Simulation and prediction method for the distribution characteristics of excavation damage zone in cemented and filled fractured rock mass

Abstract

This invention discloses a simulation and prediction method for the distribution characteristics of excavated damage zones in cemented-filled fractured rock masses, belonging to the field of surrounding rock stability analysis technology. The method includes: establishing an initial model of the excavated damage zone of rock masses containing cemented-filled fractures based on the discrete element method; setting up a monitoring program to monitor stress-strain, bond fracture, and acoustic emission counts; applying stress through boundary movement until the model fails; comparing the simulation results with physical experiments to verify and correct microscopic parameters; analyzing the influence of the filling fractures on the geometry, characteristic stress, and stress distribution of the damage zone, revealing the rock mass failure mechanism. This invention fills the gap in the simulation and analysis of excavated damage zones in cemented-filled fractured rock masses, revealing the influence of cemented-filled fractures on the geometry of the damage zone and the rock mass failure mechanism, providing a theoretical basis for the engineering stability assessment of fractured rock masses.

Description

Technical Field

[0001] This invention belongs to the field of surrounding rock stability analysis technology, specifically relating to a simulation and prediction method for the distribution characteristics of the excavation damage zone (EDZ) in cemented and filled fractured rock mass. Background Technology

[0002] Underground excavation engineering, such as rock tunnels, boreholes, and wells, is widely used in urban transportation and underground energy extraction, typically undertaking engineering tasks such as transportation, energy or nuclear waste storage, oil and gas extraction, and geological exploration. Excavation activities cause a redistribution of the stress environment in the rock strata. Under the action of compressive and tensile stresses, an excavation damage zone (EDZ) exists around the tunnel and borehole. The extent of the EDZ is related to factors such as burial depth, rock mechanical properties, geometry, distribution of primary fractures, and excavation method.

[0003] Currently, on-site measurement and geophysical monitoring methods related to excavation damage zones face numerous challenges. Existing testing techniques are mostly time-consuming, costly, and unable to comprehensively capture detailed information about the damaged areas surrounding the tunnel. To overcome these limitations, many scholars have proposed numerous theoretical control models and simulation methods. Through numerical simulation, they simulate the excavation process of rock tunnels, boreholes, and shafts under engineering geological conditions, exploring the evolution laws and control mechanisms of rock excavation damage zones. For example, Zhou Li et al. used Rhino-Griddle software for modeling and combined it with FLAC software to simulate the deformation and failure laws of fractured rock masses under uniaxial compression conditions; Xu Yang et al., based on indoor triaxial compression experiments and PFC2D particle flow numerical simulation, studied the crack propagation characteristics and energy evolution laws of rock masses with single fractures of different lengths under different confining pressures; Guo Ming et al. used the finite element analysis software ANSYS / LS-DYNA to study the explosive cracking laws under different joint fracture angles.

[0004] However, there are currently few reports on methods for simulating and analyzing excavation damage zones in cemented-filled fractured rock masses. Under the influence of tectonic movements, numerous natural fractures exist within rock masses. During the long process of groundwater erosion, these natural fractures are usually filled by minerals, forming infilled cracks. Related experimental studies have shown that infilled cracks have a significant impact on the excavation of underground engineering projects, especially on the location and shape of the excavation damage zone. Currently, there are few reports on the evolution and control mechanisms of excavation damage zones during the excavation of tunnels, boreholes, and shafts within infilled fractured rock masses, and methods for simulating and analyzing excavation damage zones in cemented-filled fractured rock masses remain lacking.

[0005] Therefore, there is an urgent need to propose a simulation analysis method for the excavation damage zone of cemented and filled fractured rock mass, so as to establish a cemented and filled fractured rock mass model, simulate the excavation process of rock tunnels, boreholes and wells in cemented and filled fractured rock mass, and explore the evolution law and control mechanism of the excavation damage zone of cemented and filled fractured rock mass. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a simulation and prediction method for the distribution characteristics of the excavation damage zone in cemented-filled fractured rock masses. This invention fills the gap in the simulation and analysis of the excavation damage zone in cemented-filled fractured rock masses, and can reveal the influence of cemented-filled fractures on the geometry of the damage zone and the failure mechanism of the rock mass, providing a theoretical basis for the engineering stability assessment of fractured rock masses.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: a method for simulating and predicting the distribution characteristics of the damage zone during excavation of cemented and filled fractured rock mass, comprising the following steps:

[0008] S1. Based on the PFC discrete element simulation method, an initial discrete element particle model of the excavation damage zone of rock mass containing cemented filling fractures is established, and the length, location and width parameters of cemented filling fractures are considered in the modeling.

[0009] S2. Set up a monitoring program in the established discrete element particle model to monitor the model's response during the loading process;

[0010] S3. Stress is applied to the model by controlling the movement of the model boundaries until the model is destroyed;

[0011] S4. Compare the discrete element simulation results with the physical experiment results to verify the accuracy of the model and correct the micro parameters;

[0012] S5. Analyze the discrete element simulation results of the model after parameter correction, including: comparing the influence of cemented filling fractures on the geometry of the excavated damage zone; determining the characteristic stress of the sample using simulated acoustic emission data and stress-strain curves; and comparing the stress distribution inside the model to reveal the failure mechanism of cemented filling fracture rock mass.

[0013] Further, in step S1, establishing the initial discrete element particle model of the excavation damage zone of the cemented and filled fractured rock mass specifically includes:

[0014] S11. Set the initial boundary conditions of the rock mass geometric model using the wall generate command in PFC software, and use the FISH language built into PFC software to write a program, set the particle size, generate discrete particles within the set range according to the set porosity, and establish the initial discrete element particle model.

[0015] S12. Use the ball attribute density command in PFC software to set the density amplitude of the particles and the self-weight stress inside the model to make the model reach initial force balance.

[0016] S13. Select the parallel bond model as the constitutive model of the rock mass model and assign values ​​to the micro parameters.

[0017] Further, in step S2, setting up a monitoring program in the established discrete element particle model specifically includes:

[0018] S21. Monitor the overall stress and strain state of the model;

[0019] S22. Monitor and record the location of parallel bond fracture in the model. When the shear stress or tensile stress in the parallel bond exceeds the corresponding strength, the parallel bond fractures and forms microcracks.

[0020] S23. Monitor and record the number of microcracks generated within a set time period to simulate acoustic emission ringing count;

[0021] S24. Monitor the stress state at the set location, including setting two sets of measuring circles in the model along the horizontal direction of the borehole wall. Each set consists of multiple measuring circles along the X-axis on the left and right walls of the borehole, and multiple measuring circles are evenly arranged around the borehole wall.

[0022] Furthermore, in step S24, each set of measuring circles set along the horizontal direction of the tunnel wall consists of 10 measuring circles, with a distance of 5 mm between adjacent measuring circles; 36 measuring circles are evenly arranged around the tunnel wall, with an angle of 10° between adjacent measuring circles in the polar coordinate system.

[0023] Furthermore, in step S4, comparing the discrete element simulation results with the physical experiment results to verify the accuracy of the model and correct the microscopic parameters specifically includes:

[0024] S41. Compare the stress-strain curves from discrete element simulation with those from physical experiments.

[0025] S42. Compare the excavation damage zone simulated by discrete element method with the excavation damage zone simulated by physical experiment.

[0026] S43. Compare the cumulative acoustic emission count-strain curve of the discrete element simulation with the cumulative acoustic emission count-strain curve of the physical experiment;

[0027] The accuracy of the model is verified by the above comparison, and the micro parameters are corrected based on the comparison results. Steps S1-S4 are repeated until the micro parameters are successfully corrected, thus completing the establishment of the discrete element particle model of the excavation damage zone of the cemented and filled fractured rock mass.

[0028] Furthermore, in step S5, the geometric dimensions of the excavated damage zone include the damage width, normalized damage depth, and damage area.

[0029] Furthermore, in step S5, the characteristic stress includes crack initiation stress, crack damage stress, and peak stress; the characteristic stress of the sample is determined by monitoring the stress-strain state and microcracks of the model, combined with the stress-strain curve and acoustic emission ringing count.

[0030] Furthermore, in step S5, the stress distribution is analyzed to reveal the failure mechanism in the following ways:

[0031] By monitoring the stress state at a set location, three measured stress components σ were obtained. x σ y and τ xy And convert it into radial stress σ using the following formula. rr tangential stress σ θθ and shear stress τ rθ :

[0032] (1)

[0033] Where θ is the angle measured counterclockwise from the x-axis.

[0034] Furthermore, in step S5, the converted measured stress is compared with the analytical stress solution, which is calculated using the following formula:

[0035] (2)

[0036] Where σ1 is the maximum principal stress, σ3 is the minimum principal stress, a is the borehole radius, and r is the radial distance from the borehole axis.

[0037] The present invention also provides a simulation and prediction system for the distribution characteristics of excavation damage zones in cemented and filled fractured rock masses, including a memory, a processor, and a computer program stored in the memory and capable of being run by the processor. When the processor runs the computer program, it can implement the above-mentioned method.

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

[0039] (1) Based on numerical simulation, a set of EDZ analysis methods for fractured rock masses is formed that can be used in engineering practice. It is simple to operate and has a theoretical basis. Compared with engineering experience judgment and simple theoretical calculation, it can consider more realistic engineering conditions.

[0040] (2) The EDZ discrete element model of a cemented and filled fractured rock mass established by the present invention determines the EDZ geometric parameters of the cemented and filled fractured model according to the distribution of cracks. The characteristic stresses (including crack initiation stress, crack damage stress and peak stress) are determined according to the stress-strain and AE ring count-strain curves. Combined with the stress state at certain specific locations inside the model, the mechanical failure mechanism of the fractured rock mass can be revealed. Attached Figure Description

[0041] Figure 1 The flowchart illustrates the method for simulating and predicting the distribution characteristics of the excavation damage zone in cemented and filled fractured rock mass, as provided in this embodiment of the invention. Detailed Implementation

[0042] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0043] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0044] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0045] like Figure 1 As shown in the figure, this embodiment provides a method for simulating and predicting the distribution characteristics of the excavation damage zone in cemented and filled fractured rock mass, including the following steps:

[0046] S1. Based on the PFC discrete element simulation method, an initial discrete element particle model of the excavation damage zone of rock mass containing cemented filling fractures is established according to the example, and the length, location and width parameters of cemented filling fractures are considered in the modeling.

[0047] S2. Set up a monitoring program in the established discrete element particle model to monitor the model's response during the loading process;

[0048] S3. Stress is applied to the model by controlling the movement of the model boundaries until the model is destroyed;

[0049] S4. Compare the discrete element simulation results with the physical experiment results to verify the accuracy of the model and correct the micro parameters;

[0050] S5. Analyze the discrete element simulation results of the model after parameter correction, including: comparing the influence of cemented filling fractures on the geometry of the excavated damage zone; determining the characteristic stress of the sample using simulated acoustic emission data and stress-strain curves; and comparing the stress distribution inside the model to reveal the failure mechanism of cemented filling fracture rock mass.

[0051] This embodiment uses the Beishan granite sample as an example. Biaxial compression tests were conducted on multiple samples, including those with circular boreholes and artificially filled rock fissures. This granite material is mainly composed of 54% potassium feldspar, 30% quartz, 10% plagioclase, and 4% biotite. The basic mechanical properties of this granite material are shown in Table 1.

[0052] Table 1. Basic physical and mechanical parameters of the granite specimens

[0053]

[0054] The sample dimensions were 200 mm long, 200 mm high, and 30 mm thick, with a circular borehole diameter of 50 mm. Artificial cracks, 10 mm long and 1 mm in aperture, were created using water jet technology. These were then followed by artificial cracks using 62.5R cement grout (K1340 ultrafine cement) containing green fluorescent powder. Specific parameters are shown in Table 2. This resulted in two different types of pre-existing discontinuities: an unexposed discontinuity approximately 1.5 mm from the tunnel boundary (sealed and within the surrounding rock); and an exposed discontinuity at 0 mm from the tunnel boundary (exposed to the tunnel wall). The dip angle of the discontinuities was 0°.

[0055] Table 2 Relevant parameters of high-strength cement

[0056]

[0057] Based on the above samples, the implementation steps of the simulation and prediction method for the distribution characteristics of the excavation damage zone in cemented and filled fractured rock mass provided in this embodiment are as follows:

[0058] S1. Based on the example, establish an initial discrete element particle model on a proportional scale. During simulation, the model considers the influence of factors such as the length, location, and width of the cemented filling cracks.

[0059] S1.1. The initial boundary conditions of the rock mass geometric model are set using the `wall generate` command in the PFC software. Based on the physical and mechanical parameters and dimensions of the sample, the model dimensions are determined to be 200*200mm, with a circular borehole radius of 25mm, and a cohesive discontinuity surface measuring 10mm in length and 1.8mm in width. The particle radius is between 0.4 and 0.6 mm. An initial discrete element particle model is then established.

[0060] S1.2. Assign a density value to the particles using the "ball attribute density" command in the PFC software. Set the density to 2700 g / m³. 3 The self-weight stress inside the model was set to 9.81 to bring the model to initial equilibrium.

[0061] S1.3 Select the parallel bond model as the constitutive model of the rock mass model, assign values ​​to the micro parameters, and use the solve command in PFC software to perform initial stress equilibrium on the model. The specific micro parameter settings are shown in Table 3.

[0062] Table 3 Microscopic parameters of the discrete element model

[0063]

[0064] S2. Set up the monitoring program. This includes:

[0065] S2.1 Monitor the overall stress and strain state of the model;

[0066] S2.2 Monitor and record the location of parallel bond fracture in the model. By determining whether the parallel bond is in a bonded state, when the shear / tensile stress in the parallel bond exceeds the corresponding strength, the parallel bond fractures and forms microcracks. The location of the microcracks is displayed by the built-in plot of PFC.

[0067] S2.3 Monitor and record the number of microcracks generated over a period of time to simulate acoustic emission ringing count;

[0068] S2.4 Monitoring the stress state at specific locations: Two sets of measuring circles are set in the model along the horizontal direction of the borehole wall. Each set of measuring circles consists of 10 measuring circles along the x-axis on the left and right walls of the borehole, with a distance of 5 mm between adjacent measuring circles. 36 measuring circles are evenly arranged around the borehole wall, with an angle of 10° between adjacent measuring circles in the polar coordinate system.

[0069] S3. Based on the established discrete element particle model, stress is applied to the model by controlling the movement of the boundary until the model is destroyed.

[0070] In the biaxial compression discrete element simulation test, the system was initially loaded into an isotropic stress state, i.e., a confining pressure of 12 MPa (x-direction) and axial stress (y-direction) were applied. Subsequently, the axial stress was continuously increased until the excavation damage zone was formed. During the simulation, the confining pressure was kept constant through a servo control algorithm.

[0071] S4. Compare the discrete element simulation results of cemented fractured rock mass EDZ with the physical test results to verify the accuracy of the model and correct the microscopic parameters. Repeat steps S1-S4 until the microscopic parameters are successfully corrected. Complete the simulation of the cemented fractured rock mass EDZ discrete element particle model.

[0072] S5. Analyze the discrete element simulation results of cemented and filled fractured rock mass in EDZ, and compare the effect of filling cracks on the geometric dimensions (width, depth and area) of the damaged zone; use simulated acoustic emission tests and stress-strain curves to determine the characteristic stresses of the specimens (including crack initiation stress, damage stress and peak stress); compare the stress distribution to explain the irregular characteristics of the damaged zone in the filled fractured rock specimens, and further reveal the failure mechanism of the fractured rock mass.

[0073] S5.1 Determine the EDZ geometric parameters (damage width, normalized damage depth, and damage area) of cemented and filled fractured rock mass based on simulation results.

[0074] S5.2. Output stress-strain data, cumulative ringing count data, and stress components (σ) at specific points using the history write command in the PFC software. x σ y and τ xy );

[0075] S5.3 Using the stress-strain data and cumulative ringing count data output in step S5.2, plot the cumulative ringing count-strain curve to determine the characteristic stresses of the model (including crack initiation stress, damage stress, and peak stress).

[0076] S5.4. Using formula (1), the stress component (σ) output in step S5.2 is... x σ y and τ xy ) is converted into radial, tangential and shear stresses (σ rr σ θθ and τ rθ The stress analytical solution is calculated using formula (2). By comparing the stress distribution, the irregular characteristics of the damage zone in the rock sample filled with fractures are explained, and the failure mechanism of the fractured rock mass is further revealed.

[0077] (1)

[0078] Where, σ x σ y and τ xy The stress component is calculated based on the measured circle, and θ is the angle measured counterclockwise from the x-axis.

[0079] (2)

[0080] Where σ1 is the maximum principal stress, σ3 is the minimum principal stress, a is the borehole radius, and r is the radial distance from the borehole axis.

[0081] This embodiment also provides a simulation and prediction system for the distribution characteristics of excavation damage zones in cemented and filled fractured rock masses, including a memory, a processor, and a computer program stored in the memory and capable of being run by the processor. When the processor runs the computer program, it can implement the above-mentioned method.

[0082] This embodiment also provides a computer-readable storage medium having a computer program stored thereon, which implements the above-described method when the computer program is executed by a processor.

[0083] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0084] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0085] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0086] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0087] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for simulating and predicting the distribution characteristics of excavation damage zones in cemented and filled fractured rock masses, characterized in that, Includes the following steps: S1. Based on the PFC discrete element simulation method, an initial discrete element particle model of the excavation damage zone of rock mass containing cemented filling fractures is established, and the length, location and width parameters of cemented filling fractures are considered in the modeling. S2. Set up a monitoring program in the established discrete element particle model to monitor the model's response during the loading process; S3. Stress is applied to the model by controlling the movement of the model boundaries until the model is destroyed; S4. Compare the discrete element simulation results with the physical experiment results to verify the accuracy of the model and correct the micro parameters; S5. Analyze the discrete element simulation results of the model after parameter correction, including: comparing the influence of cemented filling fractures on the geometry of the excavated damage zone; determining the characteristic stress of the sample using simulated acoustic emission data and stress-strain curves; and comparing the stress distribution inside the model to reveal the failure mechanism of cemented filling fracture rock mass.

2. The method for simulating and predicting the distribution characteristics of excavation damage zones in cemented and filled fractured rock masses according to claim 1, characterized in that, In step S1, establishing the initial discrete element particle model of the excavation damage zone of the cemented and filled fractured rock mass specifically includes: S11. Set the initial boundary conditions of the rock mass geometric model using the wall generate command in PFC software, and use the FISH language built into PFC software to write a program, set the particle size, generate discrete particles within the set range according to the set porosity, and establish the initial discrete element particle model. S12. Use the ball attribute density command in PFC software to set the density amplitude of the particles and the self-weight stress inside the model to make the model reach initial force balance. S13. Select the parallel bond model as the constitutive model of the rock mass model and assign values ​​to the micro parameters.

3. The method for simulating and predicting the distribution characteristics of excavation damage zones in cemented and filled fractured rock masses according to claim 1, characterized in that, In step S2, setting up a monitoring program in the established discrete element particle model specifically includes: S21. Monitor the overall stress and strain state of the model; S22. Monitor and record the location of parallel bond fracture in the model. When the shear stress or tensile stress in the parallel bond exceeds the corresponding strength, the parallel bond fractures and forms microcracks. S23. Monitor and record the number of microcracks generated within a set time period to simulate acoustic emission ringing count; S24. Monitor the stress state at the set location, including setting two sets of measuring circles in the model along the horizontal direction of the borehole wall. Each set consists of multiple measuring circles along the X-axis on the left and right walls of the borehole, and multiple measuring circles are evenly arranged around the borehole wall.

4. The method for simulating and predicting the distribution characteristics of excavation damage zones in cemented and filled fractured rock masses according to claim 3, characterized in that, In step S24, each set of measuring circles set along the horizontal direction of the tunnel wall consists of 10 measuring circles, with a distance of 5 mm between adjacent measuring circles; 36 measuring circles are evenly arranged around the tunnel wall, with an angle of 10° between adjacent measuring circles in the polar coordinate system.

5. The method for simulating and predicting the distribution characteristics of excavation damage zones in cemented and filled fractured rock masses according to claim 1, characterized in that, In step S4, comparing the discrete element simulation results with the physical experiment results to verify the accuracy of the model and correct the microscopic parameters specifically includes: S41. Compare the stress-strain curves from discrete element simulation with those from physical experiments. S42. Compare the excavation damage zone simulated by discrete element method with the excavation damage zone simulated by physical experiment. S43. Compare the cumulative acoustic emission count-strain curve of the discrete element simulation with the cumulative acoustic emission count-strain curve of the physical experiment; The accuracy of the model is verified by the above comparison, and the micro parameters are corrected based on the comparison results. Steps S1-S4 are repeated until the micro parameters are successfully corrected, thus completing the establishment of the discrete element particle model of the excavation damage zone of the cemented and filled fractured rock mass.

6. The method for simulating and predicting the distribution characteristics of excavation damage zones in cemented and filled fractured rock masses according to claim 1, characterized in that, In step S5, the geometric dimensions of the excavated damaged area include the damage width, normalized damage depth, and damage area.

7. The method for simulating and predicting the distribution characteristics of excavation damage zones in cemented and filled fractured rock masses according to claim 1, characterized in that, In step S5, the characteristic stress includes crack initiation stress, crack damage stress, and peak stress; the characteristic stress of the sample is determined by monitoring the stress-strain state and microcracks of the model, combined with the stress-strain curve and acoustic emission ringing count.

8. The method for simulating and predicting the distribution characteristics of excavation damage zones in cemented and filled fractured rock masses according to claim 1, characterized in that, In step S5, the stress distribution is analyzed to reveal the failure mechanism in the following ways: By monitoring the stress state at a set location, three measured stress components σ were obtained. x σ y and τ xy And convert it into radial stress σ using the following formula. rr tangential stress σ θθ and shear stress τ rθ : (1) Where θ is the angle measured counterclockwise from the x-axis.

9. The method for simulating and predicting the distribution characteristics of excavation damage zones in cemented and filled fractured rock masses according to claim 8, characterized in that, In step S5, the converted measured stress is compared with the analytical stress solution, which is calculated using the following formula: (2) Where σ1 is the maximum principal stress, σ3 is the minimum principal stress, a is the borehole radius, and r is the radial distance from the borehole axis.

10. A simulation and prediction system for the distribution characteristics of excavation damage zones in cemented and filled fractured rock masses, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable by the processor, which, when executed by the processor, enables the implementation of the method as described in any one of claims 1-9.

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