A discrete element modeling method for reproducing joint network in rock mass

Abstract

The application provides a rock mass internal joint network reproduction discrete element modeling method, comprising the following steps: measuring field joint information; establishing a discrete element numerical model; arranging a geological profile along the ore body dip direction; cutting a roadway boundary in the numerical model, cutting the measured joint information in the rock mass, and analyzing the correlation between the measured joint length and the triangular block length; selecting the range of the measured joint length and the triangular block length, respectively calculating the simulated joint size and the triangular block size of the hanging wall, the ore body and the footwall, simultaneously calculating the simulated joint spacing and the simulated gap, and embedding the numerical model; and based on the joint geometric parameters, constructing the joint network model of the hanging wall, the ore body and the footwall respectively. The engineering adaptability of the application is enhanced, the deep roadway surrounding rock stability analysis is supported, the model prediction result is close to the field monitoring data, and a reliable basis is provided for support design.

Description

Technical Field

[0001] This invention relates to the field of discrete element numerical modeling technology for rock masses, and particularly to a discrete element modeling method for reproducing the joint network inside a rock mass. Background Technology

[0002] In the field of discrete element numerical modeling of rock masses, existing joint generation methods, such as the through-model cutting method, the layered embedded method, and the discrete fracture network (DFN) random generation method, all have certain limitations. The through-model cutting method forces joints to intersect the boundary by cutting them through the model boundary, resulting in simulated joints much larger than actual joints (e.g., short joints in roadway surrounding rock are magnified into long, continuous fractures). This leads to a systematic underestimation of rock mass strength and a significant deviation from measured joint parameters, making it only suitable for modeling large-sized joints or layered rock masses. The layered embedded method achieves internal joint cutting through model layering, but requires the introduction of artificial layering structures and the additional generation of layered interface joints, altering the original structural characteristics of the rock mass. Furthermore, it cannot characterize the randomly distributed joint network within non-layered rock masses, limiting its application to the simulation of layered rock masses or coal seam joints. Although the DFN random generation method can freely generate joints inside and outside the model, its joint parameters (such as trace length, density, and attitude) depend on statistical distribution assumptions. The randomness is significantly different from the spatial distribution law, dominant group division and geometric parameters of measured joints. It is only suitable for generalized models with no measured data or scarce data.

[0003] The aforementioned methods all struggle to achieve high-fidelity embedding of field-measured joint information, resulting in models that cannot accurately characterize joint size effects (such as the influence of short joints on local stress concentration), spatial heterogeneity, and their control over the evolution of surrounding rock fracture. For high-stress engineering scenarios such as deep tunnels, existing modeling methods, due to joint parameter distortion, structural interference, or random bias, cannot support quantitative analysis of surrounding rock stability, thus hindering the scientific rigor and safety of support design.

[0004] For example, Chinese invention patent application CN115203900A discloses: establishing a discrete element particle model by statistically obtaining the density and attitude of rock mass joints and fractures; constructing a model containing the density and attitude of rock mass joints and fractures; generating string statements from the model containing the density and attitude of rock mass joints and fractures according to the FISH language format built into PFC2D, and writing the string statements into a specific txt file; completing the establishment of the discrete fracture network; and establishing a discrete element particle model containing joints and fractures. This achieves the import of joint and fracture attitude information generated in MATLAB into PFC2D, reconstructing a random joint and fracture model of the rock mass. However, while it uses MATLAB to generate random numbers and edit probability distribution functions, allowing users to select different probability distribution functions to characterize the center point position, dip angle, and trace length in the joints and fractures, it still lacks a basis in measured data and is difficult to support quantitative analysis of surrounding rock stability. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of the aforementioned background technology by providing a refined method for modeling internal joint networks in rock masses that can integrate measured joint data, avoid interference from artificial structures, and achieve synergistic characterization of joints and rock masses.

[0006] To achieve the above objectives, this invention provides a discrete element modeling method for reproducing joint networks within rock masses, comprising the following steps:

[0007] S1, Conduct on-site joint information measurement, use multiple measurement methods to measure joints in underground roadways, obtain joint measurement data, and summarize the statistical and converted joint information;

[0008] S2, Establish the discrete element numerical model;

[0009] S3, geological profiles are arranged along the dip direction of the ore body to form a study area including the hanging wall profile, the ore body profile, and the footwall profile;

[0010] S4. The tunnel boundary is cut out inside the numerical model. At the same time, triangular blocks are used to cut out the measured joint information inside the rock mass, and the correlation between the measured joint length and the triangular block length is analyzed.

[0011] S5, select the range of measured joint length and triangular block side length, calculate the simulated joint size and triangular block size of the hanging wall, ore body and footwall respectively, and calculate the simulated joint spacing and simulated gap. In the numerical model, set the simulated joint size, triangular block size, simulated joint spacing and simulated gap as joint geometric parameters.

[0012] S6, based on joint geometric parameters, construct joint network models for the hanging wall, ore body, and footwall respectively.

[0013] Furthermore, the measurement methods in S1 include contact measurement methods and non-contact measurement methods;

[0014] The contact measurement method includes the line measurement method and the rectangular window method; the non-contact measurement method includes the three-dimensional laser scanning method.

[0015] Furthermore, the formula for calculating the average trace length using the surveying method is:

[0016]

[0017] in, For the first m The traces of the joints are long. n The total length of the trace intersecting with the measurement line;

[0018] The formula for calculating the linear density using the line surveying method is:

[0019]

[0020] in, To measure the length of the line;

[0021] The formula for calculating the average trace length using the rectangular window method is as follows:

[0022]

[0023] in, For the first i The length of the visible trace at both ends, For the first j The length of the visible trace at one end, For the first k The expected number of traces with invisible ends and penetrating trace lengths is: The expected number of intersecting trace lengths is The expected number of the inclusive trace length is ;

[0024] The formula for calculating the two-dimensional density using the rectangular window method is as follows:

[0025]

[0026] in, and These represent the width and height of the window, respectively.

[0027] The formula for calculating the average trace length using the three-dimensional laser scanning method is:

[0028]

[0029] in, For the first q The traces of the joints are long. M This represents the total trace length obtained through three-dimensional laser scanning.

[0030] The formula for calculating areal density using the three-dimensional laser scanning method is:

[0031]

[0032] in, l Let be the arc length of the tunnel top. z The height of the tunnel sidewall, y This represents the axial scan length of the tunnel.

[0033] Furthermore, in S1, the areal density is uniformly converted into linear density for joint spacing calculation:

[0034]

[0035] in, For the converted linear density, d Joint spacing, joint spacing d This represents the average distance between adjacent joint surfaces in the normal direction.

[0036] Furthermore, a discrete element numerical model is established in S2, including:

[0037] The numerical model is divided into a near-field influence zone containing the roadway and a far-field influence zone not containing the roadway. A smaller triangular block mesh is used in the near-field influence zone compared to the far-field influence zone, and the mesh in the near-field influence zone is also locally refined.

[0038] Furthermore, the measured joint length in S4 L j With the length of the triangle L b The relationship between them is:

[0039] when L j < L b At that time, the number of joints penetrating the boundary of the triangle block were 1, 1, and 2 respectively. During the mesh generation process, the joints that penetrated the boundary of the triangle block with 1 number were automatically merged and removed by the system. For the joints that penetrated the boundary of the triangle block with 2 number, the two ends cut by the boundary of the triangle block were merged and removed, and only the joint length in the middle part was retained. The retained joints were further cut to add 1 triangle block.

[0040] When 2 L b > Lj ≥ L b At that time, the number of joints penetrating the boundary of the triangular block were 2, 3, and 4 respectively. After meshing, the two ends of the joints penetrating the boundary of the triangular block were merged and removed by the boundary of the triangular block, and only the joint length in the middle part was retained. The number of newly added triangular blocks were 1, 2, and 3 respectively.

[0041] When 3 L b > L j ≥2 L b At that time, the number of joints penetrating the boundary of the triangular blocks were 4, 5, and 6 respectively. After meshing, the two ends of the joints penetrating the boundary of the triangular blocks were removed, and only the length of the middle part of the joint was retained. The number of newly added triangular blocks were 3, 4, and 5 respectively.

[0042] When 4 L b ≥ L j ≥3 L b At that time, the number of joints penetrating the boundary of the triangular blocks were 6, 7, and 8 respectively. After meshing, the number of newly added triangular blocks were 5, 6, and 7 respectively.

[0043] Furthermore, in S5, the range of the measured joint length and the triangular block side length is selected to be 3. L b > L j ≥2 L b The side length of the triangular block L b Take the maximum size within this range and embed the joint information obtained from field measurements into the numerical model.

[0044] Furthermore, in S5 L b and L mj The calculation formula is:

[0045]

[0046]

[0047] in, L mj To simulate joint length.

[0048] Furthermore, simulated joint spacing d m The measured average spacing The calculation is based on the formula:

[0049]

[0050] in, n The number of dominant joint groups.

[0051] Furthermore, the joint network model of the hanging wall, ore body, and footwall in S6 considers the construction of each group of dominant joints at different locations.

[0052] The above-described solution of the present invention has the following beneficial effects:

[0053] The discrete element modeling method for reproducing the joint network inside the rock mass provided by this invention firstly acquires and fuses multi-source data, and then collects joint information through the survey line method, rectangular window method and three-dimensional laser scanning method. Combined with the trace length and density calculation formula, it eliminates the data deviation of traditional single measurement methods, reduces the statistical error of joint parameters, and significantly improves the accuracy of the original measured data.

[0054] Secondly, a partitioned modeling strategy was adopted, which improved computational efficiency in the large-scale model based on Voronoi-trigon triangles, while ensuring high-precision capture of stress concentration and fracture evolution in the near-field influence zone of the roadway.

[0055] Furthermore, based on the dynamic correlation modeling of joints and blocks, a quantitative matching rule for joint length and triangular block side length is proposed. Combined with the corresponding formula, the mesh size is dynamically adjusted, which solves the problem of strength misjudgment caused by joint size distortion in traditional models and ensures that the simulated joint length is highly consistent with the measured value.

[0056] Finally, the discrete element modeling method for reproducing the internal joint network of rock mass provided by this invention has enhanced engineering adaptability. Based on measured dip angle, spacing parameters, and other parameters, it constructs multiple sets of advantageous joint networks, supports the stability analysis of surrounding rock in deep roadways, and the model prediction results are close to the field monitoring data, providing a reliable basis for support design.

[0057] Other beneficial effects of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0058] Figure 1 This is a flowchart of the steps of the present invention;

[0059] Figure 2 This is a flowchart of the surveying method of the present invention;

[0060] Figure 3 This is a schematic diagram of the survey line layout plan of the survey line method of the present invention;

[0061] Figure 4 This is a flowchart of the rectangular window method of the present invention;

[0062] Figure 5 This is a schematic diagram of the rectangular window arrangement according to the present invention.

[0063] Figure 6 This is a flowchart of the three-dimensional laser scanning method of the present invention;

[0064] Figure 7 This is a schematic diagram illustrating the range of the three-dimensional laser scanning method of the present invention;

[0065] Figure 8 This is a schematic diagram of the partitioned numerical model of the present invention;

[0066] Figure 9 This is a schematic diagram showing the cross-sectional division of the ore body and hanging wall of the present invention.

[0067] Figure 10 This is a flowchart of the rock mass internal joint modeling and parameter optimization of the present invention;

[0068] Figure 11 This is a schematic diagram of the joints before and after being meshed in S5 of the present invention;

[0069] Figure 12 This is a joint network distribution model of the near-field influence zone of the roadway according to the present invention, wherein (a) is the hanging wall, (b) is the ore body, and (c) is the footwall. Detailed Implementation

[0070] The following specific examples illustrate the implementation of this disclosure. Those skilled in the art can easily understand other advantages and effects of this disclosure from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. This disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this disclosure. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0071] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this disclosure, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0072] It should also be noted that the illustrations provided in the following embodiments are merely schematic representations of the basic concept of this disclosure. The illustrations only show components relevant to this disclosure and are not drawn according to the actual number, shape, and size of components in implementation. In actual implementation, the type, quantity, and proportion of each component can be arbitrarily changed, and the component layout may be more complex. Furthermore, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.

[0073] like Figure 1 As shown, an embodiment of the present invention provides a discrete element modeling method for reproducing joint networks within a rock mass, comprising the following steps:

[0074] S1. On-site joint information is measured: Joint measurements and statistical analyses are conducted in underground roadways using both contact and non-contact measurement methods, primarily focusing on the hanging wall, ore body, and footwall areas. In this embodiment, the non-contact measurement method uses three-dimensional laser scanning, while the contact measurement method employs the survey line method and the rectangular window method.

[0075] like Figure 2 and Figure 3 As shown, the surveying line method requires selecting appropriate surveying line locations based on the research objectives and regional characteristics. The surveying line needs to cover a representative portion of the study area to ensure the representativeness of the collected data. At the selected location, tools such as measuring tapes and spray paint can be used to set the surveying line, and the start and end points of the surveying line should be marked with spray paint. The cumulative surveying line length should ideally exceed a preset value, such as 30m. Information about each joint is recorded along the surveying line, including its location, number, spacing, and trace length. Simultaneously, the surveying line location and joint information are recorded in detail in the data table. Finally, the data is processed and analyzed to eliminate duplicate or erroneous data, and information such as the average trace length, density, and spacing of the joints is calculated. The formula for calculating the average trace length using the surveying line method is:

[0076]

[0077] in, For the first m The traces of the joints are long. n This represents the total length of the traces intersecting with the measurement line.

[0078] The formula for calculating the linear density using the line surveying method is:

[0079]

[0080] in, This is for measuring the length of the line.

[0081] like Figure 4 and Figure 5 As shown, the rectangular window method selects an appropriate window location based on the research objectives and regional characteristics, ensuring the window covers a representative portion of the study area as much as possible. The size and shape of the window are measured using a measuring tape and spray paint, for example, a window 1.5m high and 3m wide. The window boundaries are clearly defined and marked. Information on each joint within the window is recorded, including its location, number, trace length, and spacing. The collected joint information is meticulously recorded in a data table, including window location, and duplicate or erroneous data is eliminated. Parameters such as the average trace length, density, and spacing of the joints are calculated. The formula for calculating the average trace length using the rectangular window method is:

[0082]

[0083] in, For the first i The length of the visible trace at both ends, For the first j The length of the visible trace at one end, For the first k The expected number of traces with invisible ends and penetrating trace lengths is: The expected number of intersecting trace lengths is The expected number of the inclusive trace length is .

[0084] The formula for calculating the two-dimensional density using the rectangular window method is as follows:

[0085]

[0086] in, and These represent the width and height of the window, respectively.

[0087] like Figure 6 , Figure 7As shown, the three-dimensional laser scanning method requires selecting a suitable scanning area based on the research objectives and regional characteristics to ensure it represents the joint features of the entire research area. During the preparation phase, key points and measurement boundaries of the representative scanning area are marked, and the laser scanner's placement is determined. The scanning length needs to be greater than a preset value, such as 12m, to ensure coverage of the entire scanning area. Subsequently, the three-dimensional laser scanner is calibrated to ensure its accuracy and stability. During the scanning phase, the three-dimensional laser scanner is started, acquiring point cloud data, performing multi-angle scanning, on-site inspection, and data transmission. In the data processing phase, data processing is completed through point cloud data merging, data filtering, and joint identification. In the data analysis phase, parameters such as joint geometry, density, and attitude are analyzed to obtain the spatial distribution characteristics and interrelationships of the joints. The formula for calculating the average trace length using the three-dimensional laser scanning method is:

[0088]

[0089] in, For the first q The traces of the joints are long. M This represents the total trace length obtained through three-dimensional laser scanning.

[0090] The formula for calculating areal density using the three-dimensional laser scanning method is:

[0091]

[0092] in, l Let be the arc length of the tunnel top. z The height of the tunnel sidewall, y This represents the axial scan length of the tunnel.

[0093] In one specific implementation, the 3D laser scanner uses the FARO FocusS plus 350 scanner, with a scanning range of 0.6m to 350m, a sampling rate of up to 2 million points per second, and a measurement accuracy of ±1mm. It also has an IP54 protection rating, meeting the Class 1 laser safety standard, and a scanning angle of 300° vertically and 360° horizontally.

[0094] As mentioned above, the densities obtained by the rectangular window method and the three-dimensional laser scanning method are both areal densities. In this embodiment, the areal density is uniformly converted into linear density for joint spacing calculation. Specifically, the linear density is calculated by multiplying the areal density by the measurement length, and the calculation formula is as follows:

[0095]

[0096] in, For the converted linear density, dThe joint spacing is the average distance between adjacent joint surfaces in the normal direction, and it is the reciprocal of the linear density.

[0097] After calculating the linear density, the statistical and converted joint information is summarized.

[0098] S2. Establish a discrete element numerical model. The model dimensions are preset, for example, 70m long and 65m high. A straight-walled arched roadway boundary is cut out in the middle of the model. The roadway cross-section dimensions can be 3.2m wide, 2.8m high, and 1.9m high at the side. For this discrete element numerical model, a -300m horizontal roadway is used as the research object, and the average elevation of the mining area is +212.35m. The numerical model uses the midpoint of the roadway floor as the coordinate zero point. The height between the roadway floor and the upper boundary of the model is 35m, and the burial depth of the upper boundary of the model is 477.35m.

[0099] like Figure 8 As shown, in this embodiment, to improve computational efficiency and ensure computational accuracy, a partitioned modeling strategy is adopted: the model is divided into a key research area containing the roadway, namely the near-field influence zone (Area A), and an outer area, namely the far-field influence zone (Area B). In the far-field influence zone, the Voronoi-trigon method is used to divide the grid into triangular blocks with a side length of up to 3m, while smaller triangular block side lengths are used in the near-field influence zone to make the mesh denser. Simultaneously, the mesh in the near-field influence zone can be further locally refined to ensure accurate capture of the stress distribution and fracture evolution characteristics of the surrounding rock. The far-field influence zone uses a relatively sparse mesh, which effectively reduces the computational load while maintaining computational accuracy.

[0100] In this embodiment, to better describe the mechanical behavior of the rock mass, the triangular blocks adopt the Mohr-Coulomb model, and the contact surface adopts the Coulomb slip model. The mechanical parameters of the triangular blocks and the contact surface are determined based on the reduced rock mass parameters. Fixed boundary conditions are used at the bottom of the model to restrict vertical and horizontal displacement; horizontal displacement constraints are used on the left and right sides of the model to restrict horizontal displacement; the top of the model is a free boundary, and a uniformly distributed load is applied to simulate the self-weight stress of the overlying rock strata.

[0101] S3, a geological profile arranged along the dip direction of the ore body. Please refer to [link / reference]. Figure 9 First, a profile of the ore body is cut along its center. Then, based on engineering geological characteristics, a profile is cut in both the hanging wall and footwall regions at a certain distance outside the ore body interface, forming a study area that includes the hanging wall profile, the ore body profile, and the footwall profile. In this embodiment, separate modeling and analysis are used to study the profiles of the hanging wall, ore body, and footwall separately for a more targeted approach.

[0102] S4. The tunnel boundary is cut out inside the model, and Voronoi-trigon blocks are used to cut out the measured joint information inside the rock mass. The measured joint length is then analyzed. L j With the length of the triangle L b The relationship between them, such as Figure 10 As shown.

[0103] Voronoi-trigon is a commonly used element partitioning method in discrete element method (DEM) software. Utilizing the Voronoi (Thieson polygon) principle, it discretizes the simulation region into contacting polygonal blocks based on user-defined or randomly generated seed points; these blocks are the Voronoi elements. "Voronoi-trigon" emphasizes that the model aims to generate a triangular-dominated block system using the Voronoi method, specifically designed to simulate the fine fracture and fragmentation processes of brittle materials. This distinguishes it from Voronoi models that may generate more quadrilaterals or larger polygons.

[0104] Specifically, when the joint length L j Less than the length of the triangle L b At that time, that is L j < L b The number of joints penetrating the triangular block boundaries are 1, 1, and 2, respectively. It's important to note that joints must penetrate the triangular block boundaries to form a valid joint. During mesh generation, joints penetrating one triangular block boundary are automatically merged and removed by the system; for joints penetrating two triangular block boundaries, the ends cut by the boundary are also merged and removed, retaining only the middle section of the joint length. Furthermore, this process further cuts the retained joints, adding one new triangular block, while most joints are merged and removed.

[0105] When 2 L b > L j ≥ L b Initially, the number of joints penetrating the triangular block boundaries was 2, 3, and 4 respectively. After meshing, the two ends of the joints penetrating the triangular block boundaries were merged and removed, retaining only the joint length in the middle. At this point, the number of newly added triangular blocks was 1, 2, and 3 respectively, and some joints were preserved.

[0106] When 3 L b > L j≥2 L b At the time step, the number of joints penetrating the boundaries of the triangular blocks were 4, 5, and 6, respectively. Similarly, after meshing, the two ends of the joints penetrating the boundaries of the triangular blocks were removed, retaining only the joint length in the middle. At this time, the number of newly added triangular blocks were 3, 4, and 5, respectively, and most of the joint length was retained.

[0107] When 4 L b ≥ L j ≥3 L b At that time, the number of joints penetrating the boundaries of the triangular blocks were 6, 7, and 8, respectively. After meshing, the number of newly added triangular blocks were 5, 6, and 7, respectively, and the joint lengths were basically preserved.

[0108] when L j >4 L b At this point, after mesh generation, the joint length approaches the true value, but computational efficiency decreases. Smaller triangle sizes result in joint lengths closer to the true value; however, excessively small triangle sizes drastically reduce computational efficiency. Therefore, through practical testing, the optimal range for joint length and triangle side length is 4. L b ≥ L j ≥3 L b Secondly, 3 L b > L j ≥2 L b That is, the possible ranges for the joint length and the side length of the triangular block are 4. L b ≥ L j ≥2 L b .

[0109] S5, Select a range of 3 for the measured joint length and the side length of the triangular block. L b > L j ≥2 L b ,like Figure 11 As shown, the side length of the triangular block L b Then, the maximum size within this range is taken, and the joint information obtained from on-site measurements is embedded into the numerical model.

[0110] It should be noted that, although 4 Lb ≥ L j ≥3 L b The simulated joint length of the range is closer to the engineering site, but the size of the numerical model is large and the number of joints is large, resulting in low computational efficiency. Therefore, the above range was selected to improve the computational efficiency of the numerical model.

[0111] Since a small portion of the joints measured in the actual mesh are merged and removed after meshing, the simulated joint length... L mj The joint length needs to be measured. L j Based on this, add a minimum triangle block side length. Specifically, L b and L mj The calculation formula is as follows:

[0112]

[0113]

[0114] The simulated joint dimensions and triangular block dimensions were calculated for the hanging wall, ore body, and footwall. Considering the involvement of multiple sets of dominant joint information during the simulation, the simulated joint spacing was determined. d m The determination needs to be based on the measured average joint spacing. The calculation is based on this, and the specific calculation method is as follows:

[0115]

[0116] in, n The number of dominant joint groups.

[0117] Therefore, the joint geometric parameters set in the numerical model are all derived from field measurement statistics or calculated values ​​based on field measurement statistics. The simulated gap value directly adopts the measured average spacing data, as shown in Table 1.

[0118] Table 1 Joint geometric parameters of the numerical model

[0119]

[0120] S6, based on joint geometric parameters, joint network models of the hanging wall, ore body, and footwall are constructed in the far-field influence zone of the roadway, respectively, as follows: Figure 12As shown in the figure, the joint network model of the hanging wall mainly considers two sets of dominant joints, with joint group 1 and joint group 2 being 85° and -81° respectively; the joint network of the ore body simulates two sets of joints, with joint group 1 and joint group 2 being 71° and -73° respectively; the joint network model of the footwall is mainly constructed based on three sets of dominant joints, with joint group 1, joint group 2 and joint group 3 being 61°, 78° and -78° respectively.

[0121] As described above, the construction of all joint network models in this embodiment strictly adheres to field-measured statistical data, ensuring a high degree of consistency between the models and actual geological conditions. Comparative analysis shows that the established joint network models effectively reflect the structural characteristics of the rock mass in the study area, providing a reliable foundation for subsequent rock mass stability analysis. Therefore, the discrete element method for reproducing the internal joint network of rock mass provided in this embodiment overcomes the bottleneck of traditional modeling methods' inability to reproduce the joint network in the field. Through innovation across the entire data-model-computation chain, it provides a high-fidelity numerical analysis tool for predicting the mechanical behavior of jointed rock masses in deep underground engineering, disaster prevention and control, and optimized design.

[0122] Based on the same inventive concept, this embodiment also provides an apparatus, which includes at least one processor and a memory communicatively connected to the at least one processor. The memory stores instructions executable by the at least one processor, which, when executed, enables the at least one processor to perform the aforementioned discrete element modeling method for reproducing joint networks within a rock mass.

[0123] Based on the same inventive concept, this embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned discrete element modeling method for reproducing joint networks inside a rock mass.

[0124] The computer-readable medium includes, but is not limited to, any type of disk (including floppy disks, hard disks, optical disks, CDs). ROM (and magneto-optical disk), ROM, RAM, EPROM (Erasable Programmable Read-Only ROM) Computer-readable media includes erasable programmable read-only memory (EPROM), flash memory, magnetic cards, or optical cards. In other words, this computer-readable medium includes any medium by which a device stores or transmits information in a readable form.

[0125] The apparatus and computer-readable storage medium provided in this embodiment have the same inventive concept and the same beneficial effects as the methods described above, and will not be repeated here.

[0126] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0127] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A discrete element modeling method for reproducing joint networks within rock masses, characterized in that, Includes the following steps: S1, Conduct on-site joint information measurement, use multiple measurement methods to measure joints in underground roadways, obtain joint measurement data, and summarize the statistical and converted joint information; S2, Establish the discrete element numerical model; S3, geological profiles are arranged along the dip direction of the ore body to form a study area including the hanging wall profile, the ore body profile, and the footwall profile; S4. The tunnel boundary is cut out within the numerical model. Simultaneously, triangular blocks are used to cut out measured joint information within the rock mass, and the correlation between the measured joint length and the triangular block length is analyzed. Measured joint length... L j With the length of the triangle L b The relationship between them is: when L j < L b At that time, the number of joints penetrating the boundary of the triangle block were 1, 1, and 2 respectively. During the mesh generation process, the joints that penetrated the boundary of the triangle block with 1 number were automatically merged and removed by the system. For the joints that penetrated the boundary of the triangle block with 2 number, the two ends cut by the boundary of the triangle block were merged and removed, and only the joint length in the middle part was retained. The retained joints were further cut to add 1 triangle block. When 2 L b > L j ≥ L b At that time, the number of joints penetrating the boundary of the triangular block were 2, 3, and 4 respectively. After meshing, the two ends of the joints penetrating the boundary of the triangular block were merged and removed by the boundary of the triangular block, and only the joint length in the middle part was retained. The number of newly added triangular blocks were 1, 2, and 3 respectively. When 3 L b > L j ≥2 L b At that time, the number of joints penetrating the boundary of the triangular blocks were 4, 5, and 6 respectively. After meshing, the two ends of the joints penetrating the boundary of the triangular blocks were removed, and only the length of the middle part of the joint was retained. The number of newly added triangular blocks were 3, 4, and 5 respectively. When 4 L b ≥ L j ≥3 L b At that time, the number of joints penetrating the boundary of the triangular blocks were 6, 7, and 8 respectively. After meshing, the number of newly added triangular blocks were 5, 6, and 7 respectively. S5, select the range of measured joint length and triangular block side length, calculate the simulated joint size and triangular block size of the hanging wall, ore body and footwall respectively, and calculate the simulated joint spacing and simulated gap. In the numerical model, set the simulated joint size, triangular block size, simulated joint spacing and simulated gap as joint geometric parameters. S6, based on joint geometric parameters, construct joint network models for the hanging wall, ore body, and footwall respectively.

2. The discrete element modeling method for reproducing joint networks within a rock mass according to claim 1, characterized in that, The measurement methods in S1 include contact measurement methods and non-contact measurement methods; The contact measurement method includes the line measurement method and the rectangular window method; the non-contact measurement method includes the three-dimensional laser scanning method.

3. The discrete element modeling method for reproducing joint networks within a rock mass according to claim 1, characterized in that, The formula for calculating the average trace length using the surveying method is: in, For the first m The traces of the joints are long. n The total length of the trace intersecting with the measurement line; The formula for calculating the linear density using the line surveying method is: in, To measure the length of the line; The formula for calculating the average trace length using the rectangular window method is as follows: in, For the first i The length of the visible trace at both ends, For the first j The length of the visible trace at one end, For the first k The expected number of traces with invisible ends and penetrating trace lengths is: The expected number of intersecting trace lengths is The expected number of the inclusive trace length is ; The formula for calculating the two-dimensional density using the rectangular window method is as follows: in, and These represent the width and height of the window, respectively. The formula for calculating the average trace length using the three-dimensional laser scanning method is: in, For the first q The traces of the joints are long. M This represents the total trace length obtained through three-dimensional laser scanning. The formula for calculating areal density using the three-dimensional laser scanning method is: in, l Let be the arc length of the tunnel top. z The height of the tunnel sidewall, y This represents the axial scan length of the tunnel.

4. The discrete element modeling method for reproducing joint networks within a rock mass according to claim 3, characterized in that, In S1, the areal density is uniformly converted into linear density for joint spacing calculation: in, For the converted linear density, d Joint spacing, joint spacing d This represents the average distance between adjacent joint surfaces in the normal direction.

5. The discrete element modeling method for reproducing joint networks within a rock mass according to claim 1, characterized in that, In S2, a discrete element numerical model is established, including: The numerical model is divided into a near-field influence zone containing the roadway and a far-field influence zone not containing the roadway. A smaller triangular block mesh is used in the near-field influence zone compared to the far-field influence zone, and the mesh in the near-field influence zone is also locally refined.

6. The discrete element modeling method for reproducing joint networks within a rock mass according to claim 1, characterized in that, In S5, the range for the measured joint length and the triangular block side length is 3. L b > L j ≥2 L b The side length of the triangular block L b Take the maximum size within this range and embed the joint information obtained from field measurements into the numerical model.

7. The discrete element modeling method for reproducing joint networks within a rock mass according to claim 6, characterized in that, S5 L b and L mj The calculation formula is: in, L mj To simulate joint length.

8. The discrete element modeling method for reproducing joint networks within a rock mass according to claim 7, characterized in that, Simulated joint spacing d m The measured average spacing The calculation is based on the formula: in, n The number of dominant joint groups.

9. The discrete element modeling method for reproducing joint networks within a rock mass according to claim 1, characterized in that, The joint network model of the hanging wall, ore body, and footwall in S6 considers the construction of each group of dominant joints at different locations.

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