energy and shear fracture energy are set at 300 Pa·m.

[0104] An impact velocity of 50 m / s was applied to the rigid surface of the numerical model of the irregular rock mass, and then numerical simulation inversion was performed using the continuous-discontinuous element method. The rock mass was modeled using linear elasticity constitutive modeling, and the structural surfaces were modeled using fracture capacity constitutive modeling.

[0105] After the initial numerical simulation was completed, the simulated particle size distribution results were compared with the experimental results. The experimental results showed that the particle size distribution was more fragmented. Therefore, the fracture energy parameter was dynamically reduced, and the numerical simulation was repeated. This process was repeated nine times within the numerical model. After nine numerical inversions, the optimized fracture energy parameter was input into the numerical model and compared with the experimental particle size distribution results for verification. The experimental results were largely consistent with the numerical simulation results.

[0106] Therefore, by dynamically adjusting the parameters, a fracture energy parameter that better matches the experimental particle size distribution data was found, and the reference fracture energy parameter for an irregular rock block with a diameter of about 10 mm at an impact velocity of 50 m / s was obtained, namely, the tensile fracture energy is 150 Pa·m and the shear fracture energy is 150 Pa·m.

[0107] This embodiment employs the continuous-discontinuous element method to test and invert the fracture energy consumption of irregular rock blocks during impact fracturing. Irregular rock blocks are characterized by irregular geometry and complex contact, making it difficult to accurately measure their fracture energy using traditional experimental methods. However, the continuous-discontinuous element method leverages the advantage of its elements and contact surfaces to precisely characterize material properties from both the perspectives of continuum and fracturing, thus providing a more accurate reflection of the deformation and fracturing of irregular rock blocks during impact.

[0108] The method provided by this invention combines the advantages of experimentation and numerical simulation, making full use of experimental data, performing multiple inversions, and repeatedly optimizing the fracture energy parameters of the numerical model. Ultimately, the results show good agreement with the experimental results, thus improving the accuracy of the test results.

[0109] The above embodiments are merely exemplary embodiments of this application and are not intended to limit this application. The scope of protection of this application is defined by the claims. Those skilled in the art can make various modifications or equivalent substitutions to this application within its substance and scope of protection, and such modifications or equivalent substitutions should also be considered to fall within the scope of protection of this application.

Claims

1. A method for testing the energy consumption of inverted rock fragmentation, characterized in that: The method includes: 1) Select the rock sample to be subjected to the impact crushing test, and establish a three-dimensional numerical calculation model for the rock sample; 2) The rock block sample was subjected to an impact crushing test, the crushed rock block sample was collected, the particle size of the crushed rock block sample was counted, and the experimental particle size distribution data was obtained. 3) Input the fracture energy parameters corresponding to the particle size of the crushed rock sample into the three-dimensional numerical calculation model for numerical inversion to obtain numerical particle size distribution data; 4) Determine whether the numerical particle size distribution data and the experimental particle size distribution data are within the error range; 5) If the fracture energy parameter is not within the error range, dynamically adjust the fracture energy parameter, input it into the three-dimensional numerical calculation model for optimization, output the optimized numerical granularity distribution data, and repeat steps 4)-5); if the fracture energy parameter is within the error range, output the corresponding fracture energy parameter. The establishment of the three-dimensional numerical calculation model in step 1) includes: The rock sample was scanned using three-dimensional scanning technology to establish a three-dimensional geometric model of the rock sample, and then meshed to construct the three-dimensional numerical calculation model. The content of dynamically adjusting the fracture energy parameter in step 5) is as follows: The numerical particle size distribution data is compared with the experimental particle size distribution data to find the differences. Then, the fracture energy parameters of the sizes corresponding to the differences in the numerical particle size distribution data are adjusted to optimize the three-dimensional numerical calculation model.

2. The method for testing and inverting rock fragmentation energy consumption according to claim 1, characterized in that: Before performing numerical inversion, the three-dimensional numerical calculation model needs to input the calculation conditions of the rock sample, specifically the material properties, boundary conditions, calculation grid type, numerical simulation method, and mechanical constitutive model.

3. The method for testing and retrieving rock fragmentation energy consumption according to claim 2, characterized in that: The material properties include the physical and mechanical parameters of the numerical model unit of the rock sample and the fracture energy parameters of the contact surface. The boundary conditions are the constraints on the rock sample and the applied impact velocity in the impact crushing experiment; The numerical simulation methods include the finite element method, finite volume method, finite difference method, block discrete element method, particle discrete element method, meshless method, and continuous and discontinuous element method; The mechanical constitutive model includes linear elastic constitutive model and fracture energy constitutive model.

4. The method for testing and retrieving rock fragmentation energy consumption according to claim 1, characterized in that: The rock sample is a brittle rock material, which can be any of the following: igneous rock, sedimentary rock, and metamorphic rock.

5. An apparatus for testing and inverting the energy consumption of rock fragmentation according to any one of claims 1-4, characterized in that: The device includes: The sample chamber is used to load rock samples and conduct impact crushing tests. A power loading device, connected to the sample chamber, provides the necessary power for launching the rock sample in the impact crushing experiment. The crushing monitoring module is connected to the sample chamber and is used to monitor the parameter changes of the rock sample in the impact crushing experiment and to statistically analyze the particle size parameters of the rock sample after crushing. The numerical inversion module is connected to the fracture monitoring module. It establishes a three-dimensional numerical calculation model based on the rock sample and performs numerical inversion based on the monitoring data of the fracture monitoring module. It dynamically adjusts the fracture energy parameters in the three-dimensional numerical calculation model to optimize the three-dimensional numerical calculation model.

6. The apparatus according to claim 5, characterized in that, The sample chamber includes a sample fixing unit, a launching sleeve, an impact target plate, and a collection chamber. The rock sample is placed on the sample fixing unit, which is connected to the power loading device. Under the driving action of the power loading device, the rock sample passes through the launching sleeve and impacts the impact target plate located in the collection chamber. The collection chamber is connected to the breakage monitoring module to perform parameter statistics on the particle size of the broken rock sample.

7. The apparatus according to claim 6, characterized in that, The breakage monitoring module includes: A velocity monitoring unit is used to measure the velocity and vibration data of the rock sample during the impact crushing experiment. A stress monitoring unit is used to measure the stress change data of the rock block sample during the impact crushing experiment. The crushed particle size statistics unit is used to measure and count the particle size of the crushed rock sample. The data acquisition and interaction unit connects to and receives the data collected by the velocity monitoring unit, the stress monitoring unit, and the crushed particle size statistics unit, and outputs experimental particle size distribution data after data processing and analysis.

8. The apparatus according to claim 5, characterized in that, The numerical inversion module includes: A geometric modeling unit is used to construct the three-dimensional numerical calculation model based on the calculation conditions of the rock sample. Mesh partitioning units are used to partition the constructed three-dimensional numerical calculation model into a mesh. The core solving unit performs numerical inversion on the three-dimensional numerical calculation model based on the monitoring data of the crushing monitoring module to obtain numerical particle size distribution data; The dynamic parameter adjustment unit is connected to the fracture monitoring model. It inputs the monitoring data of the fracture monitoring module into the core solution unit for numerical inversion, and compares the numerical particle size distribution data obtained by the core solution unit with the experimental particle size distribution data to find differences, so as to dynamically adjust the fracture energy parameters in the three-dimensional numerical calculation model.

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